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/cpu/operators/CpuSoftmax.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/cpu/operators/CpuSoftmax.cpp')
-rw-r--r-- | src/cpu/operators/CpuSoftmax.cpp | 101 |
1 files changed, 57 insertions, 44 deletions
diff --git a/src/cpu/operators/CpuSoftmax.cpp b/src/cpu/operators/CpuSoftmax.cpp index bf4c2fa3a2..e55d7f903e 100644 --- a/src/cpu/operators/CpuSoftmax.cpp +++ b/src/cpu/operators/CpuSoftmax.cpp @@ -25,9 +25,10 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/Validate.h" #include "arm_compute/runtime/NEON/NEScheduler.h" + #include "src/common/utils/Log.h" #include "src/core/helpers/MemoryHelpers.h" #include "src/core/helpers/SoftmaxHelpers.h" @@ -63,13 +64,15 @@ void CpuSoftmaxGeneric<IS_LOG>::configure(const ITensorInfo *src, ITensorInfo *d ARM_COMPUTE_ERROR_THROW_ON(CpuSoftmaxGeneric::validate(src, dst, beta, axis)); ARM_COMPUTE_LOG_PARAMS(src, dst, beta, axis); - const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(src->num_dimensions()))); + const unsigned int actual_axis = + static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(src->num_dimensions()))); _needs_permute = actual_axis > 0; - if(_needs_permute) + if (_needs_permute) { - _permute_input.configure(src, &_input_permuted, softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis)); + _permute_input.configure(src, &_input_permuted, + softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis)); } // We want to deal with a 2D input. Either it is the permuted version of the original input (4D case) @@ -79,10 +82,11 @@ void CpuSoftmaxGeneric<IS_LOG>::configure(const ITensorInfo *src, ITensorInfo *d // Create intermediate tensors shapes TensorShape max_sum_shape = tmp_input->tensor_shape(); max_sum_shape.set(0, 1); - const TensorInfo input_info = tmp_input->clone()->reset_padding().set_is_resizable(true); - DataType tmp_data_type = is_data_type_quantized_asymmetric(tmp_input->data_type()) ? DataType::F32 : tmp_input->data_type(); - TensorInfo tensor_info_tmp(input_info.clone()->set_data_type(tmp_data_type)); - TensorInfo max_info(tmp_input->clone()->set_tensor_shape(max_sum_shape)); + const TensorInfo input_info = tmp_input->clone()->reset_padding().set_is_resizable(true); + DataType tmp_data_type = + is_data_type_quantized_asymmetric(tmp_input->data_type()) ? DataType::F32 : tmp_input->data_type(); + TensorInfo tensor_info_tmp(input_info.clone()->set_data_type(tmp_data_type)); + TensorInfo max_info(tmp_input->clone()->set_tensor_shape(max_sum_shape)); // Init intermediate tensors _max = TensorInfo(max_info); @@ -94,13 +98,14 @@ void CpuSoftmaxGeneric<IS_LOG>::configure(const ITensorInfo *src, ITensorInfo *d _max_kernel = std::move(mk); auto sm = std::make_unique<kernels::CpuLogits1DSoftmaxKernel<IS_LOG>>(); - if(_needs_permute) + if (_needs_permute) { // The normalization kernel stores the result in a permuted output tensor sm->configure(tmp_input, &_max, &_output_permuted, beta, &_tmp); // Re-permute the permuted output into the requested (4D) output - _permute_output.configure(&_output_permuted, dst, softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis)); + _permute_output.configure(&_output_permuted, dst, + softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis)); } else { @@ -109,11 +114,15 @@ void CpuSoftmaxGeneric<IS_LOG>::configure(const ITensorInfo *src, ITensorInfo *d } _softmax_kernel = std::move(sm); - _aux_mem[InternalTensorIdx::MAX] = MemoryInfo(offset_int_vec(InternalTensorIdx::MAX), MemoryLifetime::Temporary, _max.total_size()); - _aux_mem[InternalTensorIdx::TMP] = MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp.total_size()); + _aux_mem[InternalTensorIdx::MAX] = + MemoryInfo(offset_int_vec(InternalTensorIdx::MAX), MemoryLifetime::Temporary, _max.total_size()); + _aux_mem[InternalTensorIdx::TMP] = + MemoryInfo(offset_int_vec(InternalTensorIdx::TMP), MemoryLifetime::Temporary, _tmp.total_size()); - _aux_mem[InternalTensorIdx::PERMUTED_SRC] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), MemoryLifetime::Temporary, _input_permuted.total_size()); - _aux_mem[InternalTensorIdx::PERMUTED_DST] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_DST), MemoryLifetime::Temporary, _output_permuted.total_size()); + _aux_mem[InternalTensorIdx::PERMUTED_SRC] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), + MemoryLifetime::Temporary, _input_permuted.total_size()); + _aux_mem[InternalTensorIdx::PERMUTED_DST] = MemoryInfo(offset_int_vec(InternalTensorIdx::PERMUTED_DST), + MemoryLifetime::Temporary, _output_permuted.total_size()); } template <bool IS_LOG> @@ -123,7 +132,8 @@ Status CpuSoftmaxGeneric<IS_LOG>::validate(const ITensorInfo *src, const ITensor ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); ARM_COMPUTE_RETURN_ERROR_ON_MSG(src->num_dimensions() > 4, "Only up to 4 dimensions are supported"); ARM_COMPUTE_UNUSED(beta); - ARM_COMPUTE_RETURN_ERROR_ON(axis < static_cast<int32_t>(-src->num_dimensions()) || static_cast<int32_t>(src->num_dimensions()) <= axis); + ARM_COMPUTE_RETURN_ERROR_ON(axis < static_cast<int32_t>(-src->num_dimensions()) || + static_cast<int32_t>(src->num_dimensions()) <= axis); // Create intermediate tensor info DataType tmp_data_type = src->data_type(); @@ -131,25 +141,33 @@ Status CpuSoftmaxGeneric<IS_LOG>::validate(const ITensorInfo *src, const ITensor TensorShape max_sum_shape = src->tensor_shape(); max_sum_shape.set(0, 1); - const TensorInfo tensor_info_max_sum(src->clone()->set_tensor_shape(max_sum_shape).set_data_type(tmp_data_type).set_quantization_info(src->quantization_info()).set_is_resizable(true)); + const TensorInfo tensor_info_max_sum(src->clone() + ->set_tensor_shape(max_sum_shape) + .set_data_type(tmp_data_type) + .set_quantization_info(src->quantization_info()) + .set_is_resizable(true)); const TensorInfo dont_care; - const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(src->num_dimensions()))); + const unsigned int actual_axis = + static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(src->num_dimensions()))); const bool needs_permute = actual_axis > 0; - if(needs_permute) + if (needs_permute) { - const PermutationVector permutation_vector = softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis); - const TensorShape permuted_shape = misc::shape_calculator::compute_permutation_output_shape(*src, permutation_vector); - TensorInfo input_permuted(src->clone()->set_tensor_shape(permuted_shape)); + const PermutationVector permutation_vector = + softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis); + const TensorShape permuted_shape = + misc::shape_calculator::compute_permutation_output_shape(*src, permutation_vector); + TensorInfo input_permuted(src->clone()->set_tensor_shape(permuted_shape)); ARM_COMPUTE_RETURN_ON_ERROR(CpuPermute::validate(src, &input_permuted, permutation_vector)); TensorInfo output_permuted(dst->clone()->set_tensor_shape(permuted_shape)); ARM_COMPUTE_RETURN_ON_ERROR(CpuPermute::validate(&output_permuted, dst, permutation_vector)); } ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuLogits1DMaxKernel::validate(src, &tensor_info_max_sum)); - ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuLogits1DSoftmaxKernel<IS_LOG>::validate(&tensor_info_tmp, &tensor_info_max_sum, dst, beta, &dont_care)); + ARM_COMPUTE_RETURN_ON_ERROR(kernels::CpuLogits1DSoftmaxKernel<IS_LOG>::validate( + &tensor_info_tmp, &tensor_info_max_sum, dst, beta, &dont_care)); return Status{}; } @@ -166,43 +184,38 @@ void CpuSoftmaxGeneric<IS_LOG>::run(ITensorPack &tensors) CpuAuxTensorHandler max(offset_int_vec(InternalTensorIdx::MAX), _max, tensors, true); CpuAuxTensorHandler input_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), _input_permuted, tensors, true); - CpuAuxTensorHandler output_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _output_permuted, tensors, true); + CpuAuxTensorHandler output_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _output_permuted, tensors, + true); ITensorPack max_pack; ITensorPack softmax_pack; - if(_needs_permute) + if (_needs_permute) { - ITensorPack permute_in_pack = { { TensorType::ACL_SRC, src }, { TensorType::ACL_DST, input_permuted.get() } }; + ITensorPack permute_in_pack = {{TensorType::ACL_SRC, src}, {TensorType::ACL_DST, input_permuted.get()}}; _permute_input.run(permute_in_pack); - max_pack = { { TensorType::ACL_SRC, input_permuted.get() }, { TensorType::ACL_DST, max.get() } }; + max_pack = {{TensorType::ACL_SRC, input_permuted.get()}, {TensorType::ACL_DST, max.get()}}; - softmax_pack = - { - { TensorType::ACL_SRC_0, input_permuted.get() }, - { TensorType::ACL_SRC_1, max.get() }, - { TensorType::ACL_DST_0, output_permuted.get() }, - { TensorType::ACL_DST_1, tmp.get() } - }; + softmax_pack = {{TensorType::ACL_SRC_0, input_permuted.get()}, + {TensorType::ACL_SRC_1, max.get()}, + {TensorType::ACL_DST_0, output_permuted.get()}, + {TensorType::ACL_DST_1, tmp.get()}}; } else { - max_pack = { { TensorType::ACL_SRC, src }, { TensorType::ACL_DST, max.get() } }; - - softmax_pack = - { - { TensorType::ACL_SRC_0, src }, - { TensorType::ACL_SRC_1, max.get() }, - { TensorType::ACL_DST_0, dst }, - { TensorType::ACL_DST_1, tmp.get() } - }; + max_pack = {{TensorType::ACL_SRC, src}, {TensorType::ACL_DST, max.get()}}; + + softmax_pack = {{TensorType::ACL_SRC_0, src}, + {TensorType::ACL_SRC_1, max.get()}, + {TensorType::ACL_DST_0, dst}, + {TensorType::ACL_DST_1, tmp.get()}}; } NEScheduler::get().schedule_op(_max_kernel.get(), Window::DimY, _max_kernel->window(), max_pack); NEScheduler::get().schedule_op(_softmax_kernel.get(), Window::DimY, _softmax_kernel->window(), softmax_pack); - if(_needs_permute) + if (_needs_permute) { ITensorPack permute_out_pack; permute_out_pack.add_tensor(TensorType::ACL_SRC, output_permuted.get()); @@ -211,7 +224,7 @@ void CpuSoftmaxGeneric<IS_LOG>::run(ITensorPack &tensors) } } -template <bool IS_LOG> +template <bool IS_LOG> experimental::MemoryRequirements CpuSoftmaxGeneric<IS_LOG>::workspace() const { return _aux_mem; |