| /* |
| * 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/core/CL/kernels/CLQuantizationLayerKernel.h" |
| |
| #include "arm_compute/core/AccessWindowStatic.h" |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| using namespace arm_compute; |
| |
| CLQuantizationLayerKernel::CLQuantizationLayerKernel() |
| : _input(nullptr), _output(nullptr), _min_max(nullptr) |
| { |
| } |
| |
| void CLQuantizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output, ICLTensor *min_max) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(output, min_max); |
| ARM_COMPUTE_ERROR_ON(input->info()->num_dimensions() < 3); |
| |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, DataType::U8, 0); |
| |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| |
| _input = input; |
| _output = output; |
| _min_max = min_max; |
| |
| constexpr unsigned int num_elems_processed_per_iteration = 4; |
| |
| // Create kernel |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("quantization_layer")); |
| |
| // Configure window |
| Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |
| AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); |
| AccessWindowStatic min_max_access(min_max->info(), 0, 0, 2, min_max->info()->dimension(1)); |
| |
| // Update window and padding |
| update_window_and_padding(win, input_access, output_access, min_max_access); |
| |
| output_access.set_valid_region(win, input->info()->valid_region()); |
| |
| ICLKernel::configure(win); |
| } |
| |
| void CLQuantizationLayerKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), 3); |
| Window slice = window_collapsed.first_slice_window_3D(); |
| |
| Window window_min_max; |
| window_min_max.use_tensor_dimensions(_min_max->info()->tensor_shape()); |
| window_min_max.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| window_min_max.collapse_if_possible(ICLKernel::window(), 1); |
| |
| Window slice_min_max = window_min_max.first_slice_window_1D(); |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_3D_tensor_argument(idx, _input, slice); |
| add_3D_tensor_argument(idx, _output, slice); |
| add_1D_tensor_argument(idx, _min_max, slice_min_max); |
| enqueue(queue, *this, slice); |
| } |
| while(window.slide_window_slice_3D(slice) && window_min_max.slide_window_slice_1D(slice_min_max)); |
| } |