From 05069f07bcf95676597698a79926327555276362 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Thu, 26 Sep 2019 17:18:26 +0100 Subject: COMPMID-2515: Merge optimized depthwise convolution to the generic depthwise convolution function 3RDPARTY_UPDATE Change-Id: Iff9e915c5329c617527b6f5042979f4e21a8b2b8 Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/2022 Comments-Addressed: Arm Jenkins Reviewed-by: Giorgio Arena Tested-by: Arm Jenkins Reviewed-by: Georgios Pinitas --- src/graph/TypeLoader.cpp | 1 - src/graph/backends/CL/CLFunctionsFactory.cpp | 9 +- src/graph/backends/CL/CLNodeValidator.cpp | 3 +- src/graph/backends/GLES/GCNodeValidator.cpp | 1 - src/graph/backends/NEON/NEFunctionFactory.cpp | 9 +- src/graph/backends/NEON/NENodeValidator.cpp | 3 +- .../CL/functions/CLDepthwiseConvolutionLayer.cpp | 536 +++++++++++--------- .../NEON/functions/NEDepthwiseConvolutionLayer.cpp | 543 +++++++-------------- 8 files changed, 484 insertions(+), 621 deletions(-) (limited to 'src') diff --git a/src/graph/TypeLoader.cpp b/src/graph/TypeLoader.cpp index b63672b39b..81a405b961 100644 --- a/src/graph/TypeLoader.cpp +++ b/src/graph/TypeLoader.cpp @@ -131,7 +131,6 @@ DepthwiseConvolutionMethod depthwise_convolution_method_from_name(const std::str static const std::map methods = { { "default", DepthwiseConvolutionMethod::Default }, - { "gemv", DepthwiseConvolutionMethod::GEMV }, { "optimized3x3", DepthwiseConvolutionMethod::Optimized3x3 }, }; diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp index 6d231f2ef3..d53b634bb1 100644 --- a/src/graph/backends/CL/CLFunctionsFactory.cpp +++ b/src/graph/backends/CL/CLFunctionsFactory.cpp @@ -56,13 +56,6 @@ struct CLConvolutionLayerFunctions using WinogradConvolutionLayer = CLWinogradConvolutionLayer; }; -/** Collection of CL depthwise convolution functions */ -struct CLDepthwiseConvolutionLayerFunctions -{ - using GenericDepthwiseConvolutionLayer = CLDepthwiseConvolutionLayer; - using OptimizedDepthwiseConvolutionLayer = CLDepthwiseConvolutionLayer; -}; - /** Collection of CL element-wise functions */ struct CLEltwiseFunctions { @@ -249,7 +242,7 @@ std::unique_ptr CLFunctionFactory::create(INode *node, GraphContext & case NodeType::ConcatenateLayer: return detail::create_concatenate_layer(*polymorphic_downcast(node)); case NodeType::DepthwiseConvolutionLayer: - return detail::create_depthwise_convolution_layer(*polymorphic_downcast(node)); + return detail::create_depthwise_convolution_layer(*polymorphic_downcast(node)); case NodeType::DetectionOutputLayer: return detail::create_detection_output_layer(*polymorphic_downcast(node)); case NodeType::DetectionPostProcessLayer: diff --git a/src/graph/backends/CL/CLNodeValidator.cpp b/src/graph/backends/CL/CLNodeValidator.cpp index 40ec508767..a2786187a2 100644 --- a/src/graph/backends/CL/CLNodeValidator.cpp +++ b/src/graph/backends/CL/CLNodeValidator.cpp @@ -58,8 +58,7 @@ Status CLNodeValidator::validate(INode *node) CLGEMMConvolutionLayer, CLWinogradConvolutionLayer>(*polymorphic_downcast(node)); case NodeType::DepthwiseConvolutionLayer: - return detail::validate_depthwise_convolution_layer(*polymorphic_downcast(node)); + return detail::validate_depthwise_convolution_layer(*polymorphic_downcast(node)); case NodeType::DetectionOutputLayer: return detail::validate_detection_output_layer(*polymorphic_downcast(node)); case NodeType::DetectionPostProcessLayer: diff --git a/src/graph/backends/GLES/GCNodeValidator.cpp b/src/graph/backends/GLES/GCNodeValidator.cpp index 9cbb9a12ef..9d848ab3b1 100644 --- a/src/graph/backends/GLES/GCNodeValidator.cpp +++ b/src/graph/backends/GLES/GCNodeValidator.cpp @@ -58,7 +58,6 @@ Status validate_depthwise_convolution_layer(DepthwiseConvolutionLayerNode &node) // TODO (geopin01) : Switch when validation is implemented // Validate function ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->tensor_shape().x() != 3 && weights->tensor_shape().y() != 3, "Unsupported depthwise convolution"); - node.set_depthwise_convolution_method(DepthwiseConvolutionMethod::Optimized3x3); return Status{}; } diff --git a/src/graph/backends/NEON/NEFunctionFactory.cpp b/src/graph/backends/NEON/NEFunctionFactory.cpp index 45e9727133..d8b0ae92ea 100644 --- a/src/graph/backends/NEON/NEFunctionFactory.cpp +++ b/src/graph/backends/NEON/NEFunctionFactory.cpp @@ -62,13 +62,6 @@ struct NEConvolutionLayerFunctions using WinogradConvolutionLayer = NEWinogradConvolutionLayer; }; -/** Collection of CL depthwise convolution functions */ -struct NEDepthwiseConvolutionLayerFunctions -{ - using GenericDepthwiseConvolutionLayer = NEDepthwiseConvolutionLayer; - using OptimizedDepthwiseConvolutionLayer = NEDepthwiseConvolutionLayerOptimized; -}; - /** Collection of CL element-wise functions */ struct NEEltwiseFunctions { @@ -213,7 +206,7 @@ std::unique_ptr NEFunctionFactory::create(INode *node, GraphContext & case NodeType::ConcatenateLayer: return detail::create_concatenate_layer(*polymorphic_downcast(node)); case NodeType::DepthwiseConvolutionLayer: - return detail::create_depthwise_convolution_layer(*polymorphic_downcast(node)); + return detail::create_depthwise_convolution_layer(*polymorphic_downcast(node)); case NodeType::DetectionOutputLayer: return detail::create_detection_output_layer(*polymorphic_downcast(node)); case NodeType::DetectionPostProcessLayer: diff --git a/src/graph/backends/NEON/NENodeValidator.cpp b/src/graph/backends/NEON/NENodeValidator.cpp index 734b3401f7..0b53657c42 100644 --- a/src/graph/backends/NEON/NENodeValidator.cpp +++ b/src/graph/backends/NEON/NENodeValidator.cpp @@ -58,8 +58,7 @@ Status NENodeValidator::validate(INode *node) NEGEMMConvolutionLayer, NEWinogradConvolutionLayer>(*polymorphic_downcast(node)); case NodeType::DepthwiseConvolutionLayer: - return detail::validate_depthwise_convolution_layer(*polymorphic_downcast(node)); + return detail::validate_depthwise_convolution_layer(*polymorphic_downcast(node)); case NodeType::DetectionOutputLayer: return detail::validate_detection_output_layer(*polymorphic_downcast(node)); case NodeType::DetectionPostProcessLayer: diff --git a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp index 5ac7a7a7c6..168d7d5c84 100644 --- a/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLDepthwiseConvolutionLayer.cpp @@ -38,14 +38,261 @@ namespace arm_compute using namespace arm_compute::misc; using namespace arm_compute::misc::shape_calculator; +namespace +{ +Status validate_arguments_3x3(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation) +{ + // This function should be removed and incorporated inside CLDepthwiseConvolutionLayerInternal3x3 once CLDepthwiseConvolutionLayer3x3 