diff options
| author | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-11-21 03:04:18 +0000 |
|---|---|---|
| committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-12-01 10:41:54 +0000 |
| commit | 40f51a63c8e7258db15269427ae4fe1ad199c550 (patch) | |
| tree | 353253a41863966995a45556731e7181a643c003 | |
| parent | 327800401c4185d98fcc01b9c9efbc038a4228ed (diff) | |
| download | ComputeLibrary-40f51a63c8e7258db15269427ae4fe1ad199c550.tar.gz | |
Update default C++ standard to C++14
(3RDPARTY_UPDATE)
Resolves: COMPMID-3849
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I6369f112337310140e2d6c8e79630cd11138dfa0
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4544
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
357 files changed, 982 insertions, 1409 deletions
diff --git a/3rdparty b/3rdparty -Subproject ba65985c4a47effae4620b95b158ecae8764d2e +Subproject 679eadd4df491b26b8b824690348e334ad588c7 diff --git a/SConstruct b/SConstruct index 4be00f3070..395fb5e59d 100644 --- a/SConstruct +++ b/SConstruct @@ -146,7 +146,7 @@ if not env['exceptions']: env.Append(CXXFLAGS = ['-Wall','-DARCH_ARM', '-Wextra','-pedantic','-Wdisabled-optimization','-Wformat=2', '-Winit-self','-Wstrict-overflow=2','-Wswitch-default', - '-std=gnu++11','-Woverloaded-virtual', '-Wformat-security', + '-std=c++14','-Woverloaded-virtual', '-Wformat-security', '-Wctor-dtor-privacy','-Wsign-promo','-Weffc++','-Wno-overlength-strings']) env.Append(CPPDEFINES = ['_GLIBCXX_USE_NANOSLEEP']) diff --git a/arm_compute/core/utils/logging/Helpers.h b/arm_compute/core/utils/logging/Helpers.h index 08b8eb354a..5f8b948592 100644 --- a/arm_compute/core/utils/logging/Helpers.h +++ b/arm_compute/core/utils/logging/Helpers.h @@ -25,7 +25,6 @@ #define ARM_COMPUTE_LOGGING_HELPERS_H #include "arm_compute/core/utils/logging/Types.h" -#include "support/MemorySupport.h" #include "support/ToolchainSupport.h" #include <cstddef> @@ -49,7 +48,7 @@ template <typename... Ts> inline std::string string_with_format(const std::string &fmt, Ts &&... args) { size_t size = support::cpp11::snprintf(nullptr, 0, fmt.c_str(), args...) + 1; - auto char_str = support::cpp14::make_unique<char[]>(size); + auto char_str = std::make_unique<char[]>(size); support::cpp11::snprintf(char_str.get(), size, fmt.c_str(), args...); return std::string(char_str.get(), char_str.get() + size - 1); } diff --git a/arm_compute/core/utils/logging/Macros.h b/arm_compute/core/utils/logging/Macros.h index 6a1b7611ec..21ed721eb1 100644 --- a/arm_compute/core/utils/logging/Macros.h +++ b/arm_compute/core/utils/logging/Macros.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 Arm Limited. + * Copyright (c) 2017-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -47,7 +47,7 @@ if(__logger != nullptr) \ { \ size_t size = ::snprintf(nullptr, 0, fmt, __VA_ARGS__) + 1; \ - auto char_str = support::cpp14::make_unique<char[]>(size); \ + auto char_str = std::make_unique<char[]>(size); \ ::snprintf(char_str.get(), size, #fmt, __VA_ARGS__); \ __logger->log(log_level, std::string(char_str.get(), char_str.get() + size - 1)); \ } \ diff --git a/arm_compute/graph/Graph.h b/arm_compute/graph/Graph.h index 0cdd8f8faa..d8d3feb1f7 100644 --- a/arm_compute/graph/Graph.h +++ b/arm_compute/graph/Graph.h @@ -238,7 +238,7 @@ inline NodeID Graph::add_node(Ts &&... args) // Create node NodeID nid = _nodes.size(); - auto node = support::cpp14::make_unique<NT>(std::forward<Ts>(args)...); + auto node = std::make_unique<NT>(std::forward<Ts>(args)...); node->set_graph(this); node->set_id(nid); diff --git a/arm_compute/graph/TensorDescriptor.h b/arm_compute/graph/TensorDescriptor.h index de67289bc8..5fa155efc8 100644 --- a/arm_compute/graph/TensorDescriptor.h +++ b/arm_compute/graph/TensorDescriptor.h @@ -27,7 +27,6 @@ #include "arm_compute/graph/Types.h" #include "support/ICloneable.h" -#include "support/MemorySupport.h" #include <memory> @@ -104,7 +103,7 @@ struct TensorDescriptor final : public misc::ICloneable<TensorDescriptor> // Inherited methods overridden: std::unique_ptr<TensorDescriptor> clone() const override { - return support::cpp14::make_unique<TensorDescriptor>(*this); + return std::make_unique<TensorDescriptor>(*this); } TensorShape shape{}; /**< Tensor shape */ diff --git a/arm_compute/graph/backends/BackendRegistry.h b/arm_compute/graph/backends/BackendRegistry.h index c4414a23f6..7c11d35faf 100644 --- a/arm_compute/graph/backends/BackendRegistry.h +++ b/arm_compute/graph/backends/BackendRegistry.h @@ -26,7 +26,6 @@ #include "arm_compute/graph/IDeviceBackend.h" #include "arm_compute/graph/Types.h" -#include "support/MemorySupport.h" #include <map> #include <memory> @@ -93,7 +92,7 @@ private: template <typename T> inline void BackendRegistry::add_backend(Target target) { - _registered_backends[target] = support::cpp14::make_unique<T>(); + _registered_backends[target] = std::make_unique<T>(); } } // namespace backends } // namespace graph diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h index e2904af0b5..05bd483cfd 100644 --- a/arm_compute/graph/backends/FunctionHelpers.h +++ b/arm_compute/graph/backends/FunctionHelpers.h @@ -113,7 +113,7 @@ std::unique_ptr<IFunction> create_activation_layer(ActivationLayerNode &node) const ActivationLayerInfo act_info = node.activation_info(); // Create function - auto func = support::cpp14::make_unique<ActivationLayerFunction>(); + auto func = std::make_unique<ActivationLayerFunction>(); func->configure(input, output, act_info); ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " @@ -152,7 +152,7 @@ std::unique_ptr<IFunction> create_arg_min_max_layer(ArgMinMaxLayerNode &node) unsigned int axis = node.axis(); // Create function - auto func = support::cpp14::make_unique<ArgMinMaxLayerFunction>(); + auto func = std::make_unique<ArgMinMaxLayerFunction>(); func->configure(input, axis, output, op); ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " @@ -194,7 +194,7 @@ std::unique_ptr<IFunction> create_batch_normalization_layer(BatchNormalizationLa const ActivationLayerInfo fused_act = node.fused_activation(); // Create and configure function - auto func = support::cpp14::make_unique<BatchNormalizationLayerFunction>(); + auto func = std::make_unique<BatchNormalizationLayerFunction>(); func->configure(input, output, mean, var, beta, gamma, epsilon, fused_act); // Log info @@ -346,7 +346,7 @@ std::unique_ptr<IFunction> create_bounding_box_transform_layer(BoundingBoxTransf const BoundingBoxTransformInfo bbox_info = node.info(); // Create and configure function - auto func = support::cpp14::make_unique<BoundingBoxTransformLayerFunction>(); + auto func = std::make_unique<BoundingBoxTransformLayerFunction>(); func->configure(input, output, deltas, bbox_info); // Log info @@ -383,7 +383,7 @@ std::unique_ptr<IFunction> create_channel_shuffle_layer(ChannelShuffleLayerNode const unsigned int num_groups = node.num_groups(); // Create function - auto func = support::cpp14::make_unique<ChannelShuffleLayerFunction>(); + auto func = std::make_unique<ChannelShuffleLayerFunction>(); func->configure(input, output, num_groups); ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " @@ -430,7 +430,7 @@ std::unique_ptr<arm_compute::IFunction> create_concatenate_layer(ConcatenateLaye const size_t concat_axis = get_dimension_idx(data_layout, node.concatenation_axis()); // Create and configure function - auto func = support::cpp14::make_unique<ConcatenateLayerFunction>(); + auto func = std::make_unique<ConcatenateLayerFunction>(); func->configure(inputs, output, concat_axis); // Log info @@ -673,7 +673,7 @@ std::unique_ptr<IFunction> create_depth_to_space_layer(DepthToSpaceLayerNode &no ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<DepthToSpaceLayerFunction>(); + auto func = std::make_unique<DepthToSpaceLayerFunction>(); func->configure(input, output, node.block_shape()); // Log info @@ -712,7 +712,7 @@ std::unique_ptr<IFunction> create_dequantization_layer(DequantizationLayerNode & ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<DequantizationLayerFunction>(); + auto func = std::make_unique<DequantizationLayerFunction>(); func->configure(input, output); // Log info @@ -755,7 +755,7 @@ std::unique_ptr<IFunction> create_detection_output_layer(DetectionOutputLayerNod ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<DetectionOutputLayerFunction>(); + auto func = std::make_unique<DetectionOutputLayerFunction>(); func->configure(input0, input1, input2, output, detect_info); // Log info @@ -807,7 +807,7 @@ std::unique_ptr<IFunction> create_detection_post_process_layer(DetectionPostProc ARM_COMPUTE_ERROR_ON(output3 == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<DetectionPostProcessLayerFunction>(); + auto func = std::make_unique<DetectionPostProcessLayerFunction>(); func->configure(input0, input1, input2, output0, output1, output2, output3, detect_info); // Log info @@ -968,7 +968,7 @@ std::unique_ptr<IFunction> create_flatten_layer(FlattenLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<FlattenLayerFunction>(); + auto func = std::make_unique<FlattenLayerFunction>(); func->configure(input, output); // Log info @@ -1013,7 +1013,7 @@ std::unique_ptr<IFunction> create_fully_connected_layer(FullyConnectedLayerNode // Create and configure function auto wm = get_weights_manager(ctx, TargetInfo::TargetType); auto mm = get_memory_manager(ctx, TargetInfo::TargetType); - auto func = support::cpp14::make_unique<FullyConnectedLayerFunction>(mm, wm.get()); + auto func = std::make_unique<FullyConnectedLayerFunction>(mm, wm.get()); func->configure(input, weights, biases, output, fc_info); const bool is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); @@ -1071,7 +1071,7 @@ std::unique_ptr<IFunction> create_generate_proposals_layer(GenerateProposalsLaye ARM_COMPUTE_ERROR_ON(scores_out == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<GenerateProposalsLayerFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); + auto func = std::make_unique<GenerateProposalsLayerFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); func->configure(scores, deltas, anchors, proposals, scores_out, num_valid_proposals, info); // Log info @@ -1115,7 +1115,7 @@ std::unique_ptr<IFunction> create_l2_normalize_layer(L2NormalizeLayerNode &node, // Create and configure function auto mm = get_memory_manager(ctx, TargetInfo::TargetType); - auto func = support::cpp14::make_unique<L2NormalizeLayerFunction>(mm); + auto func = std::make_unique<L2NormalizeLayerFunction>(mm); func->configure(input, output, axis, epsilon); // Log info @@ -1158,7 +1158,7 @@ std::unique_ptr<IFunction> create_normalization_layer(NormalizationLayerNode &no ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<NormalizationLayerFunction>(); + auto func = std::make_unique<NormalizationLayerFunction>(); func->configure(input, output, norm_info); // Log info @@ -1200,7 +1200,7 @@ std::unique_ptr<IFunction> create_normalize_planar_yuv_layer(NormalizePlanarYUVL ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<NormalizePlanarYUVLayerFunction>(); + auto func = std::make_unique<NormalizePlanarYUVLayerFunction>(); func->configure(input, output, mean, std); // Log info @@ -1238,7 +1238,7 @@ std::unique_ptr<IFunction> create_pad_layer(PadLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<PadLayerFunction>(); + auto func = std::make_unique<PadLayerFunction>(); func->configure(input, output, padding, pad_value); // Log info @@ -1276,7 +1276,7 @@ std::unique_ptr<IFunction> create_permute_layer(PermuteLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<PermuteLayerFunction>(); + auto func = std::make_unique<PermuteLayerFunction>(); func->configure(input, output, perm); // Log info @@ -1315,7 +1315,7 @@ std::unique_ptr<IFunction> create_pooling_layer(PoolingLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<PoolingLayerFunction>(); + auto func = std::make_unique<PoolingLayerFunction>(); func->configure(input, output, pool_info); // Log info @@ -1354,7 +1354,7 @@ std::unique_ptr<IFunction> create_prelu_layer(PReluLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<PReluFunction>(); + auto func = std::make_unique<PReluFunction>(); func->configure(input, alpha, output); // Log info @@ -1423,7 +1423,7 @@ std::unique_ptr<IFunction> create_priorbox_layer(PriorBoxLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<PriorBoxLayerFunction>(); + auto func = std::make_unique<PriorBoxLayerFunction>(); func->configure(input0, input1, output, prior_info); // Log info @@ -1462,7 +1462,7 @@ std::unique_ptr<IFunction> create_quantization_layer(QuantizationLayerNode &node ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<QuantizationLayerFunction>(); + auto func = std::make_unique<QuantizationLayerFunction>(); func->configure(input, output); // Log info @@ -1503,7 +1503,7 @@ std::unique_ptr<IFunction> create_reduction_operation_layer(ReductionLayerNode & ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<ReductionOperationFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); + auto func = std::make_unique<ReductionOperationFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); func->configure(input, output, axis, op, keep_dims); // Log info @@ -1543,7 +1543,7 @@ std::unique_ptr<IFunction> create_reorg_layer(ReorgLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<ReorgLayerFunction>(); + auto func = std::make_unique<ReorgLayerFunction>(); func->configure(input, output, node.stride()); // Log info @@ -1580,7 +1580,7 @@ std::unique_ptr<IFunction> create_reshape_layer(ReshapeLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<ReshapeLayerFunction>(); + auto func = std::make_unique<ReshapeLayerFunction>(); func->configure(input, output); // Log info @@ -1618,7 +1618,7 @@ std::unique_ptr<IFunction> create_resize_layer(ResizeLayerNode &node) const InterpolationPolicy policy = node.policy(); // Create and configure function - auto func = support::cpp14::make_unique<ResizeLayerFunction>(); + auto func = std::make_unique<ResizeLayerFunction>(); func->configure(input, output, ScaleKernelInfo{ policy, BorderMode::CONSTANT }); // Log info @@ -1660,7 +1660,7 @@ std::unique_ptr<IFunction> create_roi_align_layer(ROIAlignLayerNode &node) const ROIPoolingLayerInfo pool_info = node.pooling_info(); // Create and configure function - auto func = support::cpp14::make_unique<ROIAlignLayerFunction>(); + auto func = std::make_unique<ROIAlignLayerFunction>(); func->configure(input, rois, output, pool_info); @@ -1701,7 +1701,7 @@ std::unique_ptr<IFunction> create_slice_layer(SliceLayerNode &node) ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<SliceLayerFunction>(); + auto func = std::make_unique<SliceLayerFunction>(); func->configure(input, output, node.starts(), node.ends()); // Log info @@ -1740,7 +1740,7 @@ std::unique_ptr<IFunction> create_softmax_layer(SoftmaxLayerNode &node, GraphCon ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<SoftmaxLayerFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); + auto func = std::make_unique<SoftmaxLayerFunction>(get_memory_manager(ctx, TargetInfo::TargetType)); func->configure(input, output, beta); // Log info @@ -1781,7 +1781,7 @@ std::unique_ptr<arm_compute::IFunction> create_stack_layer(StackLayerNode &node) const int axis = node.axis(); // Create and configure function - auto func = support::cpp14::make_unique<StackLayerFunction>(); + auto func = std::make_unique<StackLayerFunction>(); func->configure(inputs, axis, output); // Log info @@ -1825,7 +1825,7 @@ std::unique_ptr<IFunction> create_strided_slice_layer(StridedSliceLayerNode &nod ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<StridedSliceLayerFunction>(); + auto func = std::make_unique<StridedSliceLayerFunction>(); func->configure(input, output, starts, ends, strides, info.begin_mask(), info.end_mask(), info.shrink_axis_mask()); // Log info @@ -1868,7 +1868,7 @@ std::unique_ptr<IFunction> create_upsample_layer(UpsampleLayerNode &node, GraphC ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<UpsampleLayerFunction>(); + auto func = std::make_unique<UpsampleLayerFunction>(); func->configure(input, output, info, upsampling_policy); // Log info @@ -1911,7 +1911,7 @@ std::unique_ptr<IFunction> create_yolo_layer(YOLOLayerNode &node, GraphContext & ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<YOLOlayerFunction>(); + auto func = std::make_unique<YOLOlayerFunction>(); func->configure(input, output, act_info, num_classes); // Log info diff --git a/arm_compute/graph/backends/Utils.h b/arm_compute/graph/backends/Utils.h index 7d67f3b9e3..774ce515b5 100644 --- a/arm_compute/graph/backends/Utils.h +++ b/arm_compute/graph/backends/Utils.h @@ -44,7 +44,7 @@ namespace backends template <typename FunctionType, typename FunctionNameType, typename... ParameterType> std::tuple<std::unique_ptr<arm_compute::IFunction>, FunctionNameType> create_named_function(FunctionNameType name, ParameterType... args) { - auto f = arm_compute::support::cpp14::make_unique<FunctionType>(); + auto f = std::make_unique<FunctionType>(); f->configure(std::forward<ParameterType>(args)...); return std::make_pair(std::move(f), name); } @@ -62,7 +62,7 @@ std::tuple<std::unique_ptr<arm_compute::IFunction>, FunctionNameType> create_nam MemoryManagerType mm, ParameterType... args) { - auto f = arm_compute::support::cpp14::make_unique<FunctionType>(mm); + auto f = std::make_unique<FunctionType>(mm); f->configure(std::forward<ParameterType>(args)...); return std::make_pair(std::move(f), name); } diff --git a/arm_compute/graph/frontend/Layers.h b/arm_compute/graph/frontend/Layers.h index 74c40126c8..23f503342b 100644 --- a/arm_compute/graph/frontend/Layers.h +++ b/arm_compute/graph/frontend/Layers.h @@ -300,12 +300,12 @@ public: ConcatLayer(SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) : _sub_streams(), _concat_descriptor(DataLayoutDimension::CHANNEL) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream1))); - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream2))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream1))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream2))); utility::for_each([&](SubStream && sub_stream) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream))); }, std::move(rest_sub_streams)...); } @@ -320,12 +320,12 @@ public: ConcatLayer(descriptors::ConcatLayerDescriptor concat_descriptor, SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) : _sub_streams(), _concat_descriptor(concat_descriptor) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream1))); - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream2))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream1))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream2))); utility::for_each([&](SubStream && sub_stream) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream))); }, std::move(rest_sub_streams)...); } @@ -337,7 +337,7 @@ public: ConcatLayer(SubStream &&sub_stream) : _sub_streams(), _concat_descriptor(DataLayoutDimension::CHANNEL) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream))); } NodeID create_layer(IStream &s) override { @@ -754,8 +754,8 @@ public: : _num_outputs(num_outputs), _weights(nullptr), _bias(nullptr), - _weights_ss(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream_weights))), - _bias_ss(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream_bias))), + _weights_ss(std::make_unique<SubStream>(std::move(sub_stream_weights))), + _bias_ss(std::make_unique<SubStream>(std::move(sub_stream_bias))), _fc_info(fc_info), _weights_quant_info(std::move(weights_quant_info)), _out_quant_info(std::move(out_quant_info)) @@ -1357,12 +1357,12 @@ public: StackLayer(SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) : _sub_streams(), _axis(0) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream1))); - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream2))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream1))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream2))); utility::for_each([&](SubStream && sub_stream) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream))); }, std::move(rest_sub_streams)...); } @@ -1377,12 +1377,12 @@ public: StackLayer(int axis, SubStream &&sub_stream1, SubStream &&sub_stream2, Ts &&... rest_sub_streams) : _sub_streams(), _axis(axis) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream1))); - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream2))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream1))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream2))); utility::for_each([&](SubStream && sub_stream) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream))); }, std::move(rest_sub_streams)...); } @@ -1394,7 +1394,7 @@ public: StackLayer(SubStream &&sub_stream) : _sub_streams(), _axis(0) { - _sub_streams.push_back(arm_compute::support::cpp14::make_unique<SubStream>(std::move(sub_stream))); + _sub_streams.push_back(std::make_unique<SubStream>(std::move(sub_stream))); } NodeID create_layer(IStream &s) override { diff --git a/arm_compute/runtime/Array.h b/arm_compute/runtime/Array.h index 817d97a64d..5b98b6c2bc 100644 --- a/arm_compute/runtime/Array.h +++ b/arm_compute/runtime/Array.h @@ -26,7 +26,6 @@ #include "arm_compute/core/IArray.h" #include "arm_compute/core/Types.h" -#include "support/MemorySupport.h" #include <memory> @@ -47,7 +46,7 @@ public: * @param[in] max_num_values Maximum number of values the array will be able to stored */ Array(size_t max_num_values) - : IArray<T>(max_num_values), _values(arm_compute::support::cpp14::make_unique<T[]>(max_num_values)) + : IArray<T>(max_num_values), _values(std::make_unique<T[]>(max_num_values)) { } diff --git a/arm_compute/runtime/CL/tuners/CLLWSList.h b/arm_compute/runtime/CL/tuners/CLLWSList.h index 48f3f3f7c9..fe63754dd0 100644 --- a/arm_compute/runtime/CL/tuners/CLLWSList.h +++ b/arm_compute/runtime/CL/tuners/CLLWSList.h @@ -30,7 +30,7 @@ #include "arm_compute/runtime/CL/CLTunerTypes.h" #include "support/ToolchainSupport.h" -#include "support/MemorySupport.h" +#include <memory> namespace arm_compute { @@ -199,11 +199,11 @@ public: switch(mode) { case CLTunerMode::EXHAUSTIVE: - return arm_compute::support::cpp14::make_unique<CLLWSListExhaustive>(gws); + return std::make_unique<CLLWSListExhaustive>(gws); case CLTunerMode::NORMAL: - return arm_compute::support::cpp14::make_unique<CLLWSListNormal>(gws); + return std::make_unique<CLLWSListNormal>(gws); case CLTunerMode::RAPID: - return arm_compute::support::cpp14::make_unique<CLLWSListRapid>(gws); + return std::make_unique<CLLWSListRapid>(gws); default: return nullptr; } diff --git a/arm_compute/runtime/CL/tuners/Tuners.h b/arm_compute/runtime/CL/tuners/Tuners.h index dd1c62a252..3ba9e0071d 100644 --- a/arm_compute/runtime/CL/tuners/Tuners.h +++ b/arm_compute/runtime/CL/tuners/Tuners.h @@ -27,8 +27,6 @@ #include "arm_compute/runtime/CL/tuners/BifrostTuner.h" #include "arm_compute/runtime/CL/tuners/MidgardTuner.h" -#include "support/MemorySupport.h" - #include <memory> namespace arm_compute @@ -45,9 +43,9 @@ public: switch(arch) { case GPUTarget::BIFROST: - return support::cpp14::make_unique<BifrostTuner>(); + return std::make_unique<BifrostTuner>(); case GPUTarget::MIDGARD: - return support::cpp14::make_unique<MidgardTuner>(); + return std::make_unique<MidgardTuner>(); default: return nullptr; } diff --git a/arm_compute/runtime/MemoryRegion.h b/arm_compute/runtime/MemoryRegion.h index 63feabd281..6408deceaa 100644 --- a/arm_compute/runtime/MemoryRegion.h +++ b/arm_compute/runtime/MemoryRegion.h @@ -27,7 +27,6 @@ #include "arm_compute/runtime/IMemoryRegion.h" #include "arm_compute/core/Error.h" -#include "support/MemorySupport.h" #include <cstddef> @@ -59,7 +58,7 @@ public: if(alignment != 0) { void *aligned_ptr = _mem.get(); - support::cpp11::align(alignment, size, aligned_ptr, space); + std::align(alignment, size, aligned_ptr, space); _ptr = aligned_ptr; } } @@ -94,7 +93,7 @@ public: { if(_ptr != nullptr && (offset < _size) && (_size - offset >= size)) { - return support::cpp14::make_unique<MemoryRegion>(static_cast<uint8_t *>(_ptr) + offset, size); + return std::make_unique<MemoryRegion>(static_cast<uint8_t *>(_ptr) + offset, size); } else { diff --git a/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h b/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h index fcabc1d0c4..e0054bceff 100644 --- a/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h +++ b/arm_compute/runtime/NEON/functions/NEQLSTMLayer.h @@ -33,9 +33,8 @@ #include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h" #include "arm_compute/runtime/NEON/functions/NEPixelWiseMultiplication.h" #include "arm_compute/runtime/NEON/functions/NETranspose.h" -#include "support/MemorySupport.h" - #include "arm_compute/runtime/common/LSTMParams.h" + #include <memory> namespace arm_compute diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox index 8eb0762f9f..7fe73c42f0 100644 --- a/docs/00_introduction.dox +++ b/docs/00_introduction.dox @@ -86,6 +86,9 @@ If there is more than one release in a month then an extra sequential number is @subsection S2_2_changelog Changelog +v21.02 Public major release + - Upgraded C++ standard to C++14 + v20.11 Public major release - Various bug fixes. - Various optimisations. @@ -1483,29 +1486,29 @@ The examples get automatically built by scons as part of the build process of th To cross compile a NEON example for Linux 32bit: - arm-linux-gnueabihf-g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute -larm_compute_core -o neon_convolution + arm-linux-gnueabihf-g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -mfpu=neon -L. -larm_compute -larm_compute_core -o neon_convolution To cross compile a NEON example for Linux 64bit: - aarch64-linux-gnu-g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -L. -larm_compute -larm_compute_core -o neon_convolution + aarch64-linux-gnu-g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -L. -larm_compute -larm_compute_core -o neon_convolution (notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different) To cross compile an OpenCL example for Linux 32bit: - arm-linux-gnueabihf-g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute -larm_compute_core -o cl_convolution -DARM_COMPUTE_CL + arm-linux-gnueabihf-g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -mfpu=neon -L. -larm_compute -larm_compute_core -o cl_convolution -DARM_COMPUTE_CL To cross compile an OpenCL example for Linux 64bit: - aarch64-linux-gnu-g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -L. -larm_compute -larm_compute_core -o cl_convolution -DARM_COMPUTE_CL + aarch64-linux-gnu-g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -L. -larm_compute -larm_compute_core -o cl_convolution -DARM_COMPUTE_CL To cross compile a GLES example for Linux 32bit: - arm-linux-gnueabihf-g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++11 -mfpu=neon -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff + arm-linux-gnueabihf-g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++14 -mfpu=neon -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff To cross compile a GLES example for Linux 64bit: - aarch64-linux-gnu-g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++11 -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff + aarch64-linux-gnu-g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++14 -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff (notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different) @@ -1513,11 +1516,11 @@ To cross compile the examples with the Graph API, such as graph_lenet.cpp, you n i.e. to cross compile the "graph_lenet" example for Linux 32bit: - arm-linux-gnueabihf-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet + arm-linux-gnueabihf-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++14 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet i.e. to cross compile the "graph_lenet" example for Linux 64bit: - aarch64-linux-gnu-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet + aarch64-linux-gnu-g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++14 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet (notice the only difference with the 32 bit command is that we don't need the -mfpu option and the compiler's name is different) @@ -1525,31 +1528,31 @@ i.e. to cross compile the "graph_lenet" example for Linux 64bit: To compile natively (i.e directly on an ARM device) for NEON for Linux 32bit: - g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -mfpu=neon -larm_compute -larm_compute_core -o neon_convolution + g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -mfpu=neon -larm_compute -larm_compute_core -o neon_convolution To compile natively (i.e directly on an ARM device) for NEON for Linux 64bit: - g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute -larm_compute_core -o neon_convolution + g++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute -larm_compute_core -o neon_convolution (notice the only difference with the 32 bit command is that we don't need the -mfpu option) To compile natively (i.e directly on an ARM device) for OpenCL for Linux 32bit or Linux 64bit: - g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute -larm_compute_core -o cl_convolution -DARM_COMPUTE_CL + g++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute -larm_compute_core -o cl_convolution -DARM_COMPUTE_CL To compile natively (i.e directly on an ARM device) for GLES for Linux 32bit or Linux 64bit: - g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++11 -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff + g++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude/ -L. -larm_compute -larm_compute_core -std=c++14 -DARM_COMPUTE_GC -Iinclude/linux/ -o gc_absdiff To compile natively the examples with the Graph API, such as graph_lenet.cpp, you need to link the examples against arm_compute_graph.so too. i.e. to natively compile the "graph_lenet" example for Linux 32bit: - g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet + g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++14 -mfpu=neon -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet i.e. to natively compile the "graph_lenet" example for Linux 64bit: - g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet + g++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++14 -L. -larm_compute_graph -larm_compute -larm_compute_core -Wl,--allow-shlib-undefined -o graph_lenet (notice the only difference with the 32 bit command is that we don't need the -mfpu option) @@ -1623,30 +1626,30 @@ Once you've got your Android standalone toolchain built and added to your path y To cross compile a NEON example: #32 bit: - arm-linux-androideabi-clang++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o neon_convolution_arm -static-libstdc++ -pie + arm-linux-androideabi-clang++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute-static -larm_compute_core-static -L. -o neon_convolution_arm -static-libstdc++ -pie #64 bit: - aarch64-linux-android-clang++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o neon_convolution_aarch64 -static-libstdc++ -pie + aarch64-linux-android-clang++ examples/neon_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute-static -larm_compute_core-static -L. -o neon_convolution_aarch64 -static-libstdc++ -pie To cross compile an OpenCL example: #32 bit: - arm-linux-androideabi-clang++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o cl_convolution_arm -static-libstdc++ -pie -DARM_COMPUTE_CL + arm-linux-androideabi-clang++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute-static -larm_compute_core-static -L. -o cl_convolution_arm -static-libstdc++ -pie -DARM_COMPUTE_CL #64 bit: - aarch64-linux-android-clang++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o cl_convolution_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_CL + aarch64-linux-android-clang++ examples/cl_convolution.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute-static -larm_compute_core-static -L. -o cl_convolution_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_CL To cross compile a GLES example: #32 bit: - arm-linux-androideabi-clang++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o gc_absdiff_arm -static-libstdc++ -pie -DARM_COMPUTE_GC + arm-linux-androideabi-clang++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute-static -larm_compute_core-static -L. -o gc_absdiff_arm -static-libstdc++ -pie -DARM_COMPUTE_GC #64 bit: - aarch64-linux-android-clang++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude -std=c++11 -larm_compute-static -larm_compute_core-static -L. -o gc_absdiff_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_GC + aarch64-linux-android-clang++ examples/gc_absdiff.cpp utils/Utils.cpp -I. -Iinclude -std=c++14 -larm_compute-static -larm_compute_core-static -L. -o gc_absdiff_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_GC To cross compile the examples with the Graph API, such as graph_lenet.cpp, you need to link the library arm_compute_graph also. #32 bit: - arm-linux-androideabi-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_arm -static-libstdc++ -pie -DARM_COMPUTE_CL + arm-linux-androideabi-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++14 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_arm -static-libstdc++ -pie -DARM_COMPUTE_CL #64 bit: - aarch64-linux-android-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++11 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_CL + aarch64-linux-android-clang++ examples/graph_lenet.cpp utils/Utils.cpp utils/GraphUtils.cpp utils/CommonGraphOptions.cpp -I. -Iinclude -std=c++14 -Wl,--whole-archive -larm_compute_graph-static -Wl,--no-whole-archive -larm_compute-static -larm_compute_core-static -L. -o graph_lenet_aarch64 -static-libstdc++ -pie -DARM_COMPUTE_CL @note Due to some issues in older versions of the Mali OpenCL DDK (<= r13p0), we recommend to link arm_compute statically on Android. @note When linked statically the arm_compute_graph library currently needs the --whole-archive linker flag in order to work properly diff --git a/docs/05_contribution_guidelines.dox b/docs/05_contribution_guidelines.dox index 1cdd129733..35b9f49dbc 100644 --- a/docs/05_contribution_guidelines.dox +++ b/docs/05_contribution_guidelines.dox @@ -391,7 +391,7 @@ In order to deprecate an existing API, these rules should be followed. - Deprecation of runtime APIs should strictly follow the aforementioned period, whereas core APIs can have more flexibility as they are mostly used internally rather than user-facing. - Any API changes (update, addition and deprecation) in all components should be well documented by the contribution itself. -Also, it is recommended to use the following utility macros which is designed to work with both clang and gcc using C++11 and later. +Also, it is recommended to use the following utility macros which is designed to work with both clang and gcc using C++14 and later. - ARM_COMPUTE_DEPRECATED: Just deprecate the wrapped function - ARM_COMPUTE_DEPRECATED_REL: Deprecate the wrapped function and also capture the release that was deprecated diff --git a/docs/Doxyfile b/docs/Doxyfile index bdc4b776d3..51548dc2d4 100644 --- a/docs/Doxyfile +++ b/docs/Doxyfile @@ -1082,7 +1082,7 @@ CLANG_ASSISTED_PARSING = NO # specified with INPUT and INCLUDE_PATH. # This tag requires that the tag CLANG_ASSISTED_PARSING is set to YES. -CLANG_OPTIONS = -std=c++11 +CLANG_OPTIONS = -std=c++14 #--------------------------------------------------------------------------- # Configuration options related to the alphabetical class index diff --git a/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp b/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp index c6818e48b0..8323bbd971 100644 --- a/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp +++ b/examples/gemm_tuner/cl_gemmlowp_reshaped_rhs_only_fused_output_stage_fixedpoint.cpp @@ -280,7 +280,7 @@ public: const TensorInfo info_vector_sum_row(compute_reductionB_shape(*lhs.info()), 1, DataType::S32); vector_sum_row.allocator()->init(info_vector_sum_row); - mtx_a_reduction = support::cpp14::make_unique<CLGEMMLowpMatrixAReduction>(); + mtx_a_reduction = std::make_unique<CLGEMMLowpMatrixAReduction>(); if(!mtx_a_reduction->validate(lhs.info(), vector_sum_row.info(), GEMMLowpReductionKernelInfo{})) { diff --git a/examples/graph_alexnet.cpp b/examples/graph_alexnet.cpp index 40bbee1d68..ce398be6cf 100644 --- a/examples/graph_alexnet.cpp +++ b/examples/graph_alexnet.cpp @@ -70,7 +70,7 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_googlenet.cpp b/examples/graph_googlenet.cpp index ed5cbd5120..0a53355611 100644 --- a/examples/graph_googlenet.cpp +++ b/examples/graph_googlenet.cpp @@ -66,7 +66,7 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_inception_resnet_v1.cpp b/examples/graph_inception_resnet_v1.cpp index 7c0bb0ce48..7a55733a20 100644 --- a/examples/graph_inception_resnet_v1.cpp +++ b/examples/graph_inception_resnet_v1.cpp @@ -92,7 +92,7 @@ public: } // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(0.f, 1.f); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(0.f, 1.f); // Create input descriptor const auto operation_layout = common_params.data_layout; @@ -207,7 +207,7 @@ public: get_weights_accessor(data_path, "Logits_Logits_weights.npy", weights_layout), get_weights_accessor(data_path, "Logits_Logits_biases.npy")) .set_name("Logits/Logits") - << OutputLayer(arm_compute::support::cpp14::make_unique<DummyAccessor>(0)); + << OutputLayer(std::make_unique<DummyAccessor>(0)); // Finalize graph GraphConfig config; diff --git a/examples/graph_inception_resnet_v2.cpp b/examples/graph_inception_resnet_v2.cpp index d14c34eb9d..60236d0780 100644 --- a/examples/graph_inception_resnet_v2.cpp +++ b/examples/graph_inception_resnet_v2.cpp @@ -76,7 +76,7 @@ public: } // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(0.f, 1.f); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(0.f, 1.f); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_inception_v3.cpp b/examples/graph_inception_v3.cpp index 4b6dc8d296..5cacbcb6e1 100644 --- a/examples/graph_inception_v3.cpp +++ b/examples/graph_inception_v3.cpp @@ -62,7 +62,7 @@ public: std::string data_path = common_params.data_path; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_inception_v4.cpp b/examples/graph_inception_v4.cpp index 553c96d3e4..db2a31047e 100644 --- a/examples/graph_inception_v4.cpp +++ b/examples/graph_inception_v4.cpp @@ -66,7 +66,7 @@ public: std::string data_path = common_params.data_path; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_mobilenet.cpp b/examples/graph_mobilenet.cpp index f74d25189d..b73f7a2abd 100644 --- a/examples/graph_mobilenet.cpp +++ b/examples/graph_mobilenet.cpp @@ -124,7 +124,7 @@ private: std::string model_path = (model_id == 0) ? "/cnn_data/mobilenet_v1_1_224_model/" : "/cnn_data/mobilenet_v1_075_160_model/"; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Get trainable parameters data path std::string data_path = common_params.data_path; diff --git a/examples/graph_mobilenet_v2.cpp b/examples/graph_mobilenet_v2.cpp index 5ee1f7e52a..fa16c94645 100644 --- a/examples/graph_mobilenet_v2.cpp +++ b/examples/graph_mobilenet_v2.cpp @@ -129,7 +129,7 @@ private: const std::string model_path = "/cnn_data/mobilenet_v2_1.0_224_model/"; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Get trainable parameters data path std::string data_path = common_params.data_path; diff --git a/examples/graph_resnet12.cpp b/examples/graph_resnet12.cpp index badcaec107..ebd2e5dd16 100644 --- a/examples/graph_resnet12.cpp +++ b/examples/graph_resnet12.cpp @@ -81,7 +81,7 @@ public: const std::string model_path = "/cnn_data/resnet12_model/"; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Create input descriptor const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 3U, 1U), DataLayout::NCHW, common_params.data_layout); @@ -128,7 +128,7 @@ public: .set_name("conv12/convolution") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH)).set_name("conv12/Tanh") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LINEAR, 0.58f, 0.5f)).set_name("conv12/Linear") - << OutputLayer(arm_compute::support::cpp14::make_unique<DummyAccessor>(0)); + << OutputLayer(std::make_unique<DummyAccessor>(0)); // Finalize graph GraphConfig config; diff --git a/examples/graph_resnet50.cpp b/examples/graph_resnet50.cpp index 2939ee40c4..47d258ede7 100644 --- a/examples/graph_resnet50.cpp +++ b/examples/graph_resnet50.cpp @@ -63,8 +63,8 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb, - false /* Do not convert to BGR */); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb, + false /* Do not convert to BGR */); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_resnet_v2_50.cpp b/examples/graph_resnet_v2_50.cpp index 32434f55dd..921fb145d6 100644 --- a/examples/graph_resnet_v2_50.cpp +++ b/examples/graph_resnet_v2_50.cpp @@ -67,7 +67,7 @@ public: } // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_shufflenet.cpp b/examples/graph_shufflenet.cpp index 08f884b75f..300d0f15a1 100644 --- a/examples/graph_shufflenet.cpp +++ b/examples/graph_shufflenet.cpp @@ -89,7 +89,7 @@ public: const DataLayout weights_layout = DataLayout::NCHW; // Create preprocessor - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(0); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(0); graph << common_params.target << common_params.fast_math_hint diff --git a/examples/graph_squeezenet.cpp b/examples/graph_squeezenet.cpp index f0d620c67d..2e72c14763 100644 --- a/examples/graph_squeezenet.cpp +++ b/examples/graph_squeezenet.cpp @@ -63,7 +63,7 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_squeezenet_v1_1.cpp b/examples/graph_squeezenet_v1_1.cpp index c60448639d..1708ac2f5a 100644 --- a/examples/graph_squeezenet_v1_1.cpp +++ b/examples/graph_squeezenet_v1_1.cpp @@ -63,7 +63,7 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 122.68f, 116.67f, 104.01f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_srcnn955.cpp b/examples/graph_srcnn955.cpp index a95f0c1d25..bcc3824c60 100644 --- a/examples/graph_srcnn955.cpp +++ b/examples/graph_srcnn955.cpp @@ -78,7 +78,7 @@ public: const std::string model_path = "/cnn_data/srcnn955_model/"; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Create input descriptor const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 3U, 1U), DataLayout::NCHW, common_params.data_layout); @@ -111,7 +111,7 @@ public: PadStrideInfo(1, 1, 2, 2)) .set_name("conv3/convolution") << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv3/Relu") - << OutputLayer(arm_compute::support::cpp14::make_unique<DummyAccessor>(0)); + << OutputLayer(std::make_unique<DummyAccessor>(0)); // Finalize graph GraphConfig config; diff --git a/examples/graph_ssd_mobilenet.cpp b/examples/graph_ssd_mobilenet.cpp index edd4c94d02..f5af84f4d4 100644 --- a/examples/graph_ssd_mobilenet.cpp +++ b/examples/graph_ssd_mobilenet.cpp @@ -216,7 +216,7 @@ private: { // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 127.5f, 127.5f, 127.5f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb, true, 0.007843f); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb, true, 0.007843f); // Get trainable parameters data path std::string data_path = common_params.data_path; diff --git a/examples/graph_vgg16.cpp b/examples/graph_vgg16.cpp index 990040b5ef..a4c5e6bbd2 100644 --- a/examples/graph_vgg16.cpp +++ b/examples/graph_vgg16.cpp @@ -63,7 +63,7 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 123.68f, 116.779f, 103.939f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_vgg19.cpp b/examples/graph_vgg19.cpp index 9215ba7b61..c95fb03368 100644 --- a/examples/graph_vgg19.cpp +++ b/examples/graph_vgg19.cpp @@ -62,7 +62,7 @@ public: // Create a preprocessor object const std::array<float, 3> mean_rgb{ { 123.68f, 116.779f, 103.939f } }; - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<CaffePreproccessor>(mean_rgb); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<CaffePreproccessor>(mean_rgb); // Create input descriptor const auto operation_layout = common_params.data_layout; diff --git a/examples/graph_vgg_vdsr.cpp b/examples/graph_vgg_vdsr.cpp index 65c0642485..3fa7dd1330 100644 --- a/examples/graph_vgg_vdsr.cpp +++ b/examples/graph_vgg_vdsr.cpp @@ -79,7 +79,7 @@ public: const std::string model_path = "/cnn_data/vdsr_model/"; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(); // Create input descriptor const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 1U, 1U), DataLayout::NCHW, common_params.data_layout); @@ -132,7 +132,7 @@ public: // Add residual to input graph << EltwiseLayer(std::move(left), std::move(right), EltwiseOperation::Add).set_name("add") - << OutputLayer(arm_compute::support::cpp14::make_unique<DummyAccessor>(0)); + << OutputLayer(std::make_unique<DummyAccessor>(0)); // Finalize graph GraphConfig config; diff --git a/examples/graph_yolov3.cpp b/examples/graph_yolov3.cpp index c7f917ba6e..79d891a308 100644 --- a/examples/graph_yolov3.cpp +++ b/examples/graph_yolov3.