diff options
Diffstat (limited to 'src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp')
| -rw-r--r-- | src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp | 25 |
1 files changed, 16 insertions, 9 deletions
diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp index f0f45a8659..f926b1d0a6 100644 --- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp +++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp @@ -30,9 +30,9 @@ #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/CL/kernels/CLIm2ColKernel.h" #include "src/core/CL/kernels/CLWeightsReshapeKernel.h" #include "src/core/gpu/cl/kernels/ClCol2ImKernel.h" +#include "src/core/gpu/cl/kernels/ClIm2ColKernel.h" #include "src/core/helpers/AutoConfiguration.h" #include "support/Cast.h" @@ -105,8 +105,8 @@ void CLConvolutionLayerReshapeWeights::run() } CLGEMMConvolutionLayer::CLGEMMConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager, IWeightsManager *weights_manager) - : _memory_group(memory_manager), _weights_manager(weights_manager), _reshape_weights(), _reshape_weights_managed(), _im2col_kernel(std::make_unique<CLIm2ColKernel>()), _mm_gemm(memory_manager, - weights_manager), _mm_gemmlowp(memory_manager), _col2im_kernel(nullptr), _activationlayer_function(), _original_weights(nullptr), _gemm_output_to_use(nullptr), _output(nullptr), _im2col_output(), + : _memory_group(memory_manager), _weights_manager(weights_manager), _reshape_weights(), _reshape_weights_managed(), _im2col_kernel(nullptr), _mm_gemm(memory_manager, weights_manager), + _mm_gemmlowp(memory_manager), _col2im_kernel(nullptr), _activationlayer_function(), _original_weights(nullptr), _input(nullptr), _gemm_output_to_use(nullptr), _output(nullptr), _im2col_output(), _weights_reshaped(), _gemm_output(), _skip_im2col(false), _skip_col2im(false), _is_quantized(false), _fuse_activation(true), _is_prepared(false) { } @@ -229,6 +229,7 @@ void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, _is_prepared = weights_info.retain_internal_weights(); _original_weights = weights; + _input = input; _is_quantized = is_data_type_quantized_asymmetric(input->info()->data_type()); _skip_im2col = (data_layout == DataLayout::NHWC && kernel_width == 1 && kernel_height == 1 && conv_info.stride().first == 1 && conv_info.stride().second == 1); _skip_col2im = data_layout == DataLayout::NHWC; @@ -236,9 +237,6 @@ void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, // Only for quantize there are few cases where we cannot fuse the activation function in GEMM _fuse_activation = true; - // Set the GPU target for im2col and col2im - _im2col_kernel->set_target(CLScheduler::get().target()); - const ICLTensor *gemm_input_to_use = input; ICLTensor *gemm_output_to_use = output; @@ -299,7 +297,11 @@ void CLGEMMConvolutionLayer::configure(const CLCompileContext &compile_context, _memory_group.manage(&_im2col_output); // Configure and tune im2col. im2col output shape is auto-initialized - _im2col_kernel->configure(compile_context, input, &_im2col_output, Size2D(kernel_width, kernel_height), conv_info, append_bias, dilation, num_groups); + _im2col_kernel = std::make_unique<opencl::kernels::ClIm2ColKernel>(); + + // Set the GPU target for im2col + _im2col_kernel->set_target(CLScheduler::get().target()); + _im2col_kernel->configure(compile_context, input->info(), _im2col_output.info(), Size2D(kernel_width, kernel_height), conv_info, append_bias, dilation, num_groups); // Set quantization info _im2col_output.info()->set_quantization_info(input->info()->quantization_info()); @@ -525,7 +527,7 @@ Status CLGEMMConvolutionLayer::validate(const ITensorInfo *input, const ITensorI auto_init_if_empty(im2col_reshaped_info, input->clone()->set_tensor_shape(expected_output_shape)); - ARM_COMPUTE_RETURN_ON_ERROR(CLIm2ColKernel::validate(input, &im2col_reshaped_info, kernel_dims, conv_info, append_bias, dilation, num_groups)); + ARM_COMPUTE_RETURN_ON_ERROR(opencl::kernels::ClIm2ColKernel::validate(input, &im2col_reshaped_info, kernel_dims, conv_info, append_bias, dilation, num_groups)); gemm_input_to_use = &im2col_reshaped_info; } @@ -620,7 +622,12 @@ void CLGEMMConvolutionLayer::run() // Run im2col if(!_skip_im2col) { - CLScheduler::get().enqueue(*_im2col_kernel); + ITensorPack pack = + { + { TensorType::ACL_SRC, _input }, + { TensorType::ACL_DST, &_im2col_output } + }; + CLScheduler::get().enqueue_op(*_im2col_kernel, pack, false); } // Runs CLGEMM or CLGEMMLowpMatrixMultiplyCore functions |