/* * Copyright (c) 2017-2018 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/Helpers.h" #include "arm_compute/core/NEON/kernels/NESoftmaxLayerKernel.h" #include "arm_compute/runtime/NEON/NEScheduler.h" #include using namespace arm_compute; NESoftmaxLayer::NESoftmaxLayer(std::shared_ptr memory_manager) : _memory_group(std::move(memory_manager)), _max_kernel(), _softmax_kernel(), _fill_border_kernel(), _max(), _tmp() { } void NESoftmaxLayer::configure(ITensor *input, ITensor *output, float beta, size_t axis) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_UNUSED(axis); // Configure Kernels _max_kernel.configure(input, &_max); _fill_border_kernel.configure(input, _max_kernel.border_size(), BorderMode::REPLICATE); _softmax_kernel.configure(input, &_max, output, beta, &_tmp); // Init intermediate tensors _max.allocator()->init(*_max.info()); _tmp.allocator()->init(*_tmp.info()); // Manage intermediate buffers _memory_group.manage(&_max); _memory_group.manage(&_tmp); // Allocate intermediate tensors _max.allocator()->allocate(); _tmp.allocator()->allocate(); } Status NESoftmaxLayer::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, size_t axis) { ARM_COMPUTE_RETURN_ERROR_ON_MSG(axis != 1, "Axis must be 1 for NEON"); // Perform validation step ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 2, "Only 2D inputs are supported"); const TensorShape max_shape = TensorShape(input->tensor_shape()).set(0, 1); const TensorInfo tensor_info_max_sum = TensorInfo(*input).set_tensor_shape(max_shape).reset_padding(); const TensorInfo dont_care; ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DMaxKernel::validate(input, &tensor_info_max_sum)); ARM_COMPUTE_RETURN_ON_ERROR(NELogits1DSoftmaxKernel::validate(input, &tensor_info_max_sum, output, beta, &dont_care)); return Status{}; } void NESoftmaxLayer::run() { _memory_group.acquire(); NEScheduler::get().schedule(&_fill_border_kernel, Window::DimY); NEScheduler::get().schedule(&_max_kernel, Window::DimY); NEScheduler::get().schedule(&_softmax_kernel, Window::DimY); _memory_group.release(); }