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Diffstat (limited to 'src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelGraph.cpp')
| -rw-r--r-- | src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelGraph.cpp | 271 |
1 files changed, 0 insertions, 271 deletions
diff --git a/src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelGraph.cpp b/src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelGraph.cpp deleted file mode 100644 index cab51a2ce6..0000000000 --- a/src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelGraph.cpp +++ /dev/null @@ -1,271 +0,0 @@ -/* - * Copyright (c) 2022 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. - */ -#ifdef ENABLE_EXPERIMENTAL_DYNAMIC_FUSION -#include "arm_compute/core/utils/misc/ShapeCalculator.h" - -#include "src/core/CL/CLValidate.h" -#include "src/core/experimental/dynamic_fusion/ClKernelBuildingAPI.h" -#include "src/core/experimental/dynamic_fusion/WorkloadImpl/ClKernelGraph.h" - -#include "support/Cast.h" - -namespace arm_compute -{ -namespace experimental -{ -namespace dynamic_fusion -{ -Status ClDirectConv2dKernel::generate(ClKernelBlueprint &bp) const -{ - const auto input = _tensors.get_const_tensor(TensorType::ACL_SRC_0); - const auto weight = _tensors.get_const_tensor(TensorType::ACL_SRC_1); - const auto bias = _tensors.get_const_tensor(TensorType::ACL_SRC_2); - const auto dst = _tensors.get_const_tensor(TensorType::ACL_DST_0); - ARM_COMPUTE_ERROR_ON_NULLPTR(input, weight, dst); - ArgumentID input_id; - add_tensor(bp, input->desc, input_id, input->id); - ArgumentID weight_id; - add_tensor(bp, weight->desc, weight_id, weight->id); - ArgumentID bias_id = g_arg_placeholder; - if(bias != nullptr) - { - add_tensor(bp, bias->desc, bias_id, bias->id); - } - ArgumentID dst_id; - add_tensor(bp, dst->desc, dst_id, dst->id); - - add_kcomp_direct_conv2d(bp, desc, input_id, weight_id, bias_id, dst_id); - return Status{}; -} -Status ClDirectConv2dKernel::validate(const ITensorInfo *src, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *dst, const ClDirectConv2dKernelDescriptor &conv2d_desc) -{ - // 1. Check validity - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, weights, dst); - // Matching data type - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, weights); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); - if(biases != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, biases); - } - - // Matching data layout - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, weights); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, dst); - if(biases != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, biases); - } - - // All tensor infos are initialized - ARM_COMPUTE_RETURN_ERROR_ON(src->tensor_shape().total_size() == 0); - ARM_COMPUTE_RETURN_ERROR_ON(weights->tensor_shape().total_size() == 0); - ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0); - if(biases != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON(biases->tensor_shape().total_size() == 0); - } - // Device requirements are met - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src); - // weights shape is correct - const DataLayout data_layout = src->data_layout(); - const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->dimension(channel_idx) != src->dimension(channel_idx), "Weights feature map dimension should match the respective src's one"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(weights->num_dimensions() > 4, "Weights can be at most 4 dimensional"); - - // dst shape is correct - PadStrideInfo legacy_pad_stride(conv2d_desc.conv2d.stride.x(), conv2d_desc.conv2d.stride.y(), conv2d_desc.conv2d.pad.left, conv2d_desc.conv2d.pad.right, conv2d_desc.conv2d.pad.top, - conv2d_desc.conv2d.pad.bottom, DimensionRoundingType{}); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), - misc::shape_calculator::compute_deep_convolution_shape(*src, *weights, legacy_pad_stride)); - - // biases shape is correct - if(biases != nullptr) - { - ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->dimension(0) != weights->dimension(3), - "Biases size and number of dst feature maps should match"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(biases->num_dimensions() > 1, - "Biases should be one dimensional"); - } - - // 2. Check support level - // Data type - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F16, DataType::F32); - // Data layout - ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(src, DataLayout::NHWC); - - return Status{}; -} - -bool ClDirectConv2dKernel::operator==(const ClKernel &other) const -{ - const auto converted = *utils::cast::polymorphic_downcast<const ClDirectConv2dKernel *>(&other); - return config() == other.config() && tensors() == other.tensors() && desc == converted.desc; -} - -Status ClElementwiseKernel::generate(ClKernelBlueprint &bp) const -{ - const