is properly removed + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); + ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN); + + const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); + const bool is_nhwc = input->data_layout() == DataLayout::NHWC; + const bool needs_permute = is_nhwc && (depth_multiplier > 1); + const bool needs_weights_reshape = is_nhwc && (depth_multiplier == 1) && is_quantized; + const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); + const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); + const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); + DepthwiseConvolutionReshapeInfo info; + info.c0 = 4; + info.transpose = is_stride_1_dilation_1 && is_dot8_supported; + + if(is_quantized) + { + const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); + const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = (output->total_size() == 0) ? iq_info : output->quantization_info().uniform(); + + const float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; + ARM_COMPUTE_UNUSED(multiplier); + ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); + } + + if(needs_permute) + { + TensorShape permuted_input_shape = input->tensor_shape(); + TensorShape permuted_weights_shape = weights->tensor_shape(); + TensorShape permuted_output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); + + permute(permuted_input_shape, PermutationVector(1U, 2U, 0U)); + permute(permuted_weights_shape, PermutationVector(1U, 2U, 0U)); + permute(permuted_output_shape, PermutationVector(1U, 2U, 0U)); + + const TensorInfo permuted_input = input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(DataLayout::NCHW); + const TensorInfo permuted_weights = weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(DataLayout::NCHW); + const TensorInfo permuted_output = output->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(DataLayout::NCHW); + + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(&permuted_input, &permuted_weights, biases, &permuted_output, conv_info, depth_multiplier, act_info, gpu_target, + dilation)); + } + else if(is_nhwc) + { + if(needs_weights_reshape) + { + auto reshaped_weights_shape = arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_shape(*weights, info); + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(input, &weights->clone()->set_tensor_shape(reshaped_weights_shape), biases, output, conv_info, depth_multiplier, + act_info, dilation)); + } + else + { + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); + } + } + else + { + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, gpu_target, dilation)); + } + return Status{}; +} +} // namespace + CLDepthwiseConvolutionLayer3x3::CLDepthwiseConvolutionLayer3x3(std::shared_ptr memory_manager) - : _memory_group(std::move(memory_manager)), _kernel(nullptr), _border_handler(), _permute_input_to_nchw(), _permute_weights_to_nchw(), _permute_output_to_nhwc(), _reshape_weights(), _permuted_input(), - _permuted_weights(), _permuted_output(), _original_weights(nullptr), _needs_permute(false), _needs_weights_reshape(false), _is_prepared(false) + : _func(std::move(memory_manager)) { } void CLDepthwiseConvolutionLayer3x3::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) +{ + _func.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); +} + +Status CLDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation) +{ + return validate_arguments_3x3(input, weights, biases, output, conv_info, depth_multiplier, act_info, gpu_target, dilation); +} + +void CLDepthwiseConvolutionLayer3x3::run() +{ + _func.run(); +} + +void CLDepthwiseConvolutionLayer3x3::prepare() +{ + _func.prepare(); +} + +CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::CLDepthwiseConvolutionLayerGeneric(std::shared_ptr memory_manager) + : _memory_group(std::move(memory_manager)), + _dwc_native_kernel(), + _permute_input_to_nhwc(), + _permute_weights_to_nhwc(), + _permute_output_to_nchw(), + _permuted_input(), + _permuted_weights(), + _permuted_output(), + _original_weights(), + _needs_permute(false), + _is_prepared(false) +{ +} + +void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); + ARM_COMPUTE_ERROR_THROW_ON(CLDepthwiseConvolutionLayer::validate(input->info(), + weights->info(), + biases != nullptr ? biases->info() : nullptr, + output->info(), + conv_info, + depth_multiplier, + act_info, + dilation)); + + _is_prepared = false; + _original_weights = weights; + _needs_permute = input->info()->data_layout() == DataLayout::NCHW; + + ICLTensor *input_to_use = input; + const ICLTensor *weights_to_use = weights; + ICLTensor *output_to_use = output; + if(_needs_permute) + { + _memory_group.manage(&_permuted_input); + _memory_group.manage(&_permuted_output); + + // Configure the function to transform the input tensor from NCHW -> NHWC + _permute_input_to_nhwc.configure(input, &_permuted_input, PermutationVector(2U, 0U, 1U)); + _permuted_input.info()->set_data_layout(DataLayout::NHWC); + + // Configure the function to transform the weights tensor from IHW -> HWI + _permute_weights_to_nhwc.configure(weights, &_permuted_weights, PermutationVector(2U, 0U, 1U)); + _permuted_weights.info()->set_data_layout(DataLayout::NHWC); + + // Set output quantization info before dwc kernel configure + _permuted_output.info()->set_quantization_info(output->info()->quantization_info()); + + input_to_use = &_permuted_input; + weights_to_use = &_permuted_weights; + output_to_use = &_permuted_output; + } + + DWCWeightsKernelInfo dwc_weights_info; + dwc_weights_info.n0 = (depth_multiplier == 1) ? 8 : 1; + DWCKernelInfo dwc_info; + dwc_info.activation_info = act_info; + _dwc_native_kernel.configure(input_to_use, weights_to_use, biases, output_to_use, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation); + + if(_needs_permute) + { + _permuted_input.allocator()->allocate(); + + // Configure the function to transform the convoluted output to NCHW format + _permuted_output.info()->set_data_layout(DataLayout::NCHW); + _permute_output_to_nchw.configure(&_permuted_output, output, PermutationVector(1U, 2U, 0U)); + _permuted_output.allocator()->allocate(); + } +} + +Status CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) +{ + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); + const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); + const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); + + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) > input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); + ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) > input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); + + DWCWeightsKernelInfo dwc_weights_info; + dwc_weights_info.n0 = (depth_multiplier == 1) ? 