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -66,7 +66,7 @@ public: std::string data_path = common_params.data_path; // Create a preprocessor object - std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>(0.f); + std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>(0.f); // Create input descriptor const TensorShape tensor_shape = permute_shape(TensorShape(608U, 608U, 3U, 1U), DataLayout::NCHW, common_params.data_layout); diff --git a/examples/neon_cnn.cpp b/examples/neon_cnn.cpp index 85f8792b9c..339c8c1a81 100644 --- a/examples/neon_cnn.cpp +++ b/examples/neon_cnn.cpp @@ -53,10 +53,10 @@ public: // The weights and biases tensors should be initialized with the values inferred with the training // Set memory manager where allowed to manage internal memory requirements - conv0 = arm_compute::support::cpp14::make_unique<NEConvolutionLayer>(mm_layers); - conv1 = arm_compute::support::cpp14::make_unique<NEConvolutionLayer>(mm_layers); - fc0 = arm_compute::support::cpp14::make_unique<NEFullyConnectedLayer>(mm_layers); - softmax = arm_compute::support::cpp14::make_unique<NESoftmaxLayer>(mm_layers); + conv0 = std::make_unique<NEConvolutionLayer>(mm_layers); + conv1 = std::make_unique<NEConvolutionLayer>(mm_layers); + fc0 = std::make_unique<NEFullyConnectedLayer>(mm_layers); + softmax = std::make_unique<NESoftmaxLayer>(mm_layers); /* [Initialize tensors] */ @@ -170,8 +170,8 @@ public: // We need 2 memory groups for handling the input and output // We call explicitly allocate after manage() in order to avoid overlapping lifetimes - memory_group0 = arm_compute::support::cpp14::make_unique<MemoryGroup>(mm_transitions); - memory_group1 = arm_compute::support::cpp14::make_unique<MemoryGroup>(mm_transitions); + memory_group0 = std::make_unique<MemoryGroup>(mm_transitions); + memory_group1 = std::make_unique<MemoryGroup>(mm_transitions); memory_group0->manage(&out_conv0); out_conv0.allocator()->allocate(); diff --git a/scripts/clang_tidy_rules.py b/scripts/clang_tidy_rules.py index ce467f8f55..1e24b042de 100755 --- a/scripts/clang_tidy_rules.py +++ b/scripts/clang_tidy_rules.py @@ -16,7 +16,7 @@ def get_list_includes(): def get_list_flags( filename, arch): assert arch in ["armv7", "aarch64"] - flags = ["-std=c++11"] + flags = ["-std=c++14"] flags.append("-DARM_COMPUTE_CPP_SCHEDULER=1") flags.append("-DARM_COMPUTE_CL") flags.append("-DARM_COMPUTE_GC") diff --git a/src/core/CL/gemm/native/CLGEMMNativeKernelConfiguration.h b/src/core/CL/gemm/native/CLGEMMNativeKernelConfiguration.h index aecf5a8aa8..65396b1d98 100644 --- a/src/core/CL/gemm/native/CLGEMMNativeKernelConfiguration.h +++ b/src/core/CL/gemm/native/CLGEMMNativeKernelConfiguration.h @@ -29,7 +29,7 @@ #include "src/core/CL/gemm/native/CLGEMMNativeKernelConfigurationMidgard.h" #include "src/core/CL/gemm/native/CLGEMMNativeKernelConfigurationValhall.h" -#include "support/MemorySupport.h" +#include <memory> namespace arm_compute { @@ -50,11 +50,11 @@ public: switch(get_arch_from_target(gpu)) { case GPUTarget::MIDGARD: - return support::cpp14::make_unique<CLGEMMNativeKernelConfigurationMidgard>(gpu); + return std::make_unique<CLGEMMNativeKernelConfigurationMidgard>(gpu); case GPUTarget::BIFROST: - return support::cpp14::make_unique<CLGEMMNativeKernelConfigurationBifrost>(gpu); + return std::make_unique<CLGEMMNativeKernelConfigurationBifrost>(gpu); case GPUTarget::VALHALL: - return support::cpp14::make_unique<CLGEMMNativeKernelConfigurationValhall>(gpu); + return std::make_unique<CLGEMMNativeKernelConfigurationValhall>(gpu); default: ARM_COMPUTE_ERROR("Not supported GPU target"); } diff --git a/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfiguration.h b/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfiguration.h index 21ccf2d647..2a25dc1893 100644 --- a/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfiguration.h +++ b/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfiguration.h @@ -28,7 +28,7 @@ #include "src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationBifrost.h" #include "src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationValhall.h" -#include "support/MemorySupport.h" +#include <memory> namespace arm_compute { @@ -50,9 +50,9 @@ public: { case GPUTarget::MIDGARD: case GPUTarget::BIFROST: - return support::cpp14::make_unique<CLGEMMReshapedKernelConfigurationBifrost>(gpu); + return std::make_unique<CLGEMMReshapedKernelConfigurationBifrost>(gpu); case GPUTarget::VALHALL: - return support::cpp14::make_unique<CLGEMMReshapedKernelConfigurationValhall>(gpu); + return std::make_unique<CLGEMMReshapedKernelConfigurationValhall>(gpu); default: ARM_COMPUTE_ERROR("Not supported GPU target"); } diff --git a/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfiguration.h b/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfiguration.h index 4efe28ce69..96c3045119 100644 --- a/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfiguration.h +++ b/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfiguration.h @@ -28,7 +28,7 @@ #include "src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationBifrost.h" #include "src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationValhall.h" -#include "support/MemorySupport.h" +#include <memory> namespace arm_compute { @@ -50,9 +50,9 @@ public: { case GPUTarget::MIDGARD: case GPUTarget::BIFROST: - return support::cpp14::make_unique<CLGEMMReshapedOnlyRHSKernelConfigurationBifrost>(gpu); + return std::make_unique<CLGEMMReshapedOnlyRHSKernelConfigurationBifrost>(gpu); case GPUTarget::VALHALL: - return support::cpp14::make_unique<CLGEMMReshapedOnlyRHSKernelConfigurationValhall>(gpu); + return std::make_unique<CLGEMMReshapedOnlyRHSKernelConfigurationValhall>(gpu); default: ARM_COMPUTE_ERROR("Not supported GPU target"); } diff --git a/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp b/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp index 211ebdec90..f5a0b370ab 100644 --- a/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp +++ b/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp @@ -33,11 +33,11 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "src/core/AccessWindowStatic.h" #include "src/core/NEON/kernels/convolution/common/utils.hpp" +#include "src/core/NEON/kernels/convolution/winograd/winograd_layer.hpp" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" -#include "support/MemorySupport.h" -#include "src/core/NEON/kernels/convolution/winograd/winograd_layer.hpp" +#include <memory> namespace arm_compute { @@ -225,7 +225,7 @@ void NEWinogradLayerTransformWeightsKernel<T, OutputTileRows, OutputTileCols, Ke _matrix_stride = matrix_stride; _num_output_channels = num_output_channels; _num_input_channels = num_input_channels; - _transform = arm_compute::support::cpp14::make_unique<WeightsTransform>(num_output_channels, num_input_channels); + _transform = std::make_unique<WeightsTransform>(num_output_channels, num_input_channels); Window win; auto win_last = _transform->get_window(); @@ -348,7 +348,7 @@ void NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, Kern _padding_bottom = (padding == PADDING_SAME) ? iceildiv(KernelRows - 1, 2) : 0; _padding_right = (padding == PADDING_SAME) ? iceildiv(KernelCols - 1, 2) : 0; - _transform = arm_compute::support::cpp14::make_unique<InputTransform>( + _transform = std::make_unique<InputTransform>( KernelRows, KernelCols, num_batches, @@ -492,7 +492,7 @@ void NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileCols, Ker _num_cols = num_cols; _num_channels = num_channels; // We don't have the biases buffer at this stage as it hasn't been allocated, we pass in nullptr OutputTransform is only used here to compute the window - _transform = arm_compute::support::cpp14::make_unique<OutputTransform>(num_batches, num_rows, num_cols, num_channels, activation); + _transform = std::make_unique<OutputTransform>(num_batches, num_rows, num_cols, num_channels, activation); Window win; auto win_last = _transform->get_window(); win.set(Window::DimX, Window::Dimension(0, win_last, 1)); diff --git a/src/core/TensorInfo.cpp b/src/core/TensorInfo.cpp index 414c128a27..7b1f9c542a 100644 --- a/src/core/TensorInfo.cpp +++ b/src/core/TensorInfo.cpp @@ -29,7 +29,8 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "src/core/helpers/Utils.h" -#include "support/MemorySupport.h" + +#include <memory> using namespace arm_compute; @@ -314,7 +315,7 @@ bool TensorInfo::extend_padding(const PaddingSize &padding) std::unique_ptr<ITensorInfo> TensorInfo::clone() const { - return support::cpp14::make_unique<TensorInfo>(*this); + return std::make_unique<TensorInfo>(*this); } ITensorInfo &TensorInfo::set_data_type(DataType data_type) diff --git a/src/core/utils/logging/Logger.cpp b/src/core/utils/logging/Logger.cpp index 05c5fa07d0..70b5868da8 100644 --- a/src/core/utils/logging/Logger.cpp +++ b/src/core/utils/logging/Logger.cpp @@ -24,7 +24,8 @@ #include "arm_compute/core/utils/logging/Logger.h" #include "arm_compute/core/Error.h" -#include "support/MemorySupport.h" + +#include <memory> using namespace arm_compute::logging; @@ -116,9 +117,9 @@ void Logger::add_decorator(std::unique_ptr<IDecorator> decorator) void Logger::set_default_decorators() { - _decorators.emplace_back(support::cpp14::make_unique<StringDecorator>(_name)); - _decorators.emplace_back(support::cpp14::make_unique<DateDecorator>()); - _decorators.emplace_back(support::cpp14::make_unique<LogLevelDecorator>()); + _decorators.emplace_back(std::make_unique<StringDecorator>(_name)); + _decorators.emplace_back(std::make_unique<DateDecorator>()); + _decorators.emplace_back(std::make_unique<LogLevelDecorator>()); } bool Logger::is_loggable(LogLevel log_level) diff --git a/src/graph/Graph.cpp b/src/graph/Graph.cpp index af75eacc02..4ce53589d4 100644 --- a/src/graph/Graph.cpp +++ b/src/graph/Graph.cpp @@ -96,7 +96,7 @@ EdgeID Graph::add_connection(NodeID source, size_t source_idx, NodeID sink, size // Create connections EdgeID eid = _edges.size(); - auto connection = arm_compute::support::cpp14::make_unique<Edge>(eid, source_node.get(), source_idx, sink_node.get(), sink_idx, tensor.get()); + auto connection = std::make_unique<Edge>(eid, source_node.get(), source_idx, sink_node.get(), sink_idx, tensor.get()); _edges.push_back(std::move(connection)); // Add connections to source and sink nodes @@ -155,7 +155,7 @@ bool Graph::remove_connection(EdgeID eid) TensorID Graph::create_tensor(const TensorDescriptor &desc) { TensorID tid = _tensors.size(); - auto tensor = support::cpp14::make_unique<Tensor>(tid, desc); + auto tensor = std::make_unique<Tensor>(tid, desc); _tensors.push_back(std::move(tensor)); return tid; diff --git a/src/graph/Utils.cpp b/src/graph/Utils.cpp index 64890585e0..2835af311a 100644 --- a/src/graph/Utils.cpp +++ b/src/graph/Utils.cpp @@ -83,16 +83,16 @@ PassManager create_default_pass_manager(Target target, const GraphConfig &cfg) // Passes that mutate graph IR if(cfg.convert_to_uint8) { - pm.append(support::cpp14::make_unique<SyntheticDataTypeMutator>(), !is_target_gc); + pm.append(std::make_unique<SyntheticDataTypeMutator>(), !is_target_gc); } - pm.append(support::cpp14::make_unique<NodeFusionMutator>(), !is_target_gc); - pm.append(support::cpp14::make_unique<GroupedConvolutionMutator>()); - pm.append(support::cpp14::make_unique<InPlaceOperationMutator>(), !is_target_gc); + pm.append(std::make_unique<NodeFusionMutator>(), !is_target_gc); + pm.append(std::make_unique<GroupedConvolutionMutator>()); + pm.append(std::make_unique<InPlaceOperationMutator>(), !is_target_gc); // Passes that mutate backend information - pm.append(support::cpp14::make_unique<DepthConcatSubTensorMutator>(), !is_target_gc); - pm.append(support::cpp14::make_unique<SplitLayerSubTensorMutator>(), !is_target_gc); - pm.append(support::cpp14::make_unique<NodeExecutionMethodMutator>()); + pm.append(std::make_unique<DepthConcatSubTensorMutator>(), !is_target_gc); + pm.append(std::make_unique<SplitLayerSubTensorMutator>(), !is_target_gc); + pm.append(std::make_unique<NodeExecutionMethodMutator>()); return pm; } diff --git a/src/graph/backends/CL/CLDeviceBackend.cpp b/src/graph/backends/CL/CLDeviceBackend.cpp index b2d58e35be..bc7bbddbd8 100644 --- a/src/graph/backends/CL/CLDeviceBackend.cpp +++ b/src/graph/backends/CL/CLDeviceBackend.cpp @@ -93,7 +93,7 @@ void CLDeviceBackend::initialize_backend() // Setup Scheduler CLScheduler::get().default_init(&_tuner); // Create allocator with new context - _allocator = support::cpp14::make_unique<CLBufferAllocator>(nullptr /* legacy path for CLCoreRuntimeContext */); + _allocator = std::make_unique<CLBufferAllocator>(nullptr /* legacy path for CLCoreRuntimeContext */); } void CLDeviceBackend::release_backend_context(GraphContext &ctx) @@ -170,7 +170,7 @@ std::unique_ptr<ITensorHandle> CLDeviceBackend::create_tensor(const Tensor &tens TensorInfo info(tensor_desc.shape, 1, tensor_desc.data_type, tensor_desc.quant_info); info.set_data_layout(tensor_desc.layout); - return support::cpp14::make_unique<CLTensorHandle>(info); + return std::make_unique<CLTensorHandle>(info); } std::unique_ptr<ITensorHandle> CLDeviceBackend::create_subtensor(ITensorHandle *parent, TensorShape shape, Coordinates coords, bool extend_parent) @@ -180,7 +180,7 @@ std::unique_ptr<ITensorHandle> CLDeviceBackend::create_subtensor(ITensorHandle * return nullptr; } - return support::cpp14::make_unique<CLSubTensorHandle>(parent, shape, coords, extend_parent); + return std::make_unique<CLSubTensorHandle>(parent, shape, coords, extend_parent); } std::unique_ptr<arm_compute::IFunction> CLDeviceBackend::configure_node(INode &node, GraphContext &ctx) diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp index 98013b9e49..641dcc36ce 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -143,7 +143,7 @@ std::unique_ptr<IFunction> create_detection_output_layer<CPPDetectionOutputLayer ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<CPPDetectionOutputLayer>(); + auto func = std::make_unique<CPPDetectionOutputLayer>(); func->configure(input0, input1, input2, output, detect_info); // Log info @@ -159,7 +159,7 @@ std::unique_ptr<IFunction> create_detection_output_layer<CPPDetectionOutputLayer << " DetectionOutputLayer info: " << detect_info << std::endl); - auto wrap_function = support::cpp14::make_unique<CPPWrapperFunction>(); + auto wrap_function = std::make_unique<CPPWrapperFunction>(); wrap_function->register_function(std::move(func)); wrap_function->register_tensor(input0); @@ -193,7 +193,7 @@ std::unique_ptr<IFunction> create_detection_post_process_layer<CPPDetectionPostP ARM_COMPUTE_ERROR_ON(output3 == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<CPPDetectionPostProcessLayer>(); + auto func = std::make_unique<CPPDetectionPostProcessLayer>(); func->configure(input0, input1, input2, output0, output1, output2, output3, detect_info); // Log info @@ -212,7 +212,7 @@ std::unique_ptr<IFunction> create_detection_post_process_layer<CPPDetectionPostP << " DetectionPostProcessLayer info: " << detect_info << std::endl); - auto wrap_function = support::cpp14::make_unique<CPPWrapperFunction>(); + auto wrap_function = std::make_unique<CPPWrapperFunction>(); wrap_function->register_function(std::move(func)); wrap_function->register_tensor(input0); diff --git a/src/graph/backends/GLES/GCDeviceBackend.cpp b/src/graph/backends/GLES/GCDeviceBackend.cpp index 252093cf2e..dcab2a5697 100644 --- a/src/graph/backends/GLES/GCDeviceBackend.cpp +++ b/src/graph/backends/GLES/GCDeviceBackend.cpp @@ -112,7 +112,7 @@ std::unique_ptr<ITensorHandle> GCDeviceBackend::create_tensor(const Tensor &tens TensorInfo info(tensor_desc.shape, 1, tensor_desc.data_type, tensor_desc.quant_info); info.set_data_layout(tensor_desc.layout); - return support::cpp14::make_unique<GCTensorHandle>(info); + return std::make_unique<GCTensorHandle>(info); } std::unique_ptr<ITensorHandle> GCDeviceBackend::create_subtensor(ITensorHandle *parent, TensorShape shape, Coordinates coords, bool extend_parent) diff --git a/src/graph/backends/NEON/NEDeviceBackend.cpp b/src/graph/backends/NEON/NEDeviceBackend.cpp index adb87a952b..7f87710cf3 100644 --- a/src/graph/backends/NEON/NEDeviceBackend.cpp +++ b/src/graph/backends/NEON/NEDeviceBackend.cpp @@ -123,7 +123,7 @@ std::unique_ptr<ITensorHandle> NEDeviceBackend::create_tensor(const Tensor &tens TensorInfo info(tensor_desc.shape, 1, tensor_desc.data_type, tensor_desc.quant_info); info.set_data_layout(tensor_desc.layout); - return support::cpp14::make_unique<NETensorHandle>(info); + return std::make_unique<NETensorHandle>(info); } std::unique_ptr<ITensorHandle> NEDeviceBackend::create_subtensor(ITensorHandle *parent, TensorShape shape, Coordinates coords, bool extend_parent) @@ -133,7 +133,7 @@ std::unique_ptr<ITensorHandle> NEDeviceBackend::create_subtensor(ITensorHandle * return nullptr; } - return support::cpp14::make_unique<NESubTensorHandle>(parent, shape, coords, extend_parent); + return std::make_unique<NESubTensorHandle>(parent, shape, coords, extend_parent); } std::unique_ptr<arm_compute::IFunction> NEDeviceBackend::configure_node(INode &node, GraphContext &ctx) diff --git a/src/graph/backends/NEON/NEFunctionFactory.cpp b/src/graph/backends/NEON/NEFunctionFactory.cpp index ec06f3fa30..d070433e4d 100644 --- a/src/graph/backends/NEON/NEFunctionFactory.cpp +++ b/src/graph/backends/NEON/NEFunctionFactory.cpp @@ -102,7 +102,7 @@ std::unique_ptr<IFunction> create_normalization_layer<NENormalizationLayer, NETa ARM_COMPUTE_ERROR_ON(output == nullptr); // Create and configure function - auto func = support::cpp14::make_unique<NENormalizationLayer>(get_memory_manager(ctx, NETargetInfo::TargetType)); + auto func = std::make_unique<NENormalizationLayer>(get_memory_manager(ctx, NETargetInfo::TargetType)); func->configure(input, output, norm_info); // Log info diff --git a/src/graph/mutators/SyntheticDataTypeMutator.cpp b/src/graph/mutators/SyntheticDataTypeMutator.cpp index 532c0e821b..21bafa61e1 100644 --- a/src/graph/mutators/SyntheticDataTypeMutator.cpp +++ b/src/graph/mutators/SyntheticDataTypeMutator.cpp @@ -222,7 +222,7 @@ void handle_nodes_with_bias(Graph &g) auto depth = b_desc.shape[get_dimension_idx(b_desc.layout, DataLayoutDimension::BATCHES)]; b_desc.shape = TensorShape(depth); - auto accessor = support::cpp14::make_unique<EmptyAccessor>(); + auto accessor = std::make_unique<EmptyAccessor>(); auto b_nid = GraphBuilder::add_const_node(g, params, b_desc, std::move(accessor)); g.add_connection(b_nid, 0, node_id, 2); } diff --git a/src/runtime/Allocator.cpp b/src/runtime/Allocator.cpp index 12478be482..ef7c62d64b 100644 --- a/src/runtime/Allocator.cpp +++ b/src/runtime/Allocator.cpp @@ -25,7 +25,6 @@ #include "arm_compute/runtime/MemoryRegion.h" #include "arm_compute/core/Error.h" -#include "support/MemorySupport.h" #include <cstddef> @@ -44,5 +43,5 @@ void Allocator::free(void *ptr) std::unique_ptr<IMemoryRegion> Allocator::make_region(size_t size, size_t alignment) { - return arm_compute::support::cpp14::make_unique<MemoryRegion>(size, alignment); + return std::make_unique<MemoryRegion>(size, alignment); } diff --git a/src/runtime/BlobLifetimeManager.cpp b/src/runtime/BlobLifetimeManager.cpp index 08f46e5012..1c983aa329 100644 --- a/src/runtime/BlobLifetimeManager.cpp +++ b/src/runtime/BlobLifetimeManager.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/BlobMemoryPool.h" #include "arm_compute/runtime/IAllocator.h" #include "arm_compute/runtime/IMemoryGroup.h" -#include "support/MemorySupport.h" #include <algorithm> #include <cmath> @@ -48,7 +47,7 @@ const BlobLifetimeManager::info_type &BlobLifetimeManager::info() const std::unique_ptr<IMemoryPool> BlobLifetimeManager::create_pool(IAllocator *allocator) { ARM_COMPUTE_ERROR_ON(allocator == nullptr); - return support::cpp14::make_unique<BlobMemoryPool>(allocator, _blobs); + return std::make_unique<BlobMemoryPool>(allocator, _blobs); } MappingType BlobLifetimeManager::mapping_type() const diff --git a/src/runtime/BlobMemoryPool.cpp b/src/runtime/BlobMemoryPool.cpp index 88bb421e34..e3d7f0fb65 100644 --- a/src/runtime/BlobMemoryPool.cpp +++ b/src/runtime/BlobMemoryPool.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/IAllocator.h" #include "arm_compute/runtime/IMemoryPool.h" #include "arm_compute/runtime/Types.h" -#include "support/MemorySupport.h" #include <vector> @@ -73,7 +72,7 @@ MappingType BlobMemoryPool::mapping_type() const std::unique_ptr<IMemoryPool> BlobMemoryPool::duplicate() { ARM_COMPUTE_ERROR_ON(!_allocator); - return support::cpp14::make_unique<BlobMemoryPool>(_allocator, _blob_info); + return std::make_unique<BlobMemoryPool>(_allocator, _blob_info); } void BlobMemoryPool::allocate_blobs(const std::vector<BlobInfo> &blob_info) diff --git a/src/runtime/CL/CLBufferAllocator.cpp b/src/runtime/CL/CLBufferAllocator.cpp index 3d380199e5..3673d65111 100644 --- a/src/runtime/CL/CLBufferAllocator.cpp +++ b/src/runtime/CL/CLBufferAllocator.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/Error.h" #include "arm_compute/runtime/CL/CLMemoryRegion.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "support/MemorySupport.h" #include <cstddef> @@ -63,6 +62,6 @@ void CLBufferAllocator::free(void *ptr) std::unique_ptr<IMemoryRegion> CLBufferAllocator::make_region(size_t size, size_t alignment) { ARM_COMPUTE_UNUSED(alignment); - return arm_compute::support::cpp14::make_unique<CLBufferMemoryRegion>(_ctx, CL_MEM_ALLOC_HOST_PTR | CL_MEM_READ_WRITE, size); + return std::make_unique<CLBufferMemoryRegion>(_ctx, CL_MEM_ALLOC_HOST_PTR | CL_MEM_READ_WRITE, size); } } // namespace arm_compute diff --git a/src/runtime/CL/CLRuntimeContext.cpp b/src/runtime/CL/CLRuntimeContext.cpp index 571e30931c..9d46126ee4 100644 --- a/src/runtime/CL/CLRuntimeContext.cpp +++ b/src/runtime/CL/CLRuntimeContext.cpp @@ -26,12 +26,10 @@ #include "arm_compute/runtime/CL/CLHelpers.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "support/MemorySupport.h" - namespace arm_compute { CLRuntimeContext::CLRuntimeContext() - : _gpu_owned_scheduler(support::cpp14::make_unique<CLScheduler>()), _gpu_scheduler(_gpu_owned_scheduler.get()), _symbols(), _core_context() + : _gpu_owned_scheduler(std::make_unique<CLScheduler>()), _gpu_scheduler(_gpu_owned_scheduler.get()), _symbols(), _core_context() { _symbols.load_default(); auto ctx_dev_err = create_opencl_context_and_device(); diff --git a/src/runtime/CL/CLTensorAllocator.cpp b/src/runtime/CL/CLTensorAllocator.cpp index f37fc779fe..fc789fa4b9 100644 --- a/src/runtime/CL/CLTensorAllocator.cpp +++ b/src/runtime/CL/CLTensorAllocator.cpp @@ -28,8 +28,6 @@ #include "arm_compute/runtime/CL/CLRuntimeContext.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "support/MemorySupport.h" - namespace arm_compute { const cl::Buffer CLTensorAllocator::_empty_buffer = cl::Buffer(); @@ -47,20 +45,20 @@ namespace std::unique_ptr<ICLMemoryRegion> allocate_region(CLCoreRuntimeContext *ctx, size_t size, cl_uint alignment) { // Try fine-grain SVM - std::unique_ptr<ICLMemoryRegion> region = support::cpp14::make_unique<CLFineSVMMemoryRegion>(ctx, - CL_MEM_READ_WRITE | CL_MEM_SVM_FINE_GRAIN_BUFFER, - size, - alignment); + std::unique_ptr<ICLMemoryRegion> region = std::make_unique<CLFineSVMMemoryRegion>(ctx, + CL_MEM_READ_WRITE | CL_MEM_SVM_FINE_GRAIN_BUFFER, + size, + alignment); // Try coarse-grain SVM in case of failure if(region != nullptr && region->ptr() == nullptr) { - region = support::cpp14::make_unique<CLCoarseSVMMemoryRegion>(ctx, CL_MEM_READ_WRITE, size, alignment); + region = std::make_unique<CLCoarseSVMMemoryRegion>(ctx, CL_MEM_READ_WRITE, size, alignment); } // Try legacy buffer memory in case of failure if(region != nullptr && region->ptr() == nullptr) { - region = support::cpp14::make_unique<CLBufferMemoryRegion>(ctx, CL_MEM_ALLOC_HOST_PTR | CL_MEM_READ_WRITE, size); + region = std::make_unique<CLBufferMemoryRegion>(ctx, CL_MEM_ALLOC_HOST_PTR | CL_MEM_READ_WRITE, size); } return region; } @@ -176,11 +174,11 @@ Status CLTensorAllocator::import_memory(cl::Buffer buffer) if(_ctx == nullptr) { auto legacy_ctx = CLCoreRuntimeContext(nullptr, CLScheduler::get().context(), CLScheduler::get().queue()); - _memory.set_owned_region(support::cpp14::make_unique<CLBufferMemoryRegion>(buffer, &legacy_ctx)); + _memory.set_owned_region(std::make_unique<CLBufferMemoryRegion>(buffer, &legacy_ctx)); } else { - _memory.set_owned_region(support::cpp14::make_unique<CLBufferMemoryRegion>(buffer, _ctx->core_runtime_context())); + _memory.set_owned_region(std::make_unique<CLBufferMemoryRegion>(buffer, _ctx->core_runtime_context())); } info().set_is_resizable(false); diff --git a/src/runtime/CL/ICLSimpleFunction.cpp b/src/runtime/CL/ICLSimpleFunction.cpp index b075aa17e3..4530537789 100644 --- a/src/runtime/CL/ICLSimpleFunction.cpp +++ b/src/runtime/CL/ICLSimpleFunction.cpp @@ -28,13 +28,12 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/ICLKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; ICLSimpleFunction::ICLSimpleFunction(CLRuntimeContext *ctx) // NOLINT : _kernel(), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()), + _border_handler(std::make_unique<CLFillBorderKernel>()), _ctx(ctx) { } diff --git a/src/runtime/CL/functions/CLAbsoluteDifference.cpp b/src/runtime/CL/functions/CLAbsoluteDifference.cpp index b7f40a516c..ff5b0a864d 100644 --- a/src/runtime/CL/functions/CLAbsoluteDifference.cpp +++ b/src/runtime/CL/functions/CLAbsoluteDifference.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLAbsoluteDifference.h" #include "src/core/CL/kernels/CLAbsoluteDifferenceKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLAbsoluteDifference::configure(const ICLTensor *input1, const ICLTensor *i void CLAbsoluteDifference::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLAbsoluteDifferenceKernel>(); + auto k = std::make_unique<CLAbsoluteDifferenceKernel>(); k->configure(compile_context, input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLAccumulate.cpp b/src/runtime/CL/functions/CLAccumulate.cpp index 742de64e34..44020fd816 100644 --- a/src/runtime/CL/functions/CLAccumulate.cpp +++ b/src/runtime/CL/functions/CLAccumulate.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLAccumulate.h" #include "src/core/CL/kernels/CLAccumulateKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLAccumulate::configure(const ICLTensor *input, ICLTensor *accum) void CLAccumulate::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *accum) { - auto k = arm_compute::support::cpp14::make_unique<CLAccumulateKernel>(); + auto k = std::make_unique<CLAccumulateKernel>(); k->configure(compile_context, input, accum); _kernel = std::move(k); } @@ -49,7 +48,7 @@ void CLAccumulateWeighted::configure(const ICLTensor *input, float alpha, ICLTen void CLAccumulateWeighted::configure(const CLCompileContext &compile_context, const ICLTensor *input, float alpha, ICLTensor *accum) { - auto k = arm_compute::support::cpp14::make_unique<CLAccumulateWeightedKernel>(); + auto k = std::make_unique<CLAccumulateWeightedKernel>(); k->configure(compile_context, input, alpha, accum); _kernel = std::move(k); } @@ -61,7 +60,7 @@ void CLAccumulateSquared::configure(const ICLTensor *input, uint32_t shift, ICLT void CLAccumulateSquared::configure(const CLCompileContext &compile_context, const ICLTensor *input, uint32_t shift, ICLTensor *accum) { - auto k = arm_compute::support::cpp14::make_unique<CLAccumulateSquaredKernel>(); + auto k = std::make_unique<CLAccumulateSquaredKernel>(); k->configure(compile_context, input, shift, accum); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLActivationLayer.cpp b/src/runtime/CL/functions/CLActivationLayer.cpp index 61c82b33eb..0070e43f8c 100644 --- a/src/runtime/CL/functions/CLActivationLayer.cpp +++ b/src/runtime/CL/functions/CLActivationLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Types.h" #include "arm_compute/runtime/CL/CLRuntimeContext.h" #include "src/core/CL/kernels/CLActivationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -35,7 +34,7 @@ namespace experimental { void CLActivation::configure(const CLCompileContext &compile_context, ITensorInfo *input, ITensorInfo *output, ActivationLayerInfo act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLActivationLayerKernel>(); + auto k = std::make_unique<CLActivationLayerKernel>(); k->configure(compile_context, input, output, act_info); _kernel = std::move(k); } @@ -55,7 +54,7 @@ struct CLActivationLayer::Impl }; CLActivationLayer::CLActivationLayer(CLRuntimeContext *ctx) - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { _impl->ctx = ctx; } @@ -78,7 +77,7 @@ void CLActivationLayer::configure(const CLCompileContext &compile_context, ICLTe _impl->src = input; _impl->dst = output == nullptr ? input : output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLActivation>(); + _impl->op = std::make_unique<experimental::CLActivation>(); _impl->op->configure(compile_context, _impl->src->info(), _impl->dst->info(), act_info); } diff --git a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp index 5fc849e3c5..8c32563abb 100644 --- a/src/runtime/CL/functions/CLArgMinMaxLayer.cpp +++ b/src/runtime/CL/functions/CLArgMinMaxLayer.cpp @@ -33,7 +33,6 @@ #include "src/core/CL/kernels/CLArgMinMaxLayerKernel.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/runtime/Utils.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -132,7 +131,7 @@ void CLArgMinMaxLayer::configure(const CLCompileContext &compile_context, const auto add_reduction_kernel = [this, &compile_context, axis, op](const ICLTensor * input, const ICLTensor * prev_output, ICLTensor * output) { - _reduction_kernels_vector.emplace_back(support::cpp14::make_unique<CLArgMinMaxLayerKernel>()); + _reduction_kernels_vector.emplace_back(std::make_unique<CLArgMinMaxLayerKernel>()); _reduction_kernels_vector.back()->configure(compile_context, input, prev_output, output, axis, op); }; diff --git a/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp b/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp index 77eed1140f..6b76da81c6 100644 --- a/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp +++ b/src/runtime/CL/functions/CLBatchNormalizationLayer.cpp @@ -29,14 +29,13 @@ #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "support/MemorySupport.h" #include "src/core/CL/kernels/CLBatchNormalizationLayerKernel.h" namespace arm_compute { CLBatchNormalizationLayer::CLBatchNormalizationLayer() - : _norm_kernel(support::cpp14::make_unique<CLBatchNormalizationLayerKernel>()) + : _norm_kernel(std::make_unique<CLBatchNormalizationLayerKernel>()) { } diff --git a/src/runtime/CL/functions/CLBatchToSpaceLayer.cpp b/src/runtime/CL/functions/CLBatchToSpaceLayer.cpp index e0a2c430ed..c2fdb74777 100644 --- a/src/runtime/CL/functions/CLBatchToSpaceLayer.cpp +++ b/src/runtime/CL/functions/CLBatchToSpaceLayer.cpp @@ -31,12 +31,11 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLBatchToSpaceLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLBatchToSpaceLayer::CLBatchToSpaceLayer() - : _batch_to_space_kernel(support::cpp14::make_unique<CLBatchToSpaceLayerKernel>()) + : _batch_to_space_kernel(std::make_unique<CLBatchToSpaceLayerKernel>()) { } diff --git a/src/runtime/CL/functions/CLBitwiseAnd.cpp b/src/runtime/CL/functions/CLBitwiseAnd.cpp index cfcd63f170..0f9f68cb9c 100644 --- a/src/runtime/CL/functions/CLBitwiseAnd.cpp +++ b/src/runtime/CL/functions/CLBitwiseAnd.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLBitwiseAnd.h" #include "src/core/CL/kernels/CLBitwiseAndKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLBitwiseAnd::configure(const ICLTensor *input1, const ICLTensor *input2, I void CLBitwiseAnd::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLBitwiseAndKernel>(); + auto k = std::make_unique<CLBitwiseAndKernel>(); k->configure(compile_context, input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLBitwiseNot.cpp b/src/runtime/CL/functions/CLBitwiseNot.cpp index 588c793f6a..cd2384590e 100644 --- a/src/runtime/CL/functions/CLBitwiseNot.cpp +++ b/src/runtime/CL/functions/CLBitwiseNot.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLBitwiseNot.h" #include "src/core/CL/kernels/CLBitwiseNotKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLBitwiseNot::configure(const ICLTensor *input, ICLTensor *output) void CLBitwiseNot::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLBitwiseNotKernel>(); + auto k = std::make_unique<CLBitwiseNotKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLBitwiseOr.cpp b/src/runtime/CL/functions/CLBitwiseOr.cpp index 3a5de193a3..38db5f78a0 100644 --- a/src/runtime/CL/functions/CLBitwiseOr.cpp +++ b/src/runtime/CL/functions/CLBitwiseOr.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLBitwiseOr.h" #include "src/core/CL/kernels/CLBitwiseOrKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLBitwiseOr::configure(const ICLTensor *input1, const ICLTensor *input2, IC void CLBitwiseOr::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLBitwiseOrKernel>(); + auto k = std::make_unique<CLBitwiseOrKernel>(); k->configure(compile_context, input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLBitwiseXor.cpp b/src/runtime/CL/functions/CLBitwiseXor.cpp index 62aeaaa31f..e477c3b847 100644 --- a/src/runtime/CL/functions/CLBitwiseXor.cpp +++ b/src/runtime/CL/functions/CLBitwiseXor.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLBitwiseXor.h" #include "src/core/CL/kernels/CLBitwiseXorKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLBitwiseXor::configure(const ICLTensor *input1, const ICLTensor *input2, I void CLBitwiseXor::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLBitwiseXorKernel>(); + auto k = std::make_unique<CLBitwiseXorKernel>(); k->configure(compile_context, input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLBoundingBoxTransform.cpp b/src/runtime/CL/functions/CLBoundingBoxTransform.cpp index 600d36290c..0dade0a369 100644 --- a/src/runtime/CL/functions/CLBoundingBoxTransform.cpp +++ b/src/runtime/CL/functions/CLBoundingBoxTransform.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLBoundingBoxTransform.h" #include "src/core/CL/kernels/CLBoundingBoxTransformKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void CLBoundingBoxTransform::configure(const ICLTensor *boxes, ICLTensor *pred_b void CLBoundingBoxTransform::configure(const CLCompileContext &compile_context, const ICLTensor *boxes, ICLTensor *pred_boxes, const ICLTensor *deltas, const BoundingBoxTransformInfo &info) { // Configure Bounding Box kernel - auto k = arm_compute::support::cpp14::make_unique<CLBoundingBoxTransformKernel>(); + auto k = std::make_unique<CLBoundingBoxTransformKernel>(); k->configure(compile_context, boxes, pred_boxes, deltas, info); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLBox3x3.cpp b/src/runtime/CL/functions/CLBox3x3.cpp index be40f25055..09e24d1bc0 100644 --- a/src/runtime/CL/functions/CLBox3x3.cpp +++ b/src/runtime/CL/functions/CLBox3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLBox3x3Kernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLBox3x3::configure(ICLTensor *input, ICLTensor *output, BorderMode border_ void CLBox3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLBox3x3Kernel>(); + auto k = std::make_unique<CLBox3x3Kernel>(); k->configure(compile_context, input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, BorderSize(1), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLCannyEdge.cpp b/src/runtime/CL/functions/CLCannyEdge.cpp index 5a32564d2d..7e99a1bbb3 100644 --- a/src/runtime/CL/functions/CLCannyEdge.cpp +++ b/src/runtime/CL/functions/CLCannyEdge.cpp @@ -35,17 +35,16 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLSobel5x5Kernel.h" #include "src/core/CL/kernels/CLSobel7x7Kernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLCannyEdge::CLCannyEdge(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT : _memory_group(std::move(memory_manager)), _sobel(), - _gradient(support::cpp14::make_unique<CLGradientKernel>()), - _border_mag_gradient(support::cpp14::make_unique<CLFillBorderKernel>()), - _non_max_suppr(support::cpp14::make_unique<CLEdgeNonMaxSuppressionKernel>()), - _edge_trace(support::cpp14::make_unique<CLEdgeTraceKernel>()), + _gradient(std::make_unique<CLGradientKernel>()), + _border_mag_gradient(std::make_unique<CLFillBorderKernel>()), + _non_max_suppr(std::make_unique<CLEdgeNonMaxSuppressionKernel>()), + _edge_trace(std::make_unique<CLEdgeTraceKernel>()), _gx(), _gy(), _mag(), @@ -123,19 +122,19 @@ void CLCannyEdge::configure(const CLCompileContext &compile_context, ICLTensor * // Configure/Init sobelNxN if(gradient_size == 3) { - auto k = arm_compute::support::cpp14::make_unique<CLSobel3x3>(); + auto k = std::make_unique<CLSobel3x3>(); k->configure(compile_context, input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); } else if(gradient_size == 5) { - auto k = arm_compute::support::cpp14::make_unique<CLSobel5x5>(); + auto k = std::make_unique<CLSobel5x5>(); k->configure(compile_context, input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); } else if(gradient_size == 7) { - auto k = arm_compute::support::cpp14::make_unique<CLSobel7x7>(); + auto k = std::make_unique<CLSobel7x7>(); k->configure(compile_context, input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); } diff --git a/src/runtime/CL/functions/CLCast.cpp b/src/runtime/CL/functions/CLCast.cpp index 2a28e06845..202140d8b9 100644 --- a/src/runtime/CL/functions/CLCast.cpp +++ b/src/runtime/CL/functions/CLCast.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLCast.h" #include "src/core/CL/kernels/CLDepthConvertLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLCast::configure(const ICLTensor *input, ICLTensor *output, ConvertPolicy void CLCast::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, ConvertPolicy policy) { - auto k = arm_compute::support::cpp14::make_unique<CLDepthConvertLayerKernel>(); + auto k = std::make_unique<CLDepthConvertLayerKernel>(); k->configure(compile_context, input, output, policy, 0); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLChannelCombine.cpp b/src/runtime/CL/functions/CLChannelCombine.cpp index e93aea31f4..543de9c653 100644 --- a/src/runtime/CL/functions/CLChannelCombine.cpp +++ b/src/runtime/CL/functions/CLChannelCombine.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLChannelCombine.h" #include "src/core/CL/kernels/CLChannelCombineKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLChannelCombine::configure(const ICLTensor *plane0, const ICLTensor *plane void CLChannelCombine::configure(const CLCompileContext &compile_context, const ICLTensor *plane0, const ICLTensor *plane1, const ICLTensor *plane2, const ICLTensor *plane3, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLChannelCombineKernel>(); + auto k = std::make_unique<CLChannelCombineKernel>(); k->configure(compile_context, plane0, plane1, plane2, plane3, output); _kernel = std::move(k); } @@ -49,7 +48,7 @@ void CLChannelCombine::configure(const ICLImage *plane0, const ICLImage *plane1, void CLChannelCombine::configure(const CLCompileContext &compile_context, const ICLImage *plane0, const ICLImage *plane1, const ICLImage *plane2, ICLMultiImage *output) { - auto k = arm_compute::support::cpp14::make_unique<CLChannelCombineKernel>(); + auto k = std::make_unique<CLChannelCombineKernel>(); k->configure(compile_context, plane0, plane1, plane2, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLChannelExtract.cpp b/src/runtime/CL/functions/CLChannelExtract.cpp index 8b4a3f7458..645fc051cb 100644 --- a/src/runtime/CL/functions/CLChannelExtract.cpp +++ b/src/runtime/CL/functions/CLChannelExtract.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLChannelExtract.h" #include "src/core/CL/kernels/CLChannelExtractKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLChannelExtract::configure(const ICLTensor *input, Channel channel, ICLTen void CLChannelExtract::configure(const CLCompileContext &compile_context, const ICLTensor *input, Channel channel, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLChannelExtractKernel>(); + auto k = std::make_unique<CLChannelExtractKernel>(); k->configure(compile_context, input, channel, output); _kernel = std::move(k); } @@ -49,7 +48,7 @@ void CLChannelExtract::configure(const ICLMultiImage *input, Channel channel, IC void CLChannelExtract::configure(const CLCompileContext &compile_context, const ICLMultiImage *input, Channel channel, ICLImage *output) { - auto k = arm_compute::support::cpp14::make_unique<CLChannelExtractKernel>(); + auto k = std::make_unique<CLChannelExtractKernel>(); k->configure(compile_context, input, channel, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLChannelShuffleLayer.cpp b/src/runtime/CL/functions/CLChannelShuffleLayer.cpp index c443df3b37..c6af5a05d5 100644 --- a/src/runtime/CL/functions/CLChannelShuffleLayer.cpp +++ b/src/runtime/CL/functions/CLChannelShuffleLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLChannelShuffleLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void CLChannelShuffleLayer::configure(const ICLTensor *input, ICLTensor *output, void CLChannelShuffleLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, unsigned int num_groups) { - auto k = arm_compute::support::cpp14::make_unique<CLChannelShuffleLayerKernel>(); + auto k = std::make_unique<CLChannelShuffleLayerKernel>(); k->configure(compile_context, input, output, num_groups); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLColorConvert.cpp b/src/runtime/CL/functions/CLColorConvert.cpp index 95f4257929..9aeeb65dc4 100644 --- a/src/runtime/CL/functions/CLColorConvert.cpp +++ b/src/runtime/CL/functions/CLColorConvert.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLColorConvert.h" #include "src/core/CL/kernels/CLColorConvertKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLColorConvert::configure(const ICLTensor *input, ICLTensor *output) void CLColorConvert::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLColorConvertKernel>(); + auto k = std::make_unique<CLColorConvertKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } @@ -49,7 +48,7 @@ void CLColorConvert::configure(const ICLImage *input, ICLMultiImage *output) void CLColorConvert::configure(const CLCompileContext &compile_context, const ICLImage *input, ICLMultiImage *output) { - auto k = arm_compute::support::cpp14::make_unique<CLColorConvertKernel>(); + auto k = std::make_unique<CLColorConvertKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } @@ -61,7 +60,7 @@ void CLColorConvert::configure(const ICLMultiImage *input, ICLImage *output) void CLColorConvert::configure(const CLCompileContext &compile_context, const ICLMultiImage *input, ICLImage *output) { - auto k = arm_compute::support::cpp14::make_unique<CLColorConvertKernel>(); + auto k = std::make_unique<CLColorConvertKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } @@ -73,7 +72,7 @@ void CLColorConvert::configure(const ICLMultiImage *input, ICLMultiImage *output void CLColorConvert::configure(const CLCompileContext &compile_context, const ICLMultiImage *input, ICLMultiImage *output) { - auto k = arm_compute::support::cpp14::make_unique<CLColorConvertKernel>(); + auto k = std::make_unique<CLColorConvertKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLComparison.cpp b/src/runtime/CL/functions/CLComparison.cpp index 9b5840aa95..4122928578 100644 --- a/src/runtime/CL/functions/CLComparison.cpp +++ b/src/runtime/CL/functions/CLComparison.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLComparisonKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,7 +37,7 @@ void CLComparison::configure(ICLTensor *input1, ICLTensor *input2, ICLTensor *ou void CLComparison::configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output, ComparisonOperation operation) { - auto k = arm_compute::support::cpp14::make_unique<CLComparisonKernel>(); + auto k = std::make_unique<CLComparisonKernel>(); k->configure(compile_context, input1, input2, output, operation); _kernel = std::move(k); @@ -67,7 +66,7 @@ void CLComparisonStatic<COP>::configure(ICLTensor *input1, ICLTensor *input2, IC template <ComparisonOperation COP> void CLComparisonStatic<COP>::configure(const CLCompileContext &compile_context, ICLTensor *input1, ICLTensor *input2, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLComparisonKernel>(); + auto k = std::make_unique<CLComparisonKernel>(); k->configure(compile_context, input1, input2, output, COP); _kernel = std::move(k); diff --git a/src/runtime/CL/functions/CLComputeAllAnchors.cpp b/src/runtime/CL/functions/CLComputeAllAnchors.cpp index 2cae0ee455..5838e32ed8 100644 --- a/src/runtime/CL/functions/CLComputeAllAnchors.cpp +++ b/src/runtime/CL/functions/CLComputeAllAnchors.cpp @@ -24,8 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h" #include "src/core/CL/kernels/CLGenerateProposalsLayerKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { void CLComputeAllAnchors::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info) @@ -36,7 +34,7 @@ void CLComputeAllAnchors::configure(const ICLTensor *anchors, ICLTensor *all_anc void CLComputeAllAnchors::configure(const CLCompileContext &compile_context, const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info) { // Configure ComputeAllAnchors kernel - auto k = arm_compute::support::cpp14::make_unique<CLComputeAllAnchorsKernel>(); + auto k = std::make_unique<CLComputeAllAnchorsKernel>(); k->configure(compile_context, anchors, all_anchors, info); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLConcatenateLayer.cpp b/src/runtime/CL/functions/CLConcatenateLayer.cpp index 54f71f9765..0c473a79c8 100644 --- a/src/runtime/CL/functions/CLConcatenateLayer.cpp +++ b/src/runtime/CL/functions/CLConcatenateLayer.cpp @@ -37,7 +37,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLBatchConcatenateLayerKernel.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -78,7 +77,7 @@ void CLConcatenation::configure(const CLCompileContext &compile_context, const s case 2: { // Configure WidthConcatenate2Tensors kernel - auto kernel = support::cpp14::make_unique<CLWidthConcatenate2TensorsKernel>(); + auto kernel = std::make_unique<CLWidthConcatenate2TensorsKernel>(); kernel->configure(compile_context, inputs_vector.at(0), inputs_vector.at(1), output); _concat_kernels.emplace_back(std::move(kernel)); break; @@ -86,7 +85,7 @@ void CLConcatenation::configure(const CLCompileContext &compile_context, const s case 4: { // Configure WidthConcatenate4Tensors kernel - auto kernel = support::cpp14::make_unique<CLWidthConcatenate4TensorsKernel>(); + auto kernel = std::make_unique<CLWidthConcatenate4TensorsKernel>(); kernel->configure(compile_context, inputs_vector.at(0), inputs_vector.at(1), inputs_vector.at(2), inputs_vector.at(3), output); _concat_kernels.emplace_back(std::move(kernel)); break; @@ -96,7 +95,7 @@ void CLConcatenation::configure(const CLCompileContext &compile_context, const s // Configure generic case WidthConcatenate kernels for(unsigned int i = 0; i < _num_inputs; ++i) { - auto kernel = support::cpp14::make_unique<CLWidthConcatenateLayerKernel>(); + auto kernel = std::make_unique<CLWidthConcatenateLayerKernel>(); kernel->configure(compile_context, inputs_vector.at(i), offset, output); offset += inputs_vector.at(i)->dimension(_axis); _concat_kernels.emplace_back(std::move(kernel)); @@ -110,7 +109,7 @@ void CLConcatenation::configure(const CLCompileContext &compile_context, const s { for(unsigned int i = 0; i < _num_inputs; ++i) { - auto kernel = support::cpp14::make_unique<CLHeightConcatenateLayerKernel>(); + auto kernel = std::make_unique<CLHeightConcatenateLayerKernel>(); kernel->configure(compile_context, inputs_vector.at(i), offset, output); offset += inputs_vector.at(i)->dimension(_axis); _concat_kernels.emplace_back(std::move(kernel)); @@ -121,7 +120,7 @@ void CLConcatenation::configure(const CLCompileContext &compile_context, const s { for(unsigned int i = 0; i < _num_inputs; ++i) { - auto kernel = support::cpp14::make_unique<CLDepthConcatenateLayerKernel>(); + auto kernel = std::make_unique<CLDepthConcatenateLayerKernel>(); kernel->configure(compile_context, inputs_vector.at(i), offset, output); offset += inputs_vector.at(i)->dimension(_axis); _concat_kernels.emplace_back(std::move(kernel)); @@ -132,7 +131,7 @@ void CLConcatenation::configure(const CLCompileContext &compile_context, const s { for(unsigned int i = 0; i < _num_inputs; ++i) { - auto kernel = support::cpp14::make_unique<CLBatchConcatenateLayerKernel>(); + auto kernel = std::make_unique<CLBatchConcatenateLayerKernel>(); kernel->configure(compile_context, inputs_vector.at(i), offset, output); offset += inputs_vector.at(i)->dimension(_axis); _concat_kernels.emplace_back(std::move(kernel)); @@ -263,7 +262,7 @@ struct CLConcatenateLayer::Impl }; CLConcatenateLayer::CLConcatenateLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -286,7 +285,7 @@ void CLConcatenateLayer::configure(const CLCompileContext &compile_context, std: _impl->dst = output; _impl->axis = axis; _impl->num_inputs = inputs_vector.size(); - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLConcatenation>(); + _impl->op = std::make_unique<experimental::CLConcatenation>(); std::vector<ITensorInfo *> inputs_vector_info; for(unsigned int i = 0; i < inputs_vector.size(); ++i) diff --git a/src/runtime/CL/functions/CLConvertFullyConnectedWeights.cpp b/src/runtime/CL/functions/CLConvertFullyConnectedWeights.cpp index 8ecc114343..bbe9b487e5 100644 --- a/src/runtime/CL/functions/CLConvertFullyConnectedWeights.cpp +++ b/src/runtime/CL/functions/CLConvertFullyConnectedWeights.cpp @@ -25,8 +25,6 @@ #include "src/core/CL/kernels/CLConvertFullyConnectedWeightsKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { void CLConvertFullyConnectedWeights::configure(const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, @@ -38,7 +36,7 @@ void CLConvertFullyConnectedWeights::configure(const ICLTensor *input, ICLTensor void CLConvertFullyConnectedWeights::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const TensorShape &original_input_shape, DataLayout data_layout) { - auto k = arm_compute::support::cpp14::make_unique<CLConvertFullyConnectedWeightsKernel>(); + auto k = std::make_unique<CLConvertFullyConnectedWeightsKernel>(); k->configure(compile_context, input, output, original_input_shape, data_layout); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLConvolution.cpp b/src/runtime/CL/functions/CLConvolution.cpp index 1ad32d309c..49dae49146 100644 --- a/src/runtime/CL/functions/CLConvolution.cpp +++ b/src/runtime/CL/functions/CLConvolution.cpp @@ -33,7 +33,6 @@ #include "arm_compute/runtime/ITensorAllocator.h" #include "src/core/CL/kernels/CLConvolutionKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -47,7 +46,7 @@ void CLConvolution3x3::configure(ICLTensor *input, ICLTensor *output, const int1 void CLConvolution3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLConvolution3x3Kernel>(); + auto k = std::make_unique<CLConvolution3x3Kernel>(); k->configure(compile_context, input, output, conv, scale, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); @@ -55,9 +54,8 @@ void CLConvolution3x3::configure(const CLCompileContext &compile_context, ICLTen template <unsigned int matrix_size> CLConvolutionSquare<matrix_size>::CLConvolutionSquare(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(std::move(memory_manager)), _tmp(), _is_separable(false), _kernel_hor(support::cpp14::make_unique<CLSeparableConvolutionHorKernel<matrix_size>>()), - _kernel_vert(support::cpp14::make_unique<CLSeparableConvolutionVertKernel<matrix_size>>()), _kernel(support::cpp14::make_unique<CLConvolutionKernel<matrix_size>>()), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()) + : _memory_group(std::move(memory_manager)), _tmp(), _is_separable(false), _kernel_hor(std::make_unique<CLSeparableConvolutionHorKernel<matrix_size>>()), + _kernel_vert(std::make_unique<CLSeparableConvolutionVertKernel<matrix_size>>()), _kernel(std::make_unique<CLConvolutionKernel<matrix_size>>()), _border_handler(std::make_unique<CLFillBorderKernel>()) { } @@ -138,7 +136,7 @@ void CLConvolutionRectangle::configure(ICLTensor *input, ICLTensor *output, cons void CLConvolutionRectangle::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLConvolutionRectangleKernel>(); + auto k = std::make_unique<CLConvolutionRectangleKernel>(); k->configure(compile_context, input, output, conv, rows, cols, scale, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLConvolutionLayer.cpp b/src/runtime/CL/functions/CLConvolutionLayer.cpp index e214bdf0f2..edd9298d26 100644 --- a/src/runtime/CL/functions/CLConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLConvolutionLayer.cpp @@ -29,7 +29,6 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "support/MemorySupport.h" #include <cmath> #include <memory> @@ -66,7 +65,7 @@ void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLT case ConvolutionMethod::WINOGRAD: { ARM_COMPUTE_ERROR_ON(num_groups != 1); - auto f = arm_compute::support::cpp14::make_unique<CLWinogradConvolutionLayer>(_memory_manager); + auto f = std::make_unique<CLWinogradConvolutionLayer>(_memory_manager); f->configure(compile_context, input, weights, biases, output, conv_info, act_info, enable_fast_math); _function = std::move(f); break; @@ -74,21 +73,21 @@ void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLT case ConvolutionMethod::DIRECT: { ARM_COMPUTE_ERROR_ON(num_groups != 1); - auto f = arm_compute::support::cpp14::make_unique<CLDirectConvolutionLayer>(); + auto f = std::make_unique<CLDirectConvolutionLayer>(); f->configure(compile_context, input, weights, biases, output, conv_info, act_info); _function = std::move(f); break; } case ConvolutionMethod::GEMM: { - auto f = arm_compute::support::cpp14::make_unique<CLGEMMConvolutionLayer>(_memory_manager); + auto f = std::make_unique<CLGEMMConvolutionLayer>(_memory_manager); f->configure(compile_context, input, weights, biases, output, conv_info, weights_info, dilation, act_info, num_groups); _function = std::move(f); break; } case ConvolutionMethod::FFT: { - auto f = arm_compute::support::cpp14::make_unique<CLFFTConvolutionLayer>(_memory_manager); + auto f = std::make_unique<CLFFTConvolutionLayer>(_memory_manager); f->configure(compile_context, input, weights, biases, output, conv_info, act_info); _function = std::move(f); break; diff --git a/src/runtime/CL/functions/CLCopy.cpp b/src/runtime/CL/functions/CLCopy.cpp index f7b016a779..c3e30ada6e 100644 --- a/src/runtime/CL/functions/CLCopy.cpp +++ b/src/runtime/CL/functions/CLCopy.cpp @@ -29,7 +29,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "src/core/CL/kernels/CLCopyKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -42,7 +41,7 @@ void CLCopy::configure(ICLTensor *input, ICLTensor *output) void CLCopy::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLCopyKernel>(); + auto k = std::make_unique<CLCopyKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLCropResize.cpp b/src/runtime/CL/functions/CLCropResize.cpp index 4aaa674c5c..ed31446cf9 100644 --- a/src/runtime/CL/functions/CLCropResize.cpp +++ b/src/runtime/CL/functions/CLCropResize.cpp @@ -32,8 +32,6 @@ #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" -#include "support/MemorySupport.h" - #include <cstddef> namespace arm_compute @@ -126,13 +124,13 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT _box_ind->map(CLScheduler::get().queue()); for(unsigned int num_box = 0; num_box < _num_boxes; ++num_box) { - auto crop_tensor = support::cpp14::make_unique<CLTensor>(); + auto crop_tensor = std::make_unique<CLTensor>(); TensorInfo crop_result_info(1, DataType::F32); crop_result_info.set_data_layout(DataLayout::NHWC); crop_tensor->allocator()->init(crop_result_info); _crop_results.emplace_back(std::move(crop_tensor)); - auto scale_tensor = support::cpp14::make_unique<CLTensor>(); + auto scale_tensor = std::make_unique<CLTensor>(); TensorInfo scaled_result_info(out_shape, 1, DataType::F32); scaled_result_info.set_data_layout(DataLayout::NHWC); scale_tensor->allocator()->init(scaled_result_info); @@ -144,14 +142,14 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT Coordinates end{}; configure_crop(_input, _boxes, _box_ind, _crop_results[num_box].get(), num_box, start, end, batch_index); - auto scale_kernel = support::cpp14::make_unique<CLScale>(); + auto scale_kernel = std::make_unique<CLScale>(); scale_kernel->configure(compile_context, _crop_results[num_box].get(), _scaled_results[num_box].get(), ScaleKernelInfo{ _method, BorderMode::CONSTANT, PixelValue(_extrapolation_value), SamplingPolicy::TOP_LEFT }); _scale.emplace_back(std::move(scale_kernel)); Window win = calculate_max_window(*_output->info()); win.set(3, Window::Dimension(num_box, num_box + 1, 1)); - auto copy_kernel = support::cpp14::make_unique<CLCopyKernel>(); + auto copy_kernel = std::make_unique<CLCopyKernel>(); copy_kernel->configure(compile_context, _scaled_results[num_box].get(), _output, &win); _copy.emplace_back(std::move(copy_kernel)); @@ -209,7 +207,7 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT { Window slice_fill_rows_before(full_window); slice_fill_rows_before.set(2, Window::Dimension(0, rows_out_of_bounds[0], 1)); - auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); + auto kernel = std::make_unique<CLMemsetKernel>(); kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, &slice_fill_rows_before); _internal_kernels.push_back(std::move(kernel)); } @@ -226,7 +224,7 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT { Window slice_fill_cols_before(slice_in); slice_fill_cols_before.set(1, Window::Dimension(0, cols_out_of_bounds[0], 1)); - auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); + auto kernel = std::make_unique<CLMemsetKernel>(); kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, &slice_fill_cols_before); _internal_kernels.push_back(std::move(kernel)); } @@ -235,7 +233,7 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT { Window slice_fill_cols_after(slice_in); slice_fill_cols_after.set(1, Window::Dimension(_crop_results[num_box].get()->info()->dimension(1) - cols_out_of_bounds[1], _crop_results[num_box].get()->info()->dimension(1), 1)); - auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); + auto kernel = std::make_unique<CLMemsetKernel>(); kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, &slice_fill_cols_after); _internal_kernels.push_back(std::move(kernel)); } @@ -248,7 +246,7 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT is_height_flipped ? start[1] - rows_out_of_bounds[0] : start[1] + rows_out_of_bounds[0] }; Coordinates2D end_in{ is_width_flipped ? start_in.x - cols_in_bounds + 1 : start_in.x + cols_in_bounds - 1, is_height_flipped ? start_in.y - rows_in_bounds + 1 : start_in.y + rows_in_bounds - 1 }; - auto kernel = arm_compute::support::cpp14::make_unique<CLCropKernel>(); + auto kernel = std::make_unique<CLCropKernel>(); kernel->configure(compile_context, _input, _crop_results[num_box].get(), start_in, end_in, batch_index, extrapolation_value, &slice_in); _internal_kernels.push_back(std::move(kernel)); @@ -260,7 +258,7 @@ void CLCropResize::configure(const CLCompileContext &compile_context, const ICLT { Window slice_fill_rows_after(full_window); slice_fill_rows_after.set(2, Window::Dimension(_crop_results[num_box].get()->info()->dimension(2) - rows_out_of_bounds[1], _crop_results[num_box].get()->info()->dimension(2), 1)); - auto kernel = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); + auto kernel = std::make_unique<CLMemsetKernel>(); kernel->configure(compile_context, _crop_results[num_box].get(), extrapolation_value, &slice_fill_rows_after); _internal_kernels.push_back(std::move(kernel)); } diff --git a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp index 6fe231ea6c..75f34cc5ee 100644 --- a/src/runtime/CL/functions/CLDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDeconvolutionLayer.