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path: root/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
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Diffstat (limited to 'src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp')
-rw-r--r--src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp88
1 files changed, 55 insertions, 33 deletions
diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
index c8c18f35db..aef7cddd7a 100644
--- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
@@ -27,10 +27,11 @@
#include "arm_compute/core/PixelValue.h"
#include "arm_compute/core/Size2D.h"
#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/Validate.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
+#include "arm_compute/core/Validate.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
+
#include "src/core/helpers/MemoryHelpers.h"
#include "src/gpu/cl/operators/ClGemmConv2d.h"
#include "support/Cast.h"
@@ -47,18 +48,19 @@ using namespace arm_compute::experimental;
struct CLGEMMConvolutionLayer::Impl
{
- const ITensor *weights{ nullptr };
- std::unique_ptr<opencl::ClGemmConv2d> op{ nullptr };
+ const ITensor *weights{nullptr};
+ std::unique_ptr<opencl::ClGemmConv2d> op{nullptr};
ITensorPack run_pack{};
ITensorPack prep_pack{};
MemoryGroup memory_group{};
- IWeightsManager *weights_manager{ nullptr };
+ IWeightsManager *weights_manager{nullptr};
MemoryRequirements aux_mem_req{};
WorkspaceData<CLTensor> workspace_tensors{};
- bool is_prepared{ false };
+ bool is_prepared{false};
};
-CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
+CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager,
+ IWeightsManager *weights_manager)
: _impl(std::make_unique<Impl>())
{
_impl->memory_group = MemoryGroup(memory_manager);
@@ -67,40 +69,60 @@ 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)
+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)
{
- configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, num_groups);
+ 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)
+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)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
_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->op->configure(compile_context, input->info(), weights->info(),
+ (biases != nullptr ? biases->info() : nullptr), output->info(), conv2d_info, weights_info);
- _impl->run_pack =
- {
- { TensorType::ACL_SRC_0, input },
- { TensorType::ACL_SRC_1, weights },
- { TensorType::ACL_SRC_2, biases },
- { TensorType::ACL_DST, output }
- };
- _impl->prep_pack =
- {
- { TensorType::ACL_SRC_1, weights },
- { TensorType::ACL_SRC_2, biases },
+ _impl->run_pack = {{TensorType::ACL_SRC_0, input},
+ {TensorType::ACL_SRC_1, weights},
+ {TensorType::ACL_SRC_2, biases},
+ {TensorType::ACL_DST, output}};
+ _impl->prep_pack = {
+ {TensorType::ACL_SRC_1, weights},
+ {TensorType::ACL_SRC_2, biases},
};
- _impl->aux_mem_req = _impl->op->workspace();
- _impl->workspace_tensors = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack);
+ _impl->aux_mem_req = _impl->op->workspace();
+ _impl->workspace_tensors =
+ manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack);
}
-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)
+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 Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, false, num_groups);
return opencl::ClGemmConv2d::validate(input, weights, biases, output, conv2d_info, weights_info);
@@ -115,14 +137,14 @@ void CLGEMMConvolutionLayer::run()
void CLGEMMConvolutionLayer::prepare()
{
- if(!_impl->is_prepared)
+ if (!_impl->is_prepared)
{
_impl->op->prepare(_impl->prep_pack);
- auto has_reshape = std::find_if(_impl->aux_mem_req.begin(),
- _impl->aux_mem_req.end(),
- [](const MemoryInfo & m) -> bool { return m.lifetime == MemoryLifetime::Persistent; });
+ auto has_reshape =
+ std::find_if(_impl->aux_mem_req.begin(), _impl->aux_mem_req.end(),
+ [](const MemoryInfo &m) -> bool { return m.lifetime == MemoryLifetime::Persistent; });
- if(has_reshape != std::end(_impl->aux_mem_req))
+ if (has_reshape != std::end(_impl->aux_mem_req))
{
_impl->weights->mark_as_unused();
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-30 10:02:02 +0000