Michalis Spyrou | 780db4e | 2017-11-23 09:49:51 +0000 | [diff] [blame] | 1 | /* |
Georgios Pinitas | ced7a8d | 2018-02-01 16:31:33 +0000 | [diff] [blame] | 2 | * Copyright (c) 2017-2018 ARM Limited. |
Michalis Spyrou | 780db4e | 2017-11-23 09:49:51 +0000 | [diff] [blame] | 3 | * |
| 4 | * SPDX-License-Identifier: MIT |
| 5 | * |
| 6 | * Permission is hereby granted, free of charge, to any person obtaining a copy |
| 7 | * of this software and associated documentation files (the "Software"), to |
| 8 | * deal in the Software without restriction, including without limitation the |
| 9 | * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| 10 | * sell copies of the Software, and to permit persons to whom the Software is |
| 11 | * furnished to do so, subject to the following conditions: |
| 12 | * |
| 13 | * The above copyright notice and this permission notice shall be included in all |
| 14 | * copies or substantial portions of the Software. |
| 15 | * |
| 16 | * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| 17 | * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| 18 | * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| 19 | * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| 20 | * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| 21 | * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| 22 | * SOFTWARE. |
| 23 | */ |
| 24 | #include "arm_compute/runtime/CL/functions/CLDeconvolutionLayer.h" |
| 25 | |
| 26 | #include "arm_compute/core/Helpers.h" |
| 27 | #include "arm_compute/core/Utils.h" |
| 28 | #include "arm_compute/core/Validate.h" |
| 29 | #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| 30 | |
| 31 | #include <memory> |
| 32 | #include <tuple> |
| 33 | |
| 34 | using namespace arm_compute; |
| 35 | using namespace arm_compute::misc::shape_calculator; |
| 36 | |
| 37 | CLDeconvolutionLayer::CLDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT |
| 38 | : _memory_group(std::move(memory_manager)), |
| 39 | _scale_f(), |
| 40 | _conv_f(), |
| 41 | _scaled_output() |
| 42 | { |
| 43 | } |
| 44 | |
| 45 | Status CLDeconvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info, |
| 46 | unsigned int inner_border_right, unsigned int inner_border_top) |
| 47 | { |
| 48 | ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output); |
Georgios Pinitas | 793f87d | 2018-05-18 20:08:58 +0100 | [diff] [blame] | 49 | ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); |
Michalis Spyrou | 780db4e | 2017-11-23 09:49:51 +0000 | [diff] [blame] | 50 | ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) != weights->dimension(1)); |
| 51 | ARM_COMPUTE_RETURN_ERROR_ON(weights->dimension(0) < 1); |
Anthony Barbier | 21f67d6 | 2018-02-16 15:17:48 +0000 | [diff] [blame] | 52 | ARM_COMPUTE_RETURN_ERROR_ON(!info.padding_is_symmetric()); |
Michalis Spyrou | 780db4e | 2017-11-23 09:49:51 +0000 | [diff] [blame] | 53 | |
| 54 | const unsigned int stride_x = info.stride().first; |
| 55 | const unsigned int stride_y = info.stride().second; |
| 56 | |
| 57 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_right > stride_x - 1, "inner_border_right must be smaller than stride_x"); |
| 58 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(inner_border_top > stride_y - 1, "inner_border_top must be smaller than stride_y"); |
| 59 | |
| 60 | auto out_dims = deconvolution_output_dimensions(input->dimension(0), input->dimension(1), weights->dimension(0), weights->dimension(1), |
| 61 | info.pad().first, info.pad().second, inner_border_right, inner_border_top, stride_x, stride_y); |
| 62 | |
| 63 | const TensorShape output_shape = deconvolution_output_shape(out_dims, input->tensor_shape(), weights->tensor_shape()); |
| 64 | |
wr0112358 | 3e3b371 | 2018-05-14 10:13:56 +0200 | [diff] [blame] | 65 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights); |
| 66 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output, weights); |
Michalis Spyrou | 780db4e | 2017-11-23 09:49:51 +0000 | [diff] [blame] | 67 | |
| 68 | if(bias != nullptr) |
