| /* |
| * 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/CLBatchNormalizationLayerKernel.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/FixedPoint.h" |
| #include "arm_compute/core/Helpers.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" |
| |
| #include "support/ToolchainSupport.h" |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| Error validate_arguments(const ITensorInfo *input, const ITensorInfo *output, |
| const ITensorInfo *mean, const ITensorInfo *var, |
| const ITensorInfo *beta, const ITensorInfo *gamma, |
| float epsilon) |
| { |
| ARM_COMPUTE_UNUSED(epsilon); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var, beta, gamma); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var, beta, gamma); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, mean, var, beta, gamma); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(2) != mean->dimension(0)); |
| |
| if(output != nullptr && output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); |
| } |
| |
| return Error{}; |
| } |
| |
| std::pair<Error, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) |
| { |
| const unsigned int num_elems_processed_per_iteration = 16 / input->element_size(); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input, Steps(num_elems_processed_per_iteration)); |
| AccessWindowHorizontal input_access(input, 0, num_elems_processed_per_iteration); |
| |
| bool window_changed; |
| if(output != nullptr) |
| { |
| AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); |
| window_changed = update_window_and_padding(win, input_access, output_access); |
| output_access.set_valid_region(win, input->valid_region()); |
| } |
| else |
| { |
| window_changed = update_window_and_padding(win, input_access); |
| } |
| |
| Error err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Error{}; |
| return std::make_pair(err, win); |
| } |
| } // namespace |
| |
| CLBatchNormalizationLayerKernel::CLBatchNormalizationLayerKernel() |
| : _input(nullptr), _output(nullptr), _mean(nullptr), _var(nullptr), _beta(nullptr), _gamma(nullptr), _epsilon(0) |
| { |
| } |
| |
| void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, |
| float epsilon) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var, beta, gamma); |
| |
| _input = input; |
| _output = output; |
| _mean = mean; |
| _var = var; |
| _beta = beta; |
| _gamma = gamma; |
| _epsilon = epsilon; |
| |
| if(output != nullptr) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input->info(), output->info()); |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| } |
| |
| ARM_COMPUTE_ERROR_THROW_ON(CLBatchNormalizationLayerKernel::validate(input->info(), (output != nullptr) ? output->info() : nullptr, |
| mean->info(), var->info(), beta->info(), gamma->info(), epsilon)); |
| |
| const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); |
| |
| // Set build options |
| std::set<std::string> build_opts; |
| build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type()))); |
| build_opts.emplace(("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration))); |
| build_opts.emplace(output == nullptr ? "-DIN_PLACE" : ""); |
| if(is_data_type_fixed_point(input->info()->data_type())) |
| { |
| build_opts.emplace("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())); |
| } |
| |
| // Create kernel |
| _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("batchnormalization_layer", build_opts)); |
| |
| // Set kernel static arguments |
| unsigned int include_output = (output != nullptr) ? 1 : 0; |
| unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor() + 4 * num_arguments_per_1D_tensor(); // Skip the input and output parameters |
| _kernel.setArg<cl_float>(idx++, _epsilon); |
| |
| // Configure kernel window |
| auto win_config = validate_and_configure_window(input->info(), (output == nullptr) ? nullptr : output->info()); |
| ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| ICLKernel::configure(win_config.second); |
| } |
| |
| Error CLBatchNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, |
| const ITensorInfo *mean, const ITensorInfo *var, |
| const ITensorInfo *beta, const ITensorInfo *gamma, |
| float epsilon) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, var, beta, gamma, epsilon)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), (output == nullptr) ? nullptr : output->clone().get()).first); |
| |
| return Error{}; |
| } |
| |
| void CLBatchNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); |
| |
| Window slice = window.first_slice_window_3D(); |
| |
| Window vector_slice = window.first_slice_window_1D(); |
| vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| |
| unsigned int include_output = (_output != nullptr) ? 1 : 0; |
| unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor(); |
| add_1D_tensor_argument(idx, _mean, vector_slice); |
| add_1D_tensor_argument(idx, _var, vector_slice); |
| add_1D_tensor_argument(idx, _beta, vector_slice); |
| add_1D_tensor_argument(idx, _gamma, vector_slice); |
| |
| do |
| { |
| idx = 0; |
| add_3D_tensor_argument(idx, _input, slice); |
| if(_output != nullptr) |
| { |
| add_3D_tensor_argument(idx, _output, slice); |
| } |
| enqueue(queue, *this, slice); |
| } |
| while(window.slide_window_slice_3D(slice)); |
| } |