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "support/MemorySupport.h" #include <cmath> #include <memory> @@ -57,14 +56,14 @@ void CLDeconvolutionLayer::configure(const CLCompileContext &compile_context, IC { case DeconvolutionMethod::DIRECT: { - auto f = arm_compute::support::cpp14::make_unique<CLDirectDeconvolutionLayer>(); + auto f = std::make_unique<CLDirectDeconvolutionLayer>(); f->configure(compile_context, input, weights, bias, output, deconv_info, weights_info); _function = std::move(f); break; } case DeconvolutionMethod::GEMM: { - auto f = arm_compute::support::cpp14::make_unique<CLGEMMDeconvolutionLayer>(_memory_manager); + auto f = std::make_unique<CLGEMMDeconvolutionLayer>(_memory_manager); f->configure(compile_context, input, weights, bias, output, deconv_info); _function = std::move(f); break; diff --git a/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp b/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp index 0cf2ea623f..4989f6460d 100644 --- a/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp +++ b/src/runtime/CL/functions/CLDeconvolutionLayerUpsample.cpp @@ -29,13 +29,12 @@ #include "arm_compute/runtime/CL/CLTensor.h" #include "src/core/CL/kernels/CLDeconvolutionLayerUpsampleKernel.h" #include "src/core/CL/kernels/CLMemsetKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLDeconvolutionLayerUpsample::CLDeconvolutionLayerUpsample() // NOLINT - : _upsample(support::cpp14::make_unique<CLDeconvolutionLayerUpsampleKernel>()), - _memset(support::cpp14::make_unique<CLMemsetKernel>()), + : _upsample(std::make_unique<CLDeconvolutionLayerUpsampleKernel>()), + _memset(std::make_unique<CLMemsetKernel>()), _output(nullptr) { } diff --git a/src/runtime/CL/functions/CLDepthConvertLayer.cpp b/src/runtime/CL/functions/CLDepthConvertLayer.cpp index e58c0e5f4c..47bc52364d 100644 --- a/src/runtime/CL/functions/CLDepthConvertLayer.cpp +++ b/src/runtime/CL/functions/CLDepthConvertLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLDepthConvertLayer.h" #include "src/core/CL/kernels/CLDepthConvertLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLDepthConvertLayer::configure(const ICLTensor *input, ICLTensor *output, C void CLDepthConvertLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, ConvertPolicy policy, uint32_t shift) { - auto k = arm_compute::support::cpp14::make_unique<CLDepthConvertLayerKernel>(); + auto k = std::make_unique<CLDepthConvertLayerKernel>(); k->configure(compile_context, input, output, policy, shift); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLDepthToSpaceLayer.cpp b/src/runtime/CL/functions/CLDepthToSpaceLayer.cpp index 8dbd974ceb..bd2303c410 100644 --- a/src/runtime/CL/functions/CLDepthToSpaceLayer.cpp +++ b/src/runtime/CL/functions/CLDepthToSpaceLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLDepthToSpaceLayer.h" #include "src/core/CL/kernels/CLDepthToSpaceLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLDepthToSpaceLayer::configure(const ICLTensor *input, ICLTensor *output, i void CLDepthToSpaceLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, int32_t block_shape) { - auto k = arm_compute::support::cpp14::make_unique<CLDepthToSpaceLayerKernel>(); + auto k = std::make_unique<CLDepthToSpaceLayerKernel>(); k->configure(compile_context, input, output, block_shape); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp index 2440384e3b..8d2c81bc15 100644 --- a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp @@ -37,7 +37,6 @@ #include "src/core/CL/kernels/CLDepthwiseConvolutionLayerReshapeWeightsKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/ICLDepthwiseConvolutionLayer3x3Kernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -125,7 +124,7 @@ Status validate_arguments_3x3(const ITensorInfo *input, const ITensorInfo *weigh CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::CLDepthwiseConvolutionLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _dwc_native_kernel(support::cpp14::make_unique<CLDepthwiseConvolutionLayerNativeKernel>()), + _dwc_native_kernel(std::make_unique<CLDepthwiseConvolutionLayerNativeKernel>()), _permute_input_to_nhwc(), _permute_weights_to_nhwc(), _permute_output_to_nchw(), @@ -351,11 +350,11 @@ void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::prepare() CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::CLDepthwiseConvolutionLayerInternal3x3(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _kernel(nullptr), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()), + _border_handler(std::make_unique<CLFillBorderKernel>()), _permute_input_to_nchw(), _permute_weights_to_nchw(), _permute_output_to_nhwc(), - _reshape_weights(support::cpp14::make_unique<CLDepthwiseConvolutionLayerReshapeWeightsKernel>()), + _reshape_weights(std::make_unique<CLDepthwiseConvolutionLayerReshapeWeightsKernel>()), _permuted_input(), _permuted_weights(), _permuted_output(), @@ -436,7 +435,7 @@ void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::config weights_to_use = &_permuted_weights; output_to_use = &_permuted_output; - _kernel = arm_compute::support::cpp14::make_unique<CLDepthwiseConvolutionLayer3x3NCHWKernel>(); + _kernel = std::make_unique<CLDepthwiseConvolutionLayer3x3NCHWKernel>(); } else if(is_nhwc) { @@ -445,11 +444,11 @@ void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::config _reshape_weights->configure(compile_context, weights, &_permuted_weights, info); weights_to_use = &_permuted_weights; } - _kernel = arm_compute::support::cpp14::make_unique<CLDepthwiseConvolutionLayer3x3NHWCKernel>(); + _kernel = std::make_unique<CLDepthwiseConvolutionLayer3x3NHWCKernel>(); } else { - _kernel = arm_compute::support::cpp14::make_unique<CLDepthwiseConvolutionLayer3x3NCHWKernel>(); + _kernel = std::make_unique<CLDepthwiseConvolutionLayer3x3NCHWKernel>(); } CLTensor *output_multipliers_to_use = nullptr; diff --git a/src/runtime/CL/functions/CLDequantizationLayer.cpp b/src/runtime/CL/functions/CLDequantizationLayer.cpp index 6d63463906..d358813724 100644 --- a/src/runtime/CL/functions/CLDequantizationLayer.cpp +++ b/src/runtime/CL/functions/CLDequantizationLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLDequantizationLayer.h" #include "src/core/CL/kernels/CLDequantizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -35,7 +34,7 @@ void CLDequantizationLayer::configure(const ICLTensor *input, ICLTensor *output) void CLDequantizationLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLDequantizationLayerKernel>(); + auto k = std::make_unique<CLDequantizationLayerKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLDerivative.cpp b/src/runtime/CL/functions/CLDerivative.cpp index a2b883ad28..2e3ecf7700 100644 --- a/src/runtime/CL/functions/CLDerivative.cpp +++ b/src/runtime/CL/functions/CLDerivative.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLDerivativeKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLDerivative::configure(ICLTensor *input, ICLTensor *output_x, ICLTensor *o void CLDerivative::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLDerivativeKernel>(); + auto k = std::make_unique<CLDerivativeKernel>(); k->configure(compile_context, input, output_x, output_y, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, BorderSize(1), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLDilate.cpp b/src/runtime/CL/functions/CLDilate.cpp index c3d5f8845f..92c5cc7ab1 100644 --- a/src/runtime/CL/functions/CLDilate.cpp +++ b/src/runtime/CL/functions/CLDilate.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLDilateKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLDilate::configure(ICLTensor *input, ICLTensor *output, BorderMode border_ void CLDilate::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLDilateKernel>(); + auto k = std::make_unique<CLDilateKernel>(); k->configure(compile_context, input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, BorderSize(1), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp b/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp index bff882c28b..49e97693e4 100644 --- a/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDirectConvolutionLayer.cpp @@ -30,12 +30,11 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLDirectConvolutionLayerKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLDirectConvolutionLayer::CLDirectConvolutionLayer() - : _direct_conv_kernel(support::cpp14::make_unique<CLDirectConvolutionLayerKernel>()), _input_border_handler(support::cpp14::make_unique<CLFillBorderKernel>()), _activationlayer_function(), + : _direct_conv_kernel(std::make_unique<CLDirectConvolutionLayerKernel>()), _input_border_handler(std::make_unique<CLFillBorderKernel>()), _activationlayer_function(), _is_activationlayer_enabled(false) { } diff --git a/src/runtime/CL/functions/CLElementWiseUnaryLayer.cpp b/src/runtime/CL/functions/CLElementWiseUnaryLayer.cpp index 35ed97d381..0ded640f51 100644 --- a/src/runtime/CL/functions/CLElementWiseUnaryLayer.cpp +++ b/src/runtime/CL/functions/CLElementWiseUnaryLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLElementWiseUnaryLayer.h" #include "src/core/CL/kernels/CLElementWiseUnaryLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ namespace experimental { void CLRsqrt::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::RSQRT); _kernel = std::move(k); } @@ -46,7 +45,7 @@ Status CLRsqrt::validate(const ITensorInfo *input, const ITensorInfo *output) void CLExp::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::EXP); _kernel = std::move(k); } @@ -58,7 +57,7 @@ Status CLExp::validate(const ITensorInfo *input, const ITensorInfo *output) void CLNeg::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::NEG); _kernel = std::move(k); } @@ -70,7 +69,7 @@ Status CLNeg::validate(const ITensorInfo *input, const ITensorInfo *output) void CLSin::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::SIN); _kernel = std::move(k); } @@ -82,7 +81,7 @@ Status CLSin::validate(const ITensorInfo *input, const ITensorInfo *output) void CLAbs::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::ABS); _kernel = std::move(k); } @@ -94,7 +93,7 @@ Status CLAbs::validate(const ITensorInfo *input, const ITensorInfo *output) void CLLog::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::LOG); _kernel = std::move(k); } @@ -106,7 +105,7 @@ Status CLLog::validate(const ITensorInfo *input, const ITensorInfo *output) void CLRound::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::ROUND); _kernel = std::move(k); } @@ -125,7 +124,7 @@ struct CLRsqrtLayer::Impl }; CLRsqrtLayer::CLRsqrtLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -142,7 +141,7 @@ void CLRsqrtLayer::configure(const CLCompileContext &compile_context, const ICLT { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLRsqrt>(); + _impl->op = std::make_unique<experimental::CLRsqrt>(); _impl->op->configure(compile_context, input->info(), output->info()); } @@ -167,7 +166,7 @@ struct CLExpLayer::Impl }; CLExpLayer::CLExpLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -184,7 +183,7 @@ void CLExpLayer::configure(const CLCompileContext &compile_context, const ICLTen { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLExp>(); + _impl->op = std::make_unique<experimental::CLExp>(); _impl->op->configure(compile_context, input->info(), output->info()); } @@ -209,7 +208,7 @@ struct CLNegLayer::Impl }; CLNegLayer::CLNegLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -226,7 +225,7 @@ void CLNegLayer::configure(const CLCompileContext &compile_context, const ICLTen { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLNeg>(); + _impl->op = std::make_unique<experimental::CLNeg>(); _impl->op->configure(compile_context, input->info(), output->info()); } Status CLNegLayer::validate(const ITensorInfo *input, const ITensorInfo *output) @@ -250,7 +249,7 @@ struct CLSinLayer::Impl }; CLSinLayer::CLSinLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -267,7 +266,7 @@ void CLSinLayer::configure(const CLCompileContext &compile_context, const ICLTen { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLSin>(); + _impl->op = std::make_unique<experimental::CLSin>(); _impl->op->configure(compile_context, input->info(), output->info()); } Status CLSinLayer::validate(const ITensorInfo *input, const ITensorInfo *output) @@ -291,7 +290,7 @@ struct CLAbsLayer::Impl }; CLAbsLayer::CLAbsLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -308,7 +307,7 @@ void CLAbsLayer::configure(const CLCompileContext &compile_context, const ICLTen { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLAbs>(); + _impl->op = std::make_unique<experimental::CLAbs>(); _impl->op->configure(compile_context, input->info(), output->info()); } Status CLAbsLayer::validate(const ITensorInfo *input, const ITensorInfo *output) @@ -332,7 +331,7 @@ struct CLLogLayer::Impl }; CLLogLayer::CLLogLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -349,7 +348,7 @@ void CLLogLayer::configure(const CLCompileContext &compile_context, const ICLTen { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLLog>(); + _impl->op = std::make_unique<experimental::CLLog>(); _impl->op->configure(compile_context, input->info(), output->info()); } Status CLLogLayer::validate(const ITensorInfo *input, const ITensorInfo *output) @@ -373,7 +372,7 @@ struct CLRoundLayer::Impl }; CLRoundLayer::CLRoundLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -390,7 +389,7 @@ void CLRoundLayer::configure(const CLCompileContext &compile_context, const ICLT { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLRound>(); + _impl->op = std::make_unique<experimental::CLRound>(); _impl->op->configure(compile_context, input->info(), output->info()); } Status CLRoundLayer::validate(const ITensorInfo *input, const ITensorInfo *output) diff --git a/src/runtime/CL/functions/CLElementwiseOperations.cpp b/src/runtime/CL/functions/CLElementwiseOperations.cpp index 736cf973a1..a72e957fe6 100644 --- a/src/runtime/CL/functions/CLElementwiseOperations.cpp +++ b/src/runtime/CL/functions/CLElementwiseOperations.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLElementwiseOperationKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -40,7 +39,7 @@ CLArithmeticAddition::CLArithmeticAddition() void CLArithmeticAddition::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLSaturatedArithmeticOperationKernel>(); + auto k = std::make_unique<CLSaturatedArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::ADD, input1, input2, output, policy, act_info); _kernel = std::move(k); } @@ -61,7 +60,7 @@ CLArithmeticSubtraction::CLArithmeticSubtraction() void CLArithmeticSubtraction::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLSaturatedArithmeticOperationKernel>(); + auto k = std::make_unique<CLSaturatedArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::SUB, input1, input2, output, policy, act_info); _kernel = std::move(k); } @@ -83,7 +82,7 @@ CLArithmeticDivision::CLArithmeticDivision() void CLArithmeticDivision::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLArithmeticOperationKernel>(); + auto k = std::make_unique<CLArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::DIV, input1, input2, output, act_info); _kernel = std::move(k); } @@ -104,7 +103,7 @@ CLElementwiseMax::CLElementwiseMax() void CLElementwiseMax::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLArithmeticOperationKernel>(); + auto k = std::make_unique<CLArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::MAX, input1, input2, output, act_info); _kernel = std::move(k); } @@ -125,7 +124,7 @@ CLElementwiseMin::CLElementwiseMin() void CLElementwiseMin::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLArithmeticOperationKernel>(); + auto k = std::make_unique<CLArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::MIN, input1, input2, output, act_info); _kernel = std::move(k); } @@ -146,7 +145,7 @@ CLElementwiseSquaredDiff::CLElementwiseSquaredDiff() void CLElementwiseSquaredDiff::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLArithmeticOperationKernel>(); + auto k = std::make_unique<CLArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::SQUARED_DIFF, input1, input2, output, act_info); _kernel = std::move(k); } @@ -167,7 +166,7 @@ CLElementwisePower::CLElementwisePower() void CLElementwisePower::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLArithmeticOperationKernel>(); + auto k = std::make_unique<CLArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::POWER, input1, input2, output, act_info); _kernel = std::move(k); } @@ -192,7 +191,7 @@ struct CLArithmeticAddition::Impl }; CLArithmeticAddition::CLArithmeticAddition() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLArithmeticAddition::CLArithmeticAddition(CLArithmeticAddition &&) = default; @@ -210,7 +209,7 @@ void CLArithmeticAddition::configure(const CLCompileContext &compile_context, co _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLArithmeticAddition>(); + _impl->op = std::make_unique<experimental::CLArithmeticAddition>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), policy, act_info); } @@ -238,7 +237,7 @@ struct CLArithmeticSubtraction::Impl }; CLArithmeticSubtraction::CLArithmeticSubtraction() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLArithmeticSubtraction::CLArithmeticSubtraction(CLArithmeticSubtraction &&) = default; @@ -256,7 +255,7 @@ void CLArithmeticSubtraction::configure(const CLCompileContext &compile_context, _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLArithmeticSubtraction>(); + _impl->op = std::make_unique<experimental::CLArithmeticSubtraction>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), policy, act_info); } @@ -284,7 +283,7 @@ struct CLArithmeticDivision::Impl }; CLArithmeticDivision::CLArithmeticDivision() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLArithmeticDivision::CLArithmeticDivision(CLArithmeticDivision &&) = default; @@ -301,7 +300,7 @@ void CLArithmeticDivision::configure(const CLCompileContext &compile_context, co _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLArithmeticDivision>(); + _impl->op = std::make_unique<experimental::CLArithmeticDivision>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } @@ -329,7 +328,7 @@ struct CLElementwiseMax::Impl }; CLElementwiseMax::CLElementwiseMax() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLElementwiseMax::CLElementwiseMax(CLElementwiseMax &&) = default; @@ -346,7 +345,7 @@ void CLElementwiseMax::configure(const CLCompileContext &compile_context, ICLTen _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLElementwiseMax>(); + _impl->op = std::make_unique<experimental::CLElementwiseMax>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } @@ -374,7 +373,7 @@ struct CLElementwiseMin::Impl }; CLElementwiseMin::CLElementwiseMin() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLElementwiseMin::CLElementwiseMin(CLElementwiseMin &&) = default; @@ -391,7 +390,7 @@ void CLElementwiseMin::configure(const CLCompileContext &compile_context, ICLTen _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLElementwiseMin>(); + _impl->op = std::make_unique<experimental::CLElementwiseMin>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } @@ -419,7 +418,7 @@ struct CLElementwiseSquaredDiff::Impl }; CLElementwiseSquaredDiff::CLElementwiseSquaredDiff() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLElementwiseSquaredDiff::CLElementwiseSquaredDiff(CLElementwiseSquaredDiff &&) = default; @@ -436,7 +435,7 @@ void CLElementwiseSquaredDiff::configure(const CLCompileContext &compile_context _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLElementwiseSquaredDiff>(); + _impl->op = std::make_unique<experimental::CLElementwiseSquaredDiff>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } @@ -464,7 +463,7 @@ struct CLElementwisePower::Impl }; CLElementwisePower::CLElementwisePower() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLElementwisePower::CLElementwisePower(CLElementwisePower &&) = default; @@ -481,7 +480,7 @@ void CLElementwisePower::configure(const CLCompileContext &compile_context, ICLT _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLElementwisePower>(); + _impl->op = std::make_unique<experimental::CLElementwisePower>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } diff --git a/src/runtime/CL/functions/CLEqualizeHistogram.cpp b/src/runtime/CL/functions/CLEqualizeHistogram.cpp index cc927a055b..11607cf71d 100644 --- a/src/runtime/CL/functions/CLEqualizeHistogram.cpp +++ b/src/runtime/CL/functions/CLEqualizeHistogram.cpp @@ -30,7 +30,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLHistogramKernel.h" #include "src/core/CL/kernels/CLTableLookupKernel.h" -#include "support/MemorySupport.h" #include <algorithm> #include <cmath> @@ -86,9 +85,9 @@ void calculate_cum_dist_and_lut(CLDistribution1D &dist, CLDistribution1D &cum_di } // namespace CLEqualizeHistogram::CLEqualizeHistogram() - : _histogram_kernel(support::cpp14::make_unique<CLHistogramKernel>()), - _border_histogram_kernel(support::cpp14::make_unique<CLHistogramBorderKernel>()), - _map_histogram_kernel(support::cpp14::make_unique<CLTableLookupKernel>()), + : _histogram_kernel(std::make_unique<CLHistogramKernel>()), + _border_histogram_kernel(std::make_unique<CLHistogramBorderKernel>()), + _map_histogram_kernel(std::make_unique<CLTableLookupKernel>()), _hist(nr_bins, 0, max_range), _cum_dist(nr_bins, 0, max_range), _cd_lut(nr_bins, DataType::U8) diff --git a/src/runtime/CL/functions/CLErode.cpp b/src/runtime/CL/functions/CLErode.cpp index 6880c4845a..29551fc6bd 100644 --- a/src/runtime/CL/functions/CLErode.cpp +++ b/src/runtime/CL/functions/CLErode.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLErodeKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLErode::configure(ICLTensor *input, ICLTensor *output, BorderMode border_m void CLErode::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLErodeKernel>(); + auto k = std::make_unique<CLErodeKernel>(); k->configure(compile_context, input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, BorderSize(1), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLFFT1D.cpp b/src/runtime/CL/functions/CLFFT1D.cpp index a0078689ff..c434b4e570 100644 --- a/src/runtime/CL/functions/CLFFT1D.cpp +++ b/src/runtime/CL/functions/CLFFT1D.cpp @@ -30,15 +30,14 @@ #include "src/core/CL/kernels/CLFFTRadixStageKernel.h" #include "src/core/CL/kernels/CLFFTScaleKernel.h" #include "src/core/utils/helpers/fft.h" -#include "support/MemorySupport.h" namespace arm_compute { CLFFT1D::CLFFT1D(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _digit_reverse_kernel(support::cpp14::make_unique<CLFFTDigitReverseKernel>()), + _digit_reverse_kernel(std::make_unique<CLFFTDigitReverseKernel>()), _fft_kernels(), - _scale_kernel(support::cpp14::make_unique<CLFFTScaleKernel>()), + _scale_kernel(std::make_unique<CLFFTScaleKernel>()), _digit_reversed_input(), _digit_reverse_indices(), _num_ffts(0), @@ -90,7 +89,7 @@ void CLFFT1D::configure(const CLCompileContext &compile_context, const ICLTensor fft_kernel_info.radix = radix_for_stage; fft_kernel_info.Nx = Nx; fft_kernel_info.is_first_stage = (i == 0); - _fft_kernels.emplace_back(support::cpp14::make_unique<CLFFTRadixStageKernel>()); + _fft_kernels.emplace_back(std::make_unique<CLFFTRadixStageKernel>()); _fft_kernels.back()->configure(compile_context, &_digit_reversed_input, ((i == (_num_ffts - 1)) && !is_c2r) ? output : nullptr, fft_kernel_info); Nx *= radix_for_stage; diff --git a/src/runtime/CL/functions/CLFFTConvolutionLayer.cpp b/src/runtime/CL/functions/CLFFTConvolutionLayer.cpp index 5472e8469f..97b64b24f3 100644 --- a/src/runtime/CL/functions/CLFFTConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLFFTConvolutionLayer.cpp @@ -39,8 +39,6 @@ #include "src/core/helpers/AutoConfiguration.h" #include "src/core/utils/helpers/fft.h" -#include "support/MemorySupport.h" - namespace arm_compute { namespace @@ -168,7 +166,7 @@ void CLFFTConvolutionLayer::configure(const CLCompileContext &compile_context, I _pad_weights_func.configure(compile_context, &_flipped_weights, &_padded_weights, padding_w); // Transform weights - _transform_weights_func = support::cpp14::make_unique<CLFFT2D>(); + _transform_weights_func = std::make_unique<CLFFT2D>(); _transform_weights_func->configure(compile_context, &_padded_weights, &_transformed_weights, FFT2DInfo()); // Pad input diff --git a/src/runtime/CL/functions/CLFastCorners.cpp b/src/runtime/CL/functions/CLFastCorners.cpp index 110d2c3639..a3a62d6d5e 100644 --- a/src/runtime/CL/functions/CLFastCorners.cpp +++ b/src/runtime/CL/functions/CLFastCorners.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/ITensorAllocator.h" #include "src/core/CL/kernels/CLFastCornersKernel.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <algorithm> #include <cstring> @@ -40,9 +39,9 @@ using namespace arm_compute; CLFastCorners::CLFastCorners(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _fast_corners_kernel(support::cpp14::make_unique<CLFastCornersKernel>()), + _fast_corners_kernel(std::make_unique<CLFastCornersKernel>()), _suppr_func(), - _copy_array_kernel(support::cpp14::make_unique<CLCopyToArrayKernel>()), + _copy_array_kernel(std::make_unique<CLCopyToArrayKernel>()), _output(), _suppr(), _win(), diff --git a/src/runtime/CL/functions/CLFill.cpp b/src/runtime/CL/functions/CLFill.cpp index 855ed8380a..30843d8cc0 100644 --- a/src/runtime/CL/functions/CLFill.cpp +++ b/src/runtime/CL/functions/CLFill.cpp @@ -26,8 +26,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLMemsetKernel.h" -#include "support/MemorySupport.h" - #include <utility> namespace arm_compute @@ -39,7 +37,7 @@ void CLFill::configure(ICLTensor *tensor, PixelValue constant_value) void CLFill::configure(const CLCompileContext &compile_context, ICLTensor *tensor, PixelValue constant_value) { - auto k = arm_compute::support::cpp14::make_unique<CLMemsetKernel>(); + auto k = std::make_unique<CLMemsetKernel>(); k->configure(compile_context, tensor, constant_value); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLFillBorder.cpp b/src/runtime/CL/functions/CLFillBorder.cpp index 27d132b842..2e5a29ece1 100644 --- a/src/runtime/CL/functions/CLFillBorder.cpp +++ b/src/runtime/CL/functions/CLFillBorder.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLFillBorder.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLFillBorder::configure(ICLTensor *tensor, unsigned int border_width, Borde void CLFillBorder::configure(const CLCompileContext &compile_context, ICLTensor *tensor, unsigned int border_width, BorderMode border_mode, const PixelValue &constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLFillBorderKernel>(); + auto k = std::make_unique<CLFillBorderKernel>(); k->configure(compile_context, tensor, BorderSize(border_width), border_mode, constant_border_value); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLFlattenLayer.cpp b/src/runtime/CL/functions/CLFlattenLayer.cpp index 0646a0d3a0..c10e91bf96 100644 --- a/src/runtime/CL/functions/CLFlattenLayer.cpp +++ b/src/runtime/CL/functions/CLFlattenLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFlattenLayerKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -36,7 +35,7 @@ void CLFlattenLayer::configure(const ICLTensor *input, ICLTensor *output) void CLFlattenLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLFlattenLayerKernel>(); + auto k = std::make_unique<CLFlattenLayerKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); CLScheduler::get().tune_kernel_static(*_kernel); diff --git a/src/runtime/CL/functions/CLFloor.cpp b/src/runtime/CL/functions/CLFloor.cpp index 770e6a3781..5549d09b24 100644 --- a/src/runtime/CL/functions/CLFloor.cpp +++ b/src/runtime/CL/functions/CLFloor.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLFloor.h" #include "src/core/CL/kernels/CLFloorKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -35,7 +34,7 @@ void CLFloor::configure(const ICLTensor *input, ICLTensor *output) void CLFloor::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLFloorKernel>(); + auto k = std::make_unique<CLFloorKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp index 1acf3c7a8b..46a90a54b7 100644 --- a/src/runtime/CL/functions/CLFullyConnectedLayer.cpp +++ b/src/runtime/CL/functions/CLFullyConnectedLayer.cpp @@ -42,7 +42,6 @@ #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" #include "src/core/CL/kernels/CLTransposeKernel.h" #include "support/Cast.h" -#include "support/MemorySupport.h" #include <algorithm> @@ -149,7 +148,7 @@ void CLFullyConnectedLayerReshapeWeights::configure(const ICLTensor *input, ICLT void CLFullyConnectedLayerReshapeWeights::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLTransposeKernel>(); + auto k = std::make_unique<CLTransposeKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLFuseBatchNormalization.cpp b/src/runtime/CL/functions/CLFuseBatchNormalization.cpp index f018e5a8ae..2945508012 100644 --- a/src/runtime/CL/functions/CLFuseBatchNormalization.cpp +++ b/src/runtime/CL/functions/CLFuseBatchNormalization.cpp @@ -29,12 +29,11 @@ #include "arm_compute/core/Types.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFuseBatchNormalizationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLFuseBatchNormalization::CLFuseBatchNormalization() - : _fuse_bn_kernel(support::cpp14::make_unique<CLFuseBatchNormalizationKernel>()) + : _fuse_bn_kernel(std::make_unique<CLFuseBatchNormalizationKernel>()) { } diff --git a/src/runtime/CL/functions/CLGEMM.cpp b/src/runtime/CL/functions/CLGEMM.cpp index 57a5f9739e..181ae2843b 100644 --- a/src/runtime/CL/functions/CLGEMM.cpp +++ b/src/runtime/CL/functions/CLGEMM.cpp @@ -49,8 +49,6 @@ #include "src/runtime/CL/gemm/CLGEMMKernelSelection.h" #include "support/Cast.h" -#include "support/MemorySupport.h" - namespace arm_compute { using namespace arm_compute::misc::shape_calculator; @@ -60,7 +58,7 @@ using namespace arm_compute::utils::cast; namespace weights_transformations { CLGEMMReshapeRHSMatrixKernelManaged::CLGEMMReshapeRHSMatrixKernelManaged() - : _kernel(support::cpp14::make_unique<CLGEMMReshapeRHSMatrixKernel>()) + : _kernel(std::make_unique<CLGEMMReshapeRHSMatrixKernel>()) { } @@ -102,13 +100,13 @@ void CLGEMMReshapeRHSMatrixKernelManaged::configure(const CLCompileContext &comp CLGEMM::CLGEMM(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager) : _memory_group(std::move(memory_manager)), _weights_manager(weights_manager), - _mm_kernel(support::cpp14::make_unique<CLGEMMMatrixMultiplyKernel>()), - _reshape_lhs_kernel(support::cpp14::make_unique<CLGEMMReshapeLHSMatrixKernel>()), - _reshape_rhs_kernel(support::cpp14::make_unique<CLGEMMReshapeRHSMatrixKernel>()), - _reshape_rhs_kernel_managed(support::cpp14::make_unique<weights_transformations::CLGEMMReshapeRHSMatrixKernelManaged>()), - _mm_reshaped_kernel(support::cpp14::make_unique<CLGEMMMatrixMultiplyReshapedKernel>()), - _mm_reshaped_only_rhs_kernel(support::cpp14::make_unique<CLGEMMMatrixMultiplyReshapedOnlyRHSKernel>()), - _mm_reshaped_only_rhs_fallback_kernel(support::cpp14::make_unique<CLGEMMMatrixMultiplyReshapedOnlyRHSKernel>()), + _mm_kernel(std::make_unique<CLGEMMMatrixMultiplyKernel>()), + _reshape_lhs_kernel(std::make_unique<CLGEMMReshapeLHSMatrixKernel>()), + _reshape_rhs_kernel(std::make_unique<CLGEMMReshapeRHSMatrixKernel>()), + _reshape_rhs_kernel_managed(std::make_unique<weights_transformations::CLGEMMReshapeRHSMatrixKernelManaged>()), + _mm_reshaped_kernel(std::make_unique<CLGEMMMatrixMultiplyReshapedKernel>()), + _mm_reshaped_only_rhs_kernel(std::make_unique<CLGEMMMatrixMultiplyReshapedOnlyRHSKernel>()), + _mm_reshaped_only_rhs_fallback_kernel(std::make_unique<CLGEMMMatrixMultiplyReshapedOnlyRHSKernel>()), _tmp_a(), _tmp_b(), _original_b(nullptr), diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp index 4d26df5e43..f37f06b0ff 100644 --- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp @@ -46,7 +46,6 @@ #include "src/core/CL/kernels/CLWeightsReshapeKernel.h" #include "src/core/helpers/AutoConfiguration.h" #include "support/Cast.h" -#include "support/MemorySupport.h" #include <cmath> #include <memory> @@ -58,7 +57,7 @@ using namespace arm_compute::misc::shape_calculator; using namespace arm_compute::utils::cast; CLConvolutionLayerReshapeWeights::CLConvolutionLayerReshapeWeights() - : _weights_reshape_kernel(support::cpp14::make_unique<CLWeightsReshapeKernel>()) + : _weights_reshape_kernel(std::make_unique<CLWeightsReshapeKernel>()) { } @@ -117,9 +116,9 @@ void CLConvolutionLayerReshapeWeights::run() } CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager) - : _memory_group(memory_manager), _weights_manager(weights_manager), _reshape_weights(), _reshape_weights_managed(), _im2col_kernel(support::cpp14::make_unique<CLIm2ColKernel>()), - _mm_gemm(memory_manager, weights_manager), _mm_gemmlowp(memory_manager), _col2im_kernel(support::cpp14::make_unique<CLCol2ImKernel>()), _activationlayer_function(), _original_weights(nullptr), - _im2col_output(), _weights_reshaped(), _gemm_output(), _skip_im2col(false), _skip_col2im(false), _is_quantized(false), _fuse_activation(true), _is_prepared(false) + : _memory_group(memory_manager), _weights_manager(weights_manager), _reshape_weights(), _reshape_weights_managed(), _im2col_kernel(std::make_unique<CLIm2ColKernel>()), _mm_gemm(memory_manager, + weights_manager), _mm_gemmlowp(memory_manager), _col2im_kernel(std::make_unique<CLCol2ImKernel>()), _activationlayer_function(), _original_weights(nullptr), _im2col_output(), _weights_reshaped(), + _gemm_output(), _skip_im2col(false), _skip_col2im(false), _is_quantized(false), _fuse_activation(true), _is_prepared(false) { } diff --git a/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp index 4d277f0982..a040e9d38e 100644 --- a/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLGEMMDeconvolutionLayer.cpp @@ -43,7 +43,6 @@ #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" #include "src/core/CL/kernels/CLIm2ColKernel.h" #include "src/core/CL/kernels/CLWeightsReshapeKernel.h" -#include "support/MemorySupport.h" #include <tuple> @@ -114,7 +113,7 @@ CLGEMMDeconvolutionLayer::CLGEMMDeconvolutionLayer(std::shared_ptr<IMemoryManage _permute_weights_to_nhwc(), _reshape_weights(), _transpose_weights(), - _deconv_reshape(support::cpp14::make_unique<CLDeconvolutionReshapeOutputKernel>()), + _deconv_reshape(std::make_unique<CLDeconvolutionReshapeOutputKernel>()), _slice_gemm(), _gemmlowp_final(), _reshaped_weights(), diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp index d3d80a39e3..4bf5bde61e 100644 --- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp +++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp @@ -44,7 +44,6 @@ #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/runtime/CL/gemm/CLGEMMKernelSelection.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -79,14 +78,14 @@ inline bool is_gemm_reshaped(unsigned int m, unsigned int n, unsigned int k, Dat CLGEMMLowpMatrixMultiplyCore::CLGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _weights_to_qasymm8(support::cpp14::make_unique<CLDepthConvertLayerKernel>()), - _mm_native_kernel(support::cpp14::make_unique<CLGEMMLowpMatrixMultiplyNativeKernel>()), - _mm_reshaped_only_rhs_kernel(support::cpp14::make_unique<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel>()), - _mtx_b_reshape_kernel(support::cpp14::make_unique<CLGEMMReshapeRHSMatrixKernel>()), - _mtx_a_reduction_kernel(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _mtx_b_reduction_kernel(support::cpp14::make_unique<CLGEMMLowpMatrixBReductionKernel>()), - _offset_contribution_kernel(support::cpp14::make_unique<CLGEMMLowpOffsetContributionKernel>()), - _offset_contribution_output_stage_kernel(support::cpp14::make_unique<CLGEMMLowpOffsetContributionOutputStageKernel>()), + _weights_to_qasymm8(std::make_unique<CLDepthConvertLayerKernel>()), + _mm_native_kernel(std::make_unique<CLGEMMLowpMatrixMultiplyNativeKernel>()), + _mm_reshaped_only_rhs_kernel(std::make_unique<CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel>()), + _mtx_b_reshape_kernel(std::make_unique<CLGEMMReshapeRHSMatrixKernel>()), + _mtx_a_reduction_kernel(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _mtx_b_reduction_kernel(std::make_unique<CLGEMMLowpMatrixBReductionKernel>()), + _offset_contribution_kernel(std::make_unique<CLGEMMLowpOffsetContributionKernel>()), + _offset_contribution_output_stage_kernel(std::make_unique<CLGEMMLowpOffsetContributionOutputStageKernel>()), _qasymm8_weights(), _vector_sum_col(), _vector_sum_row(), diff --git a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp index f9c5247d2d..be452aaf3d 100644 --- a/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp +++ b/src/runtime/CL/functions/CLGEMMLowpOutputStage.cpp @@ -28,7 +28,6 @@ #include "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel.h" #include "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel.h" #include "src/core/CL/kernels/CLGEMMLowpQuantizeDownInt32ScaleKernel.h" -#include "support/MemorySupport.h" #include <algorithm> @@ -52,7 +51,7 @@ void CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const CLComp info.gemmlowp_min_bound = min; info.gemmlowp_max_bound = max; info.output_data_type = DataType::QASYMM8; - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); + auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); k->configure(compile_context, input, bias, output, &info); _kernel = std::move(k); } @@ -85,7 +84,7 @@ void CLGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::configure(const CLCompi info.gemmlowp_min_bound = min; info.gemmlowp_max_bound = max; info.output_data_type = DataType::QASYMM8_SIGNED; - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); + auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); k->configure(compile_context, input, bias, output, &info); _kernel = std::move(k); } @@ -117,7 +116,7 @@ void CLGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::configure(const CLComp info.gemmlowp_min_bound = min; info.gemmlowp_max_bound = max; info.output_data_type = DataType::QSYMM16; - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); + auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); k->configure(compile_context, input, bias, output, &info); _kernel = std::move(k); } @@ -145,21 +144,21 @@ void CLGEMMLowpOutputStage::configure(const CLCompileContext &compile_context, c { case GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT: { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); + auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFixedPointKernel>(); k->configure(compile_context, input, bias, output, &info); _kernel = std::move(k); break; } case GEMMLowpOutputStageType::QUANTIZE_DOWN: { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleKernel>(); + auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleKernel>(); k->configure(compile_context, input, bias, output, &info); _kernel = std::move(k); break; } case GEMMLowpOutputStageType::QUANTIZE_DOWN_FLOAT: { - auto k = arm_compute::support::cpp14::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel>(); + auto k = std::make_unique<CLGEMMLowpQuantizeDownInt32ScaleByFloatKernel>(); k->configure(compile_context, input, bias, output, &info); _kernel = std::move(k); break; diff --git a/src/runtime/CL/functions/CLGather.cpp b/src/runtime/CL/functions/CLGather.cpp index de6296f6a3..bde34dc4db 100644 --- a/src/runtime/CL/functions/CLGather.cpp +++ b/src/runtime/CL/functions/CLGather.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/CL/ICLTensor.h" #include "src/core/CL/kernels/CLGatherKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void CLGather::configure(const ICLTensor *input, const ICLTensor *indices, ICLTe void CLGather::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *indices, ICLTensor *output, int axis) { - auto k = arm_compute::support::cpp14::make_unique<CLGatherKernel>(); + auto k = std::make_unique<CLGatherKernel>(); k->configure(compile_context, input, indices, output, axis); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLGaussian3x3.cpp b/src/runtime/CL/functions/CLGaussian3x3.cpp index 97db9ba06d..8eeade2f47 100644 --- a/src/runtime/CL/functions/CLGaussian3x3.cpp +++ b/src/runtime/CL/functions/CLGaussian3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLGaussian3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLGaussian3x3::configure(ICLTensor *input, ICLTensor *output, BorderMode bo void CLGaussian3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLGaussian3x3Kernel>(); + auto k = std::make_unique<CLGaussian3x3Kernel>(); k->configure(compile_context, input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLGaussian5x5.cpp b/src/runtime/CL/functions/CLGaussian5x5.cpp index f7470d4ecf..ee72fcbe11 100644 --- a/src/runtime/CL/functions/CLGaussian5x5.cpp +++ b/src/runtime/CL/functions/CLGaussian5x5.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/ITensorAllocator.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLGaussian5x5Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,9 +38,9 @@ using namespace arm_compute; CLGaussian5x5::CLGaussian5x5(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _kernel_hor(support::cpp14::make_unique<CLGaussian5x5HorKernel>()), - _kernel_vert(support::cpp14::make_unique<CLGaussian5x5VertKernel>()), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()), + _kernel_hor(std::make_unique<CLGaussian5x5HorKernel>()), + _kernel_vert(std::make_unique<CLGaussian5x5VertKernel>()), + _border_handler(std::make_unique<CLFillBorderKernel>()), _tmp() { } diff --git a/src/runtime/CL/functions/CLGaussianPyramid.cpp b/src/runtime/CL/functions/CLGaussianPyramid.cpp index 66b85352c1..9fe35f6f0e 100644 --- a/src/runtime/CL/functions/CLGaussianPyramid.cpp +++ b/src/runtime/CL/functions/CLGaussianPyramid.cpp @@ -38,7 +38,6 @@ #include "src/core/CL/kernels/CLGaussian5x5Kernel.h" #include "src/core/CL/kernels/CLGaussianPyramidKernel.h" #include "src/core/CL/kernels/CLScaleKernel.h" -#include "support/MemorySupport.h" #include <cstddef> @@ -101,19 +100,19 @@ void CLGaussianPyramidHalf::configure(const CLCompileContext &compile_context, I for(size_t i = 0; i < num_levels - 1; ++i) { /* Configure horizontal kernel */ - _horizontal_reduction.emplace_back(support::cpp14::make_unique<CLGaussianPyramidHorKernel>()); + _horizontal_reduction.emplace_back(std::make_unique<CLGaussianPyramidHorKernel>()); _horizontal_reduction.back()->configure(compile_context, _pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i)); /* Configure vertical kernel */ - _vertical_reduction.emplace_back(support::cpp14::make_unique<CLGaussianPyramidVertKernel>()); + _vertical_reduction.emplace_back(std::make_unique<CLGaussianPyramidVertKernel>()); _vertical_reduction.back()->configure(compile_context, _tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1)); /* Configure border */ - _horizontal_border_handler.emplace_back(support::cpp14::make_unique<CLFillBorderKernel>()); + _horizontal_border_handler.emplace_back(std::make_unique<CLFillBorderKernel>()); _horizontal_border_handler.back()->configure(compile_context, _pyramid->get_pyramid_level(i), _horizontal_reduction.back()->border_size(), border_mode, PixelValue(constant_border_value)); /* Configure border */ - _vertical_border_handler.emplace_back(support::cpp14::make_unique<CLFillBorderKernel>()); + _vertical_border_handler.emplace_back(std::make_unique<CLFillBorderKernel>()); _vertical_border_handler.back()->configure(compile_context, _tmp.get_pyramid_level(i), _vertical_reduction.back()->border_size(), border_mode, PixelValue(pixel_value_u16)); } _tmp.allocate(); @@ -185,7 +184,7 @@ void CLGaussianPyramidOrb::configure(const CLCompileContext &compile_context, IC _gauss5x5[i].configure(compile_context, _pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i), border_mode, constant_border_value); /* Configure scale image kernel */ - _scale_nearest.emplace_back(support::cpp14::make_unique<CLScaleKernel>()); + _scale_nearest.emplace_back(std::make_unique<CLScaleKernel>()); _scale_nearest.back()->configure(compile_context, _tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1), ScaleKernelInfo{ InterpolationPolicy::NEAREST_NEIGHBOR, border_mode, PixelValue(), SamplingPolicy::CENTER }); } diff --git a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp index 87bf39030a..e536816f97 100644 --- a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp +++ b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp @@ -32,22 +32,21 @@ #include "src/core/CL/kernels/CLPermuteKernel.h" #include "src/core/CL/kernels/CLQuantizationLayerKernel.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" namespace arm_compute { CLGenerateProposalsLayer::CLGenerateProposalsLayer(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(memory_manager), - _permute_deltas_kernel(support::cpp14::make_unique<CLPermuteKernel>()), + _permute_deltas_kernel(std::make_unique<CLPermuteKernel>()), _flatten_deltas(), - _permute_scores_kernel(support::cpp14::make_unique<CLPermuteKernel>()), + _permute_scores_kernel(std::make_unique<CLPermuteKernel>()), _flatten_scores(), - _compute_anchors_kernel(support::cpp14::make_unique<CLComputeAllAnchorsKernel>()), - _bounding_box_kernel(support::cpp14::make_unique<CLBoundingBoxTransformKernel>()), - _pad_kernel(support::cpp14::make_unique<CLPadLayerKernel>()), - _dequantize_anchors(support::cpp14::make_unique<CLDequantizationLayerKernel>()), - _dequantize_deltas(support::cpp14::make_unique<CLDequantizationLayerKernel>()), - _quantize_all_proposals(support::cpp14::make_unique<CLQuantizationLayerKernel>()), + _compute_anchors_kernel(std::make_unique<CLComputeAllAnchorsKernel>()), + _bounding_box_kernel(std::make_unique<CLBoundingBoxTransformKernel>()), + _pad_kernel(std::make_unique<CLPadLayerKernel>()), + _dequantize_anchors(std::make_unique<CLDequantizationLayerKernel>()), + _dequantize_deltas(std::make_unique<CLDequantizationLayerKernel>()), + _quantize_all_proposals(std::make_unique<CLQuantizationLayerKernel>()), _cpp_nms(memory_manager), _is_nhwc(false), _is_qasymm8(false), diff --git a/src/runtime/CL/functions/CLHOGDescriptor.cpp b/src/runtime/CL/functions/CLHOGDescriptor.cpp index 80026532ab..8d9ea17d66 100644 --- a/src/runtime/CL/functions/CLHOGDescriptor.cpp +++ b/src/runtime/CL/functions/CLHOGDescriptor.cpp @@ -31,15 +31,14 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLHOGDescriptorKernel.h" #include "src/core/CL/kernels/CLMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLHOGDescriptor::CLHOGDescriptor(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _gradient(), - _orient_bin(support::cpp14::make_unique<CLHOGOrientationBinningKernel>()), - _block_norm(support::cpp14::make_unique<CLHOGBlockNormalizationKernel>()), + _orient_bin(std::make_unique<CLHOGOrientationBinningKernel>()), + _block_norm(std::make_unique<CLHOGBlockNormalizationKernel>()), _mag(), _phase(), _hog_space() diff --git a/src/runtime/CL/functions/CLHOGDetector.cpp b/src/runtime/CL/functions/CLHOGDetector.cpp index 07ae8151c0..365021c723 100644 --- a/src/runtime/CL/functions/CLHOGDetector.cpp +++ b/src/runtime/CL/functions/CLHOGDetector.cpp @@ -26,14 +26,13 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLHOGDetectorKernel.h" -#include "support/MemorySupport.h" #include <algorithm> using namespace arm_compute; CLHOGDetector::CLHOGDetector() - : _hog_detector_kernel(support::cpp14::make_unique<CLHOGDetectorKernel>()), _detection_windows(nullptr), _num_detection_windows() + : _hog_detector_kernel(std::make_unique<CLHOGDetectorKernel>()), _detection_windows(nullptr), _num_detection_windows() { } diff --git a/src/runtime/CL/functions/CLHOGGradient.cpp b/src/runtime/CL/functions/CLHOGGradient.cpp index 5f3b9cf529..f3aa527417 100644 --- a/src/runtime/CL/functions/CLHOGGradient.cpp +++ b/src/runtime/CL/functions/CLHOGGradient.cpp @@ -28,14 +28,13 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLHOGGradient::CLHOGGradient(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _derivative(), - _mag_phase(support::cpp14::make_unique<CLMagnitudePhaseKernel>()), + _mag_phase(std::make_unique<CLMagnitudePhaseKernel>()), _gx(), _gy() { diff --git a/src/runtime/CL/functions/CLHOGMultiDetection.cpp b/src/runtime/CL/functions/CLHOGMultiDetection.cpp index dfc90537cf..2464e6cf9f 100644 --- a/src/runtime/CL/functions/CLHOGMultiDetection.cpp +++ b/src/runtime/CL/functions/CLHOGMultiDetection.cpp @@ -34,7 +34,6 @@ #include "src/core/CL/kernels/CLHOGDescriptorKernel.h" #include "src/core/CL/kernels/CLHOGDetectorKernel.h" #include "src/core/CL/kernels/CLMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -188,7 +187,7 @@ void CLHOGMultiDetection::configure(const CLCompileContext &compile_context, ICL _memory_group.manage(&_hog_space[i]); // Initialise orientation binning kernel - _orient_bin_kernel.emplace_back(support::cpp14::make_unique<CLHOGOrientationBinningKernel>()); + _orient_bin_kernel.emplace_back(std::make_unique<CLHOGOrientationBinningKernel>()); _orient_bin_kernel.back()->configure(compile_context, &_mag, &_phase, &_hog_space[i], multi_hog->model(idx_multi_hog)->info()); } @@ -210,7 +209,7 @@ void CLHOGMultiDetection::configure(const CLCompileContext &compile_context, ICL _memory_group.manage(&_hog_norm_space[i]); // Initialize block normalization kernel - _block_norm_kernel.emplace_back(support::cpp14::make_unique<CLHOGBlockNormalizationKernel>()); + _block_norm_kernel.emplace_back(std::make_unique<CLHOGBlockNormalizationKernel>()); _block_norm_kernel.back()->configure(compile_context, &_hog_space[idx_orient_bin], &_hog_norm_space[i], multi_hog->model(idx_multi_hog)->info()); } diff --git a/src/runtime/CL/functions/CLHarrisCorners.cpp b/src/runtime/CL/functions/CLHarrisCorners.cpp index 9d8ebceb30..37f428c677 100644 --- a/src/runtime/CL/functions/CLHarrisCorners.cpp +++ b/src/runtime/CL/functions/CLHarrisCorners.cpp @@ -37,7 +37,6 @@ #include "src/core/CL/kernels/CLHarrisCornersKernel.h" #include "src/core/CL/kernels/CLSobel5x5Kernel.h" #include "src/core/CL/kernels/CLSobel7x7Kernel.h" -#include "support/MemorySupport.h" #include <cmath> #include <utility> @@ -47,12 +46,12 @@ using namespace arm_compute; CLHarrisCorners::CLHarrisCorners(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT : _memory_group(std::move(memory_manager)), _sobel(nullptr), - _harris_score(support::cpp14::make_unique<CLHarrisScoreKernel>()), + _harris_score(std::make_unique<CLHarrisScoreKernel>()), _non_max_suppr(), _candidates(), _sort_euclidean(), - _border_gx(support::cpp14::make_unique<CLFillBorderKernel>()), - _border_gy(support::cpp14::make_unique<CLFillBorderKernel>()), + _border_gx(std::make_unique<CLFillBorderKernel>()), + _border_gy(std::make_unique<CLFillBorderKernel>()), _gx(), _gy(), _score(), @@ -106,21 +105,21 @@ void CLHarrisCorners::configure(const CLCompileContext &compile_context, ICLImag { case 3: { - auto k = arm_compute::support::cpp14::make_unique<CLSobel3x3>(); + auto k = std::make_unique<CLSobel3x3>(); k->configure(compile_context, input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); break; } case 5: { - auto k = arm_compute::support::cpp14::make_unique<CLSobel5x5>(); + auto k = std::make_unique<CLSobel5x5>(); k->configure(compile_context, input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); break; } case 7: { - auto k = arm_compute::support::cpp14::make_unique<CLSobel7x7>(); + auto k = std::make_unique<CLSobel7x7>(); k->configure(compile_context, input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); break; diff --git a/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp b/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp index bd680f448d..9bc060e6ca 100644 --- a/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp +++ b/src/runtime/CL/functions/CLInstanceNormalizationLayer.