| /* |
| * Copyright (c) 2017-2020 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 "src/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/Helpers.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Utils.h" |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include "support/StringSupport.h" |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, |
| const ITensorInfo *mean, const ITensorInfo *var, |
| const ITensorInfo *beta, const ITensorInfo *gamma, |
| float epsilon, ActivationLayerInfo act_info) |
| { |
| ARM_COMPUTE_UNUSED(epsilon); |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, var); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, mean, var); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->dimension(get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL)) != mean->dimension(0)); |
| if(beta != nullptr) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, beta); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, beta); |
| } |
| if(gamma != nullptr) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(mean, gamma); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, gamma); |
| } |
| |
| if(act_info.enabled()) |
| { |
| ActivationLayerInfo::ActivationFunction act = act_info.activation(); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() != DataType::F32 && input->data_type() != DataType::F16); |
| ARM_COMPUTE_RETURN_ERROR_ON(act != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::RELU |
| && act != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::BOUNDED_RELU |
| && act != ActivationLayerInfo::ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU); |
| ARM_COMPUTE_RETURN_ERROR_ON(act_info.b() > act_info.a()); |
| } |
| |
| if(output != nullptr && output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| } |
| |
| return Status{}; |
| } |
| |
| std::pair<Status, Window> validate_and_configure_window_nchw(ITensorInfo *input, ITensorInfo *output) |
| { |
| const unsigned int num_elems_processed_per_iteration = adjust_vec_size(16 / input->element_size(), input->dimension(0)); |
| |
| // 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 = false; |
| 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); |
| } |
| |
| Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; |
| return std::make_pair(err, win); |
| } |
| } // namespace |
| |
| CLBatchNormalizationLayerKernel::CLBatchNormalizationLayerKernel() |
| : _input(nullptr), _output(nullptr), _mean(nullptr), _var(nullptr), _beta(nullptr), _gamma(nullptr), _epsilon(0), _run_in_place(false) |
| { |
| } |
| |
| void CLBatchNormalizationLayerKernel::configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, |
| float epsilon, ActivationLayerInfo act_info) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, output, mean, var, beta, gamma, epsilon, act_info); |
| } |
| |
| void CLBatchNormalizationLayerKernel::configure(const CLCompileContext &compile_context, ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, |
| const ICLTensor *gamma, |
| float epsilon, ActivationLayerInfo act_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, mean, var); |
| |
| auto padding_info = get_padding_info({ input, output, mean, var, beta, gamma }); |
| _input = input; |
| _output = output; |
| _mean = mean; |
| _var = var; |
| _beta = beta; |
| _gamma = gamma; |
| _epsilon = epsilon; |
| |
| _run_in_place = (output == nullptr) || (output == input); |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), (output != nullptr) ? output->info() : nullptr, |
| mean->info(), var->info(), (beta != nullptr) ? beta->info() : nullptr, |
| (gamma != nullptr) ? gamma->info() : nullptr, epsilon, act_info)); |
| |
| unsigned int num_elems_processed_per_iteration = adjust_vec_size(16 / input->info()->element_size(), input->info()->dimension(0)); |
| |
| // Set build options |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); |
| build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); |
| build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(input->info()->dimension(0) % num_elems_processed_per_iteration)); |
| build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); |
| build_opts.add_option_if(act_info.enabled(), "-DA_VAL=" + float_to_string_with_full_precision(act_info.a())); |
| build_opts.add_option_if(act_info.enabled(), "-DB_VAL=" + float_to_string_with_full_precision(act_info.b())); |
| build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); |
| build_opts.add_option_if(beta == nullptr, "-DUSE_DEFAULT_BETA"); |
| build_opts.add_option_if(gamma == nullptr, "-DUSE_DEFAULT_GAMMA"); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, "batchnormalization_layer_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()); |
| |
| // Set kernel static arguments |
| unsigned int include_output = (!_run_in_place) ? 1 : 0; |
| unsigned int idx = (1 + include_output) * num_arguments_per_3D_tensor() + 2 * num_arguments_per_1D_tensor(); // Skip the input and output parameters |
| if(_beta != nullptr) |
| { |
| idx += num_arguments_per_1D_tensor(); // Skip beta parameter |
| } |
| if(_gamma != nullptr) |
| { |
| idx += num_arguments_per_1D_tensor(); // Skip gamma parameter |
| } |
| _kernel.setArg<cl_float>(idx++, _epsilon); |
| |
| if(output != nullptr) |
| { |
| // Output tensor auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), *input->info()->clone()); |
| } |
| |
| // Configure kernel window |
| if(input->info()->data_layout() == DataLayout::NHWC) |
| { |
| Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |
| ICLKernel::configure_internal(win); |
| } |
| else |
| { |
| auto win_config = validate_and_configure_window_nchw(input->info(), (_run_in_place) ? nullptr : output->info()); |
| ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| ICLKernel::configure_internal(win_config.second); |
| } |
| |
| ARM_COMPUTE_ERROR_ON(input->info()->data_layout() == DataLayout::NHWC && has_padding_changed(padding_info)); |
| |
| _config_id = "batch_normalization_layer_"; |
| _config_id += string_from_data_type(input->info()->data_type()); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(input->info()->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(input->info()->dimension(1)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(input->info()->dimension(2)); |
| _config_id += "_"; |
| _config_id += lower_string(string_from_data_layout(input->info()->data_layout())); |
| } |
| |
| Status CLBatchNormalizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, |
| const ITensorInfo *mean, const ITensorInfo *var, |
| const ITensorInfo *beta, const ITensorInfo *gamma, |
| float epsilon, ActivationLayerInfo act_info) |
| { |
| const bool run_in_place = (output == nullptr) || (output == input); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, mean, var, beta, gamma, epsilon, act_info)); |
| |
| if(input->data_layout() != DataLayout::NHWC) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_nchw(input->clone().get(), (run_in_place) ? nullptr : output->clone().get()) |
| .first); |
| } |
| |
| return Status{}; |
| } |
| |
| 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 = (!_run_in_place) ? 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); |
| if(_beta != nullptr) |
| { |
| add_1D_tensor_argument(idx, _beta, vector_slice); |
| } |
| if(_gamma != nullptr) |
