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author | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-11-21 03:04:18 +0000 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-12-01 10:41:54 +0000 |
commit | 40f51a63c8e7258db15269427ae4fe1ad199c550 (patch) | |
tree | 353253a41863966995a45556731e7181a643c003 /src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp | |
parent | 327800401c4185d98fcc01b9c9efbc038a4228ed (diff) | |
download | ComputeLibrary-40f51a63c8e7258db15269427ae4fe1ad199c550.tar.gz |
Update default C++ standard to C++14
(3RDPARTY_UPDATE)
Resolves: COMPMID-3849
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: I6369f112337310140e2d6c8e79630cd11138dfa0
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4544
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michalis Spyrou <michalis.spyrou@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp')
-rw-r--r-- | src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp | 61 |
1 files changed, 30 insertions, 31 deletions
diff --git a/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp b/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp index 1cb2458e13..265df9246f 100644 --- a/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp +++ b/src/runtime/NEON/functions/NEWinogradConvolutionLayer.cpp @@ -35,7 +35,6 @@ #include "src/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" #include "src/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" #include "src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.h" -#include "support/MemorySupport.h" #include "src/core/NEON/kernels/convolution/common/utils.hpp" #include "src/core/NEON/kernels/convolution/winograd/winograd.hpp" @@ -351,18 +350,18 @@ void NEWinogradConvolutionLayer::configure(const ITensor *input, const ITensor * if(input->info()->dimension(width_idx) > 4 && input->info()->dimension(height_idx) > 4) { using config = NEWinogradLayerConfiguration<float, float, 4, 4, 3, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else { using config = NEWinogradLayerConfiguration<float, float, 2, 2, 3, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } @@ -370,63 +369,63 @@ void NEWinogradConvolutionLayer::configure(const ITensor *input, const ITensor * else if(kernel_size == Size2D(5, 5)) { using config = NEWinogradLayerConfiguration<float, float, 2, 2, 5, 5>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(1, 3)) { using config = NEWinogradLayerConfiguration<float, float, 6, 1, 3, 1>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(3, 1)) { using config = NEWinogradLayerConfiguration<float, float, 1, 6, 1, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(1, 5)) { using config = NEWinogradLayerConfiguration<float, float, 4, 1, 5, 1>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(5, 1)) { using config = NEWinogradLayerConfiguration<float, float, 1, 4, 1, 5>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(1, 7)) { using config = NEWinogradLayerConfiguration<float, float, 2, 1, 7, 1>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } else if(kernel_size == Size2D(7, 1)) { using config = NEWinogradLayerConfiguration<float, float, 1, 2, 1, 7>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } @@ -441,9 +440,9 @@ void NEWinogradConvolutionLayer::configure(const ITensor *input, const ITensor * if(kernel_size == Size2D(3, 3)) { using config = NEWinogradLayerConfiguration<__fp16, __fp16, 4, 4, 3, 3>; - transform_input_kernel = support::cpp14::make_unique<config::TransformInputKernel>(); - transform_weights_kernel = support::cpp14::make_unique<config::TransformWeightsKernel>(); - transform_output_kernel = support::cpp14::make_unique<config::TransformOutputKernel>(); + transform_input_kernel = std::make_unique<config::TransformInputKernel>(); + transform_weights_kernel = std::make_unique<config::TransformWeightsKernel>(); + transform_output_kernel = std::make_unique<config::TransformOutputKernel>(); n_gemms = config::WinogradBase::N_GEMMS; N_BLOCK = config::WinogradConv::N_BLOCK; } |