Rename [Cl|Cpu]GemmConvolution to [Cl|Gpu]GemmConv2d
Renaming the gemm-based convolution operators to accomodate for new
operators with higher convolution dimensonality
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: Id2f2cf11404221f0e87baa0e5d08ad5d63eaf78e
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/6113
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
index 75ca77d..563dbd4 100644
--- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
@@ -32,7 +32,7 @@
#include "arm_compute/core/utils/quantization/AsymmHelpers.h"
#include "arm_compute/runtime/CL/CLScheduler.h"
#include "src/core/helpers/MemoryHelpers.h"
-#include "src/runtime/gpu/cl/operators/ClGemmConvolution.h"
+#include "src/runtime/gpu/cl/operators/ClGemmConv2d.h"
#include "support/Cast.h"
#include <cmath>
@@ -47,15 +47,15 @@
struct CLGEMMConvolutionLayer::Impl
{
- const ITensor *weights{ nullptr };
- std::unique_ptr<opencl::ClGemmConvolution> op{ nullptr };
- ITensorPack run_pack{};
- ITensorPack prep_pack{};
- MemoryGroup memory_group{};
- IWeightsManager *weights_manager{ nullptr };
- MemoryRequirements aux_mem_req{};
- WorkspaceData<CLTensor> workspace_tensors{};
- bool is_prepared{ false };
+ const ITensor *weights{ nullptr };
+ std::unique_ptr<opencl::ClGemmConv2d> op{ nullptr };
+ ITensorPack run_pack{};
+ ITensorPack prep_pack{};
+ MemoryGroup memory_group{};
+ IWeightsManager *weights_manager{ nullptr };
+ MemoryRequirements aux_mem_req{};
+ WorkspaceData<CLTensor> workspace_tensors{};
+ bool is_prepared{ false };
};
CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager)
@@ -79,7 +79,7 @@
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
_impl->weights = weights;
- _impl->op = std::make_unique<opencl::ClGemmConvolution>();
+ _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);
@@ -103,7 +103,7 @@
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::ClGemmConvolution::validate(input, weights, biases, output, conv2d_info, weights_info);
+ return opencl::ClGemmConv2d::validate(input, weights, biases, output, conv2d_info, weights_info);
}
void CLGEMMConvolutionLayer::run()