src/dynamic_fusion/sketch/gpu/components/cl/ClComponentDepthwiseConv2d.cpp - ml/ComputeLibrary - Gitiles

 /*
  * Copyright (c) 2022-2024 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.
  */
 #include "ClComponentDepthwiseConv2d.h"

 #include "arm_compute/core/CL/CLHelpers.h"
 #include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "arm_compute/dynamic_fusion/sketch/attributes/DepthwiseConv2dAttributes.h"

 #include "src/core/CL/CLValidate.h"
 #include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwDepthwiseConv2d.h"

 namespace arm_compute
 {
 namespace experimental
 {
 namespace dynamic_fusion
 {
 using Settings = ClComponentDepthwiseConv2dSettings;

 Settings &Settings::export_input_to_cl_image(bool cl_image)
 {
     _export_input_to_cl_image = cl_image;
     return *this;
 }

 bool Settings::export_input_to_cl_image() const
 {
     return _export_input_to_cl_image;
 }

 Settings &Settings::export_weights_to_cl_image(bool cl_image)
 {
     _export_weights_to_cl_image = cl_image;
     return *this;
 }

 bool Settings::export_weights_to_cl_image() const
 {
     return _export_weights_to_cl_image;
 }

 Settings &Settings::fast_relaxed_math(bool fast_relaxed_math)
 {
     _fast_relaxed_math = fast_relaxed_math;
     return *this;
 }

 bool Settings::fast_relaxed_math() const
 {
     return _fast_relaxed_math;
 }

 Settings &Settings::is_fma_available(bool is_fma_available)
 {
     _is_fma_available = is_fma_available;
     return *this;
 }

 bool Settings::is_fma_available() const
 {
     return _is_fma_available;
 }

 Settings &Settings::n0(unsigned int n0)
 {
     _n0 = n0;
     return *this;
 }

 unsigned int Settings::n0() const
 {
     return _n0;
 }

 Settings &Settings::m0(unsigned int m0)
 {
     _m0 = m0;
     return *this;
 }

 unsigned int Settings::m0() const
 {
     return _m0;
 }

 Status ClComponentDepthwiseConv2d::validate(const Properties                &properties,
                                             const ArgumentPack<ITensorInfo> &tensors,
                                             const Attributes                &attributes,
                                             const Settings                  &settings)
 {
     ARM_COMPUTE_UNUSED(properties, settings);
     const auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0);
     const auto wei = tensors.get_const_tensor(TensorType::ACL_SRC_1);
     const auto bia = tensors.get_const_tensor(TensorType::ACL_SRC_2);
     const auto dst = tensors.get_const_tensor(TensorType::ACL_DST_0);

     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, wei, dst);

     // 1. Check validity
     // Matching data type
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, wei);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
     if (bia != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, bia);
     }

     // Matching data layout
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, wei);
     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, dst);
     if (bia != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, bia);
     }

     // All tensor infos are initialized
     ARM_COMPUTE_RETURN_ERROR_ON(src->tensor_shape().total_size() == 0);
     ARM_COMPUTE_RETURN_ERROR_ON(wei->tensor_shape().total_size() == 0);
     ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0);
     if (bia != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON(bia->tensor_shape().total_size() == 0);
     }
     // Device requirements are met
     ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src);
     // wei shape is correct
     const DataLayout data_layout = src->data_layout();
     const size_t     channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);

     ARM_COMPUTE_RETURN_ERROR_ON(wei->dimension(channel_idx) !=
                                 (src->dimension(channel_idx) * attributes.depth_multiplier()));
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(wei->num_dimensions() > 3, "Weights can be at most 3 dimensional");

     // dst shape is correct
     const PadStrideInfo pad_stride_info =
         PadStrideInfo(attributes.stride().x(), attributes.stride().y(), attributes.pad().left, attributes.pad().right,
                       attributes.pad().top, attributes.pad().bottom, attributes.dimension_rounding_type());
     const ConvolutionInfo conv_info{pad_stride_info, attributes.depth_multiplier(), ActivationLayerInfo(),
                                     attributes.dilation()};
     const TensorShape output_shape = misc::shape_calculator::compute_depthwise_convolution_shape(*src, *wei, conv_info);

     ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), output_shape);

     // Check strides and dilation
     ARM_COMPUTE_RETURN_ERROR_ON(conv_info.pad_stride_info.stride().first < 1);
     ARM_COMPUTE_RETURN_ERROR_ON(conv_info.pad_stride_info.stride().second < 1);
     ARM_COMPUTE_RETURN_ERROR_ON((conv_info.dilation.x() < 1) || (conv_info.dilation.y() < 1));
     ARM_COMPUTE_RETURN_ERROR_ON(conv_info.pad_stride_info.stride().first > 1 && settings.m0() != 1);
     ARM_COMPUTE_RETURN_ERROR_ON(conv_info.dilation.x() > 1 && settings.m0() != 1);

     if (conv_info.depth_multiplier > 1 && settings.n0() > 1)
     {
         ARM_COMPUTE_RETURN_ERROR_ON((conv_info.depth_multiplier % settings.n0()) != 0);
     }