8 : 1; + DWCKernelInfo dwc_info; + dwc_info.activation_info = act_info; + + const bool needs_permute = input->data_layout() == DataLayout::NCHW; + + if(needs_permute) + { + TensorShape permuted_input_shape = input->tensor_shape(); + TensorShape permuted_weights_shape = weights->tensor_shape(); + TensorShape permuted_output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); + + permute(permuted_input_shape, PermutationVector(2U, 0U, 1U)); + permute(permuted_weights_shape, PermutationVector(2U, 0U, 1U)); + permute(permuted_output_shape, PermutationVector(2U, 0U, 1U)); + + const TensorInfo permuted_input = input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(DataLayout::NHWC); + const TensorInfo permuted_weights = weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(DataLayout::NHWC); + const TensorInfo permuted_output = output->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(DataLayout::NHWC); + + ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(input, &permuted_input, PermutationVector(2U, 0U, 1U))); + ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(weights, &permuted_weights, PermutationVector(2U, 0U, 1U))); + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(&permuted_input, &permuted_weights, biases, &permuted_output, dwc_weights_info, + dwc_info, conv_info, depth_multiplier, dilation)); + ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(&permuted_output, output, PermutationVector(1U, 2U, 0U))); + } + else + { + ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation)); + } + return Status{}; +} + +void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::run() +{ + prepare(); + + MemoryGroupResourceScope scope_mg(_memory_group); + + if(_needs_permute) + { + _permute_input_to_nhwc.run(); + } + CLScheduler::get().enqueue(_dwc_native_kernel); + if(_needs_permute) + { + _permute_output_to_nchw.run(); + } +} + +void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerGeneric::prepare() +{ + if(!_is_prepared) + { + if(_needs_permute) + { + ARM_COMPUTE_ERROR_ON(!_original_weights->is_used()); + + _permuted_weights.allocator()->allocate(); + _permute_weights_to_nhwc.run(); + _original_weights->mark_as_unused(); + } + _is_prepared = true; + } +} + +CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::CLDepthwiseConvolutionLayerInternal3x3(std::shared_ptr memory_manager) + : _memory_group(std::move(memory_manager)), _kernel(nullptr), _border_handler(), _permute_input_to_nchw(), _permute_weights_to_nchw(), _permute_output_to_nhwc(), _reshape_weights(), _permuted_input(), + _permuted_weights(), _permuted_output(), _original_weights(nullptr), _needs_permute(false), _needs_weights_reshape(false), _is_prepared(false) +{ +} + +void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); @@ -136,73 +383,13 @@ void CLDepthwiseConvolutionLayer3x3::configure(ICLTensor *input, const ICLTensor _border_handler.configure(input_to_use, _kernel->border_size(), BorderMode::CONSTANT, zero_value); } -Status CLDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation) +Status CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, unsigned int depth_multiplier, ActivationLayerInfo act_info, GPUTarget gpu_target, const Size2D &dilation) { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN); - - const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); - const bool is_nhwc = input->data_layout() == DataLayout::NHWC; - const bool needs_permute = is_nhwc && (depth_multiplier > 1); - const bool needs_weights_reshape = is_nhwc && (depth_multiplier == 1) && is_quantized; - const bool is_stride_1 = ((conv_info.stride().first == conv_info.stride().second) && (conv_info.stride().first == 1)); - const bool is_stride_1_dilation_1 = (is_stride_1 && dilation.x() == 1 && dilation.y() == 1); - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); - DepthwiseConvolutionReshapeInfo info; - info.c0 = 4; - info.transpose = is_stride_1_dilation_1 && is_dot8_supported; - - if(is_quantized) - { - const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = (output->total_size() == 0) ? iq_info : output->quantization_info().uniform(); - - const float multiplier = iq_info.scale * wq_info.scale / oq_info.scale; - ARM_COMPUTE_UNUSED(multiplier); - ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); - } - - if(needs_permute) - { - TensorShape permuted_input_shape = input->tensor_shape(); - TensorShape permuted_weights_shape = weights->tensor_shape(); - TensorShape permuted_output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); - - permute(permuted_input_shape, PermutationVector(1U, 2U, 0U)); - permute(permuted_weights_shape, PermutationVector(1U, 2U, 0U)); - permute(permuted_output_shape, PermutationVector(1U, 2U, 0U)); - - const TensorInfo permuted_input = input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(DataLayout::NCHW); - const TensorInfo permuted_weights = weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(DataLayout::NCHW); - const TensorInfo permuted_output = output->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(DataLayout::NCHW); - - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(&permuted_input, &permuted_weights, biases, &permuted_output, conv_info, depth_multiplier, act_info, gpu_target, - dilation)); - } - else if(is_nhwc) - { - if(needs_weights_reshape) - { - auto reshaped_weights_shape = arm_compute::misc::shape_calculator::compute_reshaped_depthwise_weights_shape(*weights, info); - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(input, &weights->clone()->set_tensor_shape(reshaped_weights_shape), biases, output, conv_info, depth_multiplier, - act_info, dilation)); - } - else - { - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NHWCKernel::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); - } - } - else - { - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3NCHWKernel::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, gpu_target, dilation)); - } - - return Status{}; + return validate_arguments_3x3(input, weights, biases, output, conv_info, depth_multiplier, act_info, gpu_target, dilation); } -void CLDepthwiseConvolutionLayer3x3::run() +void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::run() { prepare(); @@ -221,7 +408,7 @@ void CLDepthwiseConvolutionLayer3x3::run() } } -void CLDepthwiseConvolutionLayer3x3::prepare() +void CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayerInternal3x3::prepare() { if(!