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Diffstat (limited to 'src/runtime/cpu/operators/CpuSoftmax.cpp')
| -rw-r--r-- | src/runtime/cpu/operators/CpuSoftmax.cpp | 221 |
1 files changed, 0 insertions, 221 deletions
diff --git a/src/runtime/cpu/operators/CpuSoftmax.cpp b/src/runtime/cpu/operators/CpuSoftmax.cpp deleted file mode 100644 index e17925ee50..0000000000 --- a/src/runtime/cpu/operators/CpuSoftmax.cpp +++ /dev/null @@ -1,221 +0,0 @@ -/* - * Copyright (c) 2021 Arm Limited. - * - * SPDX-License-Identifier: MIT - * - * Permission is hereby granted, free of charge, to any person obtaining a copy - * of this software and associated documentation files (the "Software"), to - * deal in the Software without restriction, including without limitation the - * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or - * sell copies of the Software, and to permit persons to whom the Software is - * furnished to do so, subject to the following conditions: - * - * The above copyright notice and this permission notice shall be included in all - * copies or substantial portions of the Software. - * - * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR - * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, - * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE - * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER - * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, - * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE - * SOFTWARE. - */ -#include "src/runtime/cpu/operators/CpuSoftmax.h" - -#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/runtime/NEON/NEScheduler.h" -#include "src/core/cpu/kernels/CpuSoftmaxKernel.h" -#include "src/core/helpers/MemoryHelpers.h" -#include "src/core/helpers/SoftmaxHelpers.h" -#include "src/runtime/cpu/utils/CpuAuxTensorHandler.h" - -using namespace arm_compute::experimental; - -namespace arm_compute -{ -namespace cpu -{ -template <bool IS_LOG> -CpuSoftmaxGeneric<IS_LOG>::CpuSoftmaxGeneric() - : _permute_input(), - _permute_output(), - _max_kernel(), - _softmax_kernel(), - _max(), - _tmp(), - _input_permuted(), - _output_permuted(), - _needs_permute(false), - _aux_mem(InternalTensorIdx::COUNT) -{ -} - -template <bool IS_LOG> -void CpuSoftmaxGeneric<IS_LOG>::configure(const ITensorInfo *src, ITensorInfo *dst, float beta, int32_t axis) -{ - // Perform validation step - ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); - ARM_COMPUTE_ERROR_THROW_ON(CpuSoftmaxGeneric::validate(src, dst, beta, axis)); - - 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) - { - _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) - // or it is the original input case (2D case) - const ITensorInfo *tmp_input = (_needs_permute ? &_input_permuted : src); - - // 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)); - - // Init intermediate tensors - _max = TensorInfo(max_info); - _tmp = TensorInfo(tensor_info_tmp); - - // Configure kernels - auto mk = std::make_unique<kernels::CpuLogits1DMaxKernel>(); - mk->configure(tmp_input, &_max); - _max_kernel = std::move(mk); - - auto sm = std::make_unique<kernels::CpuLogits1DSoftmaxKernel<IS_LOG>>(); - 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)); - } - else - { - // Softmax 2D case - sm->configure(tmp_input, &_max, dst, beta, &_tmp); - } - _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::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> -Status CpuSoftmaxGeneric<IS_LOG>::validate(const ITensorInfo *src, const ITensorInfo *dst, float beta, int32_t axis) -{ - // Perform validation step - 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); - - // Create intermediate tensor info - DataType tmp_data_type = src->data_type(); - const TensorInfo tensor_info_tmp(src->clone()->set_data_type(tmp_data_type).set_is_resizable(true)); - - 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 dont_care; - - 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) - { - 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)); - - return Status{}; -} - -template <bool IS_LOG> -void CpuSoftmaxGeneric<IS_LOG>::run(ITensorPack &tensors) -{ - ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided"); - - auto src = tensors.get_const_tensor(TensorType::ACL_SRC); - auto dst = tensors.get_tensor(TensorType::ACL_DST); - - CpuAuxTensorHandler tmp(offset_int_vec(InternalTensorIdx::TMP), _tmp, tensors, false); - CpuAuxTensorHandler max(offset_int_vec(InternalTensorIdx::MAX), _max, tensors, false); - - CpuAuxTensorHandler input_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_SRC), _input_permuted, tensors, false); - CpuAuxTensorHandler output_permuted(offset_int_vec(InternalTensorIdx::PERMUTED_DST), _output_permuted, tensors, false); - - ITensorPack max_pack; - ITensorPack softmax_pack; - - if(_needs_permute) - { - 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() } }; - - 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() } - }; - } - - 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) - { - ITensorPack permute_out_pack; - permute_out_pack.add_tensor(TensorType::ACL_SRC, output_permuted.get()); - permute_out_pack.add_tensor(TensorType::ACL_DST, dst); - _permute_output.run(permute_out_pack); - } -} - -template <bool IS_LOG> -experimental::MemoryRequirements CpuSoftmaxGeneric<IS_LOG>::workspace() const -{ - return _aux_mem; -} - -template class CpuSoftmaxGeneric<false>; -template class CpuSoftmaxGeneric<true>; -} // namespace cpu -} // namespace arm_compute |