| /* |
| * Copyright (c) 2017-2021 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 "arm_compute/runtime/NEON/functions/NESoftmaxLayer.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/runtime/Tensor.h" |
| #include "src/core/cpu/kernels/CpuSoftmaxKernel.h" |
| #include "src/core/helpers/SoftmaxHelpers.h" |
| #include "src/runtime/cpu/operators/CpuSoftmax.h" |
| |
| namespace arm_compute |
| { |
| template <bool IS_LOG> |
| struct NESoftmaxLayerGeneric<IS_LOG>::Impl |
| { |
| const ITensor *src{ nullptr }; |
| ITensor *dst{ nullptr }; |
| Tensor max{ nullptr }; |
| Tensor tmp{ nullptr }; |
| Tensor input_permuted{ nullptr }; |
| Tensor output_permuted{ nullptr }; |
| std::unique_ptr<cpu::CpuSoftmaxGeneric<IS_LOG>> op{ nullptr }; |
| }; |
| |
| template <bool IS_LOG> |
| NESoftmaxLayerGeneric<IS_LOG>::NESoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager) |
| : _memory_group(std::move(memory_manager)), _impl(std::make_unique<Impl>()) |
| { |
| } |
| |
| template <bool IS_LOG> |
| NESoftmaxLayerGeneric<IS_LOG>::NESoftmaxLayerGeneric(NESoftmaxLayerGeneric &&) = default; |
| template <bool IS_LOG> |
| NESoftmaxLayerGeneric<IS_LOG> &NESoftmaxLayerGeneric<IS_LOG>::operator=(NESoftmaxLayerGeneric &&) = default; |
| template <bool IS_LOG> |
| NESoftmaxLayerGeneric<IS_LOG>::~NESoftmaxLayerGeneric() = default; |
| |
| template <bool IS_LOG> |
| void NESoftmaxLayerGeneric<IS_LOG>::configure(ITensor *input, ITensor *output, float beta, int32_t axis) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| _impl->src = input; |
| _impl->dst = output; |
| _impl->op = std::make_unique<cpu::CpuSoftmaxGeneric<IS_LOG>>(); |
| _impl->op->configure(input->info(), output->info(), beta, axis); |
| |
| const unsigned int actual_axis = static_cast<unsigned int>(wrap_around(axis, static_cast<int32_t>(input->info()->num_dimensions()))); |
| const bool needs_permute = actual_axis > 0; |
| if(needs_permute) |
| { |
| // Add to the memory manager _input_permuted |
| auto permute_input = std::make_unique<cpu::CpuPermute>(); |
| _memory_group.manage(&_impl->input_permuted); |
| permute_input->configure(input->info(), _impl->input_permuted.info(), 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) |
| ITensor *tmp_input = (needs_permute ? &_impl->input_permuted : input); |
| |
| // Create intermediate tensors shapes |
| const TensorInfo input_info = tmp_input->info()->clone()->reset_padding().set_is_resizable(true); |
| DataType tmp_data_type = is_data_type_quantized_asymmetric(tmp_input->info()->data_type()) ? DataType::F32 : tmp_input->info()->data_type(); |
| TensorInfo tensor_info_tmp(input_info.clone()->set_data_type(tmp_data_type)); |
| |
| // Init intermediate tensors |
| TensorShape max_sum_shape = tmp_input->info()->tensor_shape(); |
| max_sum_shape.set(0, 1); |
| _impl->max.allocator()->init(input_info.clone()->set_tensor_shape(max_sum_shape)); |
| _impl->tmp.allocator()->init(tensor_info_tmp); |
| |
| // Manage intermediate buffers |
| _memory_group.manage(&_impl->max); |
| _memory_group.manage(&_impl->tmp); |
| |
| // Configure kernels |
| auto max_kernel = std::make_unique<cpu::kernels::CpuLogits1DMaxKernel>(); |
| auto softmax_kernel = std::make_unique<cpu::kernels::CpuLogits1DSoftmaxKernel<IS_LOG>>(); |
| max_kernel->configure(tmp_input->info(), _impl->max.info()); |
| |
| if(needs_permute) |
| { |
| auto permute_output = std::make_unique<cpu::CpuPermute>(); |
| // Add to the memory manager _output_permuted |
| _memory_group.manage(&_impl->output_permuted); |
| |
| // The normalization kernel stores the result in a permuted output tensor |
| softmax_kernel->configure(tmp_input->info(), _impl->max.info(), _impl->output_permuted.info(), beta, _impl->tmp.info()); |
| _impl->input_permuted.allocator()->allocate(); |
| |
| // Re-permute the permuted output into the requested (4D) output |
| permute_output->configure(_impl->output_permuted.info(), output->info(), softmax_helpers::get_permutation_vector_from_softmax_axis(actual_axis)); |
| |
| // Allocate the intermediate permuted tensors |
| _impl->output_permuted.allocator()->allocate(); |
| } |
| else |
| { |
| softmax_kernel->configure(tmp_input->info(), _impl->max.info(), output->info(), beta, _impl->tmp.info()); |
| } |
| |
| // Allocate intermediate buffers |
| _impl->max.allocator()->allocate(); |
| _impl->tmp.allocator()->allocate(); |
| } |
| |
| template <bool IS_LOG> |
| Status NESoftmaxLayerGeneric<IS_LOG>::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, int32_t axis) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_RETURN_ON_ERROR(cpu::CpuSoftmaxGeneric<IS_LOG>::validate(input, output, beta, axis)); |
| return Status{}; |
| } |
| |
| template <bool IS_LOG> |
| void NESoftmaxLayerGeneric<IS_LOG>::run() |
| { |
| MemoryGroupResourceScope scope_mg(_memory_group); |
| ITensorPack pack; |
| pack.add_tensor(TensorType::ACL_SRC, _impl->src); |
| pack.add_tensor(TensorType::ACL_DST, _impl->dst); |
| pack.add_tensor(TensorType::ACL_INT_0, &_impl->tmp); |
| pack.add_tensor(TensorType::ACL_INT_1, &_impl->max); |
| pack.add_tensor(TensorType::ACL_INT_2, &_impl->input_permuted); |
| pack.add_tensor(TensorType::ACL_INT_3, &_impl->output_permuted); |
| _impl->op->run(pack); |
| } |
| |
| template class NESoftmaxLayerGeneric<false>; |
| template class NESoftmaxLayerGeneric<true>; |
| |
| } // namespace arm_compute |