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLInstanceNormalizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -41,7 +40,7 @@ void CLInstanceNormalizationLayer::configure(ICLTensor *input, ICLTensor *output void CLInstanceNormalizationLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, float gamma, float beta, float epsilon, bool use_mixed_precision) { - auto k = arm_compute::support::cpp14::make_unique<CLInstanceNormalizationLayerKernel>(); + auto k = std::make_unique<CLInstanceNormalizationLayerKernel>(); k->configure(compile_context, input, output, InstanceNormalizationLayerKernelInfo(gamma, beta, epsilon, use_mixed_precision)); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLIntegralImage.cpp b/src/runtime/CL/functions/CLIntegralImage.cpp index 41e47e77c7..56a151a085 100644 --- a/src/runtime/CL/functions/CLIntegralImage.cpp +++ b/src/runtime/CL/functions/CLIntegralImage.cpp @@ -25,13 +25,12 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLIntegralImageKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLIntegralImage::CLIntegralImage() - : _integral_hor(support::cpp14::make_unique<CLIntegralImageHorKernel>()), - _integral_vert(support::cpp14::make_unique<CLIntegralImageVertKernel>()) + : _integral_hor(std::make_unique<CLIntegralImageHorKernel>()), + _integral_vert(std::make_unique<CLIntegralImageVertKernel>()) { } diff --git a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp index 64aac269cd..8c360aaa9e 100644 --- a/src/runtime/CL/functions/CLL2NormalizeLayer.cpp +++ b/src/runtime/CL/functions/CLL2NormalizeLayer.cpp @@ -32,7 +32,6 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLL2NormalizeLayerKernel.h" #include "src/core/CL/kernels/CLReductionOperationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -44,7 +43,7 @@ constexpr int max_input_tensor_dim = 3; CLL2NormalizeLayer::CLL2NormalizeLayer(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _reduce_func(), - _normalize_kernel(support::cpp14::make_unique<CLL2NormalizeLayerKernel>()), + _normalize_kernel(std::make_unique<CLL2NormalizeLayerKernel>()), _sumsq() { } diff --git a/src/runtime/CL/functions/CLLSTMLayer.cpp b/src/runtime/CL/functions/CLLSTMLayer.cpp index b095c06535..77df917119 100644 --- a/src/runtime/CL/functions/CLLSTMLayer.cpp +++ b/src/runtime/CL/functions/CLLSTMLayer.cpp @@ -44,7 +44,6 @@ #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" #include "src/core/CL/kernels/CLMemsetKernel.h" #include "src/core/CL/kernels/CLTransposeKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -54,10 +53,10 @@ using namespace arm_compute::utils::info_helpers; CLLSTMLayer::CLLSTMLayer(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _fully_connected_input_gate(), _accum_input_gate1(), _subtract_input_gate(), _pixelwise_mul_input_gate(), _activation_input_gate(), _fully_connected_forget_gate(), _accum_forget_gate1(), _pixelwise_mul_forget_gate(), _activation_forget_gate(), _fully_connected_cell_state(), _gemm_cell_state1(), - _transpose_cell_state(support::cpp14::make_unique<CLTransposeKernel>()), _accum_cell_state1(), _accum_cell_state2(), _pixelwise_mul_cell_state1(), _activation_cell_state(), _cell_clip(), + _transpose_cell_state(std::make_unique<CLTransposeKernel>()), _accum_cell_state1(), _accum_cell_state2(), _pixelwise_mul_cell_state1(), _activation_cell_state(), _cell_clip(), _pixelwise_mul_cell_state2(), _fully_connected_output(), _pixelwise_mul_output_state1(), _accum_output1(), _activation_output(), _activation_output_state(), _pixelwise_mul_output_state2(), - _fully_connected_output_state(), _projection_clip(), _copy_cell_state(support::cpp14::make_unique<CLCopyKernel>()), _copy_output(support::cpp14::make_unique<CLCopyKernel>()), _concat_scratch_buffer(), - _concat_inputs_forget_gate(), _concat_weights_forget_gate(), _concat_weights_input_gate(), _concat_weights_output(), _ones_memset_kernel(support::cpp14::make_unique<CLMemsetKernel>()), + _fully_connected_output_state(), _projection_clip(), _copy_cell_state(std::make_unique<CLCopyKernel>()), _copy_output(std::make_unique<CLCopyKernel>()), _concat_scratch_buffer(), + _concat_inputs_forget_gate(), _concat_weights_forget_gate(), _concat_weights_input_gate(), _concat_weights_output(), _ones_memset_kernel(std::make_unique<CLMemsetKernel>()), _mean_std_norm_input_gate(), _pixelwise_mul_input_gate_coeff(), _accum_input_gate_bias(), _mean_std_norm_forget_gate(), _pixelwise_mul_forget_gate_coeff(), _accum_forget_gate_bias(), _mean_std_norm_cell_gate(), _pixelwise_mul_cell_gate_coeff(), _accum_cell_gate_bias(), _mean_std_norm_output_gate(), _pixelwise_mul_output_gate_coeff(), _accum_output_gate_bias(), _input_gate_out1(), _input_gate_out2(), _input_gate_out3(), _input_gate_out4(), _forget_gate_out1(), _forget_gate_out2(), _forget_gate_out3(), _forget_gate_out4(), _forget_gate_out5(), _forget_gate_out6(), diff --git a/src/runtime/CL/functions/CLLocallyConnectedLayer.cpp b/src/runtime/CL/functions/CLLocallyConnectedLayer.cpp index 04e59ac4a6..3adae07095 100644 --- a/src/runtime/CL/functions/CLLocallyConnectedLayer.cpp +++ b/src/runtime/CL/functions/CLLocallyConnectedLayer.cpp @@ -31,7 +31,6 @@ #include "src/core/CL/kernels/CLIm2ColKernel.h" #include "src/core/CL/kernels/CLLocallyConnectedMatrixMultiplyKernel.h" #include "src/core/CL/kernels/CLWeightsReshapeKernel.h" -#include "support/MemorySupport.h" #include <cmath> #include <tuple> @@ -84,10 +83,10 @@ void calculate_shapes(const ITensorInfo *input, const ITensorInfo *weights, cons CLLocallyConnectedLayer::CLLocallyConnectedLayer(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _input_im2col_kernel(support::cpp14::make_unique<CLIm2ColKernel>()), - _weights_reshape_kernel(support::cpp14::make_unique<CLWeightsReshapeKernel>()), - _mm_kernel(support::cpp14::make_unique<CLLocallyConnectedMatrixMultiplyKernel>()), - _output_col2im_kernel(support::cpp14::make_unique<CLCol2ImKernel>()), + _input_im2col_kernel(std::make_unique<CLIm2ColKernel>()), + _weights_reshape_kernel(std::make_unique<CLWeightsReshapeKernel>()), + _mm_kernel(std::make_unique<CLLocallyConnectedMatrixMultiplyKernel>()), + _output_col2im_kernel(std::make_unique<CLCol2ImKernel>()), _input_im2col_reshaped(), _weights_reshaped(), _gemm_output(), diff --git a/src/runtime/CL/functions/CLLogicalAnd.cpp b/src/runtime/CL/functions/CLLogicalAnd.cpp index 55d3dc523b..f1c53651c7 100644 --- a/src/runtime/CL/functions/CLLogicalAnd.cpp +++ b/src/runtime/CL/functions/CLLogicalAnd.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLLogicalAnd.h" #include "arm_compute/core/CL/ICLTensor.h" #include "src/core/CL/kernels/CLElementwiseOperationKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ namespace experimental { void CLLogicalAnd::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLLogicalBinaryKernel>(); + auto k = std::make_unique<CLLogicalBinaryKernel>(); k->configure(compile_context, kernels::LogicalOperation::And, input1, input2, output); _kernel = std::move(k); } @@ -59,7 +58,7 @@ struct CLLogicalAnd::Impl }; CLLogicalAnd::CLLogicalAnd() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLLogicalAnd::CLLogicalAnd(CLLogicalAnd &&) = default; @@ -76,7 +75,7 @@ void CLLogicalAnd::configure(const CLCompileContext &compile_context, ICLTensor _impl->src0 = input1; _impl->src1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLLogicalAnd>(); + _impl->op = std::make_unique<experimental::CLLogicalAnd>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info()); } diff --git a/src/runtime/CL/functions/CLLogicalNot.cpp b/src/runtime/CL/functions/CLLogicalNot.cpp index 67aa3192f8..d3774da597 100644 --- a/src/runtime/CL/functions/CLLogicalNot.cpp +++ b/src/runtime/CL/functions/CLLogicalNot.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLLogicalNot.h" #include "arm_compute/core/CL/ICLTensor.h" #include "src/core/CL/kernels/CLElementWiseUnaryLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ namespace experimental { void CLLogicalNot::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLElementWiseUnaryLayerKernel>(); + auto k = std::make_unique<CLElementWiseUnaryLayerKernel>(); k->configure(compile_context, input, output, ElementWiseUnary::LOGICAL_NOT); _kernel = std::move(k); } @@ -58,7 +57,7 @@ struct CLLogicalNot::Impl }; CLLogicalNot::CLLogicalNot() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLLogicalNot::CLLogicalNot(CLLogicalNot &&) = default; @@ -74,7 +73,7 @@ void CLLogicalNot::configure(const CLCompileContext &compile_context, const ICLT { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLLogicalNot>(); + _impl->op = std::make_unique<experimental::CLLogicalNot>(); _impl->op->configure(compile_context, input->info(), output->info()); } diff --git a/src/runtime/CL/functions/CLLogicalOr.cpp b/src/runtime/CL/functions/CLLogicalOr.cpp index b5be3cf816..8c6087ed7d 100644 --- a/src/runtime/CL/functions/CLLogicalOr.cpp +++ b/src/runtime/CL/functions/CLLogicalOr.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLLogicalOr.h" #include "arm_compute/core/CL/ICLTensor.h" #include "src/core/CL/kernels/CLElementwiseOperationKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ namespace experimental { void CLLogicalOr::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLLogicalBinaryKernel>(); + auto k = std::make_unique<CLLogicalBinaryKernel>(); k->configure(compile_context, kernels::LogicalOperation::Or, input1, input2, output); _kernel = std::move(k); } @@ -59,7 +58,7 @@ struct CLLogicalOr::Impl }; CLLogicalOr::CLLogicalOr() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLLogicalOr::CLLogicalOr(CLLogicalOr &&) = default; @@ -76,7 +75,7 @@ void CLLogicalOr::configure(const CLCompileContext &compile_context, ICLTensor * _impl->src0 = input1; _impl->src1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLLogicalOr>(); + _impl->op = std::make_unique<experimental::CLLogicalOr>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info()); } diff --git a/src/runtime/CL/functions/CLMagnitude.cpp b/src/runtime/CL/functions/CLMagnitude.cpp index fb3ebdaa96..0599a11fa1 100644 --- a/src/runtime/CL/functions/CLMagnitude.cpp +++ b/src/runtime/CL/functions/CLMagnitude.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLMagnitude.h" #include "src/core/CL/kernels/CLMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLMagnitude::configure(const ICLTensor *input1, const ICLTensor *input2, IC void CLMagnitude::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, MagnitudeType mag_type) { - auto k = arm_compute::support::cpp14::make_unique<CLMagnitudePhaseKernel>(); + auto k = std::make_unique<CLMagnitudePhaseKernel>(); k->configure(compile_context, input1, input2, output, nullptr, mag_type); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLMaxUnpoolingLayer.cpp b/src/runtime/CL/functions/CLMaxUnpoolingLayer.cpp index 392bff2b4e..c9deb301ef 100644 --- a/src/runtime/CL/functions/CLMaxUnpoolingLayer.cpp +++ b/src/runtime/CL/functions/CLMaxUnpoolingLayer.cpp @@ -29,13 +29,12 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLMaxUnpoolingLayerKernel.h" #include "src/core/CL/kernels/CLMemsetKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLMaxUnpoolingLayer::CLMaxUnpoolingLayer() - : _memset_kernel(support::cpp14::make_unique<CLMemsetKernel>()), - _unpooling_layer_kernel(support::cpp14::make_unique<CLMaxUnpoolingLayerKernel>()) + : _memset_kernel(std::make_unique<CLMemsetKernel>()), + _unpooling_layer_kernel(std::make_unique<CLMaxUnpoolingLayerKernel>()) { } diff --git a/src/runtime/CL/functions/CLMeanStdDev.cpp b/src/runtime/CL/functions/CLMeanStdDev.cpp index c91bc954b8..d8cd41d45f 100644 --- a/src/runtime/CL/functions/CLMeanStdDev.cpp +++ b/src/runtime/CL/functions/CLMeanStdDev.cpp @@ -28,7 +28,6 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLMeanStdDevKernel.h" #include "src/core/CL/kernels/CLReductionOperationKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -43,8 +42,8 @@ CLMeanStdDev::CLMeanStdDev(std::shared_ptr<IMemoryManager> memory_manager) // NO _reduction_output_stddev(), _mean(nullptr), _stddev(nullptr), - _mean_stddev_kernel(support::cpp14::make_unique<CLMeanStdDevKernel>()), - _fill_border_kernel(support::cpp14::make_unique<CLFillBorderKernel>()), + _mean_stddev_kernel(std::make_unique<CLMeanStdDevKernel>()), + _fill_border_kernel(std::make_unique<CLFillBorderKernel>()), _global_sum(), _global_sum_squared() { diff --git a/src/runtime/CL/functions/CLMeanStdDevNormalizationLayer.cpp b/src/runtime/CL/functions/CLMeanStdDevNormalizationLayer.cpp index 5b5ff49ecb..0f6a0e47a4 100644 --- a/src/runtime/CL/functions/CLMeanStdDevNormalizationLayer.cpp +++ b/src/runtime/CL/functions/CLMeanStdDevNormalizationLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLMeanStdDevNormalizationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void CLMeanStdDevNormalizationLayer::configure(ICLTensor *input, ICLTensor *outp void CLMeanStdDevNormalizationLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, float epsilon) { - auto k = arm_compute::support::cpp14::make_unique<CLMeanStdDevNormalizationKernel>(); + auto k = std::make_unique<CLMeanStdDevNormalizationKernel>(); k->configure(compile_context, input, output, epsilon); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLMedian3x3.cpp b/src/runtime/CL/functions/CLMedian3x3.cpp index 2040ebd4f5..b32063a8fe 100644 --- a/src/runtime/CL/functions/CLMedian3x3.cpp +++ b/src/runtime/CL/functions/CLMedian3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLMedian3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLMedian3x3::configure(ICLTensor *input, ICLTensor *output, BorderMode bord void CLMedian3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLMedian3x3Kernel>(); + auto k = std::make_unique<CLMedian3x3Kernel>(); k->configure(compile_context, input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLMinMaxLocation.cpp b/src/runtime/CL/functions/CLMinMaxLocation.cpp index 3ddd4d04ed..ace6a1cb21 100644 --- a/src/runtime/CL/functions/CLMinMaxLocation.cpp +++ b/src/runtime/CL/functions/CLMinMaxLocation.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/CL/functions/CLMinMaxLocation.h" #include "arm_compute/core/CL/CLHelpers.h" #include "src/core/CL/kernels/CLMinMaxLocationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLMinMaxLocation::CLMinMaxLocation() - : _min_max_kernel(support::cpp14::make_unique<CLMinMaxKernel>()), - _min_max_loc_kernel(support::cpp14::make_unique<CLMinMaxLocationKernel>()), + : _min_max_kernel(std::make_unique<CLMinMaxKernel>()), + _min_max_loc_kernel(std::make_unique<CLMinMaxLocationKernel>()), _min_max_vals(), _min_max_count_vals(), _min(nullptr), diff --git a/src/runtime/CL/functions/CLNonLinearFilter.cpp b/src/runtime/CL/functions/CLNonLinearFilter.cpp index 3312f6f9a7..ec88f879b7 100644 --- a/src/runtime/CL/functions/CLNonLinearFilter.cpp +++ b/src/runtime/CL/functions/CLNonLinearFilter.cpp @@ -25,7 +25,6 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLNonLinearFilterKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -40,7 +39,7 @@ void CLNonLinearFilter::configure(ICLTensor *input, ICLTensor *output, NonLinear void CLNonLinearFilter::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, NonLinearFilterFunction function, unsigned int mask_size, MatrixPattern pattern, const uint8_t *mask, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLNonLinearFilterKernel>(); + auto k = std::make_unique<CLNonLinearFilterKernel>(); k->configure(compile_context, input, output, function, mask_size, pattern, mask, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLNonMaximaSuppression3x3.cpp b/src/runtime/CL/functions/CLNonMaximaSuppression3x3.cpp index 22ca176a71..5906ea5a4b 100644 --- a/src/runtime/CL/functions/CLNonMaximaSuppression3x3.cpp +++ b/src/runtime/CL/functions/CLNonMaximaSuppression3x3.cpp @@ -25,7 +25,6 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLNonMaximaSuppression3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -38,7 +37,7 @@ void CLNonMaximaSuppression3x3::configure(ICLTensor *input, ICLTensor *output, B void CLNonMaximaSuppression3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, BorderMode border_mode) { - auto k = arm_compute::support::cpp14::make_unique<CLNonMaximaSuppression3x3Kernel>(); + auto k = std::make_unique<CLNonMaximaSuppression3x3Kernel>(); k->configure(compile_context, input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); diff --git a/src/runtime/CL/functions/CLNormalizationLayer.cpp b/src/runtime/CL/functions/CLNormalizationLayer.cpp index 40a6cdd2f4..ec6fa803f5 100644 --- a/src/runtime/CL/functions/CLNormalizationLayer.cpp +++ b/src/runtime/CL/functions/CLNormalizationLayer.cpp @@ -32,13 +32,12 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLNormalizationLayerKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLNormalizationLayer::CLNormalizationLayer() - : _norm_kernel(support::cpp14::make_unique<CLNormalizationLayerKernel>()), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()) + : _norm_kernel(std::make_unique<CLNormalizationLayerKernel>()), + _border_handler(std::make_unique<CLFillBorderKernel>()) { } diff --git a/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp b/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp index 9576486db0..70189a2cb6 100644 --- a/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp +++ b/src/runtime/CL/functions/CLNormalizePlanarYUVLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/runtime/CL/functions/CLNormalizePlanarYUVLayer.h" #include "src/core/CL/kernels/CLNormalizePlanarYUVLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -38,7 +37,7 @@ void CLNormalizePlanarYUVLayer::configure(const ICLTensor *input, ICLTensor *out void CLNormalizePlanarYUVLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *std) { - auto k = arm_compute::support::cpp14::make_unique<CLNormalizePlanarYUVLayerKernel>(); + auto k = std::make_unique<CLNormalizePlanarYUVLayerKernel>(); k->configure(compile_context, input, output, mean, std); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLOpticalFlow.cpp b/src/runtime/CL/functions/CLOpticalFlow.cpp index fca6192296..76e0ac5f0b 100644 --- a/src/runtime/CL/functions/CLOpticalFlow.cpp +++ b/src/runtime/CL/functions/CLOpticalFlow.cpp @@ -34,7 +34,6 @@ #include "arm_compute/runtime/CL/functions/CLScharr3x3.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLLKTrackerKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -43,7 +42,7 @@ CLOpticalFlow::CLOpticalFlow(std::shared_ptr<IMemoryManager> memory_manager) // _tracker_init_kernel(), _tracker_stage0_kernel(), _tracker_stage1_kernel(), - _tracker_finalize_kernel(support::cpp14::make_unique<CLLKTrackerFinalizeKernel>()), + _tracker_finalize_kernel(std::make_unique<CLLKTrackerFinalizeKernel>()), _func_scharr(), _scharr_gx(), _scharr_gy(), @@ -104,13 +103,13 @@ void CLOpticalFlow::configure(const CLCompileContext &compile_context, const CLP _scharr_gy.resize(_num_levels); // Create internal keypoint arrays - _old_points_internal = arm_compute::support::cpp14::make_unique<CLLKInternalKeypointArray>(list_length); + _old_points_internal = std::make_unique<CLLKInternalKeypointArray>(list_length); _old_points_internal->resize(list_length); - _new_points_internal = arm_compute::support::cpp14::make_unique<CLLKInternalKeypointArray>(list_length); + _new_points_internal = std::make_unique<CLLKInternalKeypointArray>(list_length); _new_points_internal->resize(list_length); - _coefficient_table = arm_compute::support::cpp14::make_unique<CLCoefficientTableArray>(list_length); + _coefficient_table = std::make_unique<CLCoefficientTableArray>(list_length); _coefficient_table->resize(list_length); - _old_values = arm_compute::support::cpp14::make_unique<CLOldValueArray>(old_values_list_length); + _old_values = std::make_unique<CLOldValueArray>(old_values_list_length); _old_values->resize(old_values_list_length); _new_points->resize(list_length); @@ -137,17 +136,17 @@ void CLOpticalFlow::configure(const CLCompileContext &compile_context, const CLP _func_scharr[i].configure(compile_context, old_ith_input, &_scharr_gx[i], &_scharr_gy[i], border_mode, constant_border_value); // Init Lucas-Kanade init kernel - _tracker_init_kernel.emplace_back(support::cpp14::make_unique<CLLKTrackerInitKernel>()); + _tracker_init_kernel.emplace_back(std::make_unique<CLLKTrackerInitKernel>()); _tracker_init_kernel.back()->configure(compile_context, old_points, new_points_estimates, _old_points_internal.get(), _new_points_internal.get(), use_initial_estimate, i, _num_levels, pyr_scale); // Init Lucas-Kanade stage0 kernel - _tracker_stage0_kernel.emplace_back(support::cpp14::make_unique<CLLKTrackerStage0Kernel>()); + _tracker_stage0_kernel.emplace_back(std::make_unique<CLLKTrackerStage0Kernel>()); _tracker_stage0_kernel.back()->configure(compile_context, old_ith_input, &_scharr_gx[i], &_scharr_gy[i], _old_points_internal.get(), _new_points_internal.get(), _coefficient_table.get(), _old_values.get(), window_dimension, i); // Init Lucas-Kanade stage1 kernel - _tracker_stage1_kernel.emplace_back(support::cpp14::make_unique<CLLKTrackerStage1Kernel>()); + _tracker_stage1_kernel.emplace_back(std::make_unique<CLLKTrackerStage1Kernel>()); _tracker_stage1_kernel.back()->configure(compile_context, new_ith_input, _new_points_internal.get(), _coefficient_table.get(), _old_values.get(), termination, epsilon, num_iterations, window_dimension, i); diff --git a/src/runtime/CL/functions/CLPReluLayer.cpp b/src/runtime/CL/functions/CLPReluLayer.cpp index 60cf4d1a2d..876b5de0f7 100644 --- a/src/runtime/CL/functions/CLPReluLayer.cpp +++ b/src/runtime/CL/functions/CLPReluLayer.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "arm_compute/runtime/CL/functions/CLPReluLayer.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,7 +37,7 @@ CLPReluLayer::CLPReluLayer() void CLPReluLayer::configure(const CLCompileContext &compile_context, ITensorInfo *input, ITensorInfo *alpha, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLArithmeticOperationKernel>(); + auto k = std::make_unique<CLArithmeticOperationKernel>(); k->configure(compile_context, ArithmeticOperation::PRELU, input, alpha, output); _kernel = std::move(k); } @@ -63,7 +62,7 @@ struct CLPReluLayer::Impl }; CLPReluLayer::CLPReluLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLPReluLayer::CLPReluLayer(CLPReluLayer &&) = default; @@ -80,7 +79,7 @@ void CLPReluLayer::configure(const CLCompileContext &compile_context, ICLTensor _impl->src_0 = input; _impl->src_1 = alpha; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLPReluLayer>(); + _impl->op = std::make_unique<experimental::CLPReluLayer>(); _impl->op->configure(compile_context, input->info(), alpha->info(), output->info()); } diff --git a/src/runtime/CL/functions/CLPadLayer.cpp b/src/runtime/CL/functions/CLPadLayer.cpp index 388b07b76e..8c5d529117 100644 --- a/src/runtime/CL/functions/CLPadLayer.cpp +++ b/src/runtime/CL/functions/CLPadLayer.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/CL/functions/CLPadLayer.h" #include "src/core/CL/kernels/CLCopyKernel.h" #include "src/core/CL/kernels/CLPadLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLPadLayer::CLPadLayer() - : _pad_kernel(support::cpp14::make_unique<CLPadLayerKernel>()), - _copy_kernel(support::cpp14::make_unique<CLCopyKernel>()), + : _pad_kernel(std::make_unique<CLPadLayerKernel>()), + _copy_kernel(std::make_unique<CLCopyKernel>()), _perform_pad(false) { } diff --git a/src/runtime/CL/functions/CLPermute.cpp b/src/runtime/CL/functions/CLPermute.cpp index f7f0bc4f5d..31b152c553 100644 --- a/src/runtime/CL/functions/CLPermute.cpp +++ b/src/runtime/CL/functions/CLPermute.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/Error.h" #include "src/core/CL/kernels/CLPermuteKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -37,7 +36,7 @@ void CLPermute::configure(const ICLTensor *input, ICLTensor *output, const Permu void CLPermute::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const PermutationVector &perm) { - auto k = arm_compute::support::cpp14::make_unique<CLPermuteKernel>(); + auto k = std::make_unique<CLPermuteKernel>(); k->configure(compile_context, input, output, perm); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLPhase.cpp b/src/runtime/CL/functions/CLPhase.cpp index 6594cd5bac..b2ff5d05ca 100644 --- a/src/runtime/CL/functions/CLPhase.cpp +++ b/src/runtime/CL/functions/CLPhase.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLPhase.h" #include "src/core/CL/kernels/CLMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLPhase::configure(const ICLTensor *input1, const ICLTensor *input2, ICLTen void CLPhase::configure(const CLCompileContext &compile_context, const ICLTensor *input1, const ICLTensor *input2, ICLTensor *output, PhaseType phase_type) { - auto k = arm_compute::support::cpp14::make_unique<CLMagnitudePhaseKernel>(); + auto k = std::make_unique<CLMagnitudePhaseKernel>(); k->configure(compile_context, input1, input2, nullptr, output, MagnitudeType::L1NORM, phase_type); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp b/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp index 12cc5d60af..a56018b397 100644 --- a/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp +++ b/src/runtime/CL/functions/CLPixelWiseMultiplication.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLPixelWiseMultiplicationKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -56,14 +55,14 @@ ITensorPack select_border_input(ITensorPack &tensors) namespace experimental { CLPixelWiseMultiplication::CLPixelWiseMultiplication() - : _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()) + : _border_handler(std::make_unique<CLFillBorderKernel>()) { } void CLPixelWiseMultiplication::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLPixelWiseMultiplicationKernel>(); + auto k = std::make_unique<CLPixelWiseMultiplicationKernel>(); k->configure(compile_context, input1, input2, output, scale, overflow_policy, rounding_policy, act_info); _kernel = std::move(k); @@ -92,13 +91,13 @@ void CLPixelWiseMultiplication::run(ITensorPack &tensors) } CLComplexPixelWiseMultiplication::CLComplexPixelWiseMultiplication() - : _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()) + : _border_handler(std::make_unique<CLFillBorderKernel>()) { } void CLComplexPixelWiseMultiplication::configure(const CLCompileContext &compile_context, ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { - auto k = arm_compute::support::cpp14::make_unique<CLComplexPixelWiseMultiplicationKernel>(); + auto k = std::make_unique<CLComplexPixelWiseMultiplicationKernel>(); k->configure(compile_context, input1, input2, output, act_info); _kernel = std::move(k); @@ -135,7 +134,7 @@ struct CLPixelWiseMultiplication::Impl }; CLPixelWiseMultiplication::CLPixelWiseMultiplication() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLPixelWiseMultiplication::CLPixelWiseMultiplication(CLPixelWiseMultiplication &&) = default; @@ -154,7 +153,7 @@ void CLPixelWiseMultiplication::configure(const CLCompileContext &compile_contex _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLPixelWiseMultiplication>(); + _impl->op = std::make_unique<experimental::CLPixelWiseMultiplication>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), scale, overflow_policy, rounding_policy, act_info); } @@ -183,7 +182,7 @@ struct CLComplexPixelWiseMultiplication::Impl }; CLComplexPixelWiseMultiplication::CLComplexPixelWiseMultiplication() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLComplexPixelWiseMultiplication::CLComplexPixelWiseMultiplication(CLComplexPixelWiseMultiplication &&) = default; @@ -200,7 +199,7 @@ void CLComplexPixelWiseMultiplication::configure(const CLCompileContext &compile _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLComplexPixelWiseMultiplication>(); + _impl->op = std::make_unique<experimental::CLComplexPixelWiseMultiplication>(); _impl->op->configure(compile_context, input1->info(), input2->info(), output->info(), act_info); } diff --git a/src/runtime/CL/functions/CLPoolingLayer.cpp b/src/runtime/CL/functions/CLPoolingLayer.cpp index 7f99aee9ba..f3a2dbdd51 100644 --- a/src/runtime/CL/functions/CLPoolingLayer.cpp +++ b/src/runtime/CL/functions/CLPoolingLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLPoolingLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -40,7 +39,7 @@ void CLPoolingLayer::configure(const CLCompileContext &compile_context, ICLTenso { ARM_COMPUTE_ERROR_ON_NULLPTR(input); // Configure pooling kernel - auto k = arm_compute::support::cpp14::make_unique<CLPoolingLayerKernel>(); + auto k = std::make_unique<CLPoolingLayerKernel>(); k->set_target(CLScheduler::get().target()); k->configure(compile_context, input, output, pool_info, indices); _kernel = std::move(k); diff --git a/src/runtime/CL/functions/CLPriorBoxLayer.cpp b/src/runtime/CL/functions/CLPriorBoxLayer.cpp index 8cb971793e..5ace7c6d7a 100644 --- a/src/runtime/CL/functions/CLPriorBoxLayer.cpp +++ b/src/runtime/CL/functions/CLPriorBoxLayer.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLPriorBoxLayerKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -54,7 +53,7 @@ void CLPriorBoxLayer::configure(const CLCompileContext &compile_context, const I _max = cl::Buffer(CLScheduler::get().context(), CL_MEM_ALLOC_HOST_PTR | CL_MEM_READ_WRITE, info.max_sizes().size() * sizeof(float)); } - auto k = arm_compute::support::cpp14::make_unique<CLPriorBoxLayerKernel>(); + auto k = std::make_unique<CLPriorBoxLayerKernel>(); k->configure(compile_context, input1, input2, output, info, &_min, &_max, &_aspect_ratios); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLQLSTMLayer.cpp b/src/runtime/CL/functions/CLQLSTMLayer.cpp index 54df5a0a5e..4395a39060 100644 --- a/src/runtime/CL/functions/CLQLSTMLayer.cpp +++ b/src/runtime/CL/functions/CLQLSTMLayer.cpp @@ -41,7 +41,6 @@ #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" #include "src/core/CL/kernels/CLQLSTMLayerNormalizationKernel.h" #include "src/core/helpers/WindowHelpers.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -97,21 +96,21 @@ void CLQLSTMLayer::TensorCopyKernel::run() } CLQLSTMLayer::CLQLSTMLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _input_to_input_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _recurrent_to_input_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _input_to_forget_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _recurrent_to_forget_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _input_to_cell_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _recurrent_to_cell_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _input_to_output_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _recurrent_to_output_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), - _projection_reduction(support::cpp14::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + : _input_to_input_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _recurrent_to_input_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _input_to_forget_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _recurrent_to_forget_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _input_to_cell_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _recurrent_to_cell_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _input_to_output_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _recurrent_to_output_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), + _projection_reduction(std::make_unique<CLGEMMLowpMatrixAReductionKernel>()), _layer_norms(), - _copy_output(support::cpp14::make_unique<CLCopyKernel>()) + _copy_output(std::make_unique<CLCopyKernel>()) { for(auto &norm : _layer_norms) { - norm = support::cpp14::make_unique<CLQLSTMLayerNormalizationKernel>(); + norm = std::make_unique<CLQLSTMLayerNormalizationKernel>(); } _memory_group = MemoryGroup(std::move(memory_manager)); diff --git a/src/runtime/CL/functions/CLQuantizationLayer.cpp b/src/runtime/CL/functions/CLQuantizationLayer.cpp index f132547eb9..cb8cabef87 100644 --- a/src/runtime/CL/functions/CLQuantizationLayer.cpp +++ b/src/runtime/CL/functions/CLQuantizationLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLQuantizationLayer.h" #include "src/core/CL/kernels/CLQuantizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -35,7 +34,7 @@ void CLQuantizationLayer::configure(const ICLTensor *input, ICLTensor *output) void CLQuantizationLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLQuantizationLayerKernel>(); + auto k = std::make_unique<CLQuantizationLayerKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLRNNLayer.cpp b/src/runtime/CL/functions/CLRNNLayer.cpp index be3e539f98..2a99ece388 100644 --- a/src/runtime/CL/functions/CLRNNLayer.cpp +++ b/src/runtime/CL/functions/CLRNNLayer.cpp @@ -41,14 +41,13 @@ #include "src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.h" #include "src/core/CL/kernels/CLGEMMReshapeLHSMatrixKernel.h" #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { using namespace arm_compute::misc::shape_calculator; CLRNNLayer::CLRNNLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(std::move(memory_manager)), _gemm_state_f(), _add_kernel(), _activation(), _fully_connected_kernel(), _copy_kernel(support::cpp14::make_unique<CLCopyKernel>()), _fully_connected_out(), + : _memory_group(std::move(memory_manager)), _gemm_state_f(), _add_kernel(), _activation(), _fully_connected_kernel(), _copy_kernel(std::make_unique<CLCopyKernel>()), _fully_connected_out(), _gemm_output(), _add_output(), _is_prepared(false) { } diff --git a/src/runtime/CL/functions/CLROIAlignLayer.cpp b/src/runtime/CL/functions/CLROIAlignLayer.cpp index cf28a1a0fb..291ccff958 100644 --- a/src/runtime/CL/functions/CLROIAlignLayer.cpp +++ b/src/runtime/CL/functions/CLROIAlignLayer.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/CL/ICLArray.h" #include "src/core/CL/kernels/CLROIAlignLayerKernel.h" #include "src/core/CL/kernels/CLROIPoolingLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -45,7 +44,7 @@ void CLROIAlignLayer::configure(const ICLTensor *input, const ICLTensor *rois, I void CLROIAlignLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info) { // Configure ROI pooling kernel - auto k = arm_compute::support::cpp14::make_unique<CLROIAlignLayerKernel>(); + auto k = std::make_unique<CLROIAlignLayerKernel>(); k->configure(compile_context, input, rois, output, pool_info); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLROIPoolingLayer.cpp b/src/runtime/CL/functions/CLROIPoolingLayer.cpp index b0e6716cce..debc5eb24c 100644 --- a/src/runtime/CL/functions/CLROIPoolingLayer.cpp +++ b/src/runtime/CL/functions/CLROIPoolingLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLROIPoolingLayer.h" #include "arm_compute/core/CL/ICLArray.h" #include "src/core/CL/kernels/CLROIPoolingLayerKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -36,7 +35,7 @@ void CLROIPoolingLayer::configure(const ICLTensor *input, const ICLTensor *rois, void CLROIPoolingLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *rois, ICLTensor *output, const ROIPoolingLayerInfo &pool_info) { // Configure ROI pooling kernel - auto k = arm_compute::support::cpp14::make_unique<CLROIPoolingLayerKernel>(); + auto k = std::make_unique<CLROIPoolingLayerKernel>(); k->configure(compile_context, input, rois, output, pool_info); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLRange.cpp b/src/runtime/CL/functions/CLRange.cpp index 57b57bd305..d4735c875d 100644 --- a/src/runtime/CL/functions/CLRange.cpp +++ b/src/runtime/CL/functions/CLRange.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLRangeKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -39,7 +38,7 @@ void CLRange::configure(ICLTensor *output, const float start, const float end, c void CLRange::configure(const CLCompileContext &compile_context, ICLTensor *output, const float start, const float end, const float step) { - auto k = arm_compute::support::cpp14::make_unique<CLRangeKernel>(); + auto k = std::make_unique<CLRangeKernel>(); k->set_target(CLScheduler::get().target()); k->configure(compile_context, output, start, end, step); _kernel = std::move(k); diff --git a/src/runtime/CL/functions/CLReductionOperation.cpp b/src/runtime/CL/functions/CLReductionOperation.cpp index 7423f4bc87..f40d945944 100644 --- a/src/runtime/CL/functions/CLReductionOperation.cpp +++ b/src/runtime/CL/functions/CLReductionOperation.cpp @@ -34,7 +34,6 @@ #include "src/core/CL/kernels/CLReductionOperationKernel.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/runtime/Utils.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -224,7 +223,7 @@ void CLReductionOperation::configure(const CLCompileContext &compile_context, IC _memory_group.manage(&_results_vector.back()); } - _reduction_kernels_vector.emplace_back(support::cpp14::make_unique<CLReductionOperationKernel>()); + _reduction_kernels_vector.emplace_back(std::make_unique<CLReductionOperationKernel>()); _reduction_kernels_vector[0]->configure(compile_context, input, output_internal, axis, op, 0); } else @@ -273,10 +272,10 @@ void CLReductionOperation::configure(const CLCompileContext &compile_context, IC ARM_COMPUTE_ERROR("Not supported"); } - _reduction_kernels_vector.emplace_back(support::cpp14::make_unique<CLReductionOperationKernel>()); + _reduction_kernels_vector.emplace_back(std::make_unique<CLReductionOperationKernel>()); _reduction_kernels_vector[0]->configure(compile_context, input, &_results_vector[0], axis, first_kernel_op); - _border_handlers_vector.emplace_back(support::cpp14::make_unique<CLFillBorderKernel>()); + _border_handlers_vector.emplace_back(std::make_unique<CLFillBorderKernel>()); _border_handlers_vector[0]->configure(compile_context, input, _reduction_kernels_vector[0]->border_size(), BorderMode::CONSTANT, pixelValue); // Apply ReductionOperation on intermediate stages @@ -284,10 +283,10 @@ void CLReductionOperation::configure(const CLCompileContext &compile_context, IC { _memory_group.manage(&_results_vector[i]); - _reduction_kernels_vector.emplace_back(support::cpp14::make_unique<CLReductionOperationKernel>()); + _reduction_kernels_vector.emplace_back(std::make_unique<CLReductionOperationKernel>()); _reduction_kernels_vector[i]->configure(compile_context, &_results_vector[i - 1], &_results_vector[i], axis, intermediate_kernel_op); - _border_handlers_vector.emplace_back(support::cpp14::make_unique<CLFillBorderKernel>()); + _border_handlers_vector.emplace_back(std::make_unique<CLFillBorderKernel>()); _border_handlers_vector[i]->configure(compile_context, &_results_vector[i - 1], _reduction_kernels_vector[i]->border_size(), BorderMode::CONSTANT, pixelValue); _results_vector[i - 1].allocator()->allocate(); @@ -302,10 +301,10 @@ void CLReductionOperation::configure(const CLCompileContext &compile_context, IC _memory_group.manage(&_results_vector.back()); } - _reduction_kernels_vector.emplace_back(support::cpp14::make_unique<CLReductionOperationKernel>()); + _reduction_kernels_vector.emplace_back(std::make_unique<CLReductionOperationKernel>()); _reduction_kernels_vector[last_stage]->configure(compile_context, &_results_vector[last_stage - 1], output_internal, axis, last_kernel_op, input_width); - _border_handlers_vector.emplace_back(support::cpp14::make_unique<CLFillBorderKernel>()); + _border_handlers_vector.emplace_back(std::make_unique<CLFillBorderKernel>()); _border_handlers_vector[last_stage]->configure(compile_context, &_results_vector[last_stage - 1], _reduction_kernels_vector[last_stage]->border_size(), BorderMode::CONSTANT, pixelValue); _results_vector[last_stage - 1].allocator()->allocate(); diff --git a/src/runtime/CL/functions/CLRemap.cpp b/src/runtime/CL/functions/CLRemap.cpp index 6466c2843b..a4cfc60368 100644 --- a/src/runtime/CL/functions/CLRemap.cpp +++ b/src/runtime/CL/functions/CLRemap.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/Validate.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLRemapKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -51,7 +50,7 @@ void CLRemap::configure(const CLCompileContext &compile_context, ICLTensor *inpu ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(map_y, 1, DataType::F32); ARM_COMPUTE_ERROR_ON_MSG(policy == InterpolationPolicy::AREA, "Area interpolation is not supported"); - auto k = arm_compute::support::cpp14::make_unique<CLRemapKernel>(); + auto k = std::make_unique<CLRemapKernel>(); k->configure(compile_context, input, map_x, map_y, output, policy, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLReorgLayer.cpp b/src/runtime/CL/functions/CLReorgLayer.cpp index 4b2f70334f..69b28abab3 100644 --- a/src/runtime/CL/functions/CLReorgLayer.cpp +++ b/src/runtime/CL/functions/CLReorgLayer.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "src/core/CL/kernels/CLReorgLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -41,7 +40,7 @@ void CLReorgLayer::configure(ICLTensor *input, ICLTensor *output, int32_t stride void CLReorgLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, int32_t stride) { - auto k = arm_compute::support::cpp14::make_unique<CLReorgLayerKernel>(); + auto k = std::make_unique<CLReorgLayerKernel>(); k->configure(compile_context, input, output, stride); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLReshapeLayer.cpp b/src/runtime/CL/functions/CLReshapeLayer.cpp index 5112064b23..9abaa1b4e1 100644 --- a/src/runtime/CL/functions/CLReshapeLayer.cpp +++ b/src/runtime/CL/functions/CLReshapeLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/CL/ICLTensor.h" #include "src/core/CL/kernels/CLReshapeLayerKernel.h" -#include "support/MemorySupport.h" /** [CLReshapeLayer snippet] **/ namespace arm_compute @@ -34,7 +33,7 @@ namespace experimental { void CLReshape::configure(const CLCompileContext &compile_context, const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<CLReshapeLayerKernel>(); + auto k = std::make_unique<CLReshapeLayerKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } @@ -53,7 +52,7 @@ struct CLReshapeLayer::Impl }; CLReshapeLayer::CLReshapeLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -70,7 +69,7 @@ void CLReshapeLayer::configure(const CLCompileContext &compile_context, const IC { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLReshape>(); + _impl->op = std::make_unique<experimental::CLReshape>(); _impl->op->configure(compile_context, input->info(), output->info()); } diff --git a/src/runtime/CL/functions/CLReverse.cpp b/src/runtime/CL/functions/CLReverse.cpp index b73d8de62e..2a845bae13 100644 --- a/src/runtime/CL/functions/CLReverse.cpp +++ b/src/runtime/CL/functions/CLReverse.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLReverseKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void CLReverse::configure(const ICLTensor *input, ICLTensor *output, const ICLTe void CLReverse::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ICLTensor *axis) { - auto k = arm_compute::support::cpp14::make_unique<CLReverseKernel>(); + auto k = std::make_unique<CLReverseKernel>(); k->configure(compile_context, input, output, axis); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLScale.cpp b/src/runtime/CL/functions/CLScale.cpp index 383b0cc305..6658957e07 100644 --- a/src/runtime/CL/functions/CLScale.cpp +++ b/src/runtime/CL/functions/CLScale.cpp @@ -29,7 +29,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLScaleKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -46,7 +45,7 @@ void CLScale::configure(ICLTensor *input, ICLTensor *output, InterpolationPolicy void CLScale::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ScaleKernelInfo &info) { - auto k = arm_compute::support::cpp14::make_unique<CLScaleKernel>(); + auto k = std::make_unique<CLScaleKernel>(); k->set_target(CLScheduler::get().target()); k->configure(compile_context, input, output, info); _kernel = std::move(k); diff --git a/src/runtime/CL/functions/CLScharr3x3.cpp b/src/runtime/CL/functions/CLScharr3x3.cpp index e5d0d2d630..563ec19266 100644 --- a/src/runtime/CL/functions/CLScharr3x3.cpp +++ b/src/runtime/CL/functions/CLScharr3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLScharr3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ void CLScharr3x3::configure(ICLTensor *input, ICLTensor *output_x, ICLTensor *ou void CLScharr3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLScharr3x3Kernel>(); + auto k = std::make_unique<CLScharr3x3Kernel>(); k->configure(compile_context, input, output_x, output_y, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLSelect.cpp b/src/runtime/CL/functions/CLSelect.cpp index 374da91b78..5ec18a032f 100644 --- a/src/runtime/CL/functions/CLSelect.cpp +++ b/src/runtime/CL/functions/CLSelect.cpp @@ -27,8 +27,6 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLSelectKernel.h" -#include "support/MemorySupport.h" - using namespace arm_compute; namespace arm_compute @@ -40,7 +38,7 @@ void CLSelect::configure(const ICLTensor *c, const ICLTensor *x, const ICLTensor void CLSelect::configure(const CLCompileContext &compile_context, const ICLTensor *c, const ICLTensor *x, const ICLTensor *y, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLSelectKernel>(); + auto k = std::make_unique<CLSelectKernel>(); k->configure(compile_context, c, x, y, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLSlice.cpp b/src/runtime/CL/functions/CLSlice.cpp index 940540563a..7f39143dc7 100644 --- a/src/runtime/CL/functions/CLSlice.cpp +++ b/src/runtime/CL/functions/CLSlice.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Types.h" #include "arm_compute/core/utils/helpers/tensor_transform.h" #include "src/core/CL/kernels/CLStridedSliceKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -40,7 +39,7 @@ void CLSlice::configure(const CLCompileContext &compile_context, const ITensorIn // Get absolute end coordinates const int32_t slice_end_mask = arm_compute::helpers::tensor_transform::construct_slice_end_mask(ends); - auto k = arm_compute::support::cpp14::make_unique<CLStridedSliceKernel>(); + auto k = std::make_unique<CLStridedSliceKernel>(); k->configure(compile_context, input, output, starts, ends, BiStrides(), 0, slice_end_mask, 0); _kernel = std::move(k); } @@ -70,7 +69,7 @@ struct CLSlice::Impl }; CLSlice::CLSlice() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } CLSlice::CLSlice(CLSlice &&) = default; @@ -91,7 +90,7 @@ void CLSlice::configure(const CLCompileContext &compile_context, const ICLTensor { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLSlice>(); + _impl->op = std::make_unique<experimental::CLSlice>(); _impl->op->configure(compile_context, input->info(), output->info(), starts, ends); } diff --git a/src/runtime/CL/functions/CLSobel3x3.cpp b/src/runtime/CL/functions/CLSobel3x3.cpp index 78376f935a..6724c12a72 100644 --- a/src/runtime/CL/functions/CLSobel3x3.cpp +++ b/src/runtime/CL/functions/CLSobel3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLSobel3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -41,7 +40,7 @@ void CLSobel3x3::configure(ICLTensor *input, ICLTensor *output_x, ICLTensor *out void CLSobel3x3::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output_x, ICLTensor *output_y, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLSobel3x3Kernel>(); + auto k = std::make_unique<CLSobel3x3Kernel>(); k->configure(compile_context, input, output_x, output_y, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLSobel5x5.cpp b/src/runtime/CL/functions/CLSobel5x5.cpp index fa5d8945fb..98f215794c 100644 --- a/src/runtime/CL/functions/CLSobel5x5.cpp +++ b/src/runtime/CL/functions/CLSobel5x5.cpp @@ -31,15 +31,14 @@ #include "arm_compute/runtime/ITensorAllocator.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLSobel5x5Kernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLSobel5x5::CLSobel5x5(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _sobel_hor(support::cpp14::make_unique<CLSobel5x5HorKernel>()), - _sobel_vert(support::cpp14::make_unique<CLSobel5x5VertKernel>()), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()), + _sobel_hor(std::make_unique<CLSobel5x5HorKernel>()), + _sobel_vert(std::make_unique<CLSobel5x5VertKernel>()), + _border_handler(std::make_unique<CLFillBorderKernel>()), _tmp_x(), _tmp_y() { diff --git a/src/runtime/CL/functions/CLSobel7x7.cpp b/src/runtime/CL/functions/CLSobel7x7.cpp index f462adb0ed..a3d63f98dd 100644 --- a/src/runtime/CL/functions/CLSobel7x7.cpp +++ b/src/runtime/CL/functions/CLSobel7x7.cpp @@ -31,15 +31,14 @@ #include "arm_compute/runtime/ITensorAllocator.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLSobel7x7Kernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; CLSobel7x7::CLSobel7x7(std::shared_ptr<IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), - _sobel_hor(support::cpp14::make_unique<CLSobel7x7HorKernel>()), - _sobel_vert(support::cpp14::make_unique<CLSobel7x7VertKernel>()), - _border_handler(support::cpp14::make_unique<CLFillBorderKernel>()), + _sobel_hor(std::make_unique<CLSobel7x7HorKernel>()), + _sobel_vert(std::make_unique<CLSobel7x7VertKernel>()), + _border_handler(std::make_unique<CLFillBorderKernel>()), _tmp_x(), _tmp_y() { diff --git a/src/runtime/CL/functions/CLSoftmaxLayer.cpp b/src/runtime/CL/functions/CLSoftmaxLayer.cpp index 4caf91488e..93e63dd779 100644 --- a/src/runtime/CL/functions/CLSoftmaxLayer.cpp +++ b/src/runtime/CL/functions/CLSoftmaxLayer.cpp @@ -33,7 +33,6 @@ #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLSoftmaxLayerKernel.h" #include "src/core/helpers/SoftmaxHelpers.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -42,8 +41,8 @@ CLSoftmaxLayerGeneric<IS_LOG>::CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryMana : _memory_group(std::move(memory_manager)), _permute_input(), _permute_output(), - _max_shift_exp_sum_kernel(support::cpp14::make_unique<CLLogits1DMaxShiftExpSumKernel>()), - _norm_kernel(support::cpp14::make_unique<CLLogits1DNormKernel>()), + _max_shift_exp_sum_kernel(std::make_unique<CLLogits1DMaxShiftExpSumKernel>()), + _norm_kernel(std::make_unique<CLLogits1DNormKernel>()), _max(), _sum(), _tmp(), diff --git a/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp b/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp index e83def5677..2db064af44 100644 --- a/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp +++ b/src/runtime/CL/functions/CLSpaceToBatchLayer.cpp @@ -31,13 +31,12 @@ #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLMemsetKernel.h" #include "src/core/CL/kernels/CLSpaceToBatchLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLSpaceToBatchLayer::CLSpaceToBatchLayer() - : _space_to_batch_kernel(support::cpp14::make_unique<CLSpaceToBatchLayerKernel>()), - _memset_kernel(support::cpp14::make_unique<CLMemsetKernel>()), + : _space_to_batch_kernel(std::make_unique<CLSpaceToBatchLayerKernel>()), + _memset_kernel(std::make_unique<CLMemsetKernel>()), _has_padding(false) { } diff --git a/src/runtime/CL/functions/CLSpaceToDepthLayer.cpp b/src/runtime/CL/functions/CLSpaceToDepthLayer.cpp index db8c4953cc..842d5bc5cc 100644 --- a/src/runtime/CL/functions/CLSpaceToDepthLayer.cpp +++ b/src/runtime/CL/functions/CLSpaceToDepthLayer.cpp @@ -30,12 +30,11 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLSpaceToDepthLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLSpaceToDepthLayer::CLSpaceToDepthLayer() - : _space_to_depth_kernel(support::cpp14::make_unique<CLSpaceToDepthLayerKernel>()) + : _space_to_depth_kernel(std::make_unique<CLSpaceToDepthLayerKernel>()) { } diff --git a/src/runtime/CL/functions/CLStackLayer.cpp b/src/runtime/CL/functions/CLStackLayer.cpp index f4aa78a72d..3ef6a27675 100644 --- a/src/runtime/CL/functions/CLStackLayer.cpp +++ b/src/runtime/CL/functions/CLStackLayer.cpp @@ -33,7 +33,6 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLStackLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -61,7 +60,7 @@ void CLStackLayer::configure(const CLCompileContext &compile_context, const std: for(unsigned int i = 0; i < _num_inputs; i++) { - _stack_kernels.emplace_back(support::cpp14::make_unique<CLStackLayerKernel>()); + _stack_kernels.emplace_back(std::make_unique<CLStackLayerKernel>()); _stack_kernels.back()->configure(compile_context, input[i], axis_u, i, _num_inputs, output); } } diff --git a/src/runtime/CL/functions/CLStridedSlice.cpp b/src/runtime/CL/functions/CLStridedSlice.cpp index 3f6814f5ce..fd3db9341a 100644 --- a/src/runtime/CL/functions/CLStridedSlice.cpp +++ b/src/runtime/CL/functions/CLStridedSlice.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLStridedSliceKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void CLStridedSlice::configure(const CLCompileContext &compile_context, const IT const Coordinates &starts, const Coordinates &ends, const BiStrides &strides, int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask) { - auto k = arm_compute::support::cpp14::make_unique<CLStridedSliceKernel>(); + auto k = std::make_unique<CLStridedSliceKernel>(); k->configure(compile_context, input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask); _kernel = std::move(k); } @@ -58,7 +57,7 @@ struct CLStridedSlice::Impl }; CLStridedSlice::CLStridedSlice(CLRuntimeContext *ctx) - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { _impl->ctx = ctx; } @@ -83,7 +82,7 @@ void CLStridedSlice::configure(const CLCompileContext &compile_context, const IC _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::CLStridedSlice>(); + _impl->op = std::make_unique<experimental::CLStridedSlice>(); _impl->op->configure(compile_context, _impl->src->info(), _impl->dst->info(), starts, ends, strides, begin_mask, end_mask, shrink_axis_mask); } diff --git a/src/runtime/CL/functions/CLTableLookup.cpp b/src/runtime/CL/functions/CLTableLookup.cpp index 8282f37e4b..a4671f51bd 100644 --- a/src/runtime/CL/functions/CLTableLookup.cpp +++ b/src/runtime/CL/functions/CLTableLookup.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLTableLookup.h" #include "src/core/CL/kernels/CLTableLookupKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLTableLookup::configure(const ICLTensor *input, const ICLLut *lut, ICLTens void CLTableLookup::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLLut *lut, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLTableLookupKernel>(); + auto k = std::make_unique<CLTableLookupKernel>(); k->configure(compile_context, input, lut, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLThreshold.cpp b/src/runtime/CL/functions/CLThreshold.cpp index 250f6f034f..901cfd8993 100644 --- a/src/runtime/CL/functions/CLThreshold.cpp +++ b/src/runtime/CL/functions/CLThreshold.