diff options
author | Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> | 2023-09-27 17:46:17 +0100 |
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committer | felixjohnny.thomasmathibalan <felixjohnny.thomasmathibalan@arm.com> | 2023-09-28 12:08:05 +0000 |
commit | afd38f0c617d6f89b2b4532c6c44f116617e2b6f (patch) | |
tree | 03bc7d5a762099989b16a656fa8d397b490ed70e /src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp | |
parent | bdcb4c148ee2fdeaaddf4cf1e57bbb0de02bb894 (diff) | |
download | ComputeLibrary-afd38f0c617d6f89b2b4532c6c44f116617e2b6f.tar.gz |
Apply clang-format on repository
Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Diffstat (limited to 'src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp')
-rw-r--r-- | src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp | 59 |
1 files changed, 33 insertions, 26 deletions
diff --git a/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp b/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp index 8ab0288ab1..eea57a17d3 100644 --- a/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp +++ b/src/core/NEON/kernels/NEL2NormalizeLayerKernel.cpp @@ -30,11 +30,12 @@ #include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Window.h" + #include "src/common/cpuinfo/CpuIsaInfo.h" -#include "src/core/NEON/NEMath.h" #include "src/core/common/Registrars.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" +#include "src/core/NEON/NEMath.h" #include "src/cpu/kernels/l2normlayer/list.h" #include <arm_neon.h> @@ -55,7 +56,8 @@ struct L2NormalizeLayerSelectorData using L2NormalizeLayerKernelSelctorPtr = std::add_pointer<bool(const L2NormalizeLayerSelectorData &data)>::type; -using L2NormalizeLayerPtr = std::add_pointer<void(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)>::type; +using L2NormalizeLayerPtr = std::add_pointer<void( + const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window, size_t axis)>::type; struct L2NormalizeLayerKernel { @@ -64,26 +66,25 @@ struct L2NormalizeLayerKernel L2NormalizeLayerPtr ukernel; }; -static const L2NormalizeLayerKernel available_kernels[] = -{ - { - "fp32_neon_l2normalize_x", - [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F32 && data.actual_axis == Window::DimX; }, - REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_l2_normalize_x) - }, - { - "fp32_neon_l2normalize_yz", - [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F32 && data.actual_axis != Window::DimX; }, - REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_l2_normalize_yz) - }, +static const L2NormalizeLayerKernel available_kernels[] = { + {"fp32_neon_l2normalize_x", + [](const L2NormalizeLayerSelectorData &data) + { return data.dt == DataType::F32 && data.actual_axis == Window::DimX; }, + REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_l2_normalize_x)}, + {"fp32_neon_l2normalize_yz", + [](const L2NormalizeLayerSelectorData &data) + { return data.dt == DataType::F32 && data.actual_axis != Window::DimX; }, + REGISTER_FP32_NEON(arm_compute::cpu::neon_fp32_l2_normalize_yz)}, { "fp16_neon_l2normalize_x", - [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F16 && data.isa.fp16 && data.actual_axis == Window::DimX; }, + [](const L2NormalizeLayerSelectorData &data) + { return data.dt == DataType::F16 && data.isa.fp16 && data.actual_axis == Window::DimX; }, REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_l2_normalize_x), }, { "fp16_neon_l2normalize_yz", - [](const L2NormalizeLayerSelectorData & data) { return data.dt == DataType::F16 && data.isa.fp16 && data.actual_axis != Window::DimX; }, + [](const L2NormalizeLayerSelectorData &data) + { return data.dt == DataType::F16 && data.isa.fp16 && data.actual_axis != Window::DimX; }, REGISTER_FP16_NEON(arm_compute::cpu::neon_fp16_l2_normalize_yz), }, }; @@ -96,9 +97,9 @@ static const L2NormalizeLayerKernel available_kernels[] = */ const L2NormalizeLayerKernel *get_implementation(const L2NormalizeLayerSelectorData &data) { - for(const auto &uk : available_kernels) + for (const auto &uk : available_kernels) { - if(uk.is_selected(data)) + if (uk.is_selected(data)) { return &uk; } @@ -106,7 +107,8 @@ const L2NormalizeLayerKernel *get_implementation(const L2NormalizeLayerSelectorD return nullptr; } -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) +Status +validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_UNUSED(epsilon); @@ -115,14 +117,15 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *sum, cons ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, sum); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis > 2, "Actual axis greater than 2 is not supported"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, "Actual normalization axis greater than max number of dimensions"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(actual_axis >= TensorShape::num_max_dimensions, + "Actual normalization axis greater than max number of dimensions"); // Reduce shape on axis TensorShape sum_shape = input->tensor_shape(); sum_shape.set(actual_axis, 1); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(sum->tensor_shape(), sum_shape); - if(output->total_size() != 0) + if (output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); @@ -151,7 +154,8 @@ NEL2NormalizeLayerKernel::NEL2NormalizeLayerKernel() { } -void NEL2NormalizeLayerKernel::configure(const ITensor *input, const ITensor *sum, ITensor *output, int axis, float epsilon) +void NEL2NormalizeLayerKernel::configure( + const ITensor *input, const ITensor *sum, ITensor *output, int axis, float epsilon) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), sum->info(), output->info(), axis, epsilon)); @@ -169,10 +173,12 @@ void NEL2NormalizeLayerKernel::configure(const ITensor *input, const ITensor *su INEKernel::configure(std::get<1>(win_config)); } -Status NEL2NormalizeLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) +Status NEL2NormalizeLayerKernel::validate( + const ITensorInfo *input, const ITensorInfo *sum, const ITensorInfo *output, int axis, float epsilon) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, sum, output, axis, epsilon)); - ARM_COMPUTE_RETURN_ON_ERROR(std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get()))); + ARM_COMPUTE_RETURN_ON_ERROR( + std::get<0>(validate_and_configure_window(input->clone().get(), output->clone().get()))); return Status{}; } @@ -183,12 +189,13 @@ void NEL2NormalizeLayerKernel::run(const Window &window, const ThreadInfo &info) ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - if(_actual_axis > 2) + if (_actual_axis > 2) { ARM_COMPUTE_ERROR("Unsupported normalization axis"); } - const auto *uk = get_implementation(L2NormalizeLayerSelectorData{ _output->info()->data_type(), _actual_axis, CPUInfo::get().get_isa() }); + const auto *uk = get_implementation( + L2NormalizeLayerSelectorData{_output->info()->data_type(), _actual_axis, CPUInfo::get().get_isa()}); ARM_COMPUTE_ERROR_ON(uk == nullptr); ARM_COMPUTE_ERROR_ON(uk->ukernel == nullptr); |