| /* |
| * Copyright (c) 2017 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/NEDeconvolutionLayer.h" |
| |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/PixelValue.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| |
| using namespace arm_compute; |
| |
| NEDeconvolutionLayer::NEDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT |
| : _memory_group(std::move(memory_manager)), |
| _scale_f(), |
| _conv_f(), |
| _scaled_output() |
| { |
| } |
| |
| void NEDeconvolutionLayer::configure(ITensor *input, const ITensor *weights, const ITensor *bias, ITensor *output, const PadStrideInfo &info, |
| unsigned int ax, unsigned int ay, float upscalex, float upscaley) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(output); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != weights->info()->dimension(1)); |
| ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) < 1); |
| |
| auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1), |
| info.pad().first, info.pad().second, ax, ay, upscalex, upscaley, info.round()); |
| |
| const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); |
| |
| // Output auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights, bias); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, weights, bias); |
| |
| ARM_COMPUTE_ERROR_ON_MSG(output->info()->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid."); |
| ARM_COMPUTE_ERROR_ON_MSG(output->info()->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid."); |
| ARM_COMPUTE_ERROR_ON_MSG(output->info()->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid."); |
| |
| _memory_group.manage(&_scaled_output); |
| |
| // configure scale function |
| //Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor |
| TensorShape scale_out_shape(input->info()->tensor_shape()); |
| scale_out_shape.set(0, output->info()->dimension(0)); |
| scale_out_shape.set(1, output->info()->dimension(1)); |
| TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| _scaled_output.allocator()->init(scale_out_info); |
| const unsigned int kernel_size = weights->info()->dimension(0); |
| // Padding for the upsampled image is calculated with the equiation: p' = k - p - 1, where k is kernel size and p is the input padding |
| ARM_COMPUTE_ERROR_ON(info.pad().first > (kernel_size - 1)); |
| const unsigned int tr_px = kernel_size - info.pad().first - 1; |
| const unsigned int tr_py = kernel_size - info.pad().second - 1; |
| const unsigned int tr_stride = 1; |
| const PadStrideInfo transposed_info(tr_stride, tr_stride, tr_px, tr_py); |
| _scale_f.configure(input, &_scaled_output, std::make_pair(ax, ay), std::make_pair(info.stride().first - 1u, info.stride().second - 1u), transposed_info); |
| // setup the function to convolve the upscaled output |
| switch(kernel_size) |
| { |
| case 1: |
| { |
| _conv_f.configure(&_scaled_output, weights, bias, output, PadStrideInfo(1, 1, 0, 0, DimensionRoundingType::CEIL)); |
| break; |
| } |
| case 3: |
| { |
| _conv_f.configure(&_scaled_output, weights, bias, output, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL)); |
| break; |
| } |
| case 5: |
| { |
| _conv_f.configure(&_scaled_output, weights, bias, output, PadStrideInfo(1, 1, 2, 2, DimensionRoundingType::CEIL)); |
| break; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Not supported"); |
| break; |
| } |
| } |
| _scaled_output.allocator()->allocate(); |
| } |
| |
| void NEDeconvolutionLayer::run() |
| { |
| _memory_group.acquire(); |
| _scale_f.run(); |
| _conv_f.run(); |
| _memory_group.release(); |
| } |