| 69 | { |
| 70 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, bias); |
| 71 | ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, bias); |
| 72 | } |
| 73 | |
| 74 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimX) != output_shape.x(), "Output's width is invalid."); |
| 75 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimY) != output_shape.y(), "Output's height is invalid."); |
| 76 | ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->dimension(Window::DimZ) != output_shape.z(), "Output's depth is invalid."); |
| 77 | |
| 78 | TensorInfo scale_out_info(input->clone()->set_is_resizable(true).reset_padding().set_tensor_shape(compute_deconvolution_shape(*input, stride_x, stride_y, inner_border_right, inner_border_top, |
| 79 | info))); |
| 80 | const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); |
| 81 | |
| 82 | ARM_COMPUTE_RETURN_ON_ERROR(CLDeconvolutionLayerUpsample::validate(input, &scale_out_info, BorderSize(inner_border_right, inner_border_top), info)); |
Isabella Gottardi | 96b86a9 | 2018-05-14 15:52:07 +0100 | [diff] [blame] | 83 | ARM_COMPUTE_RETURN_ON_ERROR(CLConvolutionLayer::validate(&scale_out_info, weights, bias, output, conv_info, WeightsInfo())); |
Michalis Spyrou | 780db4e | 2017-11-23 09:49:51 +0000 | [diff] [blame] | 84 | |
| 85 | return Status{}; |
| 86 | } |
| 87 | |
| 88 | void CLDeconvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, |
| 89 | unsigned int inner_border_right, unsigned int inner_border_top) |
| 90 | { |
| 91 | ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output); |
| 92 | |
| 93 | const unsigned int stride_x = info.stride().first; |
| 94 | const unsigned int stride_y = info.stride().second; |
| 95 | |
| 96 | auto out_dims = deconvolution_output_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights->info()->dimension(0), weights->info()->dimension(1), |
| 97 | info.pad().first, info.pad().second, inner_border_top, inner_border_right, stride_x, stride_y); |
| 98 | |
| 99 | const TensorShape output_shape = deconvolution_output_shape(out_dims, input->info()->tensor_shape(), weights->info()->tensor_shape()); |
| 100 | |
| 101 | // Output auto initialization if not yet initialized |
| 102 | auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| 103 | |
| 104 | // Perform validation step |
| 105 | ARM_COMPUTE_ERROR_THROW_ON(CLDeconvolutionLayer::validate(input->info(), weights->info(), bias == nullptr ? nullptr : bias->info(), output->info(), info, inner_border_right, inner_border_top)); |
| 106 | |
| 107 | _memory_group.manage(&_scaled_output); |
| 108 | |
| 109 | // configure scale function |
| 110 | // Init and allocate intermmidiate tensor for output, same size as input but the first two axis are the same as the output tensor |
| 111 | TensorShape scale_out_shape(input->info()->tensor_shape()); |
| 112 | const unsigned int out_x = input->info()->dimension(0) + (input->info()->dimension(0) - 1) * (stride_x - 1) + inner_border_right + 2 * info.pad().first; |
| 113 | const unsigned int out_y = input->info()->dimension(1) + (input->info()->dimension(1) - 1) * (stride_y - 1) + inner_border_top + 2 * info.pad().second; |
| 114 | scale_out_shape.set(0, out_x); |
| 115 | scale_out_shape.set(1, out_y); |
| 116 | TensorInfo scale_out_info(scale_out_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| 117 | _scaled_output.allocator()->init(scale_out_info); |
| 118 | |
| 119 | _scale_f.configure(input, &_scaled_output, BorderSize(inner_border_top, inner_border_right), info); |
| 120 | |
| 121 | // setup the function to convolve the upscaled output |
| 122 | const PadStrideInfo conv_info(1, 1, 0, 0, 0, 0, DimensionRoundingType::CEIL); |
| 123 | _conv_f.configure(&_scaled_output, weights, bias, output, conv_info); |
| 124 | _scaled_output.allocator()->allocate(); |
| 125 | } |
| 126 | |
| 127 | void CLDeconvolutionLayer::run() |
| 128 | { |
| 129 | _memory_group.acquire(); |
| 130 | _scale_f.run(); |
| 131 | _conv_f.run(); |
| 132 | _memory_group.release(); |
| 133 | } |