_is_prepared) { @@ -247,194 +434,91 @@ void CLDepthwiseConvolutionLayer3x3::prepare() } CLDepthwiseConvolutionLayer::CLDepthwiseConvolutionLayer(std::shared_ptr memory_manager) - : _memory_group(std::move(memory_manager)), - _optimised_function(nullptr), - _dwc_native_kernel(), - _permute_input_to_nhwc(), - _permute_weights_to_nhwc(), - _permute_output_to_nchw(), - _permuted_input(), - _permuted_weights(), - _permuted_output(), - _original_weights(), - _needs_permute(false), - _is_prepared(false) + : _memory_manager(std::move(memory_manager)), _depth_conv_func(DepthwiseConvolutionFunction::GENERIC), _func_3x3(), _func_generic() { } -void CLDepthwiseConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) +void CLDepthwiseConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, + ActivationLayerInfo act_info, const Size2D &dilation) { - ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_ERROR_THROW_ON(CLDepthwiseConvolutionLayer::validate(input->info(), - weights->info(), - biases != nullptr ? biases->info() : nullptr, - output->info(), - conv_info, - depth_multiplier, - act_info, - dilation)); - - const size_t idx_w = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::WIDTH); - const size_t idx_h = get_data_layout_dimension_index(input->info()->data_layout(), DataLayoutDimension::HEIGHT); - - const GPUTarget gpu_target = CLScheduler::get().target(); - const bool can_run_optimised_3x3_kernel = (weights->info()->dimension(idx_w) == 3) && (weights->info()->dimension(idx_h) == 3) && (is_data_type_float(input->info()->data_type()) - || (get_arch_from_target(gpu_target) == GPUTarget::MIDGARD)); - - _needs_permute = false; - _is_prepared = false; - _original_weights = weights; - - if(bool(can_run_optimised_3x3_kernel)) + const GPUTarget gpu_target = CLScheduler::get().target(); + _depth_conv_func = get_depthwiseconvolution_function(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, + dilation, gpu_target); + switch(_depth_conv_func) { - auto f = arm_compute::support::cpp14::make_unique(); - f->configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); - _optimised_function = std::move(f); - } - else - { - _needs_permute = input->info()->data_layout() == DataLayout::NCHW; - - ICLTensor *input_to_use = input; - const ICLTensor *weights_to_use = weights; - ICLTensor *output_to_use = output; - if(_needs_permute) - { - _memory_group.manage(&_permuted_input); - _memory_group.manage(&_permuted_output); - - // Configure the function to transform the input tensor from NCHW -> NHWC - _permute_input_to_nhwc.configure(input, &_permuted_input, PermutationVector(2U, 0U, 1U)); - _permuted_input.info()->set_data_layout(DataLayout::NHWC); - - // Configure the function to transform the weights tensor from IHW -> HWI - _permute_weights_to_nhwc.configure(weights, &_permuted_weights, PermutationVector(2U, 0U, 1U)); - _permuted_weights.info()->set_data_layout(DataLayout::NHWC); - - // Set output quantization info before dwc kernel configure - _permuted_output.info()->set_quantization_info(output->info()->quantization_info()); - - input_to_use = &_permuted_input; - weights_to_use = &_permuted_weights; - output_to_use = &_permuted_output; - } - - DWCWeightsKernelInfo dwc_weights_info; - dwc_weights_info.n0 = (depth_multiplier == 1) ? 8 : 1; - DWCKernelInfo dwc_info; - dwc_info.activation_info = act_info; - _dwc_native_kernel.configure(input_to_use, weights_to_use, biases, output_to_use, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation); - - if(_needs_permute) + case DepthwiseConvolutionFunction::OPTIMIZED: + _func_3x3.set_memory_group(_memory_manager); + _func_3x3.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + break; + case DepthwiseConvolutionFunction::GENERIC: { - _permuted_input.allocator()->allocate(); - - // Configure the function to transform the convoluted output to NCHW format - _permuted_output.info()->set_data_layout(DataLayout::NCHW); - _permute_output_to_nchw.configure(&_permuted_output, output, PermutationVector(1U, 2U, 0U)); - _permuted_output.allocator()->allocate(); + _func_generic.set_memory_group(_memory_manager); + _func_generic.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } + break; + default: + ARM_COMPUTE_ERROR("Unsupported DepthwiseConvolutionFunction"); } } Status CLDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) + unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); - - const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); - const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); - - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) > input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) > input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); - - const GPUTarget gpu_target = CLScheduler::get().target(); - const bool can_run_optimised_3x3_kernel = (weights->dimension(idx_w) == 3) && (weights->dimension(idx_h) == 3) && (is_data_type_float(input->data_type()) - || (get_arch_from_target(gpu_target) == GPUTarget::MIDGARD)); - - if(!can_run_optimised_3x3_kernel) + const GPUTarget gpu_target = CLScheduler::get().target(); + DepthwiseConvolutionFunction depth_conv_func = get_depthwiseconvolution_function(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation, gpu_target); + switch(depth_conv_func) { - DWCWeightsKernelInfo dwc_weights_info; - dwc_weights_info.n0 = (depth_multiplier == 1) ? 8 : 1; - DWCKernelInfo dwc_info; - dwc_info.activation_info = act_info; - - const bool needs_permute = input->data_layout() == DataLayout::NCHW; + case DepthwiseConvolutionFunction::OPTIMIZED: + return CLDepthwiseConvolutionLayerInternal3x3::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, gpu_target, dilation); + case DepthwiseConvolutionFunction::GENERIC: + return CLDepthwiseConvolutionLayerGeneric::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + default: + ARM_COMPUTE_ERROR("Unsupported DepthwiseConvolutionFunction"); + } +} - if(needs_permute) - { - TensorShape permuted_input_shape = input->tensor_shape(); - TensorShape permuted_weights_shape = weights->tensor_shape(); - TensorShape permuted_output_shape = shape_calculator::compute_depthwise_convolution_shape(*input, *weights, conv_info, depth_multiplier, dilation); - - permute(permuted_input_shape, PermutationVector(2U, 0U, 1U)); - permute(permuted_weights_shape, PermutationVector(2U, 0U, 1U)); - permute(permuted_output_shape, PermutationVector(2U, 0U, 1U)); - - const TensorInfo permuted_input = input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_input_shape).set_data_layout(DataLayout::NHWC); - const TensorInfo permuted_weights = weights->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_weights_shape).set_data_layout(DataLayout::NHWC); - const TensorInfo permuted_output = output->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(permuted_output_shape).set_data_layout(DataLayout::NHWC); - - ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(input, &permuted_input, PermutationVector(2U, 0U, 1U))); - ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(weights, &permuted_weights, PermutationVector(2U, 0U, 1U))); - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(&permuted_input, &permuted_weights, biases, &permuted_output, dwc_weights_info, - dwc_info, conv_info, depth_multiplier, dilation)); - ARM_COMPUTE_RETURN_ON_ERROR(CLPermute::validate(&permuted_output, output, PermutationVector(1U, 2U, 0U))); - } - else - { - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayerNativeKernel::validate(input, weights, biases, output, dwc_weights_info, dwc_info, conv_info, depth_multiplier, dilation)); - } +DepthwiseConvolutionFunction CLDepthwiseConvolutionLayer::get_depthwiseconvolution_function(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation, GPUTarget gpu_target) +{ + if(bool(CLDepthwiseConvolutionLayerInternal3x3::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, gpu_target, dilation)) && (is_data_type_float(input->data_type()) + || get_arch_from_target(gpu_target) == GPUTarget::MIDGARD)) + { + return DepthwiseConvolutionFunction::OPTIMIZED; } else { - ARM_COMPUTE_RETURN_ON_ERROR(CLDepthwiseConvolutionLayer3x3::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, GPUTarget::MIDGARD, dilation)); + return DepthwiseConvolutionFunction::GENERIC; } - return Status{}; } void CLDepthwiseConvolutionLayer::run() { - prepare(); - - MemoryGroupResourceScope scope_mg(_memory_group); - - if(_optimised_function != nullptr) + switch(_depth_conv_func) { - _optimised_function->run(); - } - else - { - if(_needs_permute) - { - _permute_input_to_nhwc.run(); - } - CLScheduler::get().enqueue(_dwc_native_kernel); - if(_needs_permute) - { - _permute_output_to_nchw.run(); - } + case DepthwiseConvolutionFunction::OPTIMIZED: + _func_3x3.run(); + break; + case DepthwiseConvolutionFunction::GENERIC: + _func_generic.run(); + break; + default: + ARM_COMPUTE_ERROR("DepthwiseConvolutionFunction not properly configured"); } } void CLDepthwiseConvolutionLayer::prepare() { - if(_optimised_function != nullptr) + switch(_depth_conv_func) { - _optimised_function->prepare(); - } - else if(!_is_prepared) - { - if(_needs_permute) - { - ARM_COMPUTE_ERROR_ON(!_original_weights->is_used()); - - _permuted_weights.allocator()->allocate(); - _permute_weights_to_nhwc.run(); - _original_weights->mark_as_unused(); - } - _is_prepared = true; + case DepthwiseConvolutionFunction::OPTIMIZED: + _func_3x3.prepare(); + break; + case DepthwiseConvolutionFunction::GENERIC: + _func_generic.prepare(); + break; + default: + ARM_COMPUTE_ERROR("DepthwiseConvolutionFunction not properly configured"); } } } // namespace arm_compute diff --git a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp index 76ae1fba3a..6cf7b97e66 100644 --- a/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEDepthwiseConvolutionLayer.cpp @@ -33,203 +33,10 @@ using namespace arm_compute::misc::shape_calculator; namespace arm_compute { -NEDepthwiseConvolutionLayer3x3::NEDepthwiseConvolutionLayer3x3(std::shared_ptr memory_manager) - : _memory_group(memory_manager), _dwc_kernel(), _dwc_optimized_func(memory_manager), _output_stage_kernel(), _border_handler(), _permute_input(), _permute_weights(), _permute_output(), - _activationlayer_function(), _accumulator(), _permuted_input(), _permuted_weights(), _permuted_output(), _original_weights(nullptr), _has_bias(false), _is_quantized(false), _is_optimized(false), - _is_nchw(true), _permute(false), _is_activationlayer_enabled(false), _is_prepared(false) -{ -} - -void NEDepthwiseConvolutionLayer3x3::configure_generic(ITensor *input, - const ITensor *weights, - const ITensor *biases, - ITensor *output, - const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) +namespace { - ARM_COMPUTE_UNUSED(act_info); - - PixelValue zero_value(0.f); - - // Initialize the intermediate accumulator tensor in case of quantized input - if(_is_quantized) - { - TensorShape accum_shape = output->info()->tensor_shape(); - DataLayout accum_layout = output->info()->data_layout(); - if(!_is_nchw) - { - permute(accum_shape, PermutationVector(1U, 2U, 0U)); - accum_layout = DataLayout::NCHW; - } - - _memory_group.manage(&_accumulator); - _accumulator.allocator()->init(TensorInfo(accum_shape, 1, DataType::S32, output->info()->quantization_info())); - _accumulator.info()->set_data_layout(accum_layout); - zero_value = PixelValue(static_cast(input->info()->quantization_info().uniform().offset)); - } - - if(!_is_nchw) - { - _memory_group.manage(&_permuted_input); - _memory_group.manage(&_permuted_output); - - // Configure the function to transform the input tensor from NHWC -> NCHW - _permute_input.configure(input, &_permuted_input, PermutationVector(1U, 2U, 0U)); - _permuted_input.info()->set_data_layout(DataLayout::NCHW); - - // Configure the function to transform the weights tensor from HWI -> IHW - _permute_weights.configure(weights, &_permuted_weights, PermutationVector(1U, 2U, 0U)); - _permuted_weights.info()->set_data_layout(DataLayout::NCHW); - _permuted_output.info()->set_quantization_info(output->info()->quantization_info()); - - // Configure depthwise - _dwc_kernel.configure(&_permuted_input, &_permuted_weights, (_is_quantized) ? &_accumulator : &_permuted_output, conv_info, depth_multiplier, dilation); - - // Configure border handler - _border_handler.configure(&_permuted_input, _dwc_kernel.border_size(), BorderMode::CONSTANT, zero_value); - - // Allocate tensors - _permuted_input.allocator()->allocate(); - } - else - { - // Configure depthwise convolution kernel - _dwc_kernel.configure(input, weights, (_is_quantized) ? &_accumulator : output, conv_info, depth_multiplier, dilation); - - // Configure border handler - _border_handler.configure(input, _dwc_kernel.border_size(), BorderMode::CONSTANT, zero_value); - } - - // Configure biases accumulation - if(_is_quantized) - { - const UniformQuantizationInfo iq_info = input->info()->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->info()->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = (output->info()->total_size() == 0) ? iq_info : output->info()->quantization_info().uniform(); - - float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; - int output_multiplier; - int output_shift; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - _output_stage_kernel.configure(&_accumulator, biases, _is_nchw ? output : &_permuted_output, output_multiplier, output_shift, oq_info.offset); - _accumulator.allocator()->allocate(); - } - else if(_has_bias) - { - _output_stage_kernel.configure(_is_nchw ? output : &_permuted_output, biases); - } - - // Permute output - if(!