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLThreshold.h" #include "src/core/CL/kernels/CLThresholdKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -42,7 +41,7 @@ void CLThreshold::configure(const ICLTensor *input, ICLTensor *output, const Thr void CLThreshold::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const ThresholdKernelInfo &info) { - auto k = arm_compute::support::cpp14::make_unique<CLThresholdKernel>(); + auto k = std::make_unique<CLThresholdKernel>(); k->configure(compile_context, input, output, info); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLTile.cpp b/src/runtime/CL/functions/CLTile.cpp index 8384e48baf..818f10f1ac 100644 --- a/src/runtime/CL/functions/CLTile.cpp +++ b/src/runtime/CL/functions/CLTile.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLTile.h" #include "src/core/CL/kernels/CLTileKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -35,7 +34,7 @@ void CLTile::configure(const ICLTensor *input, ICLTensor *output, const Multiple void CLTile::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, const Multiples &multiples) { - auto k = arm_compute::support::cpp14::make_unique<CLTileKernel>(); + auto k = std::make_unique<CLTileKernel>(); k->configure(compile_context, input, output, multiples); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLTranspose.cpp b/src/runtime/CL/functions/CLTranspose.cpp index 43fa7a012a..c74503f4c0 100644 --- a/src/runtime/CL/functions/CLTranspose.cpp +++ b/src/runtime/CL/functions/CLTranspose.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CL/functions/CLTranspose.h" #include "src/core/CL/kernels/CLTransposeKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void CLTranspose::configure(const ICLTensor *input, ICLTensor *output) void CLTranspose::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<CLTransposeKernel>(); + auto k = std::make_unique<CLTransposeKernel>(); k->configure(compile_context, input, output); _kernel = std::move(k); } diff --git a/src/runtime/CL/functions/CLUpsampleLayer.cpp b/src/runtime/CL/functions/CLUpsampleLayer.cpp index 10b4b76a5e..538f27f565 100644 --- a/src/runtime/CL/functions/CLUpsampleLayer.cpp +++ b/src/runtime/CL/functions/CLUpsampleLayer.cpp @@ -27,12 +27,11 @@ #include "arm_compute/core/Utils.h" #include "arm_compute/runtime/CL/CLScheduler.h" #include "src/core/CL/kernels/CLUpsampleLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { CLUpsampleLayer::CLUpsampleLayer() // NOLINT - : _upsample(support::cpp14::make_unique<CLUpsampleLayerKernel>()), + : _upsample(std::make_unique<CLUpsampleLayerKernel>()), _output(nullptr) { } diff --git a/src/runtime/CL/functions/CLWarpAffine.cpp b/src/runtime/CL/functions/CLWarpAffine.cpp index 86e5a7bd86..9a22446cf6 100644 --- a/src/runtime/CL/functions/CLWarpAffine.cpp +++ b/src/runtime/CL/functions/CLWarpAffine.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLWarpAffineKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -40,7 +39,7 @@ void CLWarpAffine::configure(ICLTensor *input, ICLTensor *output, const std::arr void CLWarpAffine::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLWarpAffineKernel>(); + auto k = std::make_unique<CLWarpAffineKernel>(); k->configure(compile_context, input, output, matrix, policy); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLWarpPerspective.cpp b/src/runtime/CL/functions/CLWarpPerspective.cpp index 7e8bc5cdff..0ec6b42e75 100644 --- a/src/runtime/CL/functions/CLWarpPerspective.cpp +++ b/src/runtime/CL/functions/CLWarpPerspective.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLWarpPerspectiveKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -40,7 +39,7 @@ void CLWarpPerspective::configure(ICLTensor *input, ICLTensor *output, const std void CLWarpPerspective::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const std::array<float, 9> &matrix, InterpolationPolicy policy, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<CLWarpPerspectiveKernel>(); + auto k = std::make_unique<CLWarpPerspectiveKernel>(); k->configure(compile_context, input, output, matrix, policy); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp b/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp index 7af42904e8..321466f05f 100644 --- a/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLWinogradConvolutionLayer.cpp @@ -36,7 +36,6 @@ #include "src/core/CL/kernels/CLGEMMReshapeRHSMatrixKernel.h" #include "src/core/CL/kernels/CLWinogradFilterTransformKernel.h" #include "src/core/CL/kernels/CLWinogradOutputTransformKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -99,8 +98,8 @@ bool check_support_fast_math(const Size2D &output_tile, const Size2D &kernel_siz } // namespace CLWinogradConvolutionLayer::CLWinogradConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _memory_group(memory_manager), _batched_mm(memory_manager), _input_transform(), _filter_transform(support::cpp14::make_unique<CLWinogradFilterTransformKernel>()), - _output_transform(support::cpp14::make_unique<CLWinogradOutputTransformKernel>()), _input0(), _input1(), _batched_mm_output(), _original_weights(nullptr), _is_prepared(false) + : _memory_group(memory_manager), _batched_mm(memory_manager), _input_transform(), _filter_transform(std::make_unique<CLWinogradFilterTransformKernel>()), + _output_transform(std::make_unique<CLWinogradOutputTransformKernel>()), _input0(), _input1(), _batched_mm_output(), _original_weights(nullptr), _is_prepared(false) { } diff --git a/src/runtime/CL/functions/CLWinogradInputTransform.cpp b/src/runtime/CL/functions/CLWinogradInputTransform.cpp index 308c41f714..6d5a692bc3 100644 --- a/src/runtime/CL/functions/CLWinogradInputTransform.cpp +++ b/src/runtime/CL/functions/CLWinogradInputTransform.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Error.h" #include "src/core/CL/kernels/CLFillBorderKernel.h" #include "src/core/CL/kernels/CLWinogradInputTransformKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -38,7 +37,7 @@ void CLWinogradInputTransform::configure(ICLTensor *input, ICLTensor *output, co void CLWinogradInputTransform::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info) { - auto k = arm_compute::support::cpp14::make_unique<CLWinogradInputTransformKernel>(); + auto k = std::make_unique<CLWinogradInputTransformKernel>(); k->configure(compile_context, input, output, winograd_info); _kernel = std::move(k); _border_handler->configure(compile_context, input, _kernel->border_size(), BorderMode::CONSTANT, PixelValue()); diff --git a/src/runtime/CL/functions/CLYOLOLayer.cpp b/src/runtime/CL/functions/CLYOLOLayer.cpp index 46bf220b0c..e21d9a7fbb 100644 --- a/src/runtime/CL/functions/CLYOLOLayer.cpp +++ b/src/runtime/CL/functions/CLYOLOLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Types.h" #include "src/core/CL/kernels/CLYOLOLayerKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -36,7 +35,7 @@ void CLYOLOLayer::configure(ICLTensor *input, ICLTensor *output, const Activatio void CLYOLOLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ActivationLayerInfo &act_info, int32_t num_classes) { - auto k = arm_compute::support::cpp14::make_unique<CLYOLOLayerKernel>(); + auto k = std::make_unique<CLYOLOLayerKernel>(); k->configure(compile_context, input, output, act_info, num_classes); _kernel = std::move(k); } diff --git a/src/runtime/CL/gemm/CLGEMMKernelSelection.h b/src/runtime/CL/gemm/CLGEMMKernelSelection.h index f6fad7e4ff..69f8349d27 100644 --- a/src/runtime/CL/gemm/CLGEMMKernelSelection.h +++ b/src/runtime/CL/gemm/CLGEMMKernelSelection.h @@ -29,8 +29,6 @@ #include "src/runtime/CL/gemm/CLGEMMKernelSelectionMidgard.h" #include "src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.h" -#include "support/MemorySupport.h" - namespace arm_compute { namespace cl_gemm @@ -50,11 +48,11 @@ public: switch(get_arch_from_target(gpu)) { case GPUTarget::MIDGARD: - return support::cpp14::make_unique<CLGEMMKernelSelectionMidgard>(gpu); + return std::make_unique<CLGEMMKernelSelectionMidgard>(gpu); case GPUTarget::BIFROST: - return support::cpp14::make_unique<CLGEMMKernelSelectionBifrost>(gpu); + return std::make_unique<CLGEMMKernelSelectionBifrost>(gpu); case GPUTarget::VALHALL: - return support::cpp14::make_unique<CLGEMMKernelSelectionValhall>(gpu); + return std::make_unique<CLGEMMKernelSelectionValhall>(gpu); default: ARM_COMPUTE_ERROR("Not supported GPU target"); } diff --git a/src/runtime/CPP/CPPScheduler.cpp b/src/runtime/CPP/CPPScheduler.cpp index e6b0ec20b8..663cde7a21 100644 --- a/src/runtime/CPP/CPPScheduler.cpp +++ b/src/runtime/CPP/CPPScheduler.cpp @@ -28,13 +28,13 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/Utils.h" #include "src/runtime/CPUUtils.h" -#include "support/MemorySupport.h" #include "support/Mutex.h" #include <atomic> #include <condition_variable> #include <iostream> #include <list> +#include <memory> #include <mutex> #include <system_error> #include <thread> @@ -281,7 +281,7 @@ CPPScheduler &CPPScheduler::get() } CPPScheduler::CPPScheduler() - : _impl(support::cpp14::make_unique<Impl>(num_threads_hint())) + : _impl(std::make_unique<Impl>(num_threads_hint())) { } diff --git a/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp b/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp index f9d2badd39..d0d0b1e98b 100644 --- a/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp +++ b/src/runtime/CPP/functions/CPPNonMaximumSuppression.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/CPP/functions/CPPNonMaximumSuppression.h" #include "arm_compute/core/CPP/kernels/CPPNonMaximumSuppressionKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -32,7 +31,7 @@ void CPPNonMaximumSuppression::configure( const ITensor *bboxes, const ITensor *scores, ITensor *indices, unsigned int max_output_size, const float score_threshold, const float nms_threshold) { - auto k = arm_compute::support::cpp14::make_unique<CPPNonMaximumSuppressionKernel>(); + auto k = std::make_unique<CPPNonMaximumSuppressionKernel>(); k->configure(bboxes, scores, indices, max_output_size, score_threshold, nms_threshold); _kernel = std::move(k); } diff --git a/src/runtime/CPP/functions/CPPPermute.cpp b/src/runtime/CPP/functions/CPPPermute.cpp index 7ea1070160..76fa09f12b 100644 --- a/src/runtime/CPP/functions/CPPPermute.cpp +++ b/src/runtime/CPP/functions/CPPPermute.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/CPP/functions/CPPPermute.h" #include "arm_compute/core/CPP/kernels/CPPPermuteKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; void CPPPermute::configure(const ITensor *input, ITensor *output, const PermutationVector &perm) { - auto k = arm_compute::support::cpp14::make_unique<CPPPermuteKernel>(); + auto k = std::make_unique<CPPPermuteKernel>(); k->configure(input, output, perm); _kernel = std::move(k); } diff --git a/src/runtime/CPP/functions/CPPTopKV.cpp b/src/runtime/CPP/functions/CPPTopKV.cpp index bd089ac680..2547e56a1d 100644 --- a/src/runtime/CPP/functions/CPPTopKV.cpp +++ b/src/runtime/CPP/functions/CPPTopKV.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/CPP/functions/CPPTopKV.h" #include "arm_compute/core/CPP/kernels/CPPTopKVKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void CPPTopKV::configure(const ITensor *predictions, const ITensor *targets, ITensor *output, const unsigned int k) { - auto kernel = arm_compute::support::cpp14::make_unique<CPPTopKVKernel>(); + auto kernel = std::make_unique<CPPTopKVKernel>(); kernel->configure(predictions, targets, output, k); _kernel = std::move(kernel); } diff --git a/src/runtime/CPP/functions/CPPUpsample.cpp b/src/runtime/CPP/functions/CPPUpsample.cpp index 7dfc3b8136..3b4ba2ba42 100644 --- a/src/runtime/CPP/functions/CPPUpsample.cpp +++ b/src/runtime/CPP/functions/CPPUpsample.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/CPP/functions/CPPUpsample.h" #include "arm_compute/core/CPP/kernels/CPPUpsampleKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; void CPPUpsample::configure(const ITensor *input, ITensor *output, const PadStrideInfo &info) { - auto k = arm_compute::support::cpp14::make_unique<CPPUpsampleKernel>(); + auto k = std::make_unique<CPPUpsampleKernel>(); k->configure(input, output, info); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/GCBufferAllocator.cpp b/src/runtime/GLES_COMPUTE/GCBufferAllocator.cpp index ec91027915..695331d743 100644 --- a/src/runtime/GLES_COMPUTE/GCBufferAllocator.cpp +++ b/src/runtime/GLES_COMPUTE/GCBufferAllocator.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -54,6 +54,6 @@ void GCBufferAllocator::free(void *ptr) std::unique_ptr<IMemoryRegion> GCBufferAllocator::make_region(size_t size, size_t alignment) { ARM_COMPUTE_UNUSED(alignment); - return arm_compute::support::cpp14::make_unique<GCBufferMemoryRegion>(size); + return std::make_unique<GCBufferMemoryRegion>(size); } } // namespace arm_compute diff --git a/src/runtime/GLES_COMPUTE/GCRuntimeContext.cpp b/src/runtime/GLES_COMPUTE/GCRuntimeContext.cpp index 6599f5296a..2ed78fe099 100644 --- a/src/runtime/GLES_COMPUTE/GCRuntimeContext.cpp +++ b/src/runtime/GLES_COMPUTE/GCRuntimeContext.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 Arm Limited. + * Copyright (c) 2019-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -30,7 +30,7 @@ namespace arm_compute { GCRuntimeContext::GCRuntimeContext() - : _gpu_owned_scheduler(support::cpp14::make_unique<GCScheduler>()), + : _gpu_owned_scheduler(std::make_unique<GCScheduler>()), _gpu_scheduler(_gpu_owned_scheduler.get()), _core_context() { diff --git a/src/runtime/GLES_COMPUTE/GCTensorAllocator.cpp b/src/runtime/GLES_COMPUTE/GCTensorAllocator.cpp index ff96c3cb83..b3344d8ecb 100644 --- a/src/runtime/GLES_COMPUTE/GCTensorAllocator.cpp +++ b/src/runtime/GLES_COMPUTE/GCTensorAllocator.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/runtime/GLES_COMPUTE/GCMemoryRegion.h" #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -46,7 +45,7 @@ void GCTensorAllocator::allocate() { if(_associated_memory_group == nullptr) { - _memory.set_owned_region(support::cpp14::make_unique<GCBufferMemoryRegion>(info().total_size())); + _memory.set_owned_region(std::make_unique<GCBufferMemoryRegion>(info().total_size())); } else { diff --git a/src/runtime/GLES_COMPUTE/functions/GCAbsoluteDifference.cpp b/src/runtime/GLES_COMPUTE/functions/GCAbsoluteDifference.cpp index 1b13143bde..29630c8981 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCAbsoluteDifference.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCAbsoluteDifference.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/GLES_COMPUTE/kernels/GCAbsoluteDifferenceKernel.h" #include "arm_compute/core/Helpers.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ using namespace arm_compute; void GCAbsoluteDifference::configure(const IGCTensor *input1, const IGCTensor *input2, IGCTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<GCAbsoluteDifferenceKernel>(); + auto k = std::make_unique<GCAbsoluteDifferenceKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCActivationLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCActivationLayer.cpp index a7ec758138..b3815f1625 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCActivationLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCActivationLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/GLES_COMPUTE/kernels/GCActivationLayerKernel.h" #include "arm_compute/core/Helpers.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,7 +37,7 @@ void GCActivationLayer::configure(IGCTensor *input, IGCTensor *output, Activatio { auto core_ctx = _ctx ? _ctx->core_runtime_context() : /* Legacy */ nullptr; - auto k = arm_compute::support::cpp14::make_unique<GCActivationLayerKernel>(core_ctx); + auto k = std::make_unique<GCActivationLayerKernel>(core_ctx); k->configure(input, output, act_info); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCArithmeticAddition.cpp b/src/runtime/GLES_COMPUTE/functions/GCArithmeticAddition.cpp index 580f8d573c..5661a9bfdd 100755 --- a/src/runtime/GLES_COMPUTE/functions/GCArithmeticAddition.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCArithmeticAddition.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/GLES_COMPUTE/functions/GCArithmeticAddition.h" #include "arm_compute/core/GLES_COMPUTE/kernels/GCArithmeticAdditionKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -33,7 +32,7 @@ using namespace arm_compute; void GCArithmeticAddition::configure(const IGCTensor *input1, const IGCTensor *input2, IGCTensor *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(act_info); - auto k = arm_compute::support::cpp14::make_unique<GCArithmeticAdditionKernel>(); + auto k = std::make_unique<GCArithmeticAdditionKernel>(); k->configure(input1, input2, output, policy); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp index 807412eb17..2c21d81e17 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCConcatenateLayer.cpp @@ -31,8 +31,6 @@ #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" - namespace arm_compute { GCConcatenateLayer::GCConcatenateLayer() @@ -61,7 +59,7 @@ void GCConcatenateLayer::configure(std::vector<IGCTensor *> inputs_vector, IGCTe { for(unsigned int i = 0; i < _num_inputs; ++i) { - auto kernel = support::cpp14::make_unique<GCDepthConcatenateLayerKernel>(); + auto kernel = std::make_unique<GCDepthConcatenateLayerKernel>(); kernel->configure(inputs_vector.at(i), offset, output); offset += inputs_vector.at(i)->info()->dimension(axis); _concat_kernels.emplace_back(std::move(kernel)); diff --git a/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp index 0d0526d5c9..93a66f012e 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 Arm Limited. + * Copyright (c) 2017-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -31,7 +31,6 @@ #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" #include <cmath> -#include <memory> #include <tuple> using namespace arm_compute; diff --git a/src/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.cpp index 4ddd0ab4ca..46d5cc40d9 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCDepthwiseConvolutionLayer.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h" #include "arm_compute/core/PixelValue.h" #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -40,7 +39,7 @@ void GCDepthwiseConvolutionLayer3x3::configure(IGCTensor *input, const IGCTensor { ARM_COMPUTE_ERROR_ON(dilation.x() != 1 || dilation.y() != 1); ARM_COMPUTE_UNUSED(dilation); - auto k = arm_compute::support::cpp14::make_unique<GCDepthwiseConvolutionLayer3x3Kernel>(); + auto k = std::make_unique<GCDepthwiseConvolutionLayer3x3Kernel>(); k->configure(input, weights, biases, output, conv_info, depth_multiplier); _kernel = std::move(k); diff --git a/src/runtime/GLES_COMPUTE/functions/GCDirectConvolutionLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCDirectConvolutionLayer.cpp index c2aa81567e..63c963196a 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCDirectConvolutionLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCDirectConvolutionLayer.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Utils.h" #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" -#include "support/MemorySupport.h" using namespace arm_compute; @@ -46,19 +45,19 @@ void GCDirectConvolutionLayer::configure(IGCTensor *input, const IGCTensor *weig if(kernel_size == 1) { - auto k = arm_compute::support::cpp14::make_unique<GCDirectConvolutionLayer1x1Kernel>(); + auto k = std::make_unique<GCDirectConvolutionLayer1x1Kernel>(); k->configure(input, weights, biases, output, conv_info, act_info); _kernel = std::move(k); } else if(kernel_size == 3) { - auto k = arm_compute::support::cpp14::make_unique<GCDirectConvolutionLayer3x3Kernel>(); + auto k = std::make_unique<GCDirectConvolutionLayer3x3Kernel>(); k->configure(input, weights, biases, output, conv_info, act_info); _kernel = std::move(k); } else if(kernel_size == 5) { - auto k = arm_compute::support::cpp14::make_unique<GCDirectConvolutionLayer5x5Kernel>(); + auto k = std::make_unique<GCDirectConvolutionLayer5x5Kernel>(); k->configure(input, weights, biases, output, conv_info, act_info); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCFillBorder.cpp b/src/runtime/GLES_COMPUTE/functions/GCFillBorder.cpp index 080b5a22ac..97b4fd946c 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCFillBorder.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCFillBorder.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/GLES_COMPUTE/kernels/GCFillBorderKernel.h" #include "arm_compute/core/Helpers.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ using namespace arm_compute; void GCFillBorder::configure(IGCTensor *tensor, unsigned int border_width, BorderMode border_mode, const PixelValue &constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<GCFillBorderKernel>(); + auto k = std::make_unique<GCFillBorderKernel>(); k->configure(tensor, BorderSize(border_width), border_mode, constant_border_value); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp index 57a09edfd6..299a027b42 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCFullyConnectedLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" -#include "support/MemorySupport.h" #include <algorithm> @@ -33,7 +32,7 @@ using namespace arm_compute; void GCFullyConnectedLayerReshapeWeights::configure(const IGCTensor *input, IGCTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<GCTransposeKernel>(); + auto k = std::make_unique<GCTransposeKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCGEMMInterleave4x4.cpp b/src/runtime/GLES_COMPUTE/functions/GCGEMMInterleave4x4.cpp index 1366a134aa..c1287f7e9c 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCGEMMInterleave4x4.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCGEMMInterleave4x4.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/GLES_COMPUTE/functions/GCGEMMInterleave4x4.h" #include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMInterleave4x4Kernel.h" -#include "support/MemorySupport.h" using namespace arm_compute; void GCGEMMInterleave4x4::configure(const IGCTensor *input, IGCTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<GCGEMMInterleave4x4Kernel>(); + auto k = std::make_unique<GCGEMMInterleave4x4Kernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCGEMMTranspose1xW.cpp b/src/runtime/GLES_COMPUTE/functions/GCGEMMTranspose1xW.cpp index 877f81ae9b..d085357eaa 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCGEMMTranspose1xW.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCGEMMTranspose1xW.cpp @@ -26,13 +26,12 @@ #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h" #include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMTranspose1xWKernel.h" #include "arm_compute/core/Types.h" -#include "support/MemorySupport.h" using namespace arm_compute; void GCGEMMTranspose1xW::configure(const IGCTensor *input, IGCTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<GCGEMMTranspose1xWKernel>(); + auto k = std::make_unique<GCGEMMTranspose1xWKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCPixelWiseMultiplication.cpp b/src/runtime/GLES_COMPUTE/functions/GCPixelWiseMultiplication.cpp index daf978f3ac..ce50a63e53 100755 --- a/src/runtime/GLES_COMPUTE/functions/GCPixelWiseMultiplication.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCPixelWiseMultiplication.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/GLES_COMPUTE/functions/GCPixelWiseMultiplication.h" #include "arm_compute/core/GLES_COMPUTE/kernels/GCPixelWiseMultiplicationKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -33,7 +32,7 @@ using namespace arm_compute; void GCPixelWiseMultiplication::configure(const IGCTensor *input1, const IGCTensor *input2, IGCTensor *output, float scale, const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(act_info); - auto k = arm_compute::support::cpp14::make_unique<GCPixelWiseMultiplicationKernel>(); + auto k = std::make_unique<GCPixelWiseMultiplicationKernel>(); k->configure(input1, input2, output, scale); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCPoolingLayer.cpp b/src/runtime/GLES_COMPUTE/functions/GCPoolingLayer.cpp index e4ccabc503..6a71fbebe7 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCPoolingLayer.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCPoolingLayer.cpp @@ -27,8 +27,6 @@ #include "arm_compute/core/GLES_COMPUTE/kernels/GCPoolingLayerKernel.h" #include "arm_compute/runtime/GLES_COMPUTE/GCScheduler.h" -#include "support/MemorySupport.h" - namespace arm_compute { GCPoolingLayer::GCPoolingLayer() @@ -39,7 +37,7 @@ GCPoolingLayer::GCPoolingLayer() void GCPoolingLayer::configure(IGCTensor *input, IGCTensor *output, const PoolingLayerInfo &pool_info, IGCTensor *indices) { // Configure pooling kernel - auto k = arm_compute::support::cpp14::make_unique<GCPoolingLayerKernel>(); + auto k = std::make_unique<GCPoolingLayerKernel>(); k->configure(input, output, pool_info, indices); _kernel = std::move(k); diff --git a/src/runtime/GLES_COMPUTE/functions/GCScale.cpp b/src/runtime/GLES_COMPUTE/functions/GCScale.cpp index dccbe9960d..720006fead 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCScale.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCScale.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/GLES_COMPUTE/IGCTensor.h" #include "arm_compute/core/GLES_COMPUTE/kernels/GCScaleKernel.h" #include "arm_compute/core/Validate.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -39,7 +38,7 @@ void GCScale::configure(IGCTensor *input, IGCTensor *output, InterpolationPolicy void GCScale::configure(IGCTensor *input, IGCTensor *output, const ScaleKernelInfo &info) { - auto k = arm_compute::support::cpp14::make_unique<GCScaleKernel>(); + auto k = std::make_unique<GCScaleKernel>(); k->configure(input, output, info); _kernel = std::move(k); _border_handler.configure(input, _kernel->border_size(), info.border_mode, info.constant_border_value); diff --git a/src/runtime/GLES_COMPUTE/functions/GCTensorShift.cpp b/src/runtime/GLES_COMPUTE/functions/GCTensorShift.cpp index 4cbd2e3e8e..050dc7e9f5 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCTensorShift.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCTensorShift.cpp @@ -28,13 +28,12 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/PixelValue.h" #include "arm_compute/core/Utils.h" -#include "support/MemorySupport.h" using namespace arm_compute; void GCTensorShift::configure(IGCTensor *input) { - auto k = arm_compute::support::cpp14::make_unique<GCTensorShiftKernel>(); + auto k = std::make_unique<GCTensorShiftKernel>(); k->configure(input); _kernel = std::move(k); } diff --git a/src/runtime/GLES_COMPUTE/functions/GCTranspose.cpp b/src/runtime/GLES_COMPUTE/functions/GCTranspose.cpp index da4471c925..14125e9db2 100644 --- a/src/runtime/GLES_COMPUTE/functions/GCTranspose.cpp +++ b/src/runtime/GLES_COMPUTE/functions/GCTranspose.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/GLES_COMPUTE/functions/GCTranspose.h" #include "arm_compute/core/GLES_COMPUTE/kernels/GCTransposeKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void GCTranspose::configure(const IGCTensor *input, IGCTensor *output) { - auto k = arm_compute::support::cpp14::make_unique<GCTransposeKernel>(); + auto k = std::make_unique<GCTransposeKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEAbsoluteDifference.cpp b/src/runtime/NEON/functions/NEAbsoluteDifference.cpp index df2bc7d72e..1c37af980e 100644 --- a/src/runtime/NEON/functions/NEAbsoluteDifference.cpp +++ b/src/runtime/NEON/functions/NEAbsoluteDifference.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEAbsoluteDifference.h" #include "src/core/NEON/kernels/NEAbsoluteDifferenceKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ NEAbsoluteDifference::~NEAbsoluteDifference() = default; void NEAbsoluteDifference::configure(const ITensor *input1, const ITensor *input2, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEAbsoluteDifferenceKernel>(); + auto k = std::make_unique<NEAbsoluteDifferenceKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEAccumulate.cpp b/src/runtime/NEON/functions/NEAccumulate.cpp index 20eefd9d2d..b81ec24a39 100644 --- a/src/runtime/NEON/functions/NEAccumulate.cpp +++ b/src/runtime/NEON/functions/NEAccumulate.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEAccumulate.h" #include "src/core/NEON/kernels/NEAccumulateKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ NEAccumulate::~NEAccumulate() = default; void NEAccumulate::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEAccumulateKernel>(); + auto k = std::make_unique<NEAccumulateKernel>(); k->configure(input, output); _kernel = std::move(k); } @@ -45,13 +44,13 @@ void NEAccumulateWeighted::configure(const ITensor *input, float alpha, ITensor { if(use_fp16) { - auto k = arm_compute::support::cpp14::make_unique<NEAccumulateWeightedFP16Kernel>(); + auto k = std::make_unique<NEAccumulateWeightedFP16Kernel>(); k->configure(input, alpha, output); _kernel = std::move(k); } else { - auto k = arm_compute::support::cpp14::make_unique<NEAccumulateWeightedKernel>(); + auto k = std::make_unique<NEAccumulateWeightedKernel>(); k->configure(input, alpha, output); _kernel = std::move(k); } @@ -61,7 +60,7 @@ NEAccumulateSquared::~NEAccumulateSquared() = default; void NEAccumulateSquared::configure(const ITensor *input, uint32_t shift, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEAccumulateSquaredKernel>(); + auto k = std::make_unique<NEAccumulateSquaredKernel>(); k->configure(input, shift, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEActivationLayer.cpp b/src/runtime/NEON/functions/NEActivationLayer.cpp index f9ad298e4d..27f01f67ce 100644 --- a/src/runtime/NEON/functions/NEActivationLayer.cpp +++ b/src/runtime/NEON/functions/NEActivationLayer.cpp @@ -28,7 +28,6 @@ #include "arm_compute/runtime/IRuntimeContext.h" #include "arm_compute/runtime/Tensor.h" #include "src/core/NEON/kernels/NEActivationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,7 +37,7 @@ NEActivationLayer::~NEActivationLayer() = default; void NEActivationLayer::configure(const ITensorInfo *input, ITensorInfo *output, const ActivationLayerInfo &activation_info) { - auto k = arm_compute::support::cpp14::make_unique<NEActivationLayerKernel>(); + auto k = std::make_unique<NEActivationLayerKernel>(); k->configure(input, output, activation_info); _kernel = std::move(k); } @@ -58,7 +57,7 @@ struct NEActivationLayer::Impl }; NEActivationLayer::NEActivationLayer(IRuntimeContext *ctx) - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { _impl->ctx = ctx; } @@ -76,7 +75,7 @@ void NEActivationLayer::configure(ITensor *input, ITensor *output, ActivationLay _impl->src = input; _impl->dst = output == nullptr ? input : output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEActivationLayer>(); + _impl->op = std::make_unique<experimental::NEActivationLayer>(); _impl->op->configure(_impl->src->info(), _impl->dst->info(), activation_info); } diff --git a/src/runtime/NEON/functions/NEArgMinMaxLayer.cpp b/src/runtime/NEON/functions/NEArgMinMaxLayer.cpp index 2a9bb76c7f..7bca20d46c 100644 --- a/src/runtime/NEON/functions/NEArgMinMaxLayer.cpp +++ b/src/runtime/NEON/functions/NEArgMinMaxLayer.cpp @@ -31,14 +31,12 @@ #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEReductionOperationKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { NEArgMinMaxLayer::~NEArgMinMaxLayer() = default; NEArgMinMaxLayer::NEArgMinMaxLayer(std::shared_ptr<IMemoryManager> memory_manager) - : _reduction_function(support::cpp14::make_unique<NEReductionOperation>()) + : _reduction_function(std::make_unique<NEReductionOperation>()) { ARM_COMPUTE_UNUSED(memory_manager); } diff --git a/src/runtime/NEON/functions/NEArithmeticAddition.cpp b/src/runtime/NEON/functions/NEArithmeticAddition.cpp index 0bf9a09333..1eaccf3396 100644 --- a/src/runtime/NEON/functions/NEArithmeticAddition.cpp +++ b/src/runtime/NEON/functions/NEArithmeticAddition.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/ITensor.h" #include "src/core/NEON/kernels/NEArithmeticAdditionKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -38,7 +37,7 @@ NEArithmeticAddition::~NEArithmeticAddition() = default; void NEArithmeticAddition::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(act_info); - auto k = arm_compute::support::cpp14::make_unique<NEArithmeticAdditionKernel>(); + auto k = std::make_unique<NEArithmeticAdditionKernel>(); k->configure(input1, input2, output, policy); _kernel = std::move(k); } @@ -58,7 +57,7 @@ struct NEArithmeticAddition::Impl }; NEArithmeticAddition::NEArithmeticAddition() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEArithmeticAddition::NEArithmeticAddition(NEArithmeticAddition &&) = default; @@ -75,7 +74,7 @@ void NEArithmeticAddition::configure(const ITensor *input1, const ITensor *input _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEArithmeticAddition>(); + _impl->op = std::make_unique<experimental::NEArithmeticAddition>(); _impl->op->configure(input1->info(), input2->info(), output->info(), policy, act_info); } diff --git a/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp b/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp index ba3f426269..512cfd6f70 100644 --- a/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp +++ b/src/runtime/NEON/functions/NEArithmeticSubtraction.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/ITensor.h" #include "src/core/NEON/kernels/NEArithmeticSubtractionKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -36,7 +35,7 @@ namespace experimental void NEArithmeticSubtraction::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, ConvertPolicy policy, const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(act_info); - auto k = arm_compute::support::cpp14::make_unique<NEArithmeticSubtractionKernel>(); + auto k = std::make_unique<NEArithmeticSubtractionKernel>(); k->configure(input1, input2, output, policy); _kernel = std::move(k); } @@ -57,7 +56,7 @@ struct NEArithmeticSubtraction::Impl }; NEArithmeticSubtraction::NEArithmeticSubtraction() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEArithmeticSubtraction::NEArithmeticSubtraction(NEArithmeticSubtraction &&) = default; @@ -74,7 +73,7 @@ void NEArithmeticSubtraction::configure(const ITensor *input1, const ITensor *in _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEArithmeticSubtraction>(); + _impl->op = std::make_unique<experimental::NEArithmeticSubtraction>(); _impl->op->configure(input1->info(), input2->info(), output->info(), policy, act_info); } diff --git a/src/runtime/NEON/functions/NEBatchNormalizationLayer.cpp b/src/runtime/NEON/functions/NEBatchNormalizationLayer.cpp index d0fdfcf101..b90a38b47f 100644 --- a/src/runtime/NEON/functions/NEBatchNormalizationLayer.cpp +++ b/src/runtime/NEON/functions/NEBatchNormalizationLayer.cpp @@ -31,8 +31,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEBatchNormalizationLayerKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { NEBatchNormalizationLayer::~NEBatchNormalizationLayer() = default; @@ -46,7 +44,7 @@ void NEBatchNormalizationLayer::configure(ITensor *input, ITensor *output, const ActivationLayerInfo act_info) { // Configure kernel - _norm_kernel = arm_compute::support::cpp14::make_unique<NEBatchNormalizationLayerKernel>(); + _norm_kernel = std::make_unique<NEBatchNormalizationLayerKernel>(); _norm_kernel->configure(input, output, mean, var, beta, gamma, epsilon, act_info); } diff --git a/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp b/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp index 77a63c0f63..8f537a650a 100644 --- a/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp +++ b/src/runtime/NEON/functions/NEBatchToSpaceLayer.cpp @@ -30,20 +30,18 @@ #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEBatchToSpaceLayerKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { void NEBatchToSpaceLayer::configure(const ITensor *input, const ITensor *block_shape, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEBatchToSpaceLayerKernel>(); + auto k = std::make_unique<NEBatchToSpaceLayerKernel>(); k->configure(input, block_shape, output); _kernel = std::move(k); } void NEBatchToSpaceLayer::configure(const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEBatchToSpaceLayerKernel>(); + auto k = std::make_unique<NEBatchToSpaceLayerKernel>(); k->configure(input, block_shape_x, block_shape_y, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEBitwiseAnd.cpp b/src/runtime/NEON/functions/NEBitwiseAnd.cpp index f3b5220ccf..81c087988a 100644 --- a/src/runtime/NEON/functions/NEBitwiseAnd.cpp +++ b/src/runtime/NEON/functions/NEBitwiseAnd.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEBitwiseAnd.h" #include "src/core/NEON/kernels/NEBitwiseAndKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void NEBitwiseAnd::configure(const ITensor *input1, const ITensor *input2, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEBitwiseAndKernel>(); + auto k = std::make_unique<NEBitwiseAndKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEBitwiseNot.cpp b/src/runtime/NEON/functions/NEBitwiseNot.cpp index 036584ea1a..3155df5db3 100644 --- a/src/runtime/NEON/functions/NEBitwiseNot.cpp +++ b/src/runtime/NEON/functions/NEBitwiseNot.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEBitwiseNot.h" #include "src/core/NEON/kernels/NEBitwiseNotKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void NEBitwiseNot::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEBitwiseNotKernel>(); + auto k = std::make_unique<NEBitwiseNotKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEBitwiseOr.cpp b/src/runtime/NEON/functions/NEBitwiseOr.cpp index fc905a0919..793eb25d80 100644 --- a/src/runtime/NEON/functions/NEBitwiseOr.cpp +++ b/src/runtime/NEON/functions/NEBitwiseOr.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEBitwiseOr.h" #include "src/core/NEON/kernels/NEBitwiseOrKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void NEBitwiseOr::configure(const ITensor *input1, const ITensor *input2, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEBitwiseOrKernel>(); + auto k = std::make_unique<NEBitwiseOrKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEBitwiseXor.cpp b/src/runtime/NEON/functions/NEBitwiseXor.cpp index 301a0c4659..2d0af63e35 100644 --- a/src/runtime/NEON/functions/NEBitwiseXor.cpp +++ b/src/runtime/NEON/functions/NEBitwiseXor.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEBitwiseXor.h" #include "src/core/NEON/kernels/NEBitwiseXorKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void NEBitwiseXor::configure(const ITensor *input1, const ITensor *input2, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEBitwiseXorKernel>(); + auto k = std::make_unique<NEBitwiseXorKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEBoundingBoxTransform.cpp b/src/runtime/NEON/functions/NEBoundingBoxTransform.cpp index 0b639430b1..cfd14faca0 100644 --- a/src/runtime/NEON/functions/NEBoundingBoxTransform.cpp +++ b/src/runtime/NEON/functions/NEBoundingBoxTransform.cpp @@ -24,14 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEBoundingBoxTransform.h" #include "src/core/NEON/kernels/NEBoundingBoxTransformKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { void NEBoundingBoxTransform::configure(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, const BoundingBoxTransformInfo &info) { // Configure Bounding Box kernel - auto k = arm_compute::support::cpp14::make_unique<NEBoundingBoxTransformKernel>(); + auto k = std::make_unique<NEBoundingBoxTransformKernel>(); k->configure(boxes, pred_boxes, deltas, info); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEBox3x3.cpp b/src/runtime/NEON/functions/NEBox3x3.cpp index 01d2356a4c..ee40e2c475 100644 --- a/src/runtime/NEON/functions/NEBox3x3.cpp +++ b/src/runtime/NEON/functions/NEBox3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEBox3x3Kernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -36,17 +35,17 @@ void NEBox3x3::configure(ITensor *input, ITensor *output, BorderMode border_mode { if(use_fp16) { - auto k = arm_compute::support::cpp14::make_unique<NEBox3x3FP16Kernel>(); + auto k = std::make_unique<NEBox3x3FP16Kernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); } else { - auto k = arm_compute::support::cpp14::make_unique<NEBox3x3Kernel>(); + auto k = std::make_unique<NEBox3x3Kernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); } - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NECannyEdge.cpp b/src/runtime/NEON/functions/NECannyEdge.cpp index bf4f7d7933..52bc81e001 100644 --- a/src/runtime/NEON/functions/NECannyEdge.cpp +++ b/src/runtime/NEON/functions/NECannyEdge.cpp @@ -36,7 +36,6 @@ #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NESobel5x5Kernel.h" #include "src/core/NEON/kernels/NESobel7x7Kernel.h" -#include "support/MemorySupport.h" #include <cstring> #include <inttypes.h> @@ -105,19 +104,19 @@ void NECannyEdge::configure(ITensor *input, ITensor *output, int32_t upper_thr, // Configure/Init sobelNxN if(gradient_size == 3) { - auto k = arm_compute::support::cpp14::make_unique<NESobel3x3>(); + auto k = std::make_unique<NESobel3x3>(); k->configure(input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); } else if(gradient_size == 5) { - auto k = arm_compute::support::cpp14::make_unique<NESobel5x5>(); + auto k = std::make_unique<NESobel5x5>(); k->configure(input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); } else if(gradient_size == 7) { - auto k = arm_compute::support::cpp14::make_unique<NESobel7x7>(); + auto k = std::make_unique<NESobel7x7>(); k->configure(input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); } @@ -131,7 +130,7 @@ void NECannyEdge::configure(ITensor *input, ITensor *output, int32_t upper_thr, _memory_group.manage(&_phase); // Configure gradient - auto k = arm_compute::support::cpp14::make_unique<NEGradientKernel>(); + auto k = std::make_unique<NEGradientKernel>(); k->configure(&_gx, &_gy, &_magnitude, &_phase, norm_type); _gradient = std::move(k); @@ -143,12 +142,12 @@ void NECannyEdge::configure(ITensor *input, ITensor *output, int32_t upper_thr, _memory_group.manage(&_nonmax); // Configure non-maxima suppression - _non_max_suppr = arm_compute::support::cpp14::make_unique<NEEdgeNonMaxSuppressionKernel>(); + _non_max_suppr = std::make_unique<NEEdgeNonMaxSuppressionKernel>(); _non_max_suppr->configure(&_magnitude, &_phase, &_nonmax, upper_thr, lower_thr, border_mode == BorderMode::UNDEFINED); // Fill border around magnitude image as non-maxima suppression will access // it. If border mode is undefined filling the border is a nop. - _border_mag_gradient = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _border_mag_gradient = std::make_unique<NEFillBorderKernel>(); _border_mag_gradient->configure(&_magnitude, _non_max_suppr->border_size(), border_mode, constant_border_value); // Allocate intermediate tensors @@ -156,11 +155,11 @@ void NECannyEdge::configure(ITensor *input, ITensor *output, int32_t upper_thr, _magnitude.allocator()->allocate(); // Configure edge tracing - _edge_trace = arm_compute::support::cpp14::make_unique<NEEdgeTraceKernel>(); + _edge_trace = std::make_unique<NEEdgeTraceKernel>(); _edge_trace->configure(&_nonmax, output); // Fill border with "No edge" to stop recursion in edge trace - _border_edge_trace = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _border_edge_trace = std::make_unique<NEFillBorderKernel>(); _border_edge_trace->configure(&_nonmax, _edge_trace->border_size(), BorderMode::CONSTANT, static_cast<float>(0.f)); // Allocate intermediate tensors diff --git a/src/runtime/NEON/functions/NECast.cpp b/src/runtime/NEON/functions/NECast.cpp index 7fd2605fd2..a42f512ce6 100644 --- a/src/runtime/NEON/functions/NECast.cpp +++ b/src/runtime/NEON/functions/NECast.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.h" #include "src/core/NEON/kernels/NEDepthConvertLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ namespace arm_compute { void NECast::configure(ITensor *input, ITensor *output, ConvertPolicy policy) { - auto k = arm_compute::support::cpp14::make_unique<NEDepthConvertLayerKernel>(); + auto k = std::make_unique<NEDepthConvertLayerKernel>(); k->configure(input, output, policy, 0); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEChannelCombine.cpp b/src/runtime/NEON/functions/NEChannelCombine.cpp index f8a9be0313..b566153bf4 100644 --- a/src/runtime/NEON/functions/NEChannelCombine.cpp +++ b/src/runtime/NEON/functions/NEChannelCombine.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEChannelCombine.h" #include "src/core/NEON/kernels/NEChannelCombineKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,14 +31,14 @@ using namespace arm_compute; void NEChannelCombine::configure(const ITensor *plane0, const ITensor *plane1, const ITensor *plane2, const ITensor *plane3, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEChannelCombineKernel>(); + auto k = std::make_unique<NEChannelCombineKernel>(); k->configure(plane0, plane1, plane2, plane3, output); _kernel = std::move(k); } void NEChannelCombine::configure(const IImage *plane0, const IImage *plane1, const IImage *plane2, IMultiImage *output) { - auto k = arm_compute::support::cpp14::make_unique<NEChannelCombineKernel>(); + auto k = std::make_unique<NEChannelCombineKernel>(); k->configure(plane0, plane1, plane2, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEChannelExtract.cpp b/src/runtime/NEON/functions/NEChannelExtract.cpp index 8f5e4d47d9..a43dc28896 100644 --- a/src/runtime/NEON/functions/NEChannelExtract.cpp +++ b/src/runtime/NEON/functions/NEChannelExtract.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEChannelExtract.h" #include "src/core/NEON/kernels/NEChannelExtractKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,14 +31,14 @@ using namespace arm_compute; void NEChannelExtract::configure(const ITensor *input, Channel channel, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEChannelExtractKernel>(); + auto k = std::make_unique<NEChannelExtractKernel>(); k->configure(input, channel, output); _kernel = std::move(k); } void NEChannelExtract::configure(const IMultiImage *input, Channel channel, IImage *output) { - auto k = arm_compute::support::cpp14::make_unique<NEChannelExtractKernel>(); + auto k = std::make_unique<NEChannelExtractKernel>(); k->configure(input, channel, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEChannelShuffleLayer.cpp b/src/runtime/NEON/functions/NEChannelShuffleLayer.cpp index c72dec67ee..bf4af83a0d 100644 --- a/src/runtime/NEON/functions/NEChannelShuffleLayer.cpp +++ b/src/runtime/NEON/functions/NEChannelShuffleLayer.cpp @@ -25,13 +25,12 @@ #include "arm_compute/core/Types.h" #include "src/core/NEON/kernels/NEChannelShuffleLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEChannelShuffleLayer::configure(const ITensor *input, ITensor *output, unsigned int num_groups) { - auto k = arm_compute::support::cpp14::make_unique<NEChannelShuffleLayerKernel>(); + auto k = std::make_unique<NEChannelShuffleLayerKernel>(); k->configure(input, output, num_groups); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NECol2Im.cpp b/src/runtime/NEON/functions/NECol2Im.cpp index 0706125157..fc61520f47 100644 --- a/src/runtime/NEON/functions/NECol2Im.cpp +++ b/src/runtime/NEON/functions/NECol2Im.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NECol2Im.h" #include "src/core/NEON/kernels/NECol2ImKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NECol2Im::configure(const ITensor *input, ITensor *output, const Size2D &convolved_dims) { - auto k = arm_compute::support::cpp14::make_unique<NECol2ImKernel>(); + auto k = std::make_unique<NECol2ImKernel>(); k->configure(input, output, convolved_dims); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEColorConvert.cpp b/src/runtime/NEON/functions/NEColorConvert.cpp index ebdd1046ce..c7c9cdd923 100644 --- a/src/runtime/NEON/functions/NEColorConvert.cpp +++ b/src/runtime/NEON/functions/NEColorConvert.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEColorConvert.h" #include "src/core/NEON/kernels/NEColorConvertKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,28 +31,28 @@ using namespace arm_compute; void NEColorConvert::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEColorConvertKernel>(); + auto k = std::make_unique<NEColorConvertKernel>(); k->configure(input, output); _kernel = std::move(k); } void NEColorConvert::configure(const IMultiImage *input, IImage *output) { - auto k = arm_compute::support::cpp14::make_unique<NEColorConvertKernel>(); + auto k = std::make_unique<NEColorConvertKernel>(); k->configure(input, output); _kernel = std::move(k); } void NEColorConvert::configure(const IImage *input, IMultiImage *output) { - auto k = arm_compute::support::cpp14::make_unique<NEColorConvertKernel>(); + auto k = std::make_unique<NEColorConvertKernel>(); k->configure(input, output); _kernel = std::move(k); } void NEColorConvert::configure(const IMultiImage *input, IMultiImage *output) { - auto k = arm_compute::support::cpp14::make_unique<NEColorConvertKernel>(); + auto k = std::make_unique<NEColorConvertKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEComputeAllAnchors.cpp b/src/runtime/NEON/functions/NEComputeAllAnchors.cpp index 3f5712dd3a..a305ca0708 100644 --- a/src/runtime/NEON/functions/NEComputeAllAnchors.cpp +++ b/src/runtime/NEON/functions/NEComputeAllAnchors.cpp @@ -24,14 +24,13 @@ #include "arm_compute/runtime/NEON/functions/NEComputeAllAnchors.h" #include "src/core/NEON/kernels/NEGenerateProposalsLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEComputeAllAnchors::configure(const ITensor *anchors, ITensor *all_anchors, const ComputeAnchorsInfo &info) { // Configure ComputeAllAnchors kernel - auto k = arm_compute::support::cpp14::make_unique<NEComputeAllAnchorsKernel>(); + auto k = std::make_unique<NEComputeAllAnchorsKernel>(); k->configure(anchors, all_anchors, info); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp index 03a01aec6b..782f8f1ff7 100644 --- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp +++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp @@ -36,7 +36,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Types.