| /* |
| * 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/CL/functions/CLDepthwiseConvolution.h" |
| |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/PixelValue.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| #include "support/ToolchainSupport.h" |
| |
| using namespace arm_compute; |
| |
| CLDepthwiseConvolution3x3::CLDepthwiseConvolution3x3() |
| : _kernel(), _border_handler() |
| { |
| } |
| |
| void CLDepthwiseConvolution3x3::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *weights, const PadStrideInfo &conv_info) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); |
| |
| _kernel.configure(input, output, weights, conv_info); |
| _border_handler.configure(input, _kernel.border_size(), BorderMode::CONSTANT, PixelValue(0)); |
| } |
| |
| void CLDepthwiseConvolution3x3::run() |
| { |
| CLScheduler::get().enqueue(_border_handler); |
| CLScheduler::get().enqueue(_kernel); |
| } |
| |
| CLDepthwiseConvolution::CLDepthwiseConvolution() |
| : _im2col_kernel(), _weights_reshape_kernel(), _v2mm_kernel(), _vector_to_tensor_kernel(), _v2mm_input_fill_border(), _v2mm_weights_fill_border(), _input_reshaped(), _weights_reshaped(), |
| _v2mm_output() |
| { |
| } |
| |
| void CLDepthwiseConvolution::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *weights, const PadStrideInfo &conv_info) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(2) != weights->info()->dimension(2)); |
| |
| const size_t weights_w = weights->info()->dimension(0); |
| const size_t weights_h = weights->info()->dimension(1); |
| const size_t weights_z = weights->info()->dimension(2); |
| |
| unsigned int conv_w = 0; |
| unsigned int conv_h = 0; |
| std::tie(conv_w, conv_h) = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1), weights_w, weights_h, conv_info); |
| |
| // Set up intermediate tensors |
| const size_t patch_size = weights_w * weights_h; |
| const size_t conv_size = conv_w * conv_h; |
| |
| TensorShape shape_im2col = input->info()->tensor_shape(); |
| shape_im2col.set(0, patch_size); |
| shape_im2col.set(1, conv_size); |
| shape_im2col.set(2, weights_z); |
| |
| const TensorShape shape_weights_reshape(patch_size, weights_z); |
| TensorShape shape_v2mm_out = output->info()->tensor_shape(); |
| shape_v2mm_out.set(0, conv_size * weights_z); |
| shape_v2mm_out.set(1, 1); |
| shape_v2mm_out.set(2, 1); |
| |
| const TensorInfo info_im2col(shape_im2col, 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| const TensorInfo info_weights_reshape(shape_weights_reshape, 1, weights->info()->data_type(), weights->info()->fixed_point_position()); |
| const TensorInfo info_v2mm_out(shape_v2mm_out, 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| |
| _input_reshaped.allocator()->init(info_im2col); |
| _weights_reshaped.allocator()->init(info_weights_reshape); |
| _v2mm_output.allocator()->init(info_v2mm_out); |
| |
| // Configure kernels |
| _im2col_kernel.configure(input, &_input_reshaped, Size2D(weights_w, weights_h), conv_info); |
| _weights_reshape_kernel.configure(weights, &_weights_reshaped); |
| _v2mm_kernel.configure(&_input_reshaped, &_weights_reshaped, &_v2mm_output); |
| _vector_to_tensor_kernel.configure(&_v2mm_output, output, conv_w, conv_h); |
| |
| BorderSize border_size = _v2mm_kernel.border_size(); |
| _v2mm_input_fill_border.configure(&_input_reshaped, border_size, BorderMode::CONSTANT, PixelValue(0)); |
| |
| border_size.bottom = 0; |
| _v2mm_weights_fill_border.configure(&_weights_reshaped, border_size, BorderMode::CONSTANT, PixelValue(0)); |
| |
| // Allocate intermediate tensors |
| _input_reshaped.allocator()->allocate(); |
| _weights_reshaped.allocator()->allocate(); |
| _v2mm_output.allocator()->allocate(); |
| } |
| |
| void CLDepthwiseConvolution::run() |
| { |
| CLScheduler::get().enqueue(_im2col_kernel); |
| |
| CLScheduler::get().enqueue(_weights_reshape_kernel); |
| |
| CLScheduler::get().enqueue(_v2mm_input_fill_border); |
| CLScheduler::get().enqueue(_v2mm_weights_fill_border); |
| CLScheduler::get().enqueue(_v2mm_kernel); |
| |
| CLScheduler::get().enqueue(_vector_to_tensor_kernel); |
| } |