diff options
Diffstat (limited to 'src/runtime/CL/functions')
-rw-r--r-- | src/runtime/CL/functions/CLConvolutionLayer.cpp | 40 | ||||
-rw-r--r-- | src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp | 33 |
2 files changed, 21 insertions, 52 deletions
diff --git a/src/runtime/CL/functions/CLConvolutionLayer.cpp b/src/runtime/CL/functions/CLConvolutionLayer.cpp index 476bf27423..f3c05adb47 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/runtime/CL/functions/CLFFTConvolutionLayer.h" #include "src/core/CL/ICLKernel.h" -#include "src/core/experimental/PostOpUtils.h" #include "src/core/helpers/MemoryHelpers.h" #include "src/gpu/cl/operators/ClConv2d.h" @@ -61,26 +60,21 @@ CLConvolutionLayer::CLConvolutionLayer(std::shared_ptr<IMemoryManager> memory_ma CLConvolutionLayer::~CLConvolutionLayer() = default; void CLConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, - const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops) + const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups) { - configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups, post_ops); + configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups); } void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, - const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops) + const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_ERROR_THROW_ON(CLConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups)); - ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups, post_ops); + ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups); - // Convert post op arguments to ITensorInfo - auto transformed_post_ops = experimental::transform_post_op_list_arguments<ICLTensor *, ITensorInfo *>(post_ops, [](auto tensor) - { - return tensor->info(); - }); - const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups, transformed_post_ops); + const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups); switch(opencl::ClConv2d::get_convolution_method(input->info(), weights->info(), output->info(), conv2d_info, weights_info, CLScheduler::get().target())) @@ -97,7 +91,6 @@ void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLT } case ConvolutionMethod::FFT: { - ARM_COMPUTE_ERROR_ON_MSG(post_ops.size() > 0, "CLFFTConvolutionLayer does not support post ops"); auto f = std::make_unique<CLFFTConvolutionLayer>(_impl->memory_manager); f->configure(compile_context, input, weights, biases, output, conv_info, act_info, enable_fast_math); _impl->func = std::move(f); @@ -110,31 +103,23 @@ void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLT if(_impl->op) { - _impl->memory_group = MemoryGroup(std::move(_impl->memory_manager)); - _impl->aux_mem_req = _impl->op->workspace(); - _impl->run_pack = { { ACL_SRC_0, input }, { ACL_SRC_1, weights }, { ACL_SRC_2, biases }, { ACL_DST, output } }; - size_t post_op_tensor_index = 0; - for(const auto &op : post_ops.get_list()) - { - for(auto &tensor : op->arguments()) - { - _impl->run_pack.add_const_tensor(experimental::get_post_op_arg_type(post_op_tensor_index++), *tensor); - } - } - _impl->prep_pack = { { ACL_SRC_1, weights }, { ACL_SRC_2, biases } }; - _impl->workspace = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack); + _impl->memory_group = MemoryGroup(std::move(_impl->memory_manager)); + _impl->aux_mem_req = _impl->op->workspace(); + _impl->run_pack = { { ACL_SRC_0, input }, { ACL_SRC_1, weights }, { ACL_SRC_2, biases }, { ACL_DST, output } }; + _impl->prep_pack = { { ACL_SRC_1, weights }, { ACL_SRC_2, biases } }; + _impl->workspace = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack); } } Status CLConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups, const experimental::PostOpList<ITensorInfo *> &post_ops) + const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!weights->are_values_constant(), "Dynamic weights are not supported"); ARM_COMPUTE_RETURN_ERROR_ON_MSG((num_groups != 1) && (input->data_layout() != DataLayout::NCHW), "Grouping (num_groups != 1) with NHWC data layout is not supported"); const GPUTarget gpu_target = CLScheduler::get().target(); - const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups, post_ops); + const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups); switch(opencl::ClConv2d::get_convolution_method(input, weights, output, conv2d_info, weights_info, gpu_target)) { @@ -149,7 +134,6 @@ Status CLConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo case ConvolutionMethod::FFT: { // Validate FFT-based convolution layer - ARM_COMPUTE_RETURN_ERROR_ON_MSG(post_ops.size() > 0, "CLFFTConvolutionLayer does not support post ops"); ARM_COMPUTE_RETURN_ON_ERROR(CLFFTConvolutionLayer::validate(input, weights, nullptr, output, conv_info, act_info, enable_fast_math)); break; } diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp index ad5bfd8dd2..c8c18f35db 100644 --- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2021 Arm Limited. + * Copyright (c) 2017-2021, 2023 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -31,7 +31,6 @@ #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "arm_compute/core/utils/quantization/AsymmHelpers.h" #include "arm_compute/runtime/CL/CLScheduler.h" -#include "src/core/experimental/PostOpUtils.h" #include "src/core/helpers/MemoryHelpers.h" #include "src/gpu/cl/operators/ClGemmConv2d.h" #include "support/Cast.h" @@ -69,24 +68,19 @@ CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> m CLGEMMConvolutionLayer::~CLGEMMConvolutionLayer() = default; void CLGEMMConvolutionLayer::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info, - const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops) + const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups) { - configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, num_groups, post_ops); + configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, num_groups); } void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ICLTensor *> &post_ops) + const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); - _impl->weights = weights; - _impl->op = std::make_unique<opencl::ClGemmConv2d>(); - // Convert post op arguments to ITensorInfo - auto transformed_post_ops = experimental::transform_post_op_list_arguments<ICLTensor *, ITensorInfo *>(post_ops, [](auto tensor) - { - return tensor->info(); - }); - const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups, transformed_post_ops); + _impl->weights = weights; + _impl->op = std::make_unique<opencl::ClGemmConv2d>(); + const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups); _impl->op->configure(compile_context, input->info(), weights->info(), (biases != nullptr ? biases->info() : nullptr), output->info(), conv2d_info, weights_info); _impl->run_pack = @@ -96,15 +90,6 @@ void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, { TensorType::ACL_SRC_2, biases }, { TensorType::ACL_DST, output } }; - // Add post op tensors - size_t post_op_tensor_index = 0; - for(const auto &op : post_ops.get_list()) - { - for(auto &tensor : op->arguments()) - { - _impl->run_pack.add_const_tensor(experimental::get_post_op_arg_type(post_op_tensor_index++), *tensor); - } - } _impl->prep_pack = { { TensorType::ACL_SRC_1, weights }, @@ -115,9 +100,9 @@ void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, } Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, - const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups, const experimental::PostOpList<ITensorInfo *> &post_ops) + const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, unsigned int num_groups) { - const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups, post_ops); + const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups); return opencl::ClGemmConv2d::validate(input, weights, biases, output, conv2d_info, weights_info); } |