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -68,28 +67,28 @@ void NEConcatenation::configure(const std::vector<const ITensorInfo *> &inputs_v { case Window::DimX: { - auto kernel = support::cpp14::make_unique<NEWidthConcatenateLayerKernel>(); + auto kernel = std::make_unique<NEWidthConcatenateLayerKernel>(); kernel->configure(inputs_vector.at(i), offset, output); _concat_kernels.emplace_back(std::move(kernel)); break; } case Window::DimY: { - auto kernel = support::cpp14::make_unique<NEHeightConcatenateLayerKernel>(); + auto kernel = std::make_unique<NEHeightConcatenateLayerKernel>(); kernel->configure(inputs_vector.at(i), offset, output); _concat_kernels.emplace_back(std::move(kernel)); break; } case Window::DimZ: { - auto kernel = support::cpp14::make_unique<NEDepthConcatenateLayerKernel>(); + auto kernel = std::make_unique<NEDepthConcatenateLayerKernel>(); kernel->configure(inputs_vector.at(i), offset, output); _concat_kernels.emplace_back(std::move(kernel)); break; } case 3: { - auto kernel = support::cpp14::make_unique<NEBatchConcatenateLayerKernel>(); + auto kernel = std::make_unique<NEBatchConcatenateLayerKernel>(); kernel->configure(inputs_vector.at(i), offset, output); _concat_kernels.emplace_back(std::move(kernel)); break; @@ -181,7 +180,7 @@ struct NEConcatenateLayer::Impl }; NEConcatenateLayer::NEConcatenateLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -199,7 +198,7 @@ void NEConcatenateLayer::configure(std::vector<const ITensor *> inputs_vector, I _impl->dst = output; _impl->axis = axis; _impl->num_inputs = inputs_vector.size(); - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEConcatenation>(); + _impl->op = std::make_unique<experimental::NEConcatenation>(); std::vector<const ITensorInfo *> inputs_vector_info; for(unsigned int i = 0; i < inputs_vector.size(); ++i) diff --git a/src/runtime/NEON/functions/NEConvertFullyConnectedWeights.cpp b/src/runtime/NEON/functions/NEConvertFullyConnectedWeights.cpp index 291afe0273..a6a7746830 100644 --- a/src/runtime/NEON/functions/NEConvertFullyConnectedWeights.cpp +++ b/src/runtime/NEON/functions/NEConvertFullyConnectedWeights.cpp @@ -23,7 +23,6 @@ */ #include "arm_compute/runtime/NEON/functions/NEConvertFullyConnectedWeights.h" #include "src/core/NEON/kernels/NEConvertFullyConnectedWeightsKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -37,7 +36,7 @@ NEConvertFullyConnectedWeights::NEConvertFullyConnectedWeights() void NEConvertFullyConnectedWeights::configure(const ITensor *input, ITensor *output, const TensorShape &original_input_shape, DataLayout data_layout) { - _kernel = arm_compute::support::cpp14::make_unique<NEConvertFullyConnectedWeightsKernel>(); + _kernel = std::make_unique<NEConvertFullyConnectedWeightsKernel>(); _kernel->configure(input, output, original_input_shape, data_layout); } diff --git a/src/runtime/NEON/functions/NEConvolution.cpp b/src/runtime/NEON/functions/NEConvolution.cpp index 07ac8bd42b..680d8f628f 100644 --- a/src/runtime/NEON/functions/NEConvolution.cpp +++ b/src/runtime/NEON/functions/NEConvolution.cpp @@ -34,7 +34,6 @@ #include "src/core/NEON/kernels/NEConvolutionKernel.h" #include "src/core/NEON/kernels/NEConvolutionKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" #include <array> #include <utility> @@ -45,11 +44,11 @@ NEConvolution3x3::~NEConvolution3x3() = default; void NEConvolution3x3::configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEConvolution3x3Kernel>(); + auto k = std::make_unique<NEConvolution3x3Kernel>(); k->configure(input, output, conv, scale, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } @@ -76,7 +75,7 @@ void NEConvolutionSquare<matrix_size>::configure(ITensor *input, ITensor *output _is_separable = separate_matrix(conv, conv_col.data(), conv_row.data(), matrix_size); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); if(_is_separable) { DataType intermediate_type = DataType::UNKNOWN; @@ -93,8 +92,8 @@ void NEConvolutionSquare<matrix_size>::configure(ITensor *input, ITensor *output scale = calculate_matrix_scale(conv, matrix_size); } - _kernel_hor = arm_compute::support::cpp14::make_unique<NESeparableConvolutionHorKernel<matrix_size>>(); - _kernel_vert = arm_compute::support::cpp14::make_unique<NESeparableConvolutionVertKernel<matrix_size>>(); + _kernel_hor = std::make_unique<NESeparableConvolutionHorKernel<matrix_size>>(); + _kernel_vert = std::make_unique<NESeparableConvolutionVertKernel<matrix_size>>(); _kernel_hor->configure(input, &_tmp, conv_row.data(), border_mode == BorderMode::UNDEFINED); _kernel_vert->configure(&_tmp, output, conv_col.data(), scale, border_mode == BorderMode::UNDEFINED); @@ -105,7 +104,7 @@ void NEConvolutionSquare<matrix_size>::configure(ITensor *input, ITensor *output } else { - _kernel = arm_compute::support::cpp14::make_unique<NEConvolutionKernel<matrix_size>>(); + _kernel = std::make_unique<NEConvolutionKernel<matrix_size>>(); _kernel->configure(input, output, conv, scale, border_mode == BorderMode::UNDEFINED); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); } @@ -138,11 +137,11 @@ NEConvolutionRectangle::~NEConvolutionRectangle() = default; void NEConvolutionRectangle::configure(ITensor *input, ITensor *output, const int16_t *conv, uint32_t rows, uint32_t cols, uint32_t scale, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEConvolutionRectangleKernel>(); + auto k = std::make_unique<NEConvolutionRectangleKernel>(); k->configure(input, output, conv, rows, cols, scale, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEConvolutionLayer.cpp b/src/runtime/NEON/functions/NEConvolutionLayer.cpp index cc5f160787..cc549ca31b 100644 --- a/src/runtime/NEON/functions/NEConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEConvolutionLayer.cpp @@ -33,8 +33,6 @@ #include "arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h" #include "arm_compute/runtime/NEON/functions/NEWinogradConvolutionLayer.h" -#include "support/MemorySupport.h" - #include <cmath> #include <tuple> #include <utility> @@ -61,35 +59,35 @@ void NEConvolutionLayer::configure(ITensor *input, const ITensor *weights, const { case ConvolutionMethod::WINOGRAD: { - auto f = arm_compute::support::cpp14::make_unique<NEWinogradConvolutionLayer>(_memory_manager); + auto f = std::make_unique<NEWinogradConvolutionLayer>(_memory_manager); f->configure(input, weights, biases, output, conv_info, act_info, enable_fast_math); _function = std::move(f); break; } case ConvolutionMethod::GEMM: { - auto f = arm_compute::support::cpp14::make_unique<NEGEMMConvolutionLayer>(_memory_manager); + auto f = std::make_unique<NEGEMMConvolutionLayer>(_memory_manager); f->configure(input, weights, biases, output, conv_info, weights_info, dilation, act_info); _function = std::move(f); break; } case ConvolutionMethod::GEMM_CONV2D: { - auto f = arm_compute::support::cpp14::make_unique<NEGEMMConv2d>(_memory_manager); + auto f = std::make_unique<NEGEMMConv2d>(_memory_manager); f->configure(input, weights, biases, output, info); _function = std::move(f); break; } case ConvolutionMethod::DIRECT: { - auto f = arm_compute::support::cpp14::make_unique<NEDirectConvolutionLayer>(_memory_manager); + auto f = std::make_unique<NEDirectConvolutionLayer>(_memory_manager); f->configure(input, weights, biases, output, conv_info, act_info); _function = std::move(f); break; } case ConvolutionMethod::FFT: { - auto f = arm_compute::support::cpp14::make_unique<NEFFTConvolutionLayer>(_memory_manager); + auto f = std::make_unique<NEFFTConvolutionLayer>(_memory_manager); f->configure(input, weights, biases, output, conv_info, act_info); _function = std::move(f); break; diff --git a/src/runtime/NEON/functions/NECopy.cpp b/src/runtime/NEON/functions/NECopy.cpp index 9e7bf40559..11707cbd4c 100644 --- a/src/runtime/NEON/functions/NECopy.cpp +++ b/src/runtime/NEON/functions/NECopy.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NECopy.h" #include "src/core/NEON/kernels/NECopyKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ NECopy::~NECopy() = default; void NECopy::configure(ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NECopyKernel>(); + auto k = std::make_unique<NECopyKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NECropResize.cpp b/src/runtime/NEON/functions/NECropResize.cpp index 2e2d2251b6..af85cac7da 100644 --- a/src/runtime/NEON/functions/NECropResize.cpp +++ b/src/runtime/NEON/functions/NECropResize.cpp @@ -26,8 +26,6 @@ #include "arm_compute/runtime/NEON/functions/NECropResize.h" #include "src/core/NEON/kernels/NECropKernel.h" -#include "support/MemorySupport.h" - #include <cstddef> namespace arm_compute @@ -82,18 +80,18 @@ void NECropResize::configure(const ITensor *input, const ITensor *boxes, const I for(unsigned int i = 0; i < _num_boxes; ++i) { - auto crop_tensor = support::cpp14::make_unique<Tensor>(); + auto crop_tensor = std::make_unique<Tensor>(); TensorInfo crop_result_info(1, DataType::F32); crop_result_info.set_data_layout(DataLayout::NHWC); crop_tensor->allocator()->init(crop_result_info); - auto scale_tensor = support::cpp14::make_unique<Tensor>(); + auto scale_tensor = std::make_unique<Tensor>(); TensorInfo scaled_result_info(out_shape, 1, DataType::F32); scaled_result_info.set_data_layout(DataLayout::NHWC); scale_tensor->allocator()->init(scaled_result_info); - auto crop_kernel = support::cpp14::make_unique<NECropKernel>(); - auto scale_kernel = support::cpp14::make_unique<NEScale>(); + auto crop_kernel = std::make_unique<NECropKernel>(); + auto scale_kernel = std::make_unique<NEScale>(); crop_kernel->configure(input, boxes, box_ind, crop_tensor.get(), i, _extrapolation_value); _crop.emplace_back(std::move(crop_kernel)); diff --git a/src/runtime/NEON/functions/NEDepthConvertLayer.cpp b/src/runtime/NEON/functions/NEDepthConvertLayer.cpp index af0f5efb69..761de8eb60 100644 --- a/src/runtime/NEON/functions/NEDepthConvertLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthConvertLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEDepthConvertLayer.h" #include "src/core/NEON/kernels/NEDepthConvertLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void NEDepthConvertLayer::configure(const ITensor *input, ITensor *output, ConvertPolicy policy, uint32_t shift) { - auto k = arm_compute::support::cpp14::make_unique<NEDepthConvertLayerKernel>(); + auto k = std::make_unique<NEDepthConvertLayerKernel>(); k->configure(input, output, policy, shift); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEDepthToSpaceLayer.cpp b/src/runtime/NEON/functions/NEDepthToSpaceLayer.cpp index c4f15e3b68..2793c3f27e 100644 --- a/src/runtime/NEON/functions/NEDepthToSpaceLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthToSpaceLayer.cpp @@ -30,13 +30,11 @@ #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEDepthToSpaceLayerKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { void NEDepthToSpaceLayer::configure(const ITensor *input, ITensor *output, int32_t block_shape) { - auto k = arm_compute::support::cpp14::make_unique<NEDepthToSpaceLayerKernel>(); + auto k = std::make_unique<NEDepthToSpaceLayerKernel>(); k->configure(input, output, block_shape); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp index fc97279211..d17f6b5cd9 100644 --- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEDepthwiseConvolutionLayerNativeKernel.h" -#include "support/MemorySupport.h" using namespace arm_compute::misc; using namespace arm_compute::misc::shape_calculator; @@ -246,7 +245,7 @@ void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerGeneric::configure( } _original_weights = weights_to_use; - _depthwise_conv_kernel = arm_compute::support::cpp14::make_unique<NEDepthwiseConvolutionLayerNativeKernel>(); + _depthwise_conv_kernel = std::make_unique<NEDepthwiseConvolutionLayerNativeKernel>(); _depthwise_conv_kernel->configure(input_to_use, weights_to_use, biases, output_to_use, conv_info, depth_multiplier, dilation); if(_is_nchw) diff --git a/src/runtime/NEON/functions/NEDequantizationLayer.cpp b/src/runtime/NEON/functions/NEDequantizationLayer.cpp index 0c0f86c82b..a345840f4f 100644 --- a/src/runtime/NEON/functions/NEDequantizationLayer.cpp +++ b/src/runtime/NEON/functions/NEDequantizationLayer.cpp @@ -25,13 +25,12 @@ #include "arm_compute/runtime/NEON/functions/NEDequantizationLayer.h" #include "src/core/NEON/kernels/NEDequantizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEDequantizationLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEDequantizationLayerKernel>(); + auto k = std::make_unique<NEDequantizationLayerKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEDerivative.cpp b/src/runtime/NEON/functions/NEDerivative.cpp index f007e9fda3..8ef42123db 100644 --- a/src/runtime/NEON/functions/NEDerivative.cpp +++ b/src/runtime/NEON/functions/NEDerivative.cpp @@ -29,7 +29,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEDerivativeKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -45,8 +44,8 @@ void NEDerivative::configure(ITensor *input, ITensor *output_x, ITensor *output_ ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); ARM_COMPUTE_ERROR_ON((output_x == nullptr) && (output_y == nullptr)); - _kernel = arm_compute::support::cpp14::make_unique<NEDerivativeKernel>(); - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _kernel = std::make_unique<NEDerivativeKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); _kernel->configure(input, output_x, output_y, border_mode == BorderMode::UNDEFINED); _border_handler->configure(input, BorderSize(1), border_mode, PixelValue(constant_border_value)); diff --git a/src/runtime/NEON/functions/NEDilate.cpp b/src/runtime/NEON/functions/NEDilate.cpp index 70c0b61639..56523abd8a 100644 --- a/src/runtime/NEON/functions/NEDilate.cpp +++ b/src/runtime/NEON/functions/NEDilate.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEDilateKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,11 +33,11 @@ using namespace arm_compute; void NEDilate::configure(ITensor *input, ITensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEDilateKernel>(); + auto k = std::make_unique<NEDilateKernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp index 98d6386ffe..a953edc78f 100644 --- a/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDirectConvolutionLayer.cpp @@ -30,7 +30,6 @@ #include "src/core/NEON/kernels/NEDirectConvolutionLayerKernel.h" #include "src/core/NEON/kernels/NEDirectConvolutionLayerOutputStageKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -45,9 +44,9 @@ NEDirectConvolutionLayer::NEDirectConvolutionLayer(std::shared_ptr<IMemoryManage void NEDirectConvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &conv_info, const ActivationLayerInfo &act_info) { ARM_COMPUTE_ERROR_ON(input->info()->data_layout() == DataLayout::UNKNOWN); - _output_stage_kernel = arm_compute::support::cpp14::make_unique<NEDirectConvolutionLayerOutputStageKernel>(); - _conv_kernel = arm_compute::support::cpp14::make_unique<NEDirectConvolutionLayerKernel>(); - _input_border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _output_stage_kernel = std::make_unique<NEDirectConvolutionLayerOutputStageKernel>(); + _conv_kernel = std::make_unique<NEDirectConvolutionLayerKernel>(); + _input_border_handler = std::make_unique<NEFillBorderKernel>(); // Free accumulator if(_accumulator.buffer() != nullptr) diff --git a/src/runtime/NEON/functions/NEElementwiseOperators.cpp b/src/runtime/NEON/functions/NEElementwiseOperators.cpp index 7f3fe8b30b..badcf2e997 100644 --- a/src/runtime/NEON/functions/NEElementwiseOperators.cpp +++ b/src/runtime/NEON/functions/NEElementwiseOperators.cpp @@ -26,7 +26,6 @@ #include <src/core/NEON/kernels/NEElementwiseOperationKernel.h> #include "arm_compute/core/ITensor.h" -#include "support/MemorySupport.h" #include <utility> @@ -36,7 +35,7 @@ namespace experimental { void NEElementwiseMax::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEArithmeticOperationKernel>(); + auto k = std::make_unique<NEArithmeticOperationKernel>(); k->configure(ArithmeticOperation::MAX, input1, input2, output); _kernel = std::move(k); } @@ -48,7 +47,7 @@ Status NEElementwiseMax::validate(const ITensorInfo *input1, const ITensorInfo * void NEElementwiseMin::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEArithmeticOperationKernel>(); + auto k = std::make_unique<NEArithmeticOperationKernel>(); k->configure(ArithmeticOperation::MIN, input1, input2, output); _kernel = std::move(k); } @@ -60,7 +59,7 @@ Status NEElementwiseMin::validate(const ITensorInfo *input1, const ITensorInfo * void NEElementwiseSquaredDiff::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEArithmeticOperationKernel>(); + auto k = std::make_unique<NEArithmeticOperationKernel>(); k->configure(ArithmeticOperation::SQUARED_DIFF, input1, input2, output); _kernel = std::move(k); } @@ -72,7 +71,7 @@ Status NEElementwiseSquaredDiff::validate(const ITensorInfo *input1, const ITens void NEElementwiseDivision::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEDivisionOperationKernel>(); + auto k = std::make_unique<NEDivisionOperationKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } @@ -84,7 +83,7 @@ Status NEElementwiseDivision::validate(const ITensorInfo *input1, const ITensorI void NEElementwisePower::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEPowerOperationKernel>(); + auto k = std::make_unique<NEPowerOperationKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } @@ -97,7 +96,7 @@ Status NEElementwisePower::validate(const ITensorInfo *input1, const ITensorInfo template <ComparisonOperation COP> void NEElementwiseComparisonStatic<COP>::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEComparisonOperationKernel>(); + auto k = std::make_unique<NEComparisonOperationKernel>(); k->configure(COP, input1, input2, output); _kernel = std::move(k); } @@ -110,7 +109,7 @@ Status NEElementwiseComparisonStatic<COP>::validate(const ITensorInfo *input1, c void NEElementwiseComparison::configure(const ITensorInfo *input1, const ITensorInfo *input2, ITensorInfo *output, ComparisonOperation op) { - auto k = arm_compute::support::cpp14::make_unique<NEComparisonOperationKernel>(); + auto k = std::make_unique<NEComparisonOperationKernel>(); k->configure(op, input1, input2, output); _kernel = std::move(k); } @@ -138,7 +137,7 @@ struct NEElementwiseMax::Impl }; NEElementwiseMax::NEElementwiseMax() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEElementwiseMax::NEElementwiseMax(NEElementwiseMax &&) = default; @@ -151,7 +150,7 @@ void NEElementwiseMax::configure(ITensor *input1, ITensor *input2, ITensor *outp _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwiseMax>(); + _impl->op = std::make_unique<experimental::NEElementwiseMax>(); _impl->op->configure(input1->info(), input2->info(), output->info()); } @@ -179,7 +178,7 @@ struct NEElementwiseMin::Impl }; NEElementwiseMin::NEElementwiseMin() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEElementwiseMin::NEElementwiseMin(NEElementwiseMin &&) = default; @@ -192,7 +191,7 @@ void NEElementwiseMin::configure(ITensor *input1, ITensor *input2, ITensor *outp _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwiseMin>(); + _impl->op = std::make_unique<experimental::NEElementwiseMin>(); _impl->op->configure(input1->info(), input2->info(), output->info()); } @@ -220,7 +219,7 @@ struct NEElementwiseSquaredDiff::Impl }; NEElementwiseSquaredDiff::NEElementwiseSquaredDiff() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEElementwiseSquaredDiff::NEElementwiseSquaredDiff(NEElementwiseSquaredDiff &&) = default; @@ -233,7 +232,7 @@ void NEElementwiseSquaredDiff::configure(ITensor *input1, ITensor *input2, ITens _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwiseSquaredDiff>(); + _impl->op = std::make_unique<experimental::NEElementwiseSquaredDiff>(); _impl->op->configure(input1->info(), input2->info(), output->info()); } @@ -261,7 +260,7 @@ struct NEElementwiseDivision::Impl }; NEElementwiseDivision::NEElementwiseDivision() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEElementwiseDivision::NEElementwiseDivision(NEElementwiseDivision &&) = default; @@ -274,7 +273,7 @@ void NEElementwiseDivision::configure(ITensor *input1, ITensor *input2, ITensor _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwiseDivision>(); + _impl->op = std::make_unique<experimental::NEElementwiseDivision>(); _impl->op->configure(input1->info(), input2->info(), output->info()); } @@ -302,7 +301,7 @@ struct NEElementwisePower::Impl }; NEElementwisePower::NEElementwisePower() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEElementwisePower::NEElementwisePower(NEElementwisePower &&) = default; @@ -315,7 +314,7 @@ void NEElementwisePower::configure(ITensor *input1, ITensor *input2, ITensor *ou _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwisePower>(); + _impl->op = std::make_unique<experimental::NEElementwisePower>(); _impl->op->configure(input1->info(), input2->info(), output->info()); } @@ -345,7 +344,7 @@ struct NEElementwiseComparisonStatic<COP>::Impl template <ComparisonOperation COP> NEElementwiseComparisonStatic<COP>::NEElementwiseComparisonStatic() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } template <ComparisonOperation COP> @@ -361,7 +360,7 @@ void NEElementwiseComparisonStatic<COP>::configure(ITensor *input1, ITensor *inp _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwiseComparisonStatic<COP>>(); + _impl->op = std::make_unique<experimental::NEElementwiseComparisonStatic<COP>>(); _impl->op->configure(input1->info(), input2->info(), output->info()); } @@ -390,7 +389,7 @@ struct NEElementwiseComparison::Impl }; NEElementwiseComparison::NEElementwiseComparison() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEElementwiseComparison::NEElementwiseComparison(NEElementwiseComparison &&) = default; @@ -402,7 +401,7 @@ void NEElementwiseComparison::configure(ITensor *input1, ITensor *input2, ITenso _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEElementwiseComparison>(); + _impl->op = std::make_unique<experimental::NEElementwiseComparison>(); _impl->op->configure(input1->info(), input2->info(), output->info(), op); } diff --git a/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp b/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp index 5e130205d2..5c779f1489 100644 --- a/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp +++ b/src/runtime/NEON/functions/NEElementwiseUnaryLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEElementwiseUnaryLayer.h" #include "src/core/NEON/kernels/NEElementwiseUnaryKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ namespace arm_compute { void NERsqrtLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::RSQRT, input, output); _kernel = std::move(k); } @@ -43,7 +42,7 @@ Status NERsqrtLayer::validate(const ITensorInfo *input, const ITensorInfo *outpu void NEExpLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::EXP, input, output); _kernel = std::move(k); } @@ -54,7 +53,7 @@ Status NEExpLayer::validate(const ITensorInfo *input, const ITensorInfo *output) void NENegLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::NEG, input, output); _kernel = std::move(k); } @@ -65,7 +64,7 @@ Status NENegLayer::validate(const ITensorInfo *input, const ITensorInfo *output) void NELogLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::LOG, input, output); _kernel = std::move(k); } @@ -76,7 +75,7 @@ Status NELogLayer::validate(const ITensorInfo *input, const ITensorInfo *output) void NEAbsLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::ABS, input, output); _kernel = std::move(k); } @@ -87,7 +86,7 @@ Status NEAbsLayer::validate(const ITensorInfo *input, const ITensorInfo *output) void NERoundLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::ROUND, input, output); _kernel = std::move(k); } @@ -98,7 +97,7 @@ Status NERoundLayer::validate(const ITensorInfo *input, const ITensorInfo *outpu void NESinLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEElementwiseUnaryKernel>(); + auto k = std::make_unique<NEElementwiseUnaryKernel>(); k->configure(ElementWiseUnary::SIN, input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEEqualizeHistogram.cpp b/src/runtime/NEON/functions/NEEqualizeHistogram.cpp index d3ff171323..0b83b7dac7 100644 --- a/src/runtime/NEON/functions/NEEqualizeHistogram.cpp +++ b/src/runtime/NEON/functions/NEEqualizeHistogram.cpp @@ -32,7 +32,6 @@ #include "src/core/NEON/kernels/NEHistogramKernel.h" #include "src/core/NEON/kernels/NEHistogramKernel.h" #include "src/core/NEON/kernels/NETableLookupKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -50,9 +49,9 @@ void NEEqualizeHistogram::configure(const IImage *input, IImage *output) ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); - _histogram_kernel = arm_compute::support::cpp14::make_unique<NEHistogramKernel>(); - _cd_histogram_kernel = arm_compute::support::cpp14::make_unique<NECumulativeDistributionKernel>(); - _map_histogram_kernel = arm_compute::support::cpp14::make_unique<NETableLookupKernel>(); + _histogram_kernel = std::make_unique<NEHistogramKernel>(); + _cd_histogram_kernel = std::make_unique<NECumulativeDistributionKernel>(); + _map_histogram_kernel = std::make_unique<NETableLookupKernel>(); // Configure kernels _histogram_kernel->configure(input, &_hist); diff --git a/src/runtime/NEON/functions/NEErode.cpp b/src/runtime/NEON/functions/NEErode.cpp index 748694fe3f..83e266140a 100644 --- a/src/runtime/NEON/functions/NEErode.cpp +++ b/src/runtime/NEON/functions/NEErode.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEErodeKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,11 +33,11 @@ namespace arm_compute { void NEErode::configure(ITensor *input, ITensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEErodeKernel>(); + auto k = std::make_unique<NEErodeKernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEFFT1D.cpp b/src/runtime/NEON/functions/NEFFT1D.cpp index b94c25832a..e72488f0f6 100644 --- a/src/runtime/NEON/functions/NEFFT1D.cpp +++ b/src/runtime/NEON/functions/NEFFT1D.cpp @@ -30,7 +30,6 @@ #include "src/core/NEON/kernels/NEFFTRadixStageKernel.h" #include "src/core/NEON/kernels/NEFFTScaleKernel.h" #include "src/core/utils/helpers/fft.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -64,7 +63,7 @@ void NEFFT1D::configure(const ITensor *input, ITensor *output, const FFT1DInfo & TensorInfo digit_reverse_indices_info(TensorShape(input->info()->tensor_shape()[config.axis]), 1, DataType::U32); _digit_reverse_indices.allocator()->init(digit_reverse_indices_info); _memory_group.manage(&_digit_reversed_input); - _digit_reverse_kernel = arm_compute::support::cpp14::make_unique<NEFFTDigitReverseKernel>(); + _digit_reverse_kernel = std::make_unique<NEFFTDigitReverseKernel>(); _digit_reverse_kernel->configure(input, &_digit_reversed_input, &_digit_reverse_indices, digit_reverse_config); // Create and configure FFT kernels @@ -82,7 +81,7 @@ void NEFFT1D::configure(const ITensor *input, ITensor *output, const FFT1DInfo & fft_kernel_info.radix = radix_for_stage; fft_kernel_info.Nx = Nx; fft_kernel_info.is_first_stage = (i == 0); - _fft_kernels[i] = arm_compute::support::cpp14::make_unique<NEFFTRadixStageKernel>(); + _fft_kernels[i] = std::make_unique<NEFFTRadixStageKernel>(); _fft_kernels[i]->configure(&_digit_reversed_input, ((i == (_num_ffts - 1)) && !is_c2r) ? output : nullptr, fft_kernel_info); Nx *= radix_for_stage; @@ -94,7 +93,7 @@ void NEFFT1D::configure(const ITensor *input, ITensor *output, const FFT1DInfo & FFTScaleKernelInfo scale_config; scale_config.scale = static_cast<float>(N); scale_config.conjugate = config.direction == FFTDirection::Inverse; - _scale_kernel = arm_compute::support::cpp14::make_unique<NEFFTScaleKernel>(); + _scale_kernel = std::make_unique<NEFFTScaleKernel>(); is_c2r ? _scale_kernel->configure(&_digit_reversed_input, output, scale_config) : _scale_kernel->configure(output, nullptr, scale_config); } diff --git a/src/runtime/NEON/functions/NEFFTConvolutionLayer.cpp b/src/runtime/NEON/functions/NEFFTConvolutionLayer.cpp index 23788b7c39..bb6b5ed6b4 100644 --- a/src/runtime/NEON/functions/NEFFTConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEFFTConvolutionLayer.cpp @@ -36,8 +36,6 @@ #include "src/core/helpers/AutoConfiguration.h" #include "src/core/utils/helpers/fft.h" -#include "support/MemorySupport.h" - namespace arm_compute { namespace @@ -161,7 +159,7 @@ void NEFFTConvolutionLayer::configure(ITensor *input, const ITensor *weights, co _pad_weights_func.configure(&_flipped_weights, &_padded_weights, padding_w); // Transform weights - _transform_weights_func = support::cpp14::make_unique<NEFFT2D>(); + _transform_weights_func = std::make_unique<NEFFT2D>(); _transform_weights_func->configure(&_padded_weights, &_transformed_weights, FFT2DInfo()); // Pad input diff --git a/src/runtime/NEON/functions/NEFastCorners.cpp b/src/runtime/NEON/functions/NEFastCorners.cpp index 1bde3cc508..5164d80947 100644 --- a/src/runtime/NEON/functions/NEFastCorners.cpp +++ b/src/runtime/NEON/functions/NEFastCorners.cpp @@ -35,7 +35,6 @@ #include "src/core/NEON/kernels/NEFillArrayKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NENonMaximaSuppression3x3Kernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -68,9 +67,9 @@ void NEFastCorners::configure(IImage *input, float threshold, bool nonmax_suppre _output.allocator()->init(tensor_info); _memory_group.manage(&_output); - _fast_corners_kernel = arm_compute::support::cpp14::make_unique<NEFastCornersKernel>(); - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); - _fill_kernel = arm_compute::support::cpp14::make_unique<NEFillArrayKernel>(); + _fast_corners_kernel = std::make_unique<NEFastCornersKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); + _fill_kernel = std::make_unique<NEFillArrayKernel>(); // If border is UNDEFINED _fast_corners_kernel will operate in xwindow (3, // width - 3) and ywindow (3, height -3) so the output image will leave the // pixels on the borders unchanged. This is reflected in the valid region @@ -87,7 +86,7 @@ void NEFastCorners::configure(IImage *input, float threshold, bool nonmax_suppre { _suppressed.allocator()->init(tensor_info); _memory_group.manage(&_suppressed); - _nonmax_kernel = arm_compute::support::cpp14::make_unique<NENonMaximaSuppression3x3Kernel>(); + _nonmax_kernel = std::make_unique<NENonMaximaSuppression3x3Kernel>(); _nonmax_kernel->configure(&_output, &_suppressed, BorderMode::UNDEFINED == border_mode); _fill_kernel->configure(&_suppressed, 1 /* we keep all texels >0 */, corners); diff --git a/src/runtime/NEON/functions/NEFill.cpp b/src/runtime/NEON/functions/NEFill.cpp index 68292c9ee0..74e366ab49 100644 --- a/src/runtime/NEON/functions/NEFill.cpp +++ b/src/runtime/NEON/functions/NEFill.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/Window.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEMemsetKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,7 +33,7 @@ namespace arm_compute { void NEFill::configure(ITensor *tensor, PixelValue constant_value) { - auto k = arm_compute::support::cpp14::make_unique<NEMemsetKernel>(); + auto k = std::make_unique<NEMemsetKernel>(); k->configure(tensor, constant_value); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEFillBorder.cpp b/src/runtime/NEON/functions/NEFillBorder.cpp index e96069f97c..bb57222eb4 100644 --- a/src/runtime/NEON/functions/NEFillBorder.cpp +++ b/src/runtime/NEON/functions/NEFillBorder.cpp @@ -26,13 +26,12 @@ #include "arm_compute/core/Window.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEFillBorder::configure(ITensor *input, unsigned int border_width, BorderMode border_mode, const PixelValue &constant_border_value) { - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); _border_handler->configure(input, BorderSize(border_width), border_mode, constant_border_value); } diff --git a/src/runtime/NEON/functions/NEFlattenLayer.cpp b/src/runtime/NEON/functions/NEFlattenLayer.cpp index 4dfe96325e..21e55665cd 100644 --- a/src/runtime/NEON/functions/NEFlattenLayer.cpp +++ b/src/runtime/NEON/functions/NEFlattenLayer.cpp @@ -25,13 +25,12 @@ #include "arm_compute/core/Size2D.h" #include "src/core/NEON/kernels/NEFlattenLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEFlattenLayer::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEFlattenLayerKernel>(); + auto k = std::make_unique<NEFlattenLayerKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEFloor.cpp b/src/runtime/NEON/functions/NEFloor.cpp index 5f6bd61017..74149e6f24 100644 --- a/src/runtime/NEON/functions/NEFloor.cpp +++ b/src/runtime/NEON/functions/NEFloor.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEFloor.h" #include "src/core/NEON/kernels/NEFloorKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEFloor::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEFloorKernel>(); + auto k = std::make_unique<NEFloorKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp index 6b0c27cf65..f12c410a59 100644 --- a/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp +++ b/src/runtime/NEON/functions/NEFullyConnectedLayer.cpp @@ -43,8 +43,6 @@ #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "src/core/NEON/kernels/NETransposeKernel.h" -#include "support/MemorySupport.h" - #include <algorithm> #include <cmath> @@ -148,7 +146,7 @@ Status validate_mm(const ITensorInfo *input, const ITensorInfo *weights, const I void NEFullyConnectedLayerReshapeWeights::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NETransposeKernel>(); + auto k = std::make_unique<NETransposeKernel>(); k->configure(input, output); _kernel = std::move(k); } @@ -215,7 +213,7 @@ void NEFullyConnectedLayer::configure_conv_fc(const ITensor *input, const ITenso // Configure flatten kernel _memory_group.manage(&_flatten_output); - _flatten_kernel = arm_compute::support::cpp14::make_unique<NEFlattenLayerKernel>(); + _flatten_kernel = std::make_unique<NEFlattenLayerKernel>(); _flatten_kernel->configure(input, &_flatten_output); // Configure matrix multiply kernel diff --git a/src/runtime/NEON/functions/NEFuseBatchNormalization.cpp b/src/runtime/NEON/functions/NEFuseBatchNormalization.cpp index c64fde050e..a8ce6b2bfc 100644 --- a/src/runtime/NEON/functions/NEFuseBatchNormalization.cpp +++ b/src/runtime/NEON/functions/NEFuseBatchNormalization.cpp @@ -29,7 +29,6 @@ #include "arm_compute/core/Types.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEFuseBatchNormalizationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -45,7 +44,7 @@ void NEFuseBatchNormalization::configure(const ITensor *input_weights, const ITe const ITensor *input_bias, const ITensor *bn_beta, const ITensor *bn_gamma, float epsilon, FuseBatchNormalizationType fbn_type) { - _fuse_bn_kernel = arm_compute::support::cpp14::make_unique<NEFuseBatchNormalizationKernel>(); + _fuse_bn_kernel = std::make_unique<NEFuseBatchNormalizationKernel>(); _fuse_bn_kernel->configure(input_weights, bn_mean, bn_var, fused_weights, fused_bias, input_bias, bn_beta, bn_gamma, epsilon, fbn_type); } diff --git a/src/runtime/NEON/functions/NEGEMM.cpp b/src/runtime/NEON/functions/NEGEMM.cpp index 9f52e458d2..03f5aa37c1 100644 --- a/src/runtime/NEON/functions/NEGEMM.cpp +++ b/src/runtime/NEON/functions/NEGEMM.cpp @@ -39,7 +39,6 @@ #include "src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" #include <cmath> @@ -110,7 +109,7 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe _memory_group.manage(&_tmp_d); } - _mm_kernel = arm_compute::support::cpp14::make_unique<NEGEMMMatrixMultiplyKernel>(); + _mm_kernel = std::make_unique<NEGEMMMatrixMultiplyKernel>(); // Select between GEMV and GEMM if(_run_vector_matrix_multiplication) @@ -148,11 +147,11 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe int k = a->info()->dimension(0); // Configure interleave kernel - _interleave_kernel = arm_compute::support::cpp14::make_unique<NEGEMMInterleave4x4Kernel>(); + _interleave_kernel = std::make_unique<NEGEMMInterleave4x4Kernel>(); _interleave_kernel->configure(a, &_tmp_a); // Configure transpose kernel - _transpose_kernel = arm_compute::support::cpp14::make_unique<NEGEMMTranspose1xWKernel>(); + _transpose_kernel = std::make_unique<NEGEMMTranspose1xWKernel>(); _transpose_kernel->configure(b, &_tmp_b); // Configure matrix multiplication kernel @@ -176,7 +175,7 @@ void NEGEMM::configure(const ITensor *a, const ITensor *b, const ITensor *c, ITe // Configure matrix addition kernel if(_run_addition) { - _ma_kernel = arm_compute::support::cpp14::make_unique<NEGEMMMatrixAdditionKernel>(); + _ma_kernel = std::make_unique<NEGEMMMatrixAdditionKernel>(); _ma_kernel->configure(c, d, beta); } diff --git a/src/runtime/NEON/functions/NEGEMMAssemblyDispatch.cpp b/src/runtime/NEON/functions/NEGEMMAssemblyDispatch.cpp index f6739ee925..394f970e54 100644 --- a/src/runtime/NEON/functions/NEGEMMAssemblyDispatch.cpp +++ b/src/runtime/NEON/functions/NEGEMMAssemblyDispatch.cpp @@ -28,8 +28,6 @@ #include "src/core/NEON/kernels/assembly/NEGEMMAssemblyWrapperKernel.h" #include "src/core/NEON/kernels/assembly/arm_gemm.hpp" -#include "support/MemorySupport.h" - #include <arm_neon.h> #include <cstdlib> @@ -485,7 +483,7 @@ void Fallback<TypeInput, TypeOutput, OutputStage>::configure(const ITensor *a, c } // arm_compute wrapper for the Gemm object (see above) - std::unique_ptr<NEGEMMAssemblyWrapperKernel<TypeInput, TypeOutput>> acl_gemm_wrapper = support::cpp14::make_unique<NEGEMMAssemblyWrapperKernel<TypeInput, TypeOutput>>(); + std::unique_ptr<NEGEMMAssemblyWrapperKernel<TypeInput, TypeOutput>> acl_gemm_wrapper = std::make_unique<NEGEMMAssemblyWrapperKernel<TypeInput, TypeOutput>>(); ARM_COMPUTE_ERROR_ON(acl_gemm_wrapper == nullptr); acl_gemm_wrapper->configure(_gemm_kernel_asm.get(), gemm_cfg.filter); const size_t workspace_size = _gemm_kernel_asm->get_working_size(); @@ -691,7 +689,7 @@ void create_arm_gemm(std::unique_ptr<NEGEMMAssemblyDispatch::IFallback> &arm_gem arm_gemm::GemmArgs args(&ci, p.M, p.N, p.K, p.sections, p.batches, p.multis, p.indirect, activation, num_threads); // Create arm_gemm fallback - auto fallback = support::cpp14::make_unique<Fallback<TypeInput, TypeOutput>>(); + auto fallback = std::make_unique<Fallback<TypeInput, TypeOutput>>(); fallback->configure(a, b, c, d, args, info, memory_group, weights_manager); arm_gemm = std::move(fallback); } @@ -709,7 +707,7 @@ void create_arm_gemm_quant(std::unique_ptr<NEGEMMAssemblyDispatch::IFallback> &a arm_gemm::GemmArgs args(&ci, p.M, p.N, p.K, p.sections, p.batches, p.multis, p.indirect, activation, num_threads); // Create arm_gemm fallback - auto fallback = support::cpp14::make_unique<Fallback<TypeInput, TypeOutput, arm_gemm::Requantize32>>(); + auto fallback = std::make_unique<Fallback<TypeInput, TypeOutput, arm_gemm::Requantize32>>(); // Configure requantization info const int32_t negation = info.negated_offsets ? 1 : -1; diff --git a/src/runtime/NEON/functions/NEGEMMConv2d.cpp b/src/runtime/NEON/functions/NEGEMMConv2d.cpp index 642b084fb4..860b6bb4e1 100644 --- a/src/runtime/NEON/functions/NEGEMMConv2d.cpp +++ b/src/runtime/NEON/functions/NEGEMMConv2d.cpp @@ -25,7 +25,9 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "arm_compute/runtime/NEON/NEScheduler.h" + #include <set> + namespace arm_compute { namespace diff --git a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp index 3f50f81af2..a3bdde24b0 100644 --- a/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEGEMMConvolutionLayer.cpp @@ -43,7 +43,6 @@ #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "src/core/NEON/kernels/NEIm2ColKernel.h" #include "src/core/NEON/kernels/NEWeightsReshapeKernel.h" -#include "support/MemorySupport.h" #include <set> #include <tuple> @@ -68,7 +67,7 @@ void NEConvolutionLayerReshapeWeights::configure(const ITensor *weights, const I const bool append_biases = (biases != nullptr) && !is_data_type_quantized_asymmetric(weights->info()->data_type()); const ITensor *biases_to_use = (append_biases) ? biases : nullptr; - _weights_reshape_kernel = arm_compute::support::cpp14::make_unique<NEWeightsReshapeKernel>(); + _weights_reshape_kernel = std::make_unique<NEWeightsReshapeKernel>(); _weights_reshape_kernel->configure(weights, biases_to_use, output); output->info()->set_quantization_info(weights->info()->quantization_info()); @@ -342,7 +341,7 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig _memory_group.manage(&_im2col_output); // Configure - _im2col_kernel = arm_compute::support::cpp14::make_unique<NEIm2ColKernel>(); + _im2col_kernel = std::make_unique<NEIm2ColKernel>(); _im2col_kernel->configure(input, &_im2col_output, Size2D(kernel_width, kernel_height), conv_info, false, dilation); // Update GEMM input @@ -385,7 +384,7 @@ void NEGEMMConvolutionLayer::configure(const ITensor *input, const ITensor *weig if(_data_layout == DataLayout::NCHW) { // Configure col2im - _col2im_kernel = arm_compute::support::cpp14::make_unique<NECol2ImKernel>(); + _col2im_kernel = std::make_unique<NECol2ImKernel>(); _col2im_kernel->configure(gemm_output_to_use, output, Size2D(conv_w, conv_h)); } else diff --git a/src/runtime/NEON/functions/NEGEMMInterleave4x4.cpp b/src/runtime/NEON/functions/NEGEMMInterleave4x4.cpp index 70fdcf492d..1e7a34bb35 100644 --- a/src/runtime/NEON/functions/NEGEMMInterleave4x4.cpp +++ b/src/runtime/NEON/functions/NEGEMMInterleave4x4.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEGEMMInterleave4x4.h" #include "src/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEGEMMInterleave4x4::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMInterleave4x4Kernel>(); + auto k = std::make_unique<NEGEMMInterleave4x4Kernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp index df8eaacf47..d8f9d08c13 100644 --- a/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp +++ b/src/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.cpp @@ -43,8 +43,6 @@ #include "src/core/NEON/kernels/NEGEMMLowpReductionKernel.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { namespace @@ -106,7 +104,7 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, _signed_a.allocator()->init(a_to_use->info()->clone()->set_data_type(dt).set_quantization_info(QuantizationInfo(iqinfo.scale, iqinfo.offset + offset_correction))); _memory_group.manage(&_signed_a); - _convert_to_signed_asymm = arm_compute::support::cpp14::make_unique<NEConvertQuantizedSignednessKernel>(); + _convert_to_signed_asymm = std::make_unique<NEConvertQuantizedSignednessKernel>(); _convert_to_signed_asymm->configure(a_to_use, &_signed_a); a_to_use = &_signed_a; _a_offset = _signed_a.info()->quantization_info().uniform().offset; @@ -182,11 +180,11 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, } // Configure interleave kernel - _mtx_a_reshape_kernel = arm_compute::support::cpp14::make_unique<NEGEMMInterleave4x4Kernel>(); + _mtx_a_reshape_kernel = std::make_unique<NEGEMMInterleave4x4Kernel>(); _mtx_a_reshape_kernel->configure(a_to_use, &_tmp_a); // Configure transpose kernel - _mtx_b_reshape_kernel = arm_compute::support::cpp14::make_unique<NEGEMMTranspose1xWKernel>(); + _mtx_b_reshape_kernel = std::make_unique<NEGEMMTranspose1xWKernel>(); _mtx_b_reshape_kernel->configure(b, &_tmp_b); } @@ -207,7 +205,7 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, } // Configure Matrix B reduction kernel - _mtx_b_reduction_kernel = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixBReductionKernel>(); + _mtx_b_reduction_kernel = std::make_unique<NEGEMMLowpMatrixBReductionKernel>(); _mtx_b_reduction_kernel->configure(b, &_vector_sum_col, reduction_info); } @@ -220,7 +218,7 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, _memory_group.manage(&_vector_sum_row); // Configure matrix A reduction kernel - _mtx_a_reduction_kernel = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _mtx_a_reduction_kernel = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); _mtx_a_reduction_kernel->configure(a_to_use, &_vector_sum_row, reduction_info); } @@ -229,11 +227,11 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, // Configure matrix multiply kernel if(!_assembly_path) { - _mm_kernel = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixMultiplyKernel>(); + _mm_kernel = std::make_unique<NEGEMMLowpMatrixMultiplyKernel>(); _mm_kernel->configure(matrix_a, matrix_b, &_mm_result_s32); } - _offset_contribution_output_stage_kernel = arm_compute::support::cpp14::make_unique<NEGEMMLowpOffsetContributionOutputStageKernel>(); + _offset_contribution_output_stage_kernel = std::make_unique<NEGEMMLowpOffsetContributionOutputStageKernel>(); _offset_contribution_output_stage_kernel->configure(&_mm_result_s32, _a_offset == 0 ? nullptr : &_vector_sum_col, _b_offset == 0 ? nullptr : &_vector_sum_row, c, @@ -243,7 +241,7 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, if(_flip_signedness) { - _convert_from_signed_asymm = arm_compute::support::cpp14::make_unique<NEConvertQuantizedSignednessKernel>(); + _convert_from_signed_asymm = std::make_unique<NEConvertQuantizedSignednessKernel>(); _convert_from_signed_asymm->configure(&_signed_output, output); } } @@ -252,11 +250,11 @@ void NEGEMMLowpMatrixMultiplyCore::configure(const ITensor *a, const ITensor *b, // Configure matrix multiply kernel if(!_assembly_path) { - _mm_kernel = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixMultiplyKernel>(); + _mm_kernel = std::make_unique<NEGEMMLowpMatrixMultiplyKernel>(); _mm_kernel->configure(matrix_a, matrix_b, output); } // Configure offset contribution kernel - _offset_contribution_kernel = arm_compute::support::cpp14::make_unique<NEGEMMLowpOffsetContributionKernel>(); + _offset_contribution_kernel = std::make_unique<NEGEMMLowpOffsetContributionKernel>(); _offset_contribution_kernel->configure(output, _a_offset == 0 ? nullptr : &_vector_sum_col, _b_offset == 0 ? nullptr : &_vector_sum_row, a_to_use->info()->dimension(0), _a_offset, _b_offset); } diff --git a/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp b/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp index 9fb8851d7a..807785a534 100644 --- a/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp +++ b/src/runtime/NEON/functions/NEGEMMLowpOutputStage.cpp @@ -29,7 +29,6 @@ #include "src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel.h" #include "src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel.h" #include "src/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,7 +37,7 @@ NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::~NEGEMMLowpQuantizeDownInt3 void NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min, int max) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max); _kernel = std::move(k); } @@ -53,7 +52,7 @@ NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::~NEGEMMLowpQuantizeDownInt32 void NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int result_offset_after_shift, int min, int max) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, result_offset_after_shift, min, max); _kernel = std::move(k); } @@ -67,7 +66,7 @@ NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::~NEGEMMLowpQuantizeDownInt3 void NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPoint::configure(const ITensor *input, const ITensor *bias, ITensor *output, int result_fixedpoint_multiplier, int result_shift, int min, int max) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); k->configure(input, bias, output, result_fixedpoint_multiplier, result_shift, min, max); _kernel = std::move(k); } @@ -93,21 +92,21 @@ void NEGEMMLowpOutputStage::configure(const ITensor *input, const ITensor *bias, { case DataType::QASYMM8: { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel>(); k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); _kernel = std::move(k); break; } case DataType::QASYMM8_SIGNED: { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel>(); k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_offset, info.gemmlowp_min_bound, info.gemmlowp_max_bound); _kernel = std::move(k); break; } case DataType::QSYMM16: { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel>(); k->configure(input, bias, output, info.gemmlowp_multiplier, info.gemmlowp_shift, info.gemmlowp_min_bound, info.gemmlowp_max_bound); _kernel = std::move(k); break; @@ -127,7 +126,7 @@ void NEGEMMLowpOutputStage::configure(const ITensor *input, const ITensor *bias, case DataType::QASYMM8: case DataType::QASYMM8_SIGNED: { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMLowpQuantizeDownInt32ScaleKernel>(); + auto k = std::make_unique<NEGEMMLowpQuantizeDownInt32ScaleKernel>(); k->configure(input, bias, output, &info); _kernel = std::move(k); break; diff --git a/src/runtime/NEON/functions/NEGEMMTranspose1xW.cpp b/src/runtime/NEON/functions/NEGEMMTranspose1xW.cpp index 90cf0bab07..0408cfa585 100644 --- a/src/runtime/NEON/functions/NEGEMMTranspose1xW.cpp +++ b/src/runtime/NEON/functions/NEGEMMTranspose1xW.cpp @@ -28,13 +28,12 @@ #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEGEMMTranspose1xW::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEGEMMTranspose1xWKernel>(); + auto k = std::make_unique<NEGEMMTranspose1xWKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEGather.cpp b/src/runtime/NEON/functions/NEGather.cpp index 5c0dae1507..86cbfd187a 100644 --- a/src/runtime/NEON/functions/NEGather.cpp +++ b/src/runtime/NEON/functions/NEGather.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEGather.h" #include "src/core/NEON/kernels/NEGatherKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ namespace arm_compute { void NEGather::configure(const ITensor *input, const ITensor *indices, ITensor *output, int axis) { - auto k = arm_compute::support::cpp14::make_unique<NEGatherKernel>(); + auto k = std::make_unique<NEGatherKernel>(); k->configure(input, indices, output, axis); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEGaussian3x3.cpp b/src/runtime/NEON/functions/NEGaussian3x3.cpp index 5290de1348..93e813c052 100644 --- a/src/runtime/NEON/functions/NEGaussian3x3.cpp +++ b/src/runtime/NEON/functions/NEGaussian3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEGaussian3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,11 +33,11 @@ namespace arm_compute { void NEGaussian3x3::configure(ITensor *input, ITensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEGaussian3x3Kernel>(); + auto k = std::make_unique<NEGaussian3x3Kernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEGaussian5x5.cpp b/src/runtime/NEON/functions/NEGaussian5x5.cpp index 7857710462..ed7e83b937 100644 --- a/src/runtime/NEON/functions/NEGaussian5x5.cpp +++ b/src/runtime/NEON/functions/NEGaussian5x5.cpp @@ -30,7 +30,6 @@ #include "arm_compute/runtime/TensorAllocator.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEGaussian5x5Kernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -50,9 +49,9 @@ void NEGaussian5x5::configure(ITensor *input, ITensor *output, BorderMode border // Manage intermediate buffers _memory_group.manage(&_tmp); - _kernel_hor = arm_compute::support::cpp14::make_unique<NEGaussian5x5HorKernel>(); - _kernel_vert = arm_compute::support::cpp14::make_unique<NEGaussian5x5VertKernel>(); - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _kernel_hor = std::make_unique<NEGaussian5x5HorKernel>(); + _kernel_vert = std::make_unique<NEGaussian5x5VertKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); // Create and configure kernels for the two passes _kernel_hor->configure(input, &_tmp, border_mode == BorderMode::UNDEFINED); diff --git a/src/runtime/NEON/functions/NEGaussianPyramid.cpp b/src/runtime/NEON/functions/NEGaussianPyramid.cpp index 30fe70f0ab..c9a36fc466 100644 --- a/src/runtime/NEON/functions/NEGaussianPyramid.cpp +++ b/src/runtime/NEON/functions/NEGaussianPyramid.cpp @@ -36,7 +36,6 @@ #include "src/core/NEON/kernels/NEGaussian5x5Kernel.h" #include "src/core/NEON/kernels/NEGaussianPyramidKernel.h" #include "src/core/NEON/kernels/NEScaleKernel.h" -#include "support/MemorySupport.h" #include <cstddef> @@ -98,19 +97,19 @@ void NEGaussianPyramidHalf::configure(const ITensor *input, IPyramid *pyramid, B for(size_t i = 0; i < num_stages; ++i) { /* Configure horizontal kernel */ - _horizontal_reduction[i] = arm_compute::support::cpp14::make_unique<NEGaussianPyramidHorKernel>(); + _horizontal_reduction[i] = std::make_unique<NEGaussianPyramidHorKernel>(); _horizontal_reduction[i]->configure(_pyramid->get_pyramid_level(i), _tmp.get_pyramid_level(i)); /* Configure vertical kernel */ - _vertical_reduction[i] = arm_compute::support::cpp14::make_unique<NEGaussianPyramidVertKernel>(); + _vertical_reduction[i] = std::make_unique<NEGaussianPyramidVertKernel>(); _vertical_reduction[i]->configure(_tmp.get_pyramid_level(i), _pyramid->get_pyramid_level(i + 1)); /* Configure border */ - _horizontal_border_handler[i] = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _horizontal_border_handler[i] = std::make_unique<NEFillBorderKernel>(); _horizontal_border_handler[i]->configure(_pyramid->get_pyramid_level(i), _horizontal_reduction[i]->border_size(), border_mode, PixelValue(constant_border_value)); /* Configure border */ - _vertical_border_handler[i] = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _vertical_border_handler[i] = std::make_unique<NEFillBorderKernel>(); _vertical_border_handler[i]->configure(_tmp.get_pyramid_level(i), _vertical_reduction[i]->border_size(), border_mode, PixelValue(pixel_value_u16)); } diff --git a/src/runtime/NEON/functions/NEHOGDescriptor.cpp b/src/runtime/NEON/functions/NEHOGDescriptor.cpp index 689e64fae7..bb125a1eae 100644 --- a/src/runtime/NEON/functions/NEHOGDescriptor.cpp +++ b/src/runtime/NEON/functions/NEHOGDescriptor.cpp @@ -31,7 +31,6 @@ #include "src/core/NEON/kernels/NEDerivativeKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEHOGDescriptorKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -88,11 +87,11 @@ void NEHOGDescriptor::configure(ITensor *input, ITensor *output, const IHOG *hog _memory_group.manage(&_hog_space); // Initialise orientation binning kernel - _orient_bin = arm_compute::support::cpp14::make_unique<NEHOGOrientationBinningKernel>(); + _orient_bin = std::make_unique<NEHOGOrientationBinningKernel>(); _orient_bin->configure(&_mag, &_phase, &_hog_space, hog->info()); // Initialize HOG norm kernel - _block_norm = arm_compute::support::cpp14::make_unique<NEHOGBlockNormalizationKernel>(); + _block_norm = std::make_unique<NEHOGBlockNormalizationKernel>(); _block_norm->configure(&_hog_space, output, hog->info()); // Allocate intermediate tensors diff --git a/src/runtime/NEON/functions/NEHOGDetector.cpp b/src/runtime/NEON/functions/NEHOGDetector.cpp index 8468b75f4e..3eda1b0ce0 100644 --- a/src/runtime/NEON/functions/NEHOGDetector.cpp +++ b/src/runtime/NEON/functions/NEHOGDetector.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEHOGDetector.h" #include "src/core/NEON/kernels/NEHOGDetectorKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -32,7 +31,7 @@ NEHOGDetector::~NEHOGDetector() = default; void NEHOGDetector::configure(const ITensor *input, const IHOG *hog, IDetectionWindowArray *detection_windows, const Size2D &detection_window_stride, float threshold, size_t idx_class) { - auto k = arm_compute::support::cpp14::make_unique<NEHOGDetectorKernel>(); + auto k = std::make_unique<NEHOGDetectorKernel>(); k->configure(input, hog, detection_windows, detection_window_stride, threshold, idx_class); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEHOGGradient.cpp b/src/runtime/NEON/functions/NEHOGGradient.cpp index 7d794bc1a0..f5a47735a9 100644 --- a/src/runtime/NEON/functions/NEHOGGradient.cpp +++ b/src/runtime/NEON/functions/NEHOGGradient.cpp @@ -28,7 +28,6 @@ #include "src/core/NEON/kernels/NEDerivativeKernel.