_is_nchw) - { - // Configure the function to transform the convoluted output to NHWC - _permute_output.configure(&_permuted_output, output, PermutationVector(2U, 0U, 1U)); - _permuted_output.allocator()->allocate(); - } -} - -void NEDepthwiseConvolutionLayer3x3::configure_optimized(const ITensor *input, - const ITensor *weights, - const ITensor *biases, - ITensor *output, - const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info) -{ - ActivationLayerInfo act_info_to_use = ActivationLayerInfo(); - const bool is_relu = arm_compute::utils::info_helpers::is_relu(act_info); - const bool is_relu6 = arm_compute::utils::info_helpers::is_relu6(act_info); - _is_activationlayer_enabled = act_info.enabled() && !(is_relu || is_relu6); - if(!_is_activationlayer_enabled) - { - act_info_to_use = act_info; - } - - if(_is_nchw) - { - _memory_group.manage(&_permuted_input); - _memory_group.manage(&_permuted_output); - - // Configure the function to transform the input tensor from NCHW -> NHWC - _permute_input.configure(input, &_permuted_input, PermutationVector(2U, 0U, 1U)); - _permuted_input.info()->set_data_layout(DataLayout::NHWC); - - // Configure the function to transform the weights tensor from IHW -> HWI - _permute_weights.configure(weights, &_permuted_weights, PermutationVector(2U, 0U, 1U)); - _permuted_weights.info()->set_data_layout(DataLayout::NHWC); - - _permuted_output.info()->set_data_layout(DataLayout::NHWC); - _permuted_output.info()->set_quantization_info(output->info()->quantization_info()); - - // Configure optimized depthwise - _dwc_optimized_func.configure(&_permuted_input, &_permuted_weights, biases, &_permuted_output, conv_info, depth_multiplier, act_info_to_use); - - // Configure the function to transform the convoluted output to ACL's native ordering format NCHW - _permuted_output.info()->set_data_layout(DataLayout::NHWC); - _permute_output.configure(&_permuted_output, output, PermutationVector(1U, 2U, 0U)); - - // Allocate tensors - _permuted_input.allocator()->allocate(); - _permuted_output.allocator()->allocate(); - } - else - { - _dwc_optimized_func.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info_to_use); - } -} - -void NEDepthwiseConvolutionLayer3x3::configure(ITensor *input, - const ITensor *weights, - const ITensor *biases, - ITensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(NEDepthwiseConvolutionLayer3x3::validate(input->info(), weights->info(), (biases == nullptr) ? nullptr : biases->info(), - output->info(), conv_info, depth_multiplier, act_info, dilation)); - - _original_weights = weights; - _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); - _has_bias = biases != nullptr; - _is_optimized = NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input->info(), - weights->info(), - conv_info, - depth_multiplier, dilation); - _is_nchw = input->info()->data_layout() == DataLayout::NCHW; - _permute = _is_optimized == _is_nchw; - _is_prepared = false; - _is_activationlayer_enabled = act_info.enabled(); - - // Configure appropriate pipeline - if(_is_optimized) - { - configure_optimized(input, weights, biases, output, conv_info, depth_multiplier, act_info); - } - else - { - configure_generic(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); - } - - // Configure activation - if(_is_activationlayer_enabled) - { - _activationlayer_function.configure(output, nullptr, act_info); - } -} - -Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input, - const ITensorInfo *weights, - const ITensorInfo *biases, - const ITensorInfo *output, - const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) +Status validate_arguments_optimized(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); @@ -248,28 +55,32 @@ Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(channel_idx)); } + const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); + + if(is_quantized) + { + const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); + const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); + const UniformQuantizationInfo oq_info = output->quantization_info().uniform(); + + float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; + ARM_COMPUTE_UNUSED(multiplier); + ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); + } + if(!NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input, weights, conv_info, depth_multiplier, dilation)) { - const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); - TensorInfo accumulator = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32)); - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseConvolutionLayer3x3Kernel::validate(input, weights, is_quantized ? &accumulator : output, conv_info, depth_multiplier)); + TensorInfo accumulator = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32)); + ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseConvolutionLayer3x3Kernel::validate(input, weights, is_quantized ? &accumulator : output, conv_info, depth_multiplier, dilation)); if(is_quantized) { - const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = output->quantization_info().uniform(); - - float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; - int output_multiplier; - int output_shift; - ARM_COMPUTE_RETURN_ON_ERROR(quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift)); - ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerOutputStageKernel::validate(&accumulator, biases, output, output_multiplier, output_shift, oq_info.offset)); + ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerOutputStageKernel::validate(&accumulator, biases, output)); } } else { - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseConvolutionAssemblyDispatch::validate(input, weights, biases, output, conv_info, depth_multiplier)); + ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseConvolutionAssemblyDispatch::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); } //Validate Activation Layer @@ -280,102 +91,55 @@ Status NEDepthwiseConvolutionLayer3x3::validate(const ITensorInfo *input return Status{}; } +} // namespace -void NEDepthwiseConvolutionLayer3x3::run_generic() +NEDepthwiseConvolutionLayerOptimized::NEDepthwiseConvolutionLayerOptimized(std::shared_ptr memory_manager) + : _func(std::move(memory_manager)) { - // Fill border - NEScheduler::get().schedule(&_border_handler, Window::DimX); - - // Execute depthwise convolution - NEScheduler::get().schedule(&_dwc_kernel, Window::DimX); - - // Add biases - if(_has_bias || _is_quantized) - { - NEScheduler::get().schedule(&_output_stage_kernel, Window::DimX); - } - - // Permute output - if(!_is_nchw) - { - _permute_output.run(); - } } -void NEDepthwiseConvolutionLayer3x3::run_optimized() +void NEDepthwiseConvolutionLayerOptimized::configure(ITensor *input, + const ITensor *weights, + const ITensor *biases, + ITensor *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, + const ActivationLayerInfo &act_info, + const Size2D &dilation) { - // Run assembly function - _dwc_optimized_func.run(); - - // Permute output - if(_is_nchw) - { - _permute_output.run(); - } + _func.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } -void NEDepthwiseConvolutionLayer3x3::run() +Status NEDepthwiseConvolutionLayerOptimized::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { - prepare(); - - MemoryGroupResourceScope scope_mg(_memory_group); - - // Permute input - if(_permute) - { - _permute_input.run(); - } - - _is_optimized ? run_optimized() : run_generic(); - - // Run activation - if(_is_activationlayer_enabled) - { - _activationlayer_function.run(); - } + return validate_arguments_optimized(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } -void NEDepthwiseConvolutionLayer3x3::prepare() +void NEDepthwiseConvolutionLayerOptimized::run() { - if(!_is_prepared) - { - // Permute weights - if(_permute) - { - _permuted_weights.allocator()->allocate(); - _permute_weights.run(); - _original_weights->mark_as_unused(); - } - - // Prepare optimized function - if(_is_optimized) - { - _dwc_optimized_func.prepare(); - if(!_permuted_weights.is_used()) - { - _permuted_weights.allocator()->free(); - } - } + _func.run(); +} - _is_prepared = true; - } +void NEDepthwiseConvolutionLayerOptimized::prepare() +{ + _func.prepare(); } -NEDepthwiseConvolutionLayerOptimized::NEDepthwiseConvolutionLayerOptimized(std::shared_ptr memory_manager) +NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::NEDepthwiseConvolutionLayerOptimizedInternal(std::shared_ptr memory_manager) : _memory_group(memory_manager), _dwc_kernel(), _dwc_optimized_func(memory_manager), _output_stage_kernel(), _border_handler(), _permute_input(), _permute_weights(), _permute_output(), _activationlayer_function(), _accumulator(), _permuted_input(), _permuted_weights(), _permuted_output(), _original_weights(nullptr), _has_bias(false), _is_quantized(false), _is_optimized(false), _is_nchw(true), _permute(false), _is_activationlayer_enabled(false), _is_prepared(false) { } -void NEDepthwiseConvolutionLayerOptimized::configure_generic(ITensor *input, - const ITensor *weights, - const ITensor *biases, - ITensor *output, - const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::configure_generic(ITensor *input, + const ITensor *weights, + const ITensor *biases, + ITensor *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, + const ActivationLayerInfo &act_info, + const Size2D &dilation) { ARM_COMPUTE_UNUSED(act_info); @@ -458,14 +222,14 @@ void NEDepthwiseConvolutionLayerOptimized::configure_generic(ITensor } } -void NEDepthwiseConvolutionLayerOptimized::configure_optimized(const ITensor *input, - const ITensor *weights, - const ITensor *biases, - ITensor *output, - const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::configure_optimized(const ITensor *input, + const ITensor *weights, + const ITensor *biases, + ITensor *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, + const ActivationLayerInfo &act_info, + const Size2D &dilation) { ActivationLayerInfo act_info_to_use = ActivationLayerInfo(); const bool is_relu = arm_compute::utils::info_helpers::is_relu(act_info); @@ -509,18 +273,18 @@ void NEDepthwiseConvolutionLayerOptimized::configure_optimized(const ITensor } } -void NEDepthwiseConvolutionLayerOptimized::configure(ITensor *input, - const ITensor *weights, - const ITensor *biases, - ITensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::configure(ITensor *input, + const ITensor *weights, + const ITensor *biases, + ITensor *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, + const ActivationLayerInfo &act_info, + const Size2D &dilation) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); // Perform validation step - ARM_COMPUTE_ERROR_THROW_ON(NEDepthwiseConvolutionLayerOptimized::validate(input->info(), weights->info(), (biases == nullptr) ? nullptr : biases->info(), - output->info(), conv_info, depth_multiplier, act_info, dilation)); + ARM_COMPUTE_ERROR_THROW_ON(NEDepthwiseConvolutionLayerOptimizedInternal::validate(input->info(), weights->info(), (biases == nullptr) ? nullptr : biases->info(), + output->info(), conv_info, depth_multiplier, act_info, dilation)); _original_weights = weights; _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); @@ -552,70 +316,19 @@ void NEDepthwiseConvolutionLayerOptimized::configure(ITensor *input, } } -Status NEDepthwiseConvolutionLayerOptimized::validate(const ITensorInfo *input, - const ITensorInfo *weights, - const ITensorInfo *biases, - const ITensorInfo *output, - const PadStrideInfo &conv_info, - unsigned int depth_multiplier, - const ActivationLayerInfo &act_info, - const Size2D &dilation) +Status NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::validate(const ITensorInfo *input, + const ITensorInfo *weights, + const ITensorInfo *biases, + const ITensorInfo *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, + const ActivationLayerInfo &act_info, + const Size2D &dilation) { - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); - ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::UNKNOWN); - ARM_COMPUTE_RETURN_ERROR_ON(dilation.x() < 1 || dilation.y() < 1); - const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH); - const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_w) + (weights->dimension(idx_w) - 1) * (dilation.x() - 1) > input->dimension(idx_w) + conv_info.pad_left() + conv_info.pad_right()); - ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(idx_h) + (weights->dimension(idx_h) - 1) * (dilation.y() - 1) > input->dimension(idx_h) + conv_info.pad_top() + conv_info.pad_bottom()); - - if(biases != nullptr) - { - const unsigned int channel_idx = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL); - ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() > 1); - ARM_COMPUTE_RETURN_ERROR_ON(biases->dimension(0) != weights->dimension(channel_idx)); - } - - const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type()); - - if(is_quantized) - { - const UniformQuantizationInfo iq_info = input->quantization_info().uniform(); - const UniformQuantizationInfo wq_info = weights->quantization_info().uniform(); - const UniformQuantizationInfo oq_info = output->quantization_info().uniform(); - - float multiplier = (iq_info.scale * wq_info.scale) / oq_info.scale; - ARM_COMPUTE_UNUSED(multiplier); - ARM_COMPUTE_RETURN_ERROR_ON(multiplier > 1.0f); - } - - if(!NEDepthwiseConvolutionAssemblyDispatch::is_optimized_supported(input, weights, conv_info, depth_multiplier, dilation)) - { - TensorInfo accumulator = TensorInfo(output->clone()->set_is_resizable(true).reset_padding().set_data_type(DataType::S32)); - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseConvolutionLayer3x3Kernel::validate(input, weights, is_quantized ? &accumulator : output, conv_info, depth_multiplier, dilation)); - - if(is_quantized) - { - ARM_COMPUTE_RETURN_ON_ERROR(NEDirectConvolutionLayerOutputStageKernel::validate(&accumulator, biases, output)); - } - } - else - { - ARM_COMPUTE_RETURN_ON_ERROR(NEDepthwiseConvolutionAssemblyDispatch::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation)); - } - - //Validate Activation Layer - if(act_info.enabled()) - { - ARM_COMPUTE_RETURN_ON_ERROR(NEActivationLayer::validate(output, nullptr, act_info)); - } - - return Status{}; + return validate_arguments_optimized(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); } -void NEDepthwiseConvolutionLayerOptimized::run_generic() +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::run_generic() { // Fill border NEScheduler::get().schedule(&_border_handler, Window::DimX); @@ -636,7 +349,7 @@ void NEDepthwiseConvolutionLayerOptimized::run_generic() } } -void NEDepthwiseConvolutionLayerOptimized::run_optimized() +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::run_optimized() { // Run assembly function _dwc_optimized_func.run(); @@ -648,7 +361,7 @@ void NEDepthwiseConvolutionLayerOptimized::run_optimized() } } -void NEDepthwiseConvolutionLayerOptimized::run() +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::run() { prepare(); @@ -669,7 +382,7 @@ void NEDepthwiseConvolutionLayerOptimized::run() } } -void NEDepthwiseConvolutionLayerOptimized::prepare() +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerOptimizedInternal::prepare() { if(!_is_prepared) { @@ -695,14 +408,14 @@ void NEDepthwiseConvolutionLayerOptimized::prepare() } } -NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayer() +NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerGeneric::NEDepthwiseConvolutionLayerGeneric() : _depthwise_conv_kernel(), _fill_border(), _permute_input(), _permute_weights(), _permute_output(), _activationlayer_function(), _permuted_input(), _permuted_weights(), _permuted_output(), _is_prepared(false), _is_nchw(false), _is_activationlayer_enabled(false), _original_weights(nullptr) { } -void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerGeneric::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_ERROR_THROW_ON(NEDepthwiseConvolutionLayer::validate(input->info(), weights->info(), (biases == nullptr) ? nullptr : biases->info(), @@ -750,8 +463,9 @@ void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weigh } } -Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) +Status NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerGeneric::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); if(input->data_layout() == DataLayout::NCHW) @@ -787,7 +501,7 @@ Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITe return Status{}; } -void NEDepthwiseConvolutionLayer::run() +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerGeneric::run() { if(_is_nchw) { @@ -809,7 +523,7 @@ void NEDepthwiseConvolutionLayer::run() } } -void NEDepthwiseConvolutionLayer::prepare() +void NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayerGeneric::prepare() { if(!_is_prepared) { @@ -820,4 +534,87 @@ void NEDepthwiseConvolutionLayer::prepare() _is_prepared = true; } } + +NEDepthwiseConvolutionLayer::NEDepthwiseConvolutionLayer(std::shared_ptr memory_manager) + : _depth_conv_func(DepthwiseConvolutionFunction::GENERIC), _func_optimized(std::move(memory_manager)), _func_generic() +{ +} + +void NEDepthwiseConvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, unsigned int depth_multiplier, + const ActivationLayerInfo &act_info, const Size2D &dilation) +{ + _depth_conv_func = get_depthwiseconvolution_function(input->info(), weights->info(), (biases != nullptr) ? biases->info() : nullptr, output->info(), conv_info, depth_multiplier, act_info, dilation); + switch(_depth_conv_func) + { + case DepthwiseConvolutionFunction::OPTIMIZED: + _func_optimized.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + break; + case DepthwiseConvolutionFunction::GENERIC: + _func_generic.configure(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + break; + default: + ARM_COMPUTE_ERROR("Unsupported DepthwiseConvolutionFunction"); + } +} + +Status NEDepthwiseConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + unsigned int depth_multiplier, const ActivationLayerInfo &act_info, const Size2D &dilation) +{ + DepthwiseConvolutionFunction depth_conv_func = get_depthwiseconvolution_function(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + switch(depth_conv_func) + { + case DepthwiseConvolutionFunction::OPTIMIZED: + return NEDepthwiseConvolutionLayerOptimized::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + break; + case DepthwiseConvolutionFunction::GENERIC: + return NEDepthwiseConvolutionLayerGeneric::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation); + break; + default: + ARM_COMPUTE_ERROR("Unsupported DepthwiseConvolutionFunction"); + } +} + +DepthwiseConvolutionFunction NEDepthwiseConvolutionLayer::get_depthwiseconvolution_function(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, + const PadStrideInfo &conv_info, + unsigned int depth_multiplier, ActivationLayerInfo act_info, const Size2D &dilation) +{ + if(bool(NEDepthwiseConvolutionLayerOptimized::validate(input, weights, biases, output, conv_info, depth_multiplier, act_info, dilation))) + { + return DepthwiseConvolutionFunction::OPTIMIZED; + } + else + { + return DepthwiseConvolutionFunction::GENERIC; + } +} + +void NEDepthwiseConvolutionLayer::run() +{ + switch(_depth_conv_func) + { + case DepthwiseConvolutionFunction::OPTIMIZED: + _func_optimized.run(); + break; + case DepthwiseConvolutionFunction::GENERIC: + _func_generic.run(); + break; + default: + ARM_COMPUTE_ERROR("DepthwiseConvolutionFunction not properly configured"); + } +} + +void NEDepthwiseConvolutionLayer::prepare() +{ + switch(_depth_conv_func) + { + case DepthwiseConvolutionFunction::OPTIMIZED: + _func_optimized.prepare(); + break; + case DepthwiseConvolutionFunction::GENERIC: + _func_generic.prepare(); + break; + default: + ARM_COMPUTE_ERROR("DepthwiseConvolutionFunction not properly configured"); + } +} } // namespace arm_compute -- cgit v1.2.1