     // Check export weights to cl image
     ARM_COMPUTE_RETURN_ERROR_ON_MSG((settings.export_weights_to_cl_image() == true) &&
                                         (export_to_cl_image(wei) == false),
                                     "Weights cannot be exported to cl_image!");
     ARM_COMPUTE_RETURN_ERROR_ON((settings.export_weights_to_cl_image() == true) && ((settings.n0() % 4) != 0));

     ARM_COMPUTE_RETURN_ERROR_ON(wei->dimension(channel_idx) !=
                                 (src->dimension(channel_idx) * conv_info.depth_multiplier));

     // bia shape is correct
     if (bia != nullptr)
     {
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(bia->dimension(0) != output_shape[channel_idx],
                                         "Biases size and number of dst feature maps should match");
         ARM_COMPUTE_RETURN_ERROR_ON_MSG(bia->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);
     // Texture in the input tensor
     ARM_COMPUTE_RETURN_ERROR_ON((settings.export_input_to_cl_image() == true));

     return Status{};
 }

 ClComponentDepthwiseConv2d::ClComponentDepthwiseConv2d(ComponentId                      id,
                                                        const Properties                &properties,
                                                        const ArgumentPack<ITensorInfo> &tensors,
                                                        const Attributes                &attributes,
                                                        const Settings                  &settings)
     : IGpuKernelComponent{id, properties, tensors},
       _component_writer{std::make_unique<GpuCkwDepthwiseConv2d>(id, tensors, attributes, settings)}
 {
     ARM_COMPUTE_UNUSED(attributes, settings);
 }
 ClComponentDepthwiseConv2d::~ClComponentDepthwiseConv2d()
 {
 }
 const IGpuCkwComponentDriver *ClComponentDepthwiseConv2d::ckw_component_driver() const
 {
     return _component_writer.get();
 }
 } // namespace dynamic_fusion
 } // namespace experimental
 } // namespace arm_compute
	/*
	* Copyright (c) 2022-2024 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.
	*/
	#include "ClComponentDepthwiseConv2d.h"

	#include "arm_compute/core/CL/CLHelpers.h"
	#include "arm_compute/core/utils/misc/ShapeCalculator.h"
	#include "arm_compute/dynamic_fusion/sketch/attributes/DepthwiseConv2dAttributes.h"

	#include "src/core/CL/CLValidate.h"
	#include "src/dynamic_fusion/sketch/gpu/ckw_driver/components/GpuCkwDepthwiseConv2d.h"

	namespace arm_compute
	{
	namespace experimental
	{
	namespace dynamic_fusion
	{
	using Settings = ClComponentDepthwiseConv2dSettings;

	Settings &Settings::export_input_to_cl_image(bool cl_image)
	{
	_export_input_to_cl_image = cl_image;
	return *this;
	}

	bool Settings::export_input_to_cl_image() const
	{
	return _export_input_to_cl_image;
	}

	Settings &Settings::export_weights_to_cl_image(bool cl_image)
	{
	_export_weights_to_cl_image = cl_image;
	return *this;
	}

	bool Settings::export_weights_to_cl_image() const
	{
	return _export_weights_to_cl_image;
	}

	Settings &Settings::fast_relaxed_math(bool fast_relaxed_math)
	{
	_fast_relaxed_math = fast_relaxed_math;
	return *this;
	}

	bool Settings::fast_relaxed_math() const
	{
	return _fast_relaxed_math;
	}

	Settings &Settings::is_fma_available(bool is_fma_available)
	{
	_is_fma_available = is_fma_available;
	return *this;
	}

	bool Settings::is_fma_available() const
	{
	return _is_fma_available;
	}

	Settings &Settings::n0(unsigned int n0)
	{
	_n0 = n0;
	return *this;
	}

	unsigned int Settings::n0() const
	{
	return _n0;
	}

	Settings &Settings::m0(unsigned int m0)
	{
	_m0 = m0;
	return *this;
	}

	unsigned int Settings::m0() const
	{
	return _m0;
	}

	Status ClComponentDepthwiseConv2d::validate(const Properties &properties,
	const ArgumentPack<ITensorInfo> &tensors,
	const Attributes &attributes,
	const Settings &settings)
	{
	ARM_COMPUTE_UNUSED(properties, settings);
	const auto src = tensors.get_const_tensor(TensorType::ACL_SRC_0);
	const auto wei = tensors.get_const_tensor(TensorType::ACL_SRC_1);
	const auto bia = tensors.get_const_tensor(TensorType::ACL_SRC_2);
	const auto dst = tensors.get_const_tensor(TensorType::ACL_DST_0);

	ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, wei, dst);

	// 1. Check validity
	// Matching data type
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, wei);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, dst);
	if (bia != nullptr)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, bia);
	}

	// Matching data layout
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, wei);
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, dst);
	if (bia != nullptr)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(src, bia);
	}

	// All tensor infos are initialized
	ARM_COMPUTE_RETURN_ERROR_ON(src->tensor_shape().total_size() == 0);
	ARM_COMPUTE_RETURN_ERROR_ON(wei->tensor_shape().total_size() == 0);
	ARM_COMPUTE_RETURN_ERROR_ON(dst->tensor_shape().total_size() == 0);
	if (bia != nullptr)
	{
	ARM_COMPUTE_RETURN_ERROR_ON(bia->tensor_shape().total_size() == 0);
	}
	// Device requirements are met
	ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src);
	// wei shape is correct
	const DataLayout data_layout = src->data_layout();
	const size_t channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);

	ARM_COMPUTE_RETURN_ERROR_ON(wei->dimension(channel_idx) !=
	(src->dimension(channel_idx) * attributes.depth_multiplier()));
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(wei->num_dimensions() > 3, "Weights can be at most 3 dimensional");

	// dst shape is correct
	const PadStrideInfo pad_stride_info =
	PadStrideInfo(attributes.stride().x(), attributes.stride().y(), attributes.pad().left, attributes.pad().right,
	attributes.pad().top, attributes.pad().bottom, attributes.dimension_rounding_type());
	const ConvolutionInfo conv_info{pad_stride_info, attributes.depth_multiplier(), ActivationLayerInfo(),
	attributes.dilation()};
	const TensorShape output_shape = misc::shape_calculator::compute_depthwise_convolution_shape(src, wei, conv_info);

	ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(dst->tensor_shape(), output_shape);

	// Check strides and dilation
	ARM_COMPUTE_RETURN_ERROR_ON(conv_info.pad_stride_info.stride().first < 1);
	ARM_COMPUTE_RETURN_ERROR_ON(conv_info.pad_stride_info.stride().second < 1);
	ARM_COMPUTE_RETURN_ERROR_ON((conv_info.dilation.x() < 1) \|\| (conv_info.dilation.y() < 1));
	ARM_COMPUTE_RETURN_ERROR_ON(conv_info.pad_stride_info.stride().first > 1 && settings.m0() != 1);
	ARM_COMPUTE_RETURN_ERROR_ON(conv_info.dilation.x() > 1 && settings.m0() != 1);

	if (conv_info.depth_multiplier > 1 && settings.n0() > 1)
	{
	ARM_COMPUTE_RETURN_ERROR_ON((conv_info.depth_multiplier % settings.n0()) != 0);
	}

	// Check export weights to cl image
	ARM_COMPUTE_RETURN_ERROR_ON_MSG((settings.export_weights_to_cl_image() == true) &&
	(export_to_cl_image(wei) == false),
	"Weights cannot be exported to cl_image!");
	ARM_COMPUTE_RETURN_ERROR_ON((settings.export_weights_to_cl_image() == true) && ((settings.n0() % 4) != 0));

	ARM_COMPUTE_RETURN_ERROR_ON(wei->dimension(channel_idx) !=
	(src->dimension(channel_idx) * conv_info.depth_multiplier));

	// bia shape is correct
	if (bia != nullptr)
	{
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(bia->dimension(0) != output_shape[channel_idx],
	"Biases size and number of dst feature maps should match");
	ARM_COMPUTE_RETURN_ERROR_ON_MSG(bia->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);
	// Texture in the input tensor
	ARM_COMPUTE_RETURN_ERROR_ON((settings.export_input_to_cl_image() == true));

	return Status{};
	}

	ClComponentDepthwiseConv2d::ClComponentDepthwiseConv2d(ComponentId id,
	const Properties &properties,
	const ArgumentPack<ITensorInfo> &tensors,
	const Attributes &attributes,
	const Settings &settings)
	: IGpuKernelComponent{id, properties, tensors},
	_component_writer{std::make_unique<GpuCkwDepthwiseConv2d>(id, tensors, attributes, settings)}
	{
	ARM_COMPUTE_UNUSED(attributes, settings);
	}
	ClComponentDepthwiseConv2d::~ClComponentDepthwiseConv2d()
	{
	}
	const IGpuCkwComponentDriver *ClComponentDepthwiseConv2d::ckw_component_driver() const
	{
	return _component_writer.get();
	}
	} // namespace dynamic_fusion
	} // namespace experimental
	} // namespace arm_compute