auto lhs = _tensors.get_const_tensor(TensorType::ACL_SRC_0); - const auto rhs = _tensors.get_const_tensor(TensorType::ACL_SRC_1); - const auto dst = _tensors.get_const_tensor(TensorType::ACL_DST_0); - ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst); - ArgumentID lhs_id; - add_tensor(bp, lhs->desc, lhs_id, lhs->id); - ArgumentID rhs_id; - add_tensor(bp, rhs->desc, rhs_id, rhs->id); - ArgumentID dst_id; - add_tensor(bp, dst->desc, dst_id, dst->id); - - add_kcomp_eltwise_op(bp, desc, lhs_id, rhs_id, dst_id); - return Status{}; -} - -Status ClElementwiseKernel::validate(const ITensorInfo *lhs, const ITensorInfo *rhs, const ITensorInfo *dst) -{ - // 1. Check validity - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst); - - // Matching data type - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); - - // Matching data layout - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(lhs, rhs); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(lhs, dst); - - // All tensor infos are initialized - ARM_COMPUTE_RETURN_ERROR_ON(lhs->tensor_shape().total_size() == 0); - ARM_COMPUTE_RETURN_ERROR_ON(rhs->tensor_shape().total_size() == 0); - ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0); - - // Device requirements are met - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(lhs); - - const bool in_place = (lhs == dst) || (rhs == dst); - const bool src0_in_place = in_place && (lhs == dst); - - // dst shape is correct - const TensorShape out_shape = TensorShape::broadcast_shape(lhs->tensor_shape(), rhs->tensor_shape()); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, dst->tensor_shape(), 0), "Wrong shape for dst"); - if(in_place) - { - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, src0_in_place ? lhs->tensor_shape() : rhs->tensor_shape(), 0), - "Wrong shape for dst, cannot do in_place calculation"); - } - - // 2. Check support level - - // Data type - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::F32, DataType::F16); - - // Data layout - ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(lhs, DataLayout::NHWC); - - return Status{}; -} - -bool ClElementwiseKernel::operator==(const ClKernel &other) const -{ - const auto converted = *utils::cast::polymorphic_downcast<const ClElementwiseKernel *>(&other); - return config() == other.config() && tensors() == other.tensors() && desc == converted.desc; -} - -Status ClFloorKernel::generate(ClKernelBlueprint &bp) const -{ - const auto src = _tensors.get_const_tensor(TensorType::ACL_SRC_0); - const auto dst = _tensors.get_const_tensor(TensorType::ACL_DST_0); - ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); - ArgumentID src_id; - add_tensor(bp, src->desc, src_id, src->id); - ArgumentID dst_id; - add_tensor(bp, dst->desc, dst_id, dst->id); - - add_kcomp_floor(bp, desc, src_id, dst_id); - return Status{}; -} - -Status ClFloorKernel::validate(const ITensorInfo *src, const ITensorInfo *dst) -{ - // 1. Check validity - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); - - // Matching data type - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst); - - // Matching data layout - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, dst); - - // All tensor infos are initialized - ARM_COMPUTE_RETURN_ERROR_ON(src->tensor_shape().total_size() == 0); - ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0); - - // Device requirements are met - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src); - - // dst shape is correct - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(src->tensor_shape(), dst->tensor_shape(), 0), "Wrong shape for dst"); - - // 2. Check support level - - // Data type - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::F32, DataType::F16); - - // Data layout - ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(src, DataLayout::NHWC); - - return Status{}; -} - -bool ClFloorKernel::operator==(const ClKernel &other) const -{ - const auto converted = *utils::cast::polymorphic_downcast<const ClFloorKernel *>(&other); - return config() == other.config() && tensors() == other.tensors() && desc == converted.desc; -} - -std::vector<const ClKernel *> traverse(const ClKernelGraph &graph) -{ - std::vector<const ClKernel *> kernels; - const auto sorted = graph.graph.topological_sort(); - for(const auto &pack : sorted.second) - { - kernels.push_back(graph.kernels.at(pack.op).get()); - } - return kernels; -} - -std::vector<ClKernel *> traverse(ClKernelGraph &graph) -{ - std::vector<ClKernel *> kernels; - const auto sorted = graph.graph.topological_sort(); - for(const auto &pack : sorted.second) - { - kernels.push_back(graph.kernels.at(pack.op).get()); - } - return kernels; -} -} // namespace dynamic_fusion -} // namespace experimental -} // namespace arm_compute -#endif /* ENABLE_EXPERIMENTAL_DYNAMIC_FUSION */
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