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -66,13 +65,13 @@ void NEHOGGradient::configure(ITensor *input, ITensor *output_magnitude, ITensor // Initialise magnitude/phase kernel if(PhaseType::UNSIGNED == phase_type) { - auto k = arm_compute::support::cpp14::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::UNSIGNED>>(); + auto k = std::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::UNSIGNED>>(); k->configure(&_gx, &_gy, output_magnitude, output_phase); _mag_phase = std::move(k); } else { - auto k = arm_compute::support::cpp14::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::SIGNED>>(); + auto k = std::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::SIGNED>>(); k->configure(&_gx, &_gy, output_magnitude, output_phase); _mag_phase = std::move(k); } diff --git a/src/runtime/NEON/functions/NEHarrisCorners.cpp b/src/runtime/NEON/functions/NEHarrisCorners.cpp index 23fcf8c805..6b15596f8a 100644 --- a/src/runtime/NEON/functions/NEHarrisCorners.cpp +++ b/src/runtime/NEON/functions/NEHarrisCorners.cpp @@ -37,7 +37,6 @@ #include "src/core/NEON/kernels/NEHarrisCornersKernel.h" #include "src/core/NEON/kernels/NESobel5x5Kernel.h" #include "src/core/NEON/kernels/NESobel7x7Kernel.h" -#include "support/MemorySupport.h" #include <cmath> #include <utility> @@ -102,21 +101,21 @@ void NEHarrisCorners::configure(IImage *input, float threshold, float min_dist, { case 3: { - auto k = arm_compute::support::cpp14::make_unique<NESobel3x3>(); + auto k = std::make_unique<NESobel3x3>(); k->configure(input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); break; } case 5: { - auto k = arm_compute::support::cpp14::make_unique<NESobel5x5>(); + auto k = std::make_unique<NESobel5x5>(); k->configure(input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); break; } case 7: { - auto k = arm_compute::support::cpp14::make_unique<NESobel7x7>(); + auto k = std::make_unique<NESobel7x7>(); k->configure(input, &_gx, &_gy, border_mode, constant_border_value); _sobel = std::move(k); break; @@ -136,21 +135,21 @@ void NEHarrisCorners::configure(IImage *input, float threshold, float min_dist, { case 3: { - auto k = arm_compute::support::cpp14::make_unique<NEHarrisScoreKernel<3>>(); + auto k = std::make_unique<NEHarrisScoreKernel<3>>(); k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED); _harris_score = std::move(k); } break; case 5: { - auto k = arm_compute::support::cpp14::make_unique<NEHarrisScoreKernel<5>>(); + auto k = std::make_unique<NEHarrisScoreKernel<5>>(); k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED); _harris_score = std::move(k); } break; case 7: { - auto k = arm_compute::support::cpp14::make_unique<NEHarrisScoreKernel<7>>(); + auto k = std::make_unique<NEHarrisScoreKernel<7>>(); k->configure(&_gx, &_gy, &_score, norm_factor, threshold, sensitivity, border_mode == BorderMode::UNDEFINED); _harris_score = std::move(k); } @@ -159,8 +158,8 @@ void NEHarrisCorners::configure(IImage *input, float threshold, float min_dist, } // Configure border filling before harris score - _border_gx = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); - _border_gy = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _border_gx = std::make_unique<NEFillBorderKernel>(); + _border_gy = std::make_unique<NEFillBorderKernel>(); _border_gx->configure(&_gx, _harris_score->border_size(), border_mode, constant_border_value); _border_gy->configure(&_gy, _harris_score->border_size(), border_mode, constant_border_value); diff --git a/src/runtime/NEON/functions/NEHistogram.cpp b/src/runtime/NEON/functions/NEHistogram.cpp index 40ea3a16c6..1b093d60e5 100644 --- a/src/runtime/NEON/functions/NEHistogram.cpp +++ b/src/runtime/NEON/functions/NEHistogram.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEHistogramKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -51,7 +50,7 @@ void NEHistogram::configure(const IImage *input, IDistribution1D *output) _local_hist.resize(_local_hist_size); // Configure kernel - _histogram_kernel = arm_compute::support::cpp14::make_unique<NEHistogramKernel>(); + _histogram_kernel = std::make_unique<NEHistogramKernel>(); _histogram_kernel->configure(input, output, _local_hist.data(), _window_lut.data()); } diff --git a/src/runtime/NEON/functions/NEIm2Col.cpp b/src/runtime/NEON/functions/NEIm2Col.cpp index bc0c60112e..d6d72aa712 100644 --- a/src/runtime/NEON/functions/NEIm2Col.cpp +++ b/src/runtime/NEON/functions/NEIm2Col.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEIm2ColKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -41,7 +40,7 @@ void NEIm2Col::configure(const ITensor *input, ITensor *output, const Size2D &ke { _y_dim = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); - _kernel = arm_compute::support::cpp14::make_unique<NEIm2ColKernel>(); + _kernel = std::make_unique<NEIm2ColKernel>(); _kernel->configure(input, output, kernel_dims, conv_info, has_bias, dilation, num_groups); } diff --git a/src/runtime/NEON/functions/NEInstanceNormalizationLayer.cpp b/src/runtime/NEON/functions/NEInstanceNormalizationLayer.cpp index e3fb284796..5965b9722f 100644 --- a/src/runtime/NEON/functions/NEInstanceNormalizationLayer.cpp +++ b/src/runtime/NEON/functions/NEInstanceNormalizationLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/KernelDescriptors.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEInstanceNormalizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -46,7 +45,7 @@ void NEInstanceNormalizationLayer::configure(ITensor *input, ITensor *output, fl // Configure Kernels _is_nchw = data_layout == DataLayout::NCHW; - _normalization_kernel = arm_compute::support::cpp14::make_unique<NEInstanceNormalizationLayerKernel>(); + _normalization_kernel = std::make_unique<NEInstanceNormalizationLayerKernel>(); if(!_is_nchw) { diff --git a/src/runtime/NEON/functions/NEIntegralImage.cpp b/src/runtime/NEON/functions/NEIntegralImage.cpp index 63bcd53373..38f04247f6 100644 --- a/src/runtime/NEON/functions/NEIntegralImage.cpp +++ b/src/runtime/NEON/functions/NEIntegralImage.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/Types.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEIntegralImageKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -36,11 +35,11 @@ NEIntegralImage::~NEIntegralImage() = default; void NEIntegralImage::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NEIntegralImageKernel>(); + auto k = std::make_unique<NEIntegralImageKernel>(); k->configure(input, output); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(output, _kernel->border_size(), BorderMode::CONSTANT, PixelValue()); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp b/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp index 4a99968cc3..505ee0a962 100644 --- a/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp +++ b/src/runtime/NEON/functions/NEL2NormalizeLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEL2NormalizeLayerKernel.h" #include "src/core/NEON/kernels/NEReductionOperationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -50,7 +49,7 @@ void NEL2NormalizeLayer::configure(ITensor *input, ITensor *output, int axis, fl // Configure Kernels const uint32_t actual_axis = wrap_around(axis, max_input_tensor_dim); _reduce_func.configure(input, &_sumsq, actual_axis, ReductionOperation::SUM_SQUARE); - _normalize_kernel = arm_compute::support::cpp14::make_unique<NEL2NormalizeLayerKernel>(); + _normalize_kernel = std::make_unique<NEL2NormalizeLayerKernel>(); _normalize_kernel->configure(input, &_sumsq, output, axis, epsilon); // Allocate intermediate tensors diff --git a/src/runtime/NEON/functions/NELocallyConnectedLayer.cpp b/src/runtime/NEON/functions/NELocallyConnectedLayer.cpp index 131ac82ba8..c1164c3bee 100644 --- a/src/runtime/NEON/functions/NELocallyConnectedLayer.cpp +++ b/src/runtime/NEON/functions/NELocallyConnectedLayer.cpp @@ -30,7 +30,6 @@ #include "src/core/NEON/kernels/NEIm2ColKernel.h" #include "src/core/NEON/kernels/NELocallyConnectedMatrixMultiplyKernel.h" #include "src/core/NEON/kernels/NEWeightsReshapeKernel.h" -#include "support/MemorySupport.h" #include <cmath> #include <tuple> @@ -160,9 +159,9 @@ void NELocallyConnectedLayer::configure(const ITensor *input, const ITensor *wei // Configure kernels _input_im2col.configure(input, &_input_im2col_reshaped, Size2D(kernel_width, kernel_height), conv_info, _has_bias); - _weights_reshape_kernel = arm_compute::support::cpp14::make_unique<NEWeightsReshapeKernel>(); + _weights_reshape_kernel = std::make_unique<NEWeightsReshapeKernel>(); _weights_reshape_kernel->configure(weights, biases, &_weights_reshaped); - _mm_kernel = arm_compute::support::cpp14::make_unique<NELocallyConnectedMatrixMultiplyKernel>(); + _mm_kernel = std::make_unique<NELocallyConnectedMatrixMultiplyKernel>(); _mm_kernel->configure(&_input_im2col_reshaped, &_weights_reshaped, &_gemm_output); _output_col2im.configure(&_gemm_output, output, Size2D(conv_w, conv_h)); diff --git a/src/runtime/NEON/functions/NELogical.cpp b/src/runtime/NEON/functions/NELogical.cpp index 8e43d60bef..2c9ebd5f29 100644 --- a/src/runtime/NEON/functions/NELogical.cpp +++ b/src/runtime/NEON/functions/NELogical.cpp @@ -26,7 +26,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "arm_compute/runtime/Tensor.h" #include "src/core/NEON/kernels/NELogicalKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -40,7 +39,7 @@ struct NELogicalAnd::Impl : public LogicalArgs { }; NELogicalAnd::NELogicalAnd() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NELogicalAnd &NELogicalAnd::operator=(NELogicalAnd &&) = default; @@ -50,7 +49,7 @@ void NELogicalAnd::configure(const ITensor *input1, const ITensor *input2, ITens { ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - _impl->kernel = arm_compute::support::cpp14::make_unique<kernels::NELogicalKernel>(); + _impl->kernel = std::make_unique<kernels::NELogicalKernel>(); _impl->kernel->configure(input1->info(), input2->info(), output->info(), kernels::LogicalOperation::And); _impl->pack = ITensorPack(); @@ -73,7 +72,7 @@ struct NELogicalOr::Impl : public LogicalArgs { }; NELogicalOr::NELogicalOr() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NELogicalOr &NELogicalOr::operator=(NELogicalOr &&) = default; @@ -83,7 +82,7 @@ void NELogicalOr::configure(const ITensor *input1, const ITensor *input2, ITenso { ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - _impl->kernel = arm_compute::support::cpp14::make_unique<kernels::NELogicalKernel>(); + _impl->kernel = std::make_unique<kernels::NELogicalKernel>(); _impl->kernel->configure(input1->info(), input2->info(), output->info(), kernels::LogicalOperation::Or); _impl->pack = ITensorPack(); @@ -106,7 +105,7 @@ struct NELogicalNot::Impl : public LogicalArgs { }; NELogicalNot::NELogicalNot() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NELogicalNot &NELogicalNot::operator=(NELogicalNot &&) = default; @@ -116,7 +115,7 @@ void NELogicalNot::configure(const ITensor *input, ITensor *output) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - _impl->kernel = arm_compute::support::cpp14::make_unique<kernels::NELogicalKernel>(); + _impl->kernel = std::make_unique<kernels::NELogicalKernel>(); _impl->kernel->configure(input->info(), nullptr, output->info(), kernels::LogicalOperation::Not); _impl->pack = ITensorPack(); diff --git a/src/runtime/NEON/functions/NEMagnitude.cpp b/src/runtime/NEON/functions/NEMagnitude.cpp index 06ed8d46c9..34d9a7fb0b 100644 --- a/src/runtime/NEON/functions/NEMagnitude.cpp +++ b/src/runtime/NEON/functions/NEMagnitude.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Types.h" #include "src/core/NEON/kernels/NEMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,13 +36,13 @@ void NEMagnitude::configure(const ITensor *input1, const ITensor *input2, ITenso { if(mag_type == MagnitudeType::L1NORM) { - auto k = arm_compute::support::cpp14::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L1NORM, PhaseType::SIGNED>>(); + auto k = std::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L1NORM, PhaseType::SIGNED>>(); k->configure(input1, input2, output, nullptr); _kernel = std::move(k); } else { - auto k = arm_compute::support::cpp14::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::SIGNED>>(); + auto k = std::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::SIGNED>>(); k->configure(input1, input2, output, nullptr); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEMaxUnpoolingLayer.cpp b/src/runtime/NEON/functions/NEMaxUnpoolingLayer.cpp index e8c9d09d95..da6260b0c5 100644 --- a/src/runtime/NEON/functions/NEMaxUnpoolingLayer.cpp +++ b/src/runtime/NEON/functions/NEMaxUnpoolingLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEMaxUnpoolingLayerKernel.h" #include "src/core/NEON/kernels/NEMemsetKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -42,8 +41,8 @@ NEMaxUnpoolingLayer::NEMaxUnpoolingLayer() void NEMaxUnpoolingLayer::configure(ITensor *input, ITensor *indices, ITensor *output, const PoolingLayerInfo &pool_info) { const PixelValue zero_value(0.f); - _memset_kernel = arm_compute::support::cpp14::make_unique<NEMemsetKernel>(); - _unpooling_layer_kernel = arm_compute::support::cpp14::make_unique<NEMaxUnpoolingLayerKernel>(); + _memset_kernel = std::make_unique<NEMemsetKernel>(); + _unpooling_layer_kernel = std::make_unique<NEMaxUnpoolingLayerKernel>(); _memset_kernel->configure(output, zero_value); _unpooling_layer_kernel->configure(input, indices, output, pool_info); } diff --git a/src/runtime/NEON/functions/NEMeanStdDev.cpp b/src/runtime/NEON/functions/NEMeanStdDev.cpp index e073420114..6e2d7fc81d 100644 --- a/src/runtime/NEON/functions/NEMeanStdDev.cpp +++ b/src/runtime/NEON/functions/NEMeanStdDev.cpp @@ -26,7 +26,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEMeanStdDevKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -39,8 +38,8 @@ NEMeanStdDev::NEMeanStdDev() void NEMeanStdDev::configure(IImage *input, float *mean, float *stddev) { - _mean_stddev_kernel = arm_compute::support::cpp14::make_unique<NEMeanStdDevKernel>(); - _fill_border_kernel = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _mean_stddev_kernel = std::make_unique<NEMeanStdDevKernel>(); + _fill_border_kernel = std::make_unique<NEFillBorderKernel>(); _mean_stddev_kernel->configure(input, mean, &_global_sum, stddev, &_global_sum_squared); _fill_border_kernel->configure(input, _mean_stddev_kernel->border_size(), BorderMode::CONSTANT, PixelValue(static_cast<uint8_t>(0))); diff --git a/src/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.cpp b/src/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.cpp index d128c4456a..02de983b77 100644 --- a/src/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.cpp +++ b/src/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEMeanStdDevNormalizationLayer.h" #include "src/core/NEON/kernels/NEMeanStdDevNormalizationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -32,7 +31,7 @@ NEMeanStdDevNormalizationLayer::~NEMeanStdDevNormalizationLayer() = default; void NEMeanStdDevNormalizationLayer::configure(ITensor *input, ITensor *output, float epsilon) { - auto k = arm_compute::support::cpp14::make_unique<NEMeanStdDevNormalizationKernel>(); + auto k = std::make_unique<NEMeanStdDevNormalizationKernel>(); k->configure(input, output, epsilon); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEMedian3x3.cpp b/src/runtime/NEON/functions/NEMedian3x3.cpp index b7b7c2cb47..4d117783ed 100644 --- a/src/runtime/NEON/functions/NEMedian3x3.cpp +++ b/src/runtime/NEON/functions/NEMedian3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEMedian3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,11 +33,11 @@ namespace arm_compute { void NEMedian3x3::configure(ITensor *input, ITensor *output, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEMedian3x3Kernel>(); + auto k = std::make_unique<NEMedian3x3Kernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEMinMaxLocation.cpp b/src/runtime/NEON/functions/NEMinMaxLocation.cpp index 3c2219ca07..ffbc33bc2e 100644 --- a/src/runtime/NEON/functions/NEMinMaxLocation.cpp +++ b/src/runtime/NEON/functions/NEMinMaxLocation.cpp @@ -25,7 +25,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEMinMaxLocationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,10 +37,10 @@ NEMinMaxLocation::NEMinMaxLocation() void NEMinMaxLocation::configure(const IImage *input, void *min, void *max, ICoordinates2DArray *min_loc, ICoordinates2DArray *max_loc, uint32_t *min_count, uint32_t *max_count) { - _min_max = arm_compute::support::cpp14::make_unique<NEMinMaxKernel>(); + _min_max = std::make_unique<NEMinMaxKernel>(); _min_max->configure(input, min, max); - _min_max_loc = arm_compute::support::cpp14::make_unique<NEMinMaxLocationKernel>(); + _min_max_loc = std::make_unique<NEMinMaxLocationKernel>(); _min_max_loc->configure(input, min, max, min_loc, max_loc, min_count, max_count); } diff --git a/src/runtime/NEON/functions/NENonLinearFilter.cpp b/src/runtime/NEON/functions/NENonLinearFilter.cpp index 4d8fd00cbd..f3acabfa6d 100644 --- a/src/runtime/NEON/functions/NENonLinearFilter.cpp +++ b/src/runtime/NEON/functions/NENonLinearFilter.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NENonLinearFilterKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -36,11 +35,11 @@ void NENonLinearFilter::configure(ITensor *input, ITensor *output, NonLinearFilt BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NENonLinearFilterKernel>(); + auto k = std::make_unique<NENonLinearFilterKernel>(); k->configure(input, output, function, mask_size, pattern, mask, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NENonMaximaSuppression3x3.cpp b/src/runtime/NEON/functions/NENonMaximaSuppression3x3.cpp index b8f5c251b7..a34be71ea0 100644 --- a/src/runtime/NEON/functions/NENonMaximaSuppression3x3.cpp +++ b/src/runtime/NEON/functions/NENonMaximaSuppression3x3.cpp @@ -25,7 +25,6 @@ #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NENonMaximaSuppression3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -33,11 +32,11 @@ namespace arm_compute { void NENonMaximaSuppression3x3::configure(ITensor *input, ITensor *output, BorderMode border_mode) { - auto k = arm_compute::support::cpp14::make_unique<NENonMaximaSuppression3x3Kernel>(); + auto k = std::make_unique<NENonMaximaSuppression3x3Kernel>(); k->configure(input, output, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); if(border_mode != BorderMode::UNDEFINED) { b->configure(input, BorderSize(1), BorderMode::CONSTANT, static_cast<float>(0.f)); diff --git a/src/runtime/NEON/functions/NENormalizationLayer.cpp b/src/runtime/NEON/functions/NENormalizationLayer.cpp index dfc73b2a57..9dcb157c03 100644 --- a/src/runtime/NEON/functions/NENormalizationLayer.cpp +++ b/src/runtime/NEON/functions/NENormalizationLayer.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NENormalizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -52,7 +51,7 @@ void NENormalizationLayer::configure(const ITensor *input, ITensor *output, cons _memory_group.manage(&_input_squared); // Configure kernels - _norm_kernel = arm_compute::support::cpp14::make_unique<NENormalizationLayerKernel>(); + _norm_kernel = std::make_unique<NENormalizationLayerKernel>(); _norm_kernel->configure(input, &_input_squared, output, norm_info); _multiply_f.configure(input, input, &_input_squared, 1.0f, ConvertPolicy::SATURATE, RoundingPolicy::TO_ZERO); diff --git a/src/runtime/NEON/functions/NEOpticalFlow.cpp b/src/runtime/NEON/functions/NEOpticalFlow.cpp index 565346bfce..a868208aaf 100644 --- a/src/runtime/NEON/functions/NEOpticalFlow.cpp +++ b/src/runtime/NEON/functions/NEOpticalFlow.cpp @@ -34,7 +34,6 @@ #include "arm_compute/runtime/TensorAllocator.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NELKTrackerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -114,7 +113,7 @@ void NEOpticalFlow::configure(const Pyramid *old_pyramid, const Pyramid *new_pyr _func_scharr[i].configure(old_ith_input, &_scharr_gx[i], &_scharr_gy[i], border_mode, constant_border_value); // Init Lucas-Kanade kernel - _kernel_tracker[i] = arm_compute::support::cpp14::make_unique<NELKTrackerKernel>(); + _kernel_tracker[i] = std::make_unique<NELKTrackerKernel>(); _kernel_tracker[i]->configure(old_ith_input, new_ith_input, &_scharr_gx[i], &_scharr_gy[i], old_points, new_points_estimates, new_points, &_old_points_internal, &_new_points_internal, diff --git a/src/runtime/NEON/functions/NEPReluLayer.cpp b/src/runtime/NEON/functions/NEPReluLayer.cpp index 00a1a4257a..fe656c0be0 100644 --- a/src/runtime/NEON/functions/NEPReluLayer.cpp +++ b/src/runtime/NEON/functions/NEPReluLayer.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/ITensor.h" #include "src/core/NEON/kernels/NEElementwiseOperationKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -33,7 +32,7 @@ namespace experimental { void NEPRelu::configure(const ITensorInfo *input, const ITensorInfo *alpha, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEArithmeticOperationKernel>(); + auto k = std::make_unique<NEArithmeticOperationKernel>(); k->configure(ArithmeticOperation::PRELU, input, alpha, output); _kernel = std::move(k); } @@ -53,7 +52,7 @@ struct NEPReluLayer::Impl }; NEPReluLayer::NEPReluLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEPReluLayer::NEPReluLayer(NEPReluLayer &&) = default; @@ -65,7 +64,7 @@ void NEPReluLayer::configure(const ITensor *input, const ITensor *alpha, ITensor _impl->src_0 = input; _impl->src_1 = alpha; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEPRelu>(); + _impl->op = std::make_unique<experimental::NEPRelu>(); _impl->op->configure(input->info(), alpha->info(), output->info()); } diff --git a/src/runtime/NEON/functions/NEPadLayer.cpp b/src/runtime/NEON/functions/NEPadLayer.cpp index 92659f39a2..88a73b8b0d 100644 --- a/src/runtime/NEON/functions/NEPadLayer.cpp +++ b/src/runtime/NEON/functions/NEPadLayer.cpp @@ -30,7 +30,6 @@ #include "src/core/NEON/kernels/NECopyKernel.h" #include "src/core/NEON/kernels/NEPadLayerKernel.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -59,7 +58,7 @@ NEPadLayer::NEPadLayer() void NEPadLayer::configure_constant_mode(ITensor *input, ITensor *output, const PaddingList &padding, const PixelValue constant_value) { - _pad_kernel = arm_compute::support::cpp14::make_unique<NEPadLayerKernel>(); + _pad_kernel = std::make_unique<NEPadLayerKernel>(); _pad_kernel->configure(input, output, padding, constant_value, PaddingMode::CONSTANT); } @@ -201,7 +200,7 @@ void NEPadLayer::configure(ITensor *input, ITensor *output, const PaddingList &p else { // Copy the input to the whole output if no padding is applied - _copy_kernel = arm_compute::support::cpp14::make_unique<NECopyKernel>(); + _copy_kernel = std::make_unique<NECopyKernel>(); _copy_kernel->configure(input, output); } } diff --git a/src/runtime/NEON/functions/NEPermute.cpp b/src/runtime/NEON/functions/NEPermute.cpp index d2a115fdc8..cceb22f8c6 100644 --- a/src/runtime/NEON/functions/NEPermute.cpp +++ b/src/runtime/NEON/functions/NEPermute.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEPermute.h" #include "src/core/NEON/kernels/NEPermuteKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEPermute::configure(const ITensor *input, ITensor *output, const PermutationVector &perm) { - auto k = arm_compute::support::cpp14::make_unique<NEPermuteKernel>(); + auto k = std::make_unique<NEPermuteKernel>(); k->configure(input, output, perm); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEPhase.cpp b/src/runtime/NEON/functions/NEPhase.cpp index 3b6182a269..3b69a10e7f 100644 --- a/src/runtime/NEON/functions/NEPhase.cpp +++ b/src/runtime/NEON/functions/NEPhase.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEPhase.h" #include "src/core/NEON/kernels/NEMagnitudePhaseKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,13 +33,13 @@ void NEPhase::configure(const ITensor *input1, const ITensor *input2, ITensor *o { if(phase_type == PhaseType::UNSIGNED) { - auto k = arm_compute::support::cpp14::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::UNSIGNED>>(); + auto k = std::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::UNSIGNED>>(); k->configure(input1, input2, nullptr, output); _kernel = std::move(k); } else { - auto k = arm_compute::support::cpp14::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::SIGNED>>(); + auto k = std::make_unique<NEMagnitudePhaseKernel<MagnitudeType::L2NORM, PhaseType::SIGNED>>(); k->configure(input1, input2, nullptr, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEPixelWiseMultiplication.cpp b/src/runtime/NEON/functions/NEPixelWiseMultiplication.cpp index f7f4437554..179bcdaf3e 100644 --- a/src/runtime/NEON/functions/NEPixelWiseMultiplication.cpp +++ b/src/runtime/NEON/functions/NEPixelWiseMultiplication.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/ITensor.h" #include "src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void NEPixelWiseMultiplication::configure(ITensorInfo *input1, ITensorInfo *inpu const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(act_info); - auto k = arm_compute::support::cpp14::make_unique<NEPixelWiseMultiplicationKernel>(); + auto k = std::make_unique<NEPixelWiseMultiplicationKernel>(); k->configure(input1, input2, output, scale, overflow_policy, rounding_policy); _kernel = std::move(k); } @@ -51,7 +50,7 @@ Status NEPixelWiseMultiplication::validate(const ITensorInfo *input1, const ITen void NEComplexPixelWiseMultiplication::configure(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output, const ActivationLayerInfo &act_info) { ARM_COMPUTE_UNUSED(act_info); - auto k = arm_compute::support::cpp14::make_unique<NEComplexPixelWiseMultiplicationKernel>(); + auto k = std::make_unique<NEComplexPixelWiseMultiplicationKernel>(); k->configure(input1, input2, output); _kernel = std::move(k); } @@ -72,7 +71,7 @@ struct NEPixelWiseMultiplication::Impl }; NEPixelWiseMultiplication::NEPixelWiseMultiplication() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEPixelWiseMultiplication::NEPixelWiseMultiplication(NEPixelWiseMultiplication &&) = default; @@ -91,7 +90,7 @@ void NEPixelWiseMultiplication::configure(const ITensor *input1, const ITensor * _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEPixelWiseMultiplication>(); + _impl->op = std::make_unique<experimental::NEPixelWiseMultiplication>(); _impl->op->configure(input1->info(), input2->info(), output->info(), scale, overflow_policy, rounding_policy, act_info); } @@ -113,7 +112,7 @@ struct NEComplexPixelWiseMultiplication::Impl }; NEComplexPixelWiseMultiplication::NEComplexPixelWiseMultiplication() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEComplexPixelWiseMultiplication::NEComplexPixelWiseMultiplication(NEComplexPixelWiseMultiplication &&) = default; @@ -130,7 +129,7 @@ void NEComplexPixelWiseMultiplication::configure(ITensor *input1, ITensor *input _impl->src_0 = input1; _impl->src_1 = input2; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEComplexPixelWiseMultiplication>(); + _impl->op = std::make_unique<experimental::NEComplexPixelWiseMultiplication>(); _impl->op->configure(input1->info(), input2->info(), output->info(), act_info); } diff --git a/src/runtime/NEON/functions/NEPoolingLayer.cpp b/src/runtime/NEON/functions/NEPoolingLayer.cpp index 12ac8d6d7d..887f00de24 100644 --- a/src/runtime/NEON/functions/NEPoolingLayer.cpp +++ b/src/runtime/NEON/functions/NEPoolingLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEPoolingLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -47,7 +46,7 @@ void NEPoolingLayer::configure(ITensor *input, ITensor *output, const PoolingLay _data_layout = pool_info.data_layout == DataLayout::UNKNOWN ? input->info()->data_layout() : pool_info.data_layout; // Configure pooling kernel - _pooling_layer_kernel = arm_compute::support::cpp14::make_unique<NEPoolingLayerKernel>(); + _pooling_layer_kernel = std::make_unique<NEPoolingLayerKernel>(); _pooling_layer_kernel->configure(input, output, pool_info, indices); switch(_data_layout) @@ -61,7 +60,7 @@ void NEPoolingLayer::configure(ITensor *input, ITensor *output, const PoolingLay { zero_value = PixelValue(0, input->info()->data_type(), input->info()->quantization_info()); } - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); _border_handler->configure(input, _pooling_layer_kernel->border_size(), border_mode, zero_value); break; } diff --git a/src/runtime/NEON/functions/NEPriorBoxLayer.cpp b/src/runtime/NEON/functions/NEPriorBoxLayer.cpp index bfa06da04e..0c71706586 100644 --- a/src/runtime/NEON/functions/NEPriorBoxLayer.cpp +++ b/src/runtime/NEON/functions/NEPriorBoxLayer.cpp @@ -32,13 +32,11 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEPriorBoxLayerKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { void NEPriorBoxLayer::configure(const ITensor *input1, const ITensor *input2, ITensor *output, const PriorBoxLayerInfo &info) { - auto k = arm_compute::support::cpp14::make_unique<NEPriorBoxLayerKernel>(); + auto k = std::make_unique<NEPriorBoxLayerKernel>(); k->configure(input1, input2, output, info); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEQLSTMLayer.cpp b/src/runtime/NEON/functions/NEQLSTMLayer.cpp index 1013730235..85d62ac058 100644 --- a/src/runtime/NEON/functions/NEQLSTMLayer.cpp +++ b/src/runtime/NEON/functions/NEQLSTMLayer.cpp @@ -39,7 +39,6 @@ #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "src/core/NEON/kernels/NEQLSTMLayerNormalizationKernel.h" #include "src/core/helpers/WindowHelpers.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -75,7 +74,7 @@ void NEQLSTMLayer::configure_layer_norm(NEQLSTMLayer::LayerNormGate g, const ITe _memory_group.manage(&out); out.allocator()->init(*(in->info())); - get_layer_norm(g) = arm_compute::support::cpp14::make_unique<NEQLSTMLayerNormalizationKernel>(); + get_layer_norm(g) = std::make_unique<NEQLSTMLayerNormalizationKernel>(); get_layer_norm(g)->configure(in, &out, get_layer_norm_weight(g), get_layer_norm_bias(g)); } @@ -226,18 +225,18 @@ void NEQLSTMLayer::configure(const ITensor *input, _input_to_input_weights = lstm_params.input_to_input_weights(); _recurrent_to_input_weights = lstm_params.recurrent_to_input_weights(); - _input_to_input_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); - _recurrent_to_input_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _input_to_input_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _recurrent_to_input_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); _input_to_input_reduction->configure(_input_to_input_weights, &_input_to_input_eff_bias, GEMMLowpReductionKernelInfo(num_units, false, -qinput.offset, true)); _recurrent_to_input_reduction->configure(_recurrent_to_input_weights, &_recurrent_to_input_eff_bias, GEMMLowpReductionKernelInfo(num_units, false, -qoutput_state_in.offset, true)); } - _input_to_forget_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); - _recurrent_to_forget_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); - _input_to_cell_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); - _recurrent_to_cell_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); - _input_to_output_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); - _recurrent_to_output_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _input_to_forget_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _recurrent_to_forget_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _input_to_cell_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _recurrent_to_cell_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _input_to_output_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _recurrent_to_output_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); _recurrent_to_cell_reduction->configure(input_to_forget_weights, &_input_to_forget_eff_bias, GEMMLowpReductionKernelInfo(num_units, false, -qinput.offset, true)); _recurrent_to_forget_reduction->configure(recurrent_to_forget_weights, &_recurrent_to_forget_eff_bias, GEMMLowpReductionKernelInfo(num_units, false, -qoutput_state_in.offset, true)); @@ -247,7 +246,7 @@ void NEQLSTMLayer::configure(const ITensor *input, _recurrent_to_output_reduction->configure(recurrent_to_output_weights, &_recurrent_to_output_eff_bias, GEMMLowpReductionKernelInfo(num_units, false, -qoutput_state_in.offset, true)); if(_has_projection) { - _projection_reduction = arm_compute::support::cpp14::make_unique<NEGEMMLowpMatrixAReductionKernel>(); + _projection_reduction = std::make_unique<NEGEMMLowpMatrixAReductionKernel>(); _projection_reduction->configure(_projection_weights, &_projection_eff_bias, GEMMLowpReductionKernelInfo(output_size, false, lstm_params.hidden_state_zero(), true)); if(_projection_bias != nullptr) { diff --git a/src/runtime/NEON/functions/NEQuantizationLayer.cpp b/src/runtime/NEON/functions/NEQuantizationLayer.cpp index a20ffb8858..42eb12d05d 100644 --- a/src/runtime/NEON/functions/NEQuantizationLayer.cpp +++ b/src/runtime/NEON/functions/NEQuantizationLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEQuantizationLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -44,7 +43,7 @@ void NEQuantizationLayer::configure(const ITensor *input, ITensor *output) ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); // Configure quantize kernel - auto k = arm_compute::support::cpp14::make_unique<NEQuantizationLayerKernel>(); + auto k = std::make_unique<NEQuantizationLayerKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NERNNLayer.cpp b/src/runtime/NEON/functions/NERNNLayer.cpp index a8e10482a7..c16d09f60c 100644 --- a/src/runtime/NEON/functions/NERNNLayer.cpp +++ b/src/runtime/NEON/functions/NERNNLayer.cpp @@ -42,7 +42,6 @@ #include "src/core/NEON/kernels/NEGEMMMatrixAdditionKernel.h" #include "src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -114,7 +113,7 @@ void NERNNLayer::configure(const ITensor *input, const ITensor *weights, const I _activation.configure(&_add_output, hidden_state, info); _add_output.allocator()->allocate(); - _copy_kernel = arm_compute::support::cpp14::make_unique<NECopyKernel>(); + _copy_kernel = std::make_unique<NECopyKernel>(); _copy_kernel->configure(hidden_state, output); } diff --git a/src/runtime/NEON/functions/NEROIAlignLayer.cpp b/src/runtime/NEON/functions/NEROIAlignLayer.cpp index a046140551..a946358e18 100644 --- a/src/runtime/NEON/functions/NEROIAlignLayer.cpp +++ b/src/runtime/NEON/functions/NEROIAlignLayer.cpp @@ -25,7 +25,6 @@ #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEROIAlignLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -39,7 +38,7 @@ Status NEROIAlignLayer::validate(const ITensorInfo *input, const ITensorInfo *ro void NEROIAlignLayer::configure(const ITensor *input, const ITensor *rois, ITensor *output, const ROIPoolingLayerInfo &pool_info) { // Configure ROI pooling kernel - auto k = arm_compute::support::cpp14::make_unique<NEROIAlignLayerKernel>(); + auto k = std::make_unique<NEROIAlignLayerKernel>(); k->configure(input, rois, output, pool_info); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEROIPoolingLayer.cpp b/src/runtime/NEON/functions/NEROIPoolingLayer.cpp index 8bcf152881..7ca6ecc737 100644 --- a/src/runtime/NEON/functions/NEROIPoolingLayer.cpp +++ b/src/runtime/NEON/functions/NEROIPoolingLayer.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEROIPoolingLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -39,7 +38,7 @@ NEROIPoolingLayer::NEROIPoolingLayer() void NEROIPoolingLayer::configure(const ITensor *input, const ITensor *rois, ITensor *output, const ROIPoolingLayerInfo &pool_info) { - _roi_kernel = arm_compute::support::cpp14::make_unique<NEROIPoolingLayerKernel>(); + _roi_kernel = std::make_unique<NEROIPoolingLayerKernel>(); _roi_kernel->configure(input, rois, output, pool_info); } diff --git a/src/runtime/NEON/functions/NERange.cpp b/src/runtime/NEON/functions/NERange.cpp index ba166b2d58..56ef2bf657 100644 --- a/src/runtime/NEON/functions/NERange.cpp +++ b/src/runtime/NEON/functions/NERange.cpp @@ -25,7 +25,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NERangeKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -38,7 +37,7 @@ NERange::NERange() void NERange::configure(ITensor *output, const float start, const float end, const float step) { - _kernel = arm_compute::support::cpp14::make_unique<NERangeKernel>(); + _kernel = std::make_unique<NERangeKernel>(); _kernel->configure(output, start, end, step); } diff --git a/src/runtime/NEON/functions/NEReductionOperation.cpp b/src/runtime/NEON/functions/NEReductionOperation.cpp index 463b65ec28..5d6f520a52 100644 --- a/src/runtime/NEON/functions/NEReductionOperation.cpp +++ b/src/runtime/NEON/functions/NEReductionOperation.cpp @@ -28,7 +28,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEReductionOperationKernel.h" #include "src/core/helpers/AutoConfiguration.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -129,7 +128,7 @@ void NEReductionOperation::configure(ITensor *input, ITensor *output, unsigned i ARM_COMPUTE_ERROR_THROW_ON(NEReductionOperation::validate(input->info(), output->info(), axis, op, keep_dims)); // Configure reduction kernel - _reduction_kernel = arm_compute::support::cpp14::make_unique<NEReductionOperationKernel>(); + _reduction_kernel = std::make_unique<NEReductionOperationKernel>(); _reduction_kernel->configure(input, output_internal, axis, op); _window_split = reduction_window_split_dimension(axis); _reduction_axis = axis; diff --git a/src/runtime/NEON/functions/NERemap.cpp b/src/runtime/NEON/functions/NERemap.cpp index 9276d49cf5..f2f57aa599 100644 --- a/src/runtime/NEON/functions/NERemap.cpp +++ b/src/runtime/NEON/functions/NERemap.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/TensorAllocator.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NERemapKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -45,11 +44,11 @@ void NERemap::configure(ITensor *input, const ITensor *map_x, const ITensor *map ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(map_y, 1, DataType::F32); ARM_COMPUTE_ERROR_ON_MSG(policy == InterpolationPolicy::AREA, "Area interpolation is not supported"); - auto k = arm_compute::support::cpp14::make_unique<NERemapKernel>(); + auto k = std::make_unique<NERemapKernel>(); k->configure(input, map_x, map_y, output, policy); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEReorgLayer.cpp b/src/runtime/NEON/functions/NEReorgLayer.cpp index 77ec7fbfb1..23ca3a4eea 100644 --- a/src/runtime/NEON/functions/NEReorgLayer.cpp +++ b/src/runtime/NEON/functions/NEReorgLayer.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEReorgLayer.h" #include "src/core/NEON/kernels/NEReorgLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEReorgLayer::configure(const ITensor *input, ITensor *output, int32_t stride) { - auto k = arm_compute::support::cpp14::make_unique<NEReorgLayerKernel>(); + auto k = std::make_unique<NEReorgLayerKernel>(); k->configure(input, output, stride); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEReshapeLayer.cpp b/src/runtime/NEON/functions/NEReshapeLayer.cpp index 915d5d408f..9ad6a35cc3 100644 --- a/src/runtime/NEON/functions/NEReshapeLayer.cpp +++ b/src/runtime/NEON/functions/NEReshapeLayer.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "arm_compute/runtime/Types.h" #include "src/core/NEON/kernels/NEReshapeLayerKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -39,7 +38,7 @@ NEReshape::~NEReshape() = default; void NEReshape::configure(const ITensorInfo *input, ITensorInfo *output) { - auto k = arm_compute::support::cpp14::make_unique<NEReshapeLayerKernel>(); + auto k = std::make_unique<NEReshapeLayerKernel>(); k->configure(input, output); _kernel = std::move(k); } @@ -58,7 +57,7 @@ struct NEReshapeLayer::Impl }; NEReshapeLayer::NEReshapeLayer() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } @@ -72,7 +71,7 @@ void NEReshapeLayer::configure(const ITensor *input, ITensor *output) { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEReshape>(); + _impl->op = std::make_unique<experimental::NEReshape>(); _impl->op->configure(input->info(), output->info()); } diff --git a/src/runtime/NEON/functions/NEReverse.cpp b/src/runtime/NEON/functions/NEReverse.cpp index 3ed0688386..36127ef83c 100644 --- a/src/runtime/NEON/functions/NEReverse.cpp +++ b/src/runtime/NEON/functions/NEReverse.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEReverse.h" #include "src/core/NEON/kernels/NEReverseKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEReverse::configure(const ITensor *input, ITensor *output, const ITensor *axis) { - auto k = arm_compute::support::cpp14::make_unique<NEReverseKernel>(); + auto k = std::make_unique<NEReverseKernel>(); k->configure(input, output, axis); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEScale.cpp b/src/runtime/NEON/functions/NEScale.cpp index 0290fe5a01..9d6e2ca754 100644 --- a/src/runtime/NEON/functions/NEScale.cpp +++ b/src/runtime/NEON/functions/NEScale.cpp @@ -36,7 +36,6 @@ #include "src/core/utils/ScaleUtils.h" -#include "support/MemorySupport.h" #include "support/Rounding.h" #include <cmath> @@ -125,7 +124,7 @@ void NEScale::configure(ITensor *input, ITensor *output, const ScaleKernelInfo & // Area interpolation behaves as Nearest Neighbour in case of up-sampling const auto policy_to_use = (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) ? InterpolationPolicy::NEAREST_NEIGHBOR : info.interpolation_policy; - auto scale_kernel = arm_compute::support::cpp14::make_unique<NEScaleKernel>(); + auto scale_kernel = std::make_unique<NEScaleKernel>(); switch(policy_to_use) { case InterpolationPolicy::NEAREST_NEIGHBOR: diff --git a/src/runtime/NEON/functions/NEScharr3x3.cpp b/src/runtime/NEON/functions/NEScharr3x3.cpp index cea0eefdb0..414e9470ea 100644 --- a/src/runtime/NEON/functions/NEScharr3x3.cpp +++ b/src/runtime/NEON/functions/NEScharr3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEScharr3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,11 +33,11 @@ using namespace arm_compute; void NEScharr3x3::configure(ITensor *input, ITensor *output_x, ITensor *output_y, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NEScharr3x3Kernel>(); + auto k = std::make_unique<NEScharr3x3Kernel>(); k->configure(input, output_x, output_y, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NESelect.cpp b/src/runtime/NEON/functions/NESelect.cpp index 0d1f490767..f8ba9f03ed 100644 --- a/src/runtime/NEON/functions/NESelect.cpp +++ b/src/runtime/NEON/functions/NESelect.cpp @@ -25,13 +25,12 @@ #include "arm_compute/core/Types.h" #include "src/core/NEON/kernels/NESelectKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NESelect::configure(const ITensor *c, const ITensor *x, const ITensor *y, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NESelectKernel>(); + auto k = std::make_unique<NESelectKernel>(); k->configure(c, x, y, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NESlice.cpp b/src/runtime/NEON/functions/NESlice.cpp index dd56eaba8b..9b08bca38a 100644 --- a/src/runtime/NEON/functions/NESlice.cpp +++ b/src/runtime/NEON/functions/NESlice.cpp @@ -29,8 +29,6 @@ #include "arm_compute/core/utils/helpers/tensor_transform.h" #include "src/core/NEON/kernels/NEStridedSliceKernel.h" -#include "support/MemorySupport.h" - namespace arm_compute { namespace experimental @@ -42,7 +40,7 @@ void NESlice::configure(const ITensorInfo *input, ITensorInfo *output, const Coo // Get absolute end coordinates const int32_t slice_end_mask = arm_compute::helpers::tensor_transform::construct_slice_end_mask(ends); - auto k = arm_compute::support::cpp14::make_unique<NEStridedSliceKernel>(); + auto k = std::make_unique<NEStridedSliceKernel>(); k->configure(input, output, starts, ends, BiStrides(), 0, slice_end_mask, 0); _kernel = std::move(k); } @@ -72,7 +70,7 @@ struct NESlice::Impl }; NESlice::NESlice() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NESlice::NESlice(NESlice &&) = default; @@ -88,7 +86,7 @@ void NESlice::configure(const ITensor *input, ITensor *output, const Coordinates { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NESlice>(); + _impl->op = std::make_unique<experimental::NESlice>(); _impl->op->configure(input->info(), output->info(), starts, ends); } diff --git a/src/runtime/NEON/functions/NESobel3x3.cpp b/src/runtime/NEON/functions/NESobel3x3.cpp index 38d2dc227e..1a57bc3fc6 100644 --- a/src/runtime/NEON/functions/NESobel3x3.cpp +++ b/src/runtime/NEON/functions/NESobel3x3.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/PixelValue.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NESobel3x3Kernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -34,11 +33,11 @@ namespace arm_compute { void NESobel3x3::configure(ITensor *input, ITensor *output_x, ITensor *output_y, BorderMode border_mode, uint8_t constant_border_value) { - auto k = arm_compute::support::cpp14::make_unique<NESobel3x3Kernel>(); + auto k = std::make_unique<NESobel3x3Kernel>(); k->configure(input, output_x, output_y, border_mode == BorderMode::UNDEFINED); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, PixelValue(constant_border_value)); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NESobel5x5.cpp b/src/runtime/NEON/functions/NESobel5x5.cpp index e631fb3ed7..e587981fa9 100644 --- a/src/runtime/NEON/functions/NESobel5x5.cpp +++ b/src/runtime/NEON/functions/NESobel5x5.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/TensorAllocator.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NESobel5x5Kernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -51,9 +50,9 @@ void NESobel5x5::configure(ITensor *input, ITensor *output_x, ITensor *output_y, TensorInfo tensor_info(input->info()->tensor_shape(), Format::S16); - _sobel_hor = arm_compute::support::cpp14::make_unique<NESobel5x5HorKernel>(); - _sobel_vert = arm_compute::support::cpp14::make_unique<NESobel5x5VertKernel>(); - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _sobel_hor = std::make_unique<NESobel5x5HorKernel>(); + _sobel_vert = std::make_unique<NESobel5x5VertKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); if(run_sobel_x && run_sobel_y) { diff --git a/src/runtime/NEON/functions/NESobel7x7.cpp b/src/runtime/NEON/functions/NESobel7x7.cpp index bc5f87c1ec..7b1a975951 100644 --- a/src/runtime/NEON/functions/NESobel7x7.cpp +++ b/src/runtime/NEON/functions/NESobel7x7.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/TensorAllocator.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NESobel7x7Kernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -50,9 +49,9 @@ void NESobel7x7::configure(ITensor *input, ITensor *output_x, ITensor *output_y, const bool run_sobel_y = output_y != nullptr; TensorInfo tensor_info(input->info()->tensor_shape(), Format::S32); - _sobel_hor = arm_compute::support::cpp14::make_unique<NESobel7x7HorKernel>(); - _sobel_vert = arm_compute::support::cpp14::make_unique<NESobel7x7VertKernel>(); - _border_handler = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _sobel_hor = std::make_unique<NESobel7x7HorKernel>(); + _sobel_vert = std::make_unique<NESobel7x7VertKernel>(); + _border_handler = std::make_unique<NEFillBorderKernel>(); if(run_sobel_x && run_sobel_y) { diff --git a/src/runtime/NEON/functions/NESoftmaxLayer.cpp b/src/runtime/NEON/functions/NESoftmaxLayer.cpp index e79ab0ee2d..6be34ad1a4 100644 --- a/src/runtime/NEON/functions/NESoftmaxLayer.cpp +++ b/src/runtime/NEON/functions/NESoftmaxLayer.cpp @@ -30,7 +30,6 @@ #include "src/core/NEON/kernels/NESoftmaxLayerKernel.h" #include "src/core/NEON/kernels/NESoftmaxLayerKernel.h" #include "src/core/helpers/SoftmaxHelpers.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -83,8 +82,8 @@ void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, f _memory_group.manage(&_tmp); // Configure kernels - _max_kernel = arm_compute::support::cpp14::make_unique<NELogits1DMaxKernel>(); - _softmax_kernel = arm_compute::support::cpp14::make_unique<NELogits1DSoftmaxKernel<IS_LOG>>(); + _max_kernel = std::make_unique<NELogits1DMaxKernel>(); + _softmax_kernel = std::make_unique<NELogits1DSoftmaxKernel<IS_LOG>>(); _max_kernel->configure(tmp_input, &_max); if(_needs_permute) { @@ -104,7 +103,7 @@ void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, f else { // Softmax 2D case - _fill_border_kernel = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + _fill_border_kernel = std::make_unique<NEFillBorderKernel>(); _fill_border_kernel->configure(tmp_input, _max_kernel->border_size(), BorderMode::REPLICATE); _softmax_kernel->configure(tmp_input, &_max, output, beta, &_tmp); } diff --git a/src/runtime/NEON/functions/NESpaceToBatchLayer.cpp b/src/runtime/NEON/functions/NESpaceToBatchLayer.cpp index 516e8d604c..10b384157d 100644 --- a/src/runtime/NEON/functions/NESpaceToBatchLayer.cpp +++ b/src/runtime/NEON/functions/NESpaceToBatchLayer.cpp @@ -31,7 +31,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEMemsetKernel.h" #include "src/core/NEON/kernels/NESpaceToBatchLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -49,10 +48,10 @@ void NESpaceToBatchLayer::configure(const ITensor *input, const ITensor *block_s if(input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size()) { _has_padding = true; - _memset_kernel = arm_compute::support::cpp14::make_unique<NEMemsetKernel>(); + _memset_kernel = std::make_unique<NEMemsetKernel>(); _memset_kernel->configure(output, PixelValue(0, input->info()->data_type(), input->info()->quantization_info())); } - _space_to_batch_kernel = arm_compute::support::cpp14::make_unique<NESpaceToBatchLayerKernel>(); + _space_to_batch_kernel = std::make_unique<NESpaceToBatchLayerKernel>(); _space_to_batch_kernel->configure(input, block_shape, paddings, output); } @@ -63,10 +62,10 @@ void NESpaceToBatchLayer::configure(const ITensor *input, const int block_shape_ if(input->info()->tensor_shape().total_size() != output->info()->tensor_shape().total_size()) { _has_padding = true; - _memset_kernel = arm_compute::support::cpp14::make_unique<NEMemsetKernel>(); + _memset_kernel = std::make_unique<NEMemsetKernel>(); _memset_kernel->configure(output, PixelValue(0, input->info()->data_type(), input->info()->quantization_info())); } - _space_to_batch_kernel = arm_compute::support::cpp14::make_unique<NESpaceToBatchLayerKernel>(); + _space_to_batch_kernel = std::make_unique<NESpaceToBatchLayerKernel>(); _space_to_batch_kernel->configure(input, block_shape_x, block_shape_y, padding_left, padding_right, output); } diff --git a/src/runtime/NEON/functions/NESpaceToDepthLayer.cpp b/src/runtime/NEON/functions/NESpaceToDepthLayer.cpp index a834600199..1e3776c448 100644 --- a/src/runtime/NEON/functions/NESpaceToDepthLayer.cpp +++ b/src/runtime/NEON/functions/NESpaceToDepthLayer.cpp @@ -30,7 +30,6 @@ #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NESpaceToDepthLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -44,7 +43,7 @@ NESpaceToDepthLayer::NESpaceToDepthLayer() void NESpaceToDepthLayer::configure(const ITensor *input, ITensor *output, int32_t block_shape) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - _space_to_depth_kernel = arm_compute::support::cpp14::make_unique<NESpaceToDepthLayerKernel>(); + _space_to_depth_kernel = std::make_unique<NESpaceToDepthLayerKernel>(); _space_to_depth_kernel->configure(input, output, block_shape); } diff --git a/src/runtime/NEON/functions/NEStackLayer.cpp b/src/runtime/NEON/functions/NEStackLayer.cpp index e38ff6bee7..af5c80d036 100644 --- a/src/runtime/NEON/functions/NEStackLayer.cpp +++ b/src/runtime/NEON/functions/NEStackLayer.cpp @@ -31,7 +31,6 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include "src/core/NEON/kernels/NEStackLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -54,7 +53,7 @@ void NEStackLayer::configure(const std::vector<ITensor *> &input, int axis, ITen for(unsigned int i = 0; i < _num_inputs; i++) { - _stack_kernels[i] = arm_compute::support::cpp14::make_unique<NEStackLayerKernel>(); + _stack_kernels[i] = std::make_unique<NEStackLayerKernel>(); _stack_kernels[i]->configure(input[i], axis_u, i, _num_inputs, output); } } diff --git a/src/runtime/NEON/functions/NEStridedSlice.cpp b/src/runtime/NEON/functions/NEStridedSlice.cpp index 308b856ec6..fffb38c3ca 100644 --- a/src/runtime/NEON/functions/NEStridedSlice.cpp +++ b/src/runtime/NEON/functions/NEStridedSlice.cpp @@ -26,7 +26,6 @@ #include "arm_compute/core/ITensor.h" #include "arm_compute/core/Types.h" #include "src/core/NEON/kernels/NEStridedSliceKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -36,7 +35,7 @@ void NEStridedSlice::configure(const ITensorInfo *input, ITensorInfo *output, const Coordinates &starts, const Coordinates &ends, const BiStrides &strides, int32_t begin_mask, int32_t end_mask, int32_t shrink_axis_mask) { - auto k = arm_compute::support::cpp14::make_unique<NEStridedSliceKernel>(); + auto k = std::make_unique<NEStridedSliceKernel>(); k->configure(input, output, starts, ends, strides, begin_mask, end_mask, shrink_axis_mask); _kernel = std::move(k); } @@ -57,7 +56,7 @@ struct NEStridedSlice::Impl }; NEStridedSlice::NEStridedSlice() - : _impl(support::cpp14::make_unique<Impl>()) + : _impl(std::make_unique<Impl>()) { } NEStridedSlice::NEStridedSlice(NEStridedSlice &&) = default; @@ -70,7 +69,7 @@ void NEStridedSlice::configure(const ITensor *input, ITensor *output, { _impl->src = input; _impl->dst = output; - _impl->op = arm_compute::support::cpp14::make_unique<experimental::NEStridedSlice>(); + _impl->op = std::make_unique<experimental::NEStridedSlice>(); _impl->op->configure(input->info(), output->info(), starts, ends, strides, begin_mask, end_mask, shrink_axis_mask); } diff --git a/src/runtime/NEON/functions/NETableLookup.cpp b/src/runtime/NEON/functions/NETableLookup.cpp index 9295bf0ece..fde3908c81 100644 --- a/src/runtime/NEON/functions/NETableLookup.cpp +++ b/src/runtime/NEON/functions/NETableLookup.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NETableLookup.h" #include "src/core/NEON/kernels/NETableLookupKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ using namespace arm_compute; void NETableLookup::configure(const ITensor *input, const ILut *lut, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NETableLookupKernel>(); + auto k = std::make_unique<NETableLookupKernel>(); k->configure(input, lut, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEThreshold.cpp b/src/runtime/NEON/functions/NEThreshold.cpp index 2f1e3047b5..4d382d6fab 100644 --- a/src/runtime/NEON/functions/NEThreshold.cpp +++ b/src/runtime/NEON/functions/NEThreshold.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEThreshold.h" #include "src/core/NEON/kernels/NEThresholdKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -37,7 +36,7 @@ void NEThreshold::configure(const ITensor *input, ITensor *output, uint8_t thres void NEThreshold::configure(const ITensor *input, ITensor *output, const ThresholdKernelInfo &info) { - auto k = arm_compute::support::cpp14::make_unique<NEThresholdKernel>(); + auto k = std::make_unique<NEThresholdKernel>(); k->configure(input, output, info); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NETile.cpp b/src/runtime/NEON/functions/NETile.cpp index 6a1e20ddf8..088816eb95 100644 --- a/src/runtime/NEON/functions/NETile.cpp +++ b/src/runtime/NEON/functions/NETile.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NETile.h" #include "src/core/NEON/kernels/NETileKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NETile::configure(const ITensor *input, ITensor *output, const Multiples &multiples) { - auto k = arm_compute::support::cpp14::make_unique<NETileKernel>(); + auto k = std::make_unique<NETileKernel>(); k->configure(input, output, multiples); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NETranspose.cpp b/src/runtime/NEON/functions/NETranspose.cpp index 5af417f4ed..aaa52e36b9 100644 --- a/src/runtime/NEON/functions/NETranspose.cpp +++ b/src/runtime/NEON/functions/NETranspose.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NETranspose.h" #include "src/core/NEON/kernels/NETransposeKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -32,7 +31,7 @@ namespace arm_compute { void NETranspose::configure(const ITensor *input, ITensor *output) { - auto k = arm_compute::support::cpp14::make_unique<NETransposeKernel>(); + auto k = std::make_unique<NETransposeKernel>(); k->configure(input, output); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/NEUpsampleLayer.cpp b/src/runtime/NEON/functions/NEUpsampleLayer.cpp index aae58387e2..1a08494c63 100644 --- a/src/runtime/NEON/functions/NEUpsampleLayer.cpp +++ b/src/runtime/NEON/functions/NEUpsampleLayer.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/NEON/functions/NEUpsampleLayer.h" #include "src/core/NEON/kernels/NEUpsampleLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -44,7 +43,7 @@ Status NEUpsampleLayer::validate(const ITensorInfo *input, const ITensorInfo *ou void NEUpsampleLayer::configure(const ITensor *input, ITensor *output, const Size2D &info, const InterpolationPolicy &policy) { _data_layout = input->info()->data_layout(); - _kernel = arm_compute::support::cpp14::make_unique<NEUpsampleLayerKernel>(); + _kernel = std::make_unique<NEUpsampleLayerKernel>(); _kernel->configure(input, output, info, policy); } diff --git a/src/runtime/NEON/functions/NEWarpAffine.cpp b/src/runtime/NEON/functions/NEWarpAffine.cpp index b5dbfe0d5c..1e8907b895 100644 --- a/src/runtime/NEON/functions/NEWarpAffine.cpp +++ b/src/runtime/NEON/functions/NEWarpAffine.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEWarpKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -42,14 +41,14 @@ void NEWarpAffine::configure(ITensor *input, ITensor *output, const std::array<f { case InterpolationPolicy::NEAREST_NEIGHBOR: { - auto k = arm_compute::support::cpp14::make_unique<NEWarpAffineKernel<InterpolationPolicy::NEAREST_NEIGHBOR>>(); + auto k = std::make_unique<NEWarpAffineKernel<InterpolationPolicy::NEAREST_NEIGHBOR>>(); k->configure(input, output, matrix, border_mode, constant_border_value); _kernel = std::move(k); break; } case InterpolationPolicy::BILINEAR: { - auto k = arm_compute::support::cpp14::make_unique<NEWarpAffineKernel<InterpolationPolicy::BILINEAR>>(); + auto k = std::make_unique<NEWarpAffineKernel<InterpolationPolicy::BILINEAR>>(); k->configure(input, output, matrix, border_mode, constant_border_value); _kernel = std::move(k); break; @@ -59,7 +58,7 @@ void NEWarpAffine::configure(ITensor *input, ITensor *output, const std::array<f ARM_COMPUTE_ERROR("Interpolation type not supported"); } - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, constant_border_value); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEWarpPerspective.cpp b/src/runtime/NEON/functions/NEWarpPerspective.cpp index 8d42121005..d546da89b8 100644 --- a/src/runtime/NEON/functions/NEWarpPerspective.cpp +++ b/src/runtime/NEON/functions/NEWarpPerspective.cpp @@ -27,7 +27,6 @@ #include "arm_compute/core/Validate.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" #include "src/core/NEON/kernels/NEWarpKernel.h" -#include "support/MemorySupport.h" #include <utility> @@ -42,14 +41,14 @@ void NEWarpPerspective::configure(ITensor *input, ITensor *output, const std::ar { case InterpolationPolicy::NEAREST_NEIGHBOR: { - auto k = arm_compute::support::cpp14::make_unique<NEWarpPerspectiveKernel<InterpolationPolicy::NEAREST_NEIGHBOR>>(); + auto k = std::make_unique<NEWarpPerspectiveKernel<InterpolationPolicy::NEAREST_NEIGHBOR>>(); k->configure(input, output, matrix, border_mode, constant_border_value); _kernel = std::move(k); break; } case InterpolationPolicy::BILINEAR: { - auto k = arm_compute::support::cpp14::make_unique<NEWarpPerspectiveKernel<InterpolationPolicy::BILINEAR>>(); + auto k = std::make_unique<NEWarpPerspectiveKernel<InterpolationPolicy::BILINEAR>>(); k->configure(input, output, matrix, border_mode, constant_border_value); _kernel = std::move(k); break; @@ -59,7 +58,7 @@ void NEWarpPerspective::configure(ITensor *input, ITensor *output, const std::ar ARM_COMPUTE_ERROR("Interpolation type not supported"); } - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(input, _kernel->border_size(), border_mode, constant_border_value); _border_handler = std::move(b); } diff --git a/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp b/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp index 1cb2458e13..265df9246f 100644 --- a/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp @@ -35,7 +35,6 @@ #include "src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h" -#include "support/MemorySupport.h" #include "src/core/NEON/kernels/convolution/common/utils.hpp" #include "src/core/NEON/kernels/convolution/winograd/winograd.hpp" @@ -351,18 +350,18 @@ void NEWinogradConvolutionLayer::configure(const ITensor *input, const ITensor * if(input->info()->dimension(width_idx) > 4 && input->info()->dimension(height_idx) > 4) { using config = NEWinogradLayerConfiguration<float, float, 4, 4, 3, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else { using config = NEWinogradLayerConfiguration<float, float, 2, 2, 3, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } @@ -370,63 +369,63 @@ void NEWinogradConvolutionLayer::configure(const ITensor *input, const ITensor * else if(kernel_size == Size2D(5, 5)) { using config = NEWinogradLayerConfiguration<float, float, 2, 2, 5, 5>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(1, 3)) { using config = NEWinogradLayerConfiguration<float, float, 6, 1, 3, 1>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(3, 1)) { using config = NEWinogradLayerConfiguration<float, float, 1, 6, 1, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(1, 5)) { using config = NEWinogradLayerConfiguration<float, float, 4, 1, 5, 1>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(5, 1)) { using config = NEWinogradLayerConfiguration<float, float, 1, 4, 1, 5>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(1, 7)) { using config = NEWinogradLayerConfiguration<float, float, 2, 1, 7, 1>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(7, 1)) { using config = NEWinogradLayerConfiguration<float, float, 1, 2, 1, 7>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } @@ -441,9 +440,9 @@ void NEWinogradConvolutionLayer::configure(const ITensor *input, const ITensor * if(kernel_size == Size2D(3, 3)) { using config = NEWinogradLayerConfiguration<__fp16, __fp16, 4, 4, 3, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } diff --git a/src/runtime/NEON/functions/NEYOLOLayer.cpp b/src/runtime/NEON/functions/NEYOLOLayer.cpp index 5cad53bffd..515b177060 100644 --- a/src/runtime/NEON/functions/NEYOLOLayer.cpp +++ b/src/runtime/NEON/functions/NEYOLOLayer.cpp @@ -24,13 +24,12 @@ #include "arm_compute/runtime/NEON/functions/NEYOLOLayer.h" #include "src/core/NEON/kernels/NEYOLOLayerKernel.h" -#include "support/MemorySupport.h" namespace arm_compute { void NEYOLOLayer::configure(ITensor *input, ITensor *output, const ActivationLayerInfo &act_info, int32_t num_classes) { - auto k = arm_compute::support::cpp14::make_unique<NEYOLOLayerKernel>(); + auto k = std::make_unique<NEYOLOLayerKernel>(); k->configure(input, output, act_info, num_classes); _kernel = std::move(k); } diff --git a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp index 11e89cb23b..101df98b7d 100644 --- a/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp +++ b/src/runtime/NEON/functions/assembly/NEDepthwiseConvolutionAssemblyDispatch.cpp @@ -37,8 +37,6 @@ #include "arm_compute/runtime/NEON/NEScheduler.h" -#include "support/MemorySupport.h" - #include <set> namespace arm_compute @@ -59,10 +57,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_qasymm8_convolver(int kern switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 3, 3, 1, 1>>( + return std::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 3, 3, 1, 1>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 3, 3, 2, 2>>( + return std::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 3, 3, 2, 2>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -73,10 +71,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_qasymm8_convolver(int kern switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 5, 5, 1, 1>>( + return std::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 5, 5, 1, 1>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 5, 5, 2, 2>>( + return std::make_unique<depthwise::QAsymm8DilatedDepthwiseConvolution<2, 2, 5, 5, 2, 2>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -101,10 +99,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_qsymm8_perchannel_convolve switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 3, 3, 1, 1>>( + return std::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 3, 3, 1, 1>>( n_batches, in_rows, in_cols, n_channels, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 3, 3, 2, 2>>( + return std::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 3, 3, 2, 2>>( n_batches, in_rows, in_cols, n_channels, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -115,10 +113,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_qsymm8_perchannel_convolve switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 5, 5, 1, 1>>( + return std::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 5, 5, 1, 1>>( n_batches, in_rows, in_cols, n_channels, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 5, 5, 2, 2>>( + return std::make_unique<depthwise::QSymm8HybridPerChannelDepthwiseConvolution<2, 2, 5, 5, 2, 2>>( n_batches, in_rows, in_cols, n_channels, activation, wqinfo, iqinfo, oqinfo, rescale_params, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -142,10 +140,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_fp16_convolver(int kernel_ switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 3, 3, 1, 1, float16_t, float16_t, float16_t>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 3, 3, 1, 1, float16_t, float16_t, float16_t>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 3, 3, 2, 2, float16_t, float16_t, float16_t>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 3, 3, 2, 2, float16_t, float16_t, float16_t>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -156,10 +154,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_fp16_convolver(int kernel_ switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 5, 5, 1, 1, float16_t, float16_t, float16_t>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 5, 5, 1, 1, float16_t, float16_t, float16_t>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 5, 5, 2, 2, float16_t, float16_t, float16_t>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 5, 5, 2, 2, float16_t, float16_t, float16_t>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -183,10 +181,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_fp32_convolver(int kernel_ switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<4, 4, 3, 3, 1, 1, float, float, float>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<4, 4, 3, 3, 1, 1, float, float, float>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 3, 3, 2, 2, float, float, float>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 3, 3, 2, 2, float, float, float>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -197,10 +195,10 @@ std::unique_ptr<depthwise::IDepthwiseConvolution> get_fp32_convolver(int kernel_ switch(stride_x) { case 1: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<4, 4, 5, 5, 1, 1, float, float, float>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<4, 4, 5, 5, 1, 1, float, float, float>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); case 2: - return arm_compute::support::cpp14::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 5, 5, 2, 2, float, float, float>>( + return std::make_unique<depthwise::DilatedDepthwiseConvolution<3, 3, 5, 5, 2, 2, float, float, float>>( n_batches, in_rows, in_cols, n_channels, dilation_factor, activation, padding_top, padding_left, padding_bottom, padding_right); default: return nullptr; @@ -339,7 +337,7 @@ struct NEDepthwiseConvolutionAssemblyDispatch::LocalImpl #ifndef DOXYGEN_SKIP_THIS NEDepthwiseConvolutionAssemblyDispatch::NEDepthwiseConvolutionAssemblyDispatch(std::shared_ptr<arm_compute::IMemoryManager> memory_manager) : _memory_group(std::move(memory_manager)), _input(nullptr), _weights(nullptr), _bias(nullptr), _output(nullptr), _packed_weights(), _workspace(), _is_prepared(false), - _pImpl(support::cpp14::make_unique<LocalImpl>()) + _pImpl(std::make_unique<LocalImpl>()) { } #endif /* DOXYGEN_SKIP_THIS */ diff --git a/src/runtime/OffsetLifetimeManager.cpp b/src/runtime/OffsetLifetimeManager.cpp index 3bd8b02cf1..a47fa184fa 100644 --- a/src/runtime/OffsetLifetimeManager.cpp +++ b/src/runtime/OffsetLifetimeManager.cpp @@ -27,7 +27,6 @@ #include "arm_compute/runtime/IAllocator.h" #include "arm_compute/runtime/IMemoryGroup.h" #include "arm_compute/runtime/OffsetMemoryPool.h" -#include "support/MemorySupport.h" #include <algorithm> #include <cmath> @@ -57,7 +56,7 @@ const OffsetLifetimeManager::info_type &OffsetLifetimeManager::info() const std::unique_ptr<IMemoryPool> OffsetLifetimeManager::create_pool(IAllocator *allocator) { ARM_COMPUTE_ERROR_ON(allocator == nullptr); - return support::cpp14::make_unique<OffsetMemoryPool>(allocator, _blob); + return std::make_unique<OffsetMemoryPool>(allocator, _blob); } MappingType OffsetLifetimeManager::mapping_type() const diff --git a/src/runtime/OffsetMemoryPool.cpp b/src/runtime/OffsetMemoryPool.cpp index 677c55c7c4..ffedf5586c 100644 --- a/src/runtime/OffsetMemoryPool.cpp +++ b/src/runtime/OffsetMemoryPool.cpp @@ -30,7 +30,6 @@ #include "arm_compute/runtime/IMemoryPool.h" #include "arm_compute/runtime/MemoryRegion.h" #include "arm_compute/runtime/Types.h" -#include "support/MemorySupport.h" namespace arm_compute { @@ -75,6 +74,6 @@ MappingType OffsetMemoryPool::mapping_type() const std::unique_ptr<IMemoryPool> OffsetMemoryPool::duplicate() { ARM_COMPUTE_ERROR_ON(!_allocator); - return support::cpp14::make_unique<OffsetMemoryPool>(_allocator, _blob_info); + return std::make_unique<OffsetMemoryPool>(_allocator, _blob_info); } } // namespace arm_compute diff --git a/src/runtime/PoolManager.cpp b/src/runtime/PoolManager.cpp index 19ed2577dc..87376a71a4 100644 --- a/src/runtime/PoolManager.cpp +++ b/src/runtime/PoolManager.cpp @@ -25,7 +25,6 @@ #include "arm_compute/core/Error.h" #include "arm_compute/runtime/IMemoryPool.h" -#include "support/MemorySupport.h" #include <algorithm> #include <list> @@ -71,7 +70,7 @@ void PoolManager::register_pool(std::unique_ptr<IMemoryPool> pool) _free_pools.push_front(std::move(pool)); // Update semaphore - _sem = arm_compute::support::cpp14::make_unique<arm_compute::Semaphore>(_free_pools.size()); + _sem = std::make_unique<arm_compute::Semaphore>(_free_pools.size()); } std::unique_ptr<IMemoryPool> PoolManager::release_pool() @@ -86,7 +85,7 @@ std::unique_ptr<IMemoryPool> PoolManager::release_pool() _free_pools.pop_front(); // Update semaphore - _sem = arm_compute::support::cpp14::make_unique<arm_compute::Semaphore>(_free_pools.size()); + _sem = std::make_unique<arm_compute::Semaphore>(_free_pools.size()); return pool; } diff --git a/src/runtime/Scheduler.cpp b/src/runtime/Scheduler.cpp index 5b3010b173..0713b9a2ad 100644 --- a/src/runtime/Scheduler.cpp +++ b/src/runtime/Scheduler.cpp @@ -24,7 +24,6 @@ #include "arm_compute/runtime/Scheduler.h" #include "arm_compute/core/Error.h" -#include "support/MemorySupport.h" #if ARM_COMPUTE_CPP_SCHEDULER #include "arm_compute/runtime/CPP/CPPScheduler.h" @@ -55,12 +54,12 @@ namespace std::map<Scheduler::Type, std::unique_ptr<IScheduler>> init() { std::map<Scheduler::Type, std::unique_ptr<IScheduler>> m; - m[Scheduler::Type::ST] = support::cpp14::make_unique<SingleThreadScheduler>(); + m[Scheduler::Type::ST] = std::make_unique<SingleThreadScheduler>(); #if defined(ARM_COMPUTE_CPP_SCHEDULER) - m[Scheduler::Type::CPP] = support::cpp14::make_unique<CPPScheduler>(); + m[Scheduler::Type::CPP] = std::make_unique<CPPScheduler>(); #endif // defined(ARM_COMPUTE_CPP_SCHEDULER) #if defined(ARM_COMPUTE_OPENMP_SCHEDULER) - m[Scheduler::Type::OMP] = support::cpp14::make_unique<OMPScheduler>(); + m[Scheduler::Type::OMP] = std::make_unique<OMPScheduler>(); #endif // defined(ARM_COMPUTE_OPENMP_SCHEDULER) return m; diff --git a/src/runtime/SchedulerFactory.cpp b/src/runtime/SchedulerFactory.cpp index e395c2e029..cc21d62630 100644 --- a/src/runtime/SchedulerFactory.cpp +++ b/src/runtime/SchedulerFactory.cpp @@ -23,8 +23,6 @@ */ #include "arm_compute/runtime/SchedulerFactory.h" -#include "support/MemorySupport.h" - #include "arm_compute/core/Error.h" #if ARM_COMPUTE_CPP_SCHEDULER #include "arm_compute/runtime/CPP/CPPScheduler.h" @@ -54,12 +52,12 @@ std::unique_ptr<IScheduler> SchedulerFactory::create(Type type) { case Type::ST: { - return support::cpp14::make_unique<SingleThreadScheduler>(); + return std::make_unique<SingleThreadScheduler>(); } case Type::CPP: { #if ARM_COMPUTE_CPP_SCHEDULER - return support::cpp14::make_unique<CPPScheduler>(); + return std::make_unique<CPPScheduler>(); #else /* ARM_COMPUTE_CPP_SCHEDULER */ ARM_COMPUTE_ERROR("Recompile with cppthreads=1 to use C++11 scheduler."); #endif /* ARM_COMPUTE_CPP_SCHEDULER */ @@ -67,7 +65,7 @@ std::unique_ptr<IScheduler> SchedulerFactory::create(Type type) case Type::OMP: { #if ARM_COMPUTE_OPENMP_SCHEDULER - return support::cpp14::make_unique<OMPScheduler>(); + return std::make_unique<OMPScheduler>(); #else /* ARM_COMPUTE_OPENMP_SCHEDULER */ ARM_COMPUTE_ERROR("Recompile with openmp=1 to use openmp scheduler."); #endif /* ARM_COMPUTE_OPENMP_SCHEDULER */ diff --git a/src/runtime/TensorAllocator.cpp b/src/runtime/TensorAllocator.cpp index e8c5c49018..4ae27c59fc 100644 --- a/src/runtime/TensorAllocator.cpp +++ b/src/runtime/TensorAllocator.cpp @@ -28,7 +28,6 @@ #include "arm_compute/core/TensorInfo.h" #include "arm_compute/runtime/MemoryGroup.h" #include "arm_compute/runtime/MemoryRegion.h" -#include "support/MemorySupport.h" #include <cstddef> @@ -136,7 +135,7 @@ void TensorAllocator::allocate() const size_t alignment_to_use = (alignment() != 0) ? alignment() : 64; if(_associated_memory_group == nullptr) { - _memory.set_owned_region(support::cpp14::make_unique<MemoryRegion>(info().total_size(), alignment_to_use)); + _memory.set_owned_region(std::make_unique<MemoryRegion>(info().total_size(), alignment_to_use)); } else { @@ -157,7 +156,7 @@ Status TensorAllocator::import_memory(void *memory) ARM_COMPUTE_RETURN_ERROR_ON(_associated_memory_group != nullptr); ARM_COMPUTE_RETURN_ERROR_ON(alignment() != 0 && !arm_compute::utility::check_aligned(memory, alignment())); - _memory.set_owned_region(support::cpp14::make_unique<MemoryRegion>(memory, info().total_size())); + _memory.set_owned_region(std::make_unique<MemoryRegion>(memory, info().total_size())); info().set_is_resizable(false); return Status{}; diff --git a/support/MemorySupport.h b/support/MemorySupport.h deleted file mode 100644 index a904f34f97..0000000000 --- a/support/MemorySupport.h +++ /dev/null @@ -1,114 +0,0 @@ -/* - * Copyright (c) 2017-2020 Arm Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#ifndef ARM_COMPUTE_SUPPORT_MEMORYSUPPORT -#define ARM_COMPUTE_SUPPORT_MEMORYSUPPORT - -#include <memory> - -namespace arm_compute -{ -namespace support -{ -namespace cpp11 -{ -// std::align is missing in GCC 4.9 -// https://gcc.gnu.org/bugzilla/show_bug.cgi?id=57350 -inline void *align(std::size_t alignment, std::size_t size, void *&ptr, std::size_t &space) -{ - std::uintptr_t pn = reinterpret_cast<std::uintptr_t>(ptr); - std::uintptr_t aligned = (pn + alignment - 1) & -alignment; - std::size_t padding = aligned - pn; - if(space < size + padding) - { - return nullptr; - } - - space -= padding; - - return ptr = reinterpret_cast<void *>(aligned); -} -} //namespace cpp11 -namespace cpp14 -{ -/** make_unique is missing in CPP11. Re-implement it according to the standard proposal. */ - -/**<Template for single object */ -template <class T> -struct _Unique_if -{ - typedef std::unique_ptr<T> _Single_object; /**< Single object type */ -}; - -/** Template for array */ -template <class T> -struct _Unique_if<T[]> -{ - typedef std::unique_ptr<T[]> _Unknown_bound; /**< Array type */ -}; - -/** Template for array with known bounds (to throw an error). - * - * @note this is intended to never be hit. - */ -template <class T, size_t N> -struct _Unique_if<T[N]> -{ - typedef void _Known_bound; /**< Should never be used */ -}; - -/** Construct a single object and return a unique pointer to it. - * - * @param[in] args Constructor arguments. - * - * @return a unique pointer to the new object. - */ -template <class T, class... Args> -typename _Unique_if<T>::_Single_object -make_unique(Args &&... args) -{ - return std::unique_ptr<T>(new T(std::forward<Args>(args)...)); -} - -/** Construct an array of objects and return a unique pointer to it. - * - * @param[in] n Array size - * - * @return a unique pointer to the new array. - */ -template <class T> -typename _Unique_if<T>::_Unknown_bound -make_unique(size_t n) -{ - typedef typename std::remove_extent<T>::type U; - return std::unique_ptr<T>(new U[n]()); -} - -/** It is invalid to attempt to make_unique an array with known bounds. */ -template <class T, class... Args> -typename _Unique_if<T>::_Known_bound -make_unique(Args &&...) = delete; -} // namespace cpp14 -} // namespace support -} // namespace arm_compute -#endif /* ARM_COMPUTE_SUPPORT_MEMORYSUPPORT */ diff --git a/tests/CL/Helper.h b/tests/CL/Helper.h index e548af4938..d217af6e18 100644 --- a/tests/CL/Helper.h +++ b/tests/CL/Helper.h @@ -33,7 +33,7 @@ #include "src/core/CL/ICLKernel.h" -#include "support/MemorySupport.h" +#include <memory> namespace arm_compute { @@ -51,7 +51,7 @@ public: template <typename... Args> void configure(Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->configure(std::forward<Args>(args)...); _kernel = std::move(k); } @@ -63,7 +63,7 @@ public: template <typename... Args> void configure(GPUTarget gpu_target, Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->set_target(gpu_target); k->configure(std::forward<Args>(args)...); _kernel = std::move(k); @@ -92,7 +92,7 @@ public: template <typename T, typename... Args> void configure(T first, Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->configure(first, std::forward<Args>(args)...); _kernel = std::move(k); _border_handler->configure(first, BorderSize(bordersize), BorderMode::CONSTANT, PixelValue()); @@ -113,7 +113,7 @@ public: template <typename T, typename... Args> void configure(T first, T second, Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->set_target(CLScheduler::get().target()); k->configure(first, second, std::forward<Args>(args)...); _kernel = std::move(k); diff --git a/tests/NEON/Helper.h b/tests/NEON/Helper.h index ea47a416b1..714152ebcd 100644 --- a/tests/NEON/Helper.h +++ b/tests/NEON/Helper.h @@ -28,11 +28,11 @@ #include "arm_compute/runtime/NEON/INESimpleFunction.h" #include "arm_compute/runtime/NEON/INESimpleFunctionNoBorder.h" #include "src/core/NEON/kernels/NEFillBorderKernel.h" -#include "support/MemorySupport.h" #include "tests/Globals.h" #include <algorithm> #include <array> +#include <memory> #include <vector> namespace arm_compute @@ -64,7 +64,7 @@ public: template <typename... Args> void configure(Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->configure(std::forward<Args>(args)...); _kernel = std::move(k); } @@ -92,11 +92,11 @@ public: template <typename T, typename... Args> void configure(T first, Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->configure(first, std::forward<Args>(args)...); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(first, BorderSize(bordersize), BorderMode::CONSTANT, PixelValue()); _border_handler = std::move(b); } @@ -115,11 +115,11 @@ public: template <typename T, typename... Args> void configure(T first, Args &&... args) { - auto k = arm_compute::support::cpp14::make_unique<K>(); + auto k = std::make_unique<K>(); k->configure(first, std::forward<Args>(args)...); _kernel = std::move(k); - auto b = arm_compute::support::cpp14::make_unique<NEFillBorderKernel>(); + auto b = std::make_unique<NEFillBorderKernel>(); b->configure(first, BorderSize(_kernel->border_size()), BorderMode::CONSTANT, PixelValue()); _border_handler = std::move(b); } diff --git a/tests/RawTensor.cpp b/tests/RawTensor.cpp index a32886e425..8d610a4969 100644 --- a/tests/RawTensor.cpp +++ b/tests/RawTensor.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 Arm Limited. + * Copyright (c) 2017-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -30,20 +30,20 @@ namespace test RawTensor::RawTensor(TensorShape shape, Format format) : SimpleTensor(shape, format) { - _buffer = support::cpp14::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size()); + _buffer = std::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size()); } RawTensor::RawTensor(TensorShape shape, DataType data_type, int num_channels) : SimpleTensor(shape, data_type, num_channels) { - _buffer = support::cpp14::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size()); + _buffer = std::make_unique<uint8_t[]>(SimpleTensor::num_elements() * SimpleTensor::num_channels() * SimpleTensor::element_size()); } RawTensor::RawTensor(const RawTensor &tensor) : SimpleTensor(tensor.shape(), tensor.data_type(), tensor.num_channels()) { _format = tensor.format(); - _buffer = support::cpp14::make_unique<uint8_t[]>(num_elements() * num_channels() * element_size()); + _buffer = std::make_unique<uint8_t[]>(num_elements() * num_channels() * element_size()); std::copy_n(tensor.data(), num_elements() * num_channels() * element_size(), _buffer.get()); } diff --git a/tests/SimpleTensor.h b/tests/SimpleTensor.h index 82a53521ac..c1bd7f87b5 100644 --- a/tests/SimpleTensor.h +++ b/tests/SimpleTensor.h @@ -27,7 +27,6 @@ #include "arm_compute/core/TensorShape.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Utils.h" -#include "support/MemorySupport.h" #include "tests/IAccessor.h" #include "tests/Utils.h" @@ -268,7 +267,7 @@ SimpleTensor<T>::SimpleTensor(TensorShape shape, Format format) _data_layout(DataLayout::NCHW) { _num_channels = num_channels(); - _buffer = support::cpp14::make_unique<T[]>(num_elements() * _num_channels); + _buffer = std::make_unique<T[]>(num_elements() * _num_channels); } template <typename T> @@ -280,7 +279,7 @@ SimpleTensor<T>::SimpleTensor(TensorShape shape, DataType data_type, int num_cha _quantization_info(quantization_info), _data_layout(data_layout) { - _buffer = support::cpp14::make_unique<T[]>(this->_shape.total_size() * _num_channels); + _buffer = std::make_unique<T[]>(this->_shape.total_size() * _num_channels); } template <typename T> @@ -293,7 +292,7 @@ SimpleTensor<T>::SimpleTensor(const SimpleTensor &tensor) _quantization_info(tensor.quantization_info()), _data_layout(tensor.data_layout()) { - _buffer = support::cpp14::make_unique<T[]>(tensor.num_elements() * _num_channels); + _buffer = std::make_unique<T[]>(tensor.num_elements() * _num_channels); std::copy_n(tensor.data(), this->_shape.total_size() * _num_channels, _buffer.get()); } diff --git a/tests/framework/Framework.cpp b/tests/framework/Framework.cpp index 8e836ee41f..a1c684c08a 100644 --- a/tests/framework/Framework.cpp +++ b/tests/framework/Framework.cpp @@ -24,7 +24,6 @@ #include "Framework.h" #include "arm_compute/runtime/Scheduler.h" -#include "support/MemorySupport.h" #include "tests/framework/ParametersLibrary.h" #include "tests/framework/TestFilter.h" @@ -36,6 +35,7 @@ #include <chrono> #include <iostream> +#include <memory> #include <sstream> #include <type_traits> @@ -94,7 +94,7 @@ Framework::Framework() Instrument::make_instrument<OpenCLMemoryUsage, ScaleFactor::SCALE_1M>); #endif /* ARM_COMPUTE_CL */ - instruments_info = support::cpp14::make_unique<InstrumentsInfo>(); + instruments_info = std::make_unique<InstrumentsInfo>(); } std::set<InstrumentsDescription> Framework::available_instruments() const diff --git a/tests/framework/Framework.h b/tests/framework/Framework.h index 01ab37347e..cf854f2351 100644 --- a/tests/framework/Framework.h +++ b/tests/framework/Framework.h @@ -355,7 +355,7 @@ private: template <typename T> inline void Framework::add_test_case(std::string test_name, DatasetMode mode, TestCaseFactory::Status status) { - _test_factories.emplace_back(support::cpp14::make_unique<SimpleTestCaseFactory<T>>(current_suite_name(), std::move(test_name), mode, status)); + _test_factories.emplace_back(std::make_unique<SimpleTestCaseFactory<T>>(current_suite_name(), std::move(test_name), mode, status)); } template <typename T, typename D> diff --git a/tests/framework/TestCaseFactory.h b/tests/framework/TestCaseFactory.h index 97ba230743..a41226af24 100644 --- a/tests/framework/TestCaseFactory.h +++ b/tests/framework/TestCaseFactory.h @@ -26,7 +26,6 @@ #include "DatasetModes.h" #include "TestCase.h" -#include "support/MemorySupport.h" #include <memory> #include <string> @@ -183,7 +182,7 @@ inline ::std::ostream &operator<<(::std::ostream &stream, TestCaseFactory::Statu template <typename T> inline std::unique_ptr<TestCase> SimpleTestCaseFactory<T>::make() const { - return support::cpp14::make_unique<T>(); + return std::make_unique<T>(); } template <typename T, typename D> @@ -195,7 +194,7 @@ inline DataTestCaseFactory<T, D>::DataTestCaseFactory(std::string suite_name, st template <typename T, typename D> inline std::unique_ptr<TestCase> DataTestCaseFactory<T, D>::make() const { - return support::cpp14::make_unique<T>(_data); + return std::make_unique<T>(_data); } } // namespace framework } // namespace test diff --git a/tests/framework/command_line/CommonOptions.cpp b/tests/framework/command_line/CommonOptions.cpp index b4bf58bfdc..6fb37470c1 100644 --- a/tests/framework/command_line/CommonOptions.cpp +++ b/tests/framework/command_line/CommonOptions.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -101,7 +101,7 @@ std::vector<std::unique_ptr<Printer>> CommonOptions::create_printers() if(pretty_console->value() && (log_file->is_set() || log_format->value() != LogFormat::PRETTY)) { - auto pretty_printer = support::cpp14::make_unique<PrettyPrinter>(); + auto pretty_printer = std::make_unique<PrettyPrinter>(); pretty_printer->set_color_output(color_output->value()); printers.push_back(std::move(pretty_printer)); } @@ -110,13 +110,13 @@ std::vector<std::unique_ptr<Printer>> CommonOptions::create_printers() switch(log_format->value()) { case LogFormat::JSON: - printer = support::cpp14::make_unique<JSONPrinter>(); + printer = std::make_unique<JSONPrinter>(); break; case LogFormat::NONE: break; case LogFormat::PRETTY: default: - auto pretty_printer = support::cpp14::make_unique<PrettyPrinter>(); + auto pretty_printer = std::make_unique<PrettyPrinter>(); // Don't use colours if we print to a file: pretty_printer->set_color_output((!log_file->is_set()) && color_output->value()); printer = std::move(pretty_printer); @@ -139,14 +139,14 @@ std::vector<std::unique_ptr<Printer>> CommonOptions::create_printers() if(json_file->is_set()) { - printers.push_back(support::cpp14::make_unique<JSONPrinter>()); + printers.push_back(std::make_unique<JSONPrinter>()); log_streams.push_back(std::make_shared<std::ofstream>(json_file->value())); printers.back()->set_stream(*log_streams.back().get()); } if(pretty_file->is_set()) { - printers.push_back(support::cpp14::make_unique<PrettyPrinter>()); + printers.push_back(std::make_unique<PrettyPrinter>()); log_streams.push_back(std::make_shared<std::ofstream>(pretty_file->value())); printers.back()->set_stream(*log_streams.back().get()); } diff --git a/tests/framework/instruments/Instrument.h b/tests/framework/instruments/Instrument.h index 4506460515..3ea15825ad 100644 --- a/tests/framework/instruments/Instrument.h +++ b/tests/framework/instruments/Instrument.h @@ -24,8 +24,6 @@ #ifndef ARM_COMPUTE_TEST_INSTRUMENT #define ARM_COMPUTE_TEST_INSTRUMENT -#include "support/MemorySupport.h" - #include "../Utils.h" #include "Measurement.h" @@ -135,7 +133,7 @@ protected: template <typename T, ScaleFactor scale> inline std::unique_ptr<Instrument> Instrument::make_instrument() { - return support::cpp14::make_unique<T>(scale); + return std::make_unique<T>(scale); } } // namespace framework diff --git a/tests/framework/instruments/SchedulerTimer.cpp b/tests/framework/instruments/SchedulerTimer.cpp index b4d1c597e7..c81b807c3e 100644 --- a/tests/framework/instruments/SchedulerTimer.cpp +++ b/tests/framework/instruments/SchedulerTimer.cpp @@ -188,7 +188,7 @@ void SchedulerClock<output_timestamps>::test_start() { if(user != nullptr && user->scheduler() != nullptr) { - user->intercept_scheduler(support::cpp14::make_unique<Interceptor<output_timestamps>>(_kernels, *user->scheduler(), _scale_factor)); + user->intercept_scheduler(std::make_unique<Interceptor<output_timestamps>>(_kernels, *user->scheduler(), _scale_factor)); } }); } diff --git a/tests/main.cpp b/tests/main.cpp index f0d5df7d84..46a081b6c8 100644 --- a/tests/main.cpp +++ b/tests/main.cpp @@ -21,7 +21,6 @@ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE * SOFTWARE. */ -#include "support/MemorySupport.h" #include "support/StringSupport.h" #include "tests/AssetsLibrary.h" #include "tests/framework/DatasetModes.h" @@ -166,20 +165,20 @@ int main(int argc, char **argv) Scheduler::get().set_num_threads(threads->value()); // Create CPU context - auto cpu_ctx = support::cpp14::make_unique<RuntimeContext>(); + auto cpu_ctx = std::make_unique<RuntimeContext>(); cpu_ctx->set_scheduler(&Scheduler::get()); // Track CPU context - auto cpu_ctx_track = support::cpp14::make_unique<ContextSchedulerUser>(cpu_ctx.get()); + auto cpu_ctx_track = std::make_unique<ContextSchedulerUser>(cpu_ctx.get()); // Create parameters - parameters = support::cpp14::make_unique<ParametersLibrary>(); + parameters = std::make_unique<ParametersLibrary>(); parameters->set_cpu_ctx(std::move(cpu_ctx)); #ifdef ARM_COMPUTE_GC // Setup OpenGL context { - auto gles_ctx = support::cpp14::make_unique<GCRuntimeContext>(); + auto gles_ctx = std::make_unique<GCRuntimeContext>(); ARM_COMPUTE_ERROR_ON(gles_ctx == nullptr); { // Legacy singletons API: This has been deprecated and the singletons will be removed @@ -312,8 +311,8 @@ int main(int argc, char **argv) return 0; } - library = support::cpp14::make_unique<AssetsLibrary>(assets->value(), seed->value()); - fixed_library = support::cpp14::make_unique<AssetsLibrary>(assets->value(), fixed_seed); + library = std::make_unique<AssetsLibrary>(assets->value(), seed->value()); + fixed_library = std::make_unique<AssetsLibrary>(assets->value(), fixed_seed); if(!parser.validate()) { diff --git a/tests/validate_examples/RunExample.cpp b/tests/validate_examples/RunExample.cpp index aca4ddcc7c..736d4816f5 100644 --- a/tests/validate_examples/RunExample.cpp +++ b/tests/validate_examples/RunExample.cpp @@ -27,8 +27,8 @@ #include "utils/Utils.cpp" #include "ValidateExample.h" -#include "arm_compute/runtime/Scheduler.h" #include "arm_compute/runtime/CL/CLHelpers.h" +#include "arm_compute/runtime/Scheduler.h" #include "tests/AssetsLibrary.h" #include "tests/Globals.h" #include "tests/framework/Framework.h" @@ -139,8 +139,8 @@ int run_example(int argc, char **argv, std::unique_ptr<ValidateExample> example) g_example_argv.emplace_back(const_cast<char *>(arg.c_str())); // NOLINT } - library = support::cpp14::make_unique<AssetsLibrary>("." /* Only using random values */, seed->value()); - fixed_library = support::cpp14::make_unique<AssetsLibrary>(".", fixed_seed); + library = std::make_unique<AssetsLibrary>("." /* Only using random values */, seed->value()); + fixed_library = std::make_unique<AssetsLibrary>(".", fixed_seed); if(options.log_level->value() > framework::LogLevel::NONE) { diff --git a/tests/validate_examples/graph_validate_utils.h b/tests/validate_examples/graph_validate_utils.h index 36134a4cea..f6f47cc2c3 100644 --- a/tests/validate_examples/graph_validate_utils.h +++ b/tests/validate_examples/graph_validate_utils.h @@ -337,11 +337,11 @@ inline std::unique_ptr<graph::ITensorAccessor> get_accessor(const TensorParams & { if(!tensor.npy.empty()) { - return arm_compute::support::cpp14::make_unique<arm_compute::graph_utils::NumPyBinLoader>(tensor.npy); + return std::make_unique<arm_compute::graph_utils::NumPyBinLoader>(tensor.npy); } else { - return arm_compute::support::cpp14::make_unique<arm_compute::graph_utils::RandomAccessor>(lower, upper, seed); + return std::make_unique<arm_compute::graph_utils::RandomAccessor>(lower, upper, seed); } } @@ -607,17 +607,17 @@ inline std::unique_ptr<graph::ITensorAccessor> get_verify_accessor(ExampleParams { case DataType::QASYMM8: { - return arm_compute::support::cpp14::make_unique<VerifyAccessorT<uint8_t>>( + return std::make_unique<VerifyAccessorT<uint8_t>>( params); } case DataType::F16: { - return arm_compute::support::cpp14::make_unique<VerifyAccessorT<half>>( + return std::make_unique<VerifyAccessorT<half>>( params); } case DataType::F32: { - return arm_compute::support::cpp14::make_unique<VerifyAccessorT<float>>( + return std::make_unique<VerifyAccessorT<float>>( params); } default: diff --git a/tests/validation/CL/UNIT/TensorAllocator.cpp b/tests/validation/CL/UNIT/TensorAllocator.cpp index 9db98fb534..3ccdd99fe3 100644 --- a/tests/validation/CL/UNIT/TensorAllocator.cpp +++ b/tests/validation/CL/UNIT/TensorAllocator.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -135,10 +135,10 @@ TEST_CASE(ImportMemoryMalloc, framework::DatasetMode::ALL) const size_t total_size_in_bytes = tensor.info()->total_size(); const size_t alignment = CLKernelLibrary::get().get_device().getInfo<CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE>(); size_t space = total_size_in_bytes + alignment; - auto raw_data = support::cpp14::make_unique<uint8_t[]>(space); + auto raw_data = std::make_unique<uint8_t[]>(space); void *aligned_ptr = raw_data.get(); - support::cpp11::align(alignment, total_size_in_bytes, aligned_ptr, space); + std::align(alignment, total_size_in_bytes, aligned_ptr, space); cl::Buffer wrapped_buffer(import_malloc_memory_helper(aligned_ptr, total_size_in_bytes)); ARM_COMPUTE_EXPECT(bool(tensor.allocator()->import_memory(wrapped_buffer)), framework::LogLevel::ERRORS); diff --git a/tests/validation/NEON/UNIT/TensorAllocator.cpp b/tests/validation/NEON/UNIT/TensorAllocator.cpp index 273d2e0a4f..ef19524d1c 100644 --- a/tests/validation/NEON/UNIT/TensorAllocator.cpp +++ b/tests/validation/NEON/UNIT/TensorAllocator.cpp @@ -29,8 +29,6 @@ #include "arm_compute/runtime/MemoryRegion.h" #include "arm_compute/runtime/NEON/functions/NEActivationLayer.h" -#include "support/MemorySupport.h" - #include "tests/Globals.h" #include "tests/Utils.h" #include "tests/framework/Asserts.h" @@ -58,7 +56,7 @@ TEST_CASE(ImportMemory, framework::DatasetMode::ALL) // Allocate memory buffer const size_t total_size = info.total_size(); - auto data = support::cpp14::make_unique<uint8_t[]>(total_size); + auto data = std::make_unique<uint8_t[]>(total_size); // Negative case : Import nullptr Tensor t1; @@ -111,10 +109,10 @@ TEST_CASE(ImportMemoryMalloc, framework::DatasetMode::ALL) const size_t total_size_in_elems = tensor.info()->tensor_shape().total_size(); const size_t total_size_in_bytes = tensor.info()->total_size(); size_t space = total_size_in_bytes + required_alignment; - auto raw_data = support::cpp14::make_unique<uint8_t[]>(space); + auto raw_data = std::make_unique<uint8_t[]>(space); void *aligned_ptr = raw_data.get(); - support::cpp11::align(required_alignment, total_size_in_bytes, aligned_ptr, space); + std::align(required_alignment, total_size_in_bytes, aligned_ptr, space); ARM_COMPUTE_EXPECT(bool(tensor.allocator()->import_memory(aligned_ptr)), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(!tensor.info()->is_resizable(), framework::LogLevel::ERRORS); @@ -160,7 +158,7 @@ TEST_CASE(ImportMemoryMallocPadded, framework::DatasetMode::ALL) // Allocate and import tensor const size_t total_size_in_bytes = tensor.info()->total_size(); - auto raw_data = support::cpp14::make_unique<uint8_t[]>(total_size_in_bytes); + auto raw_data = std::make_unique<uint8_t[]>(total_size_in_bytes); ARM_COMPUTE_EXPECT(bool(tensor.allocator()->import_memory(raw_data.get())), framework::LogLevel::ERRORS); ARM_COMPUTE_EXPECT(!tensor.info()->is_resizable(), framework::LogLevel::ERRORS); diff --git a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h index 74e62fb77f..4ac19bf3ba 100644 --- a/tests/validation/fixtures/UNIT/DynamicTensorFixture.h +++ b/tests/validation/fixtures/UNIT/DynamicTensorFixture.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019 Arm Limited. + * Copyright (c) 2019-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -264,7 +264,7 @@ public: _info = info; // Create function - _f_target = support::cpp14::make_unique<ComplexFunctionType>(_ms.mm); + _f_target = std::make_unique<ComplexFunctionType>(_ms.mm); } void run_iteration(unsigned int idx) @@ -425,7 +425,7 @@ protected: for(unsigned int i = 0; i < num_functions; ++i) { - _functions.emplace_back(support::cpp14::make_unique<ComplexFunctionType>(_ms.mm)); + _functions.emplace_back(std::make_unique<ComplexFunctionType>(_ms.mm)); } for(unsigned int i = 0; i < num_resizes; ++i) diff --git a/utils/GraphUtils.h b/utils/GraphUtils.h index 9ab9e54ce0..acd924da28 100644 --- a/utils/GraphUtils.h +++ b/utils/GraphUtils.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2019 Arm Limited. + * Copyright (c) 2017-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -459,7 +459,7 @@ private: */ inline std::unique_ptr<graph::ITensorAccessor> get_random_accessor(PixelValue lower, PixelValue upper, const std::random_device::result_type seed = 0) { - return arm_compute::support::cpp14::make_unique<RandomAccessor>(lower, upper, seed); + return std::make_unique<RandomAccessor>(lower, upper, seed); } /** Generates appropriate weights accessor according to the specified path @@ -478,11 +478,11 @@ inline std::unique_ptr<graph::ITensorAccessor> get_weights_accessor(const std::s { if(path.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(); + return std::make_unique<DummyAccessor>(); } else { - return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(path + data_file, file_layout); + return std::make_unique<NumPyBinLoader>(path + data_file, file_layout); } } @@ -500,12 +500,12 @@ inline std::unique_ptr<graph::ITensorAccessor> get_input_accessor(const arm_comp { if(!graph_parameters.validation_file.empty()) { - return arm_compute::support::cpp14::make_unique<ValidationInputAccessor>(graph_parameters.validation_file, - graph_parameters.validation_path, - std::move(preprocessor), - bgr, - graph_parameters.validation_range_start, - graph_parameters.validation_range_end); + return std::make_unique<ValidationInputAccessor>(graph_parameters.validation_file, + graph_parameters.validation_path, + std::move(preprocessor), + bgr, + graph_parameters.validation_range_start, + graph_parameters.validation_range_end); } else { @@ -513,17 +513,17 @@ inline std::unique_ptr<graph::ITensorAccessor> get_input_accessor(const arm_comp const std::string &image_file_lower = lower_string(image_file); if(arm_compute::utility::endswith(image_file_lower, ".npy")) { - return arm_compute::support::cpp14::make_unique<NumPyBinLoader>(image_file, graph_parameters.data_layout); + return std::make_unique<NumPyBinLoader>(image_file, graph_parameters.data_layout); } else if(arm_compute::utility::endswith(image_file_lower, ".jpeg") || arm_compute::utility::endswith(image_file_lower, ".jpg") || arm_compute::utility::endswith(image_file_lower, ".ppm")) { - return arm_compute::support::cpp14::make_unique<ImageAccessor>(image_file, bgr, std::move(preprocessor)); + return std::make_unique<ImageAccessor>(image_file, bgr, std::move(preprocessor)); } else { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(); + return std::make_unique<DummyAccessor>(); } } } @@ -548,18 +548,18 @@ inline std::unique_ptr<graph::ITensorAccessor> get_output_accessor(const arm_com ARM_COMPUTE_UNUSED(is_validation); if(!graph_parameters.validation_file.empty()) { - return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, - output_stream, - graph_parameters.validation_range_start, - graph_parameters.validation_range_end); + return std::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, + output_stream, + graph_parameters.validation_range_start, + graph_parameters.validation_range_end); } else if(graph_parameters.labels.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream); + return std::make_unique<TopNPredictionsAccessor>(graph_parameters.labels, top_n, output_stream); } } /** Generates appropriate output accessor according to the specified graph parameters @@ -582,18 +582,18 @@ inline std::unique_ptr<graph::ITensorAccessor> get_detection_output_accessor(con ARM_COMPUTE_UNUSED(is_validation); if(!graph_parameters.validation_file.empty()) { - return arm_compute::support::cpp14::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, - output_stream, - graph_parameters.validation_range_start, - graph_parameters.validation_range_end); + return std::make_unique<ValidationOutputAccessor>(graph_parameters.validation_file, + output_stream, + graph_parameters.validation_range_start, + graph_parameters.validation_range_end); } else if(graph_parameters.labels.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream); + return std::make_unique<DetectionOutputAccessor>(graph_parameters.labels, tensor_shapes, output_stream); } } /** Generates appropriate npy output accessor according to the specified npy_path @@ -613,11 +613,11 @@ inline std::unique_ptr<graph::ITensorAccessor> get_npy_output_accessor(const std { if(npy_path.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<NumPyAccessor>(npy_path, shape, data_type, data_layout, output_stream); + return std::make_unique<NumPyAccessor>(npy_path, shape, data_type, data_layout, output_stream); } } @@ -634,11 +634,11 @@ inline std::unique_ptr<graph::ITensorAccessor> get_save_npy_output_accessor(cons { if(npy_name.empty()) { - return arm_compute::support::cpp14::make_unique<DummyAccessor>(0); + return std::make_unique<DummyAccessor>(0); } else { - return arm_compute::support::cpp14::make_unique<SaveNumPyAccessor>(npy_name, is_fortran); + return std::make_unique<SaveNumPyAccessor>(npy_name, is_fortran); } } @@ -650,7 +650,7 @@ inline std::unique_ptr<graph::ITensorAccessor> get_save_npy_output_accessor(cons */ inline std::unique_ptr<graph::ITensorAccessor> get_print_output_accessor(std::ostream &output_stream = std::cout) { - return arm_compute::support::cpp14::make_unique<PrintAccessor>(output_stream); + return std::make_unique<PrintAccessor>(output_stream); } /** Permutes a given tensor shape given the input and output data layout diff --git a/utils/ImageLoader.h b/utils/ImageLoader.h index 2dbb6f9421..5abcb7a60f 100644 --- a/utils/ImageLoader.h +++ b/utils/ImageLoader.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2018-2019 Arm Limited. + * Copyright (c) 2018-2020 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -392,7 +392,7 @@ public: ARM_COMPUTE_ERROR_ON_MSG_VAR(max_val >= 256, "2 bytes per colour channel not supported in file %s", filename.c_str()); - _feeder = support::cpp14::make_unique<FileImageFeeder>(_fs); + _feeder = std::make_unique<FileImageFeeder>(_fs); } catch(std::runtime_error &e) { @@ -467,7 +467,7 @@ public: _height = height; _data = std::unique_ptr<uint8_t, malloc_deleter>(rgb_image); _is_loaded = true; - _feeder = support::cpp14::make_unique<MemoryImageFeeder>(_data.get()); + _feeder = std::make_unique<MemoryImageFeeder>(_data.get()); } } void close() override @@ -512,9 +512,9 @@ public: switch(type) { case ImageType::PPM: - return support::cpp14::make_unique<PPMLoader>(); + return std::make_unique<PPMLoader>(); case ImageType::JPEG: - return support::cpp14::make_unique<JPEGLoader>(); + return std::make_unique<JPEGLoader>(); case ImageType::UNKNOWN: default: return nullptr; diff --git a/utils/Utils.h b/utils/Utils.h index e44d978b24..b10d18aca2 100644 --- a/utils/Utils.h +++ b/utils/Utils.h @@ -38,7 +38,6 @@ #pragma GCC diagnostic ignored "-Wstrict-overflow" #include "libnpy/npy.hpp" #pragma GCC diagnostic pop -#include "support/MemorySupport.h" #include "support/StringSupport.h" #ifdef ARM_COMPUTE_CL @@ -54,6 +53,7 @@ #include <cstring> #include <fstream> #include <iostream> +#include <memory> #include <random> #include <string> #include <tuple> @@ -110,7 +110,7 @@ int run_example(int argc, char **argv, std::unique_ptr<Example> example); template <typename T> int run_example(int argc, char **argv) { - return run_example(argc, argv, support::cpp14::make_unique<T>()); + return run_example(argc, argv, std::make_unique<T>()); } /** Draw a RGB rectangular window for the detected object diff --git a/utils/command_line/CommandLineParser.h b/utils/command_line/CommandLineParser.h index 5881723da8..e8fabc4251 100644 --- a/utils/command_line/CommandLineParser.h +++ b/utils/command_line/CommandLineParser.h @@ -26,11 +26,11 @@ #include "Option.h" #include "arm_compute/core/utils/misc/Utility.h" -#include "support/MemorySupport.h" #include <iostream> #include <map> #include <memory> +#include <memory> #include <regex> #include <string> #include <utility> @@ -102,14 +102,14 @@ private: template <typename T, typename... As> inline T *CommandLineParser::add_option(const std::string &name, As &&... args) { - auto result = _options.emplace(name, support::cpp14::make_unique<T>(name, std::forward<As>(args)...)); + auto result = _options.emplace(name, std::make_unique<T>(name, std::forward<As>(args)...)); return static_cast<T *>(result.first->second.get()); } template <typename T, typename... As> inline T *CommandLineParser::add_positional_option(As &&... args) { - _positional_options.emplace_back(support::cpp14::make_unique<T>(std::forward<As>(args)...)); + _positional_options.emplace_back(std::make_unique<T>(std::forward<As>(args)...)); return static_cast<T *>(_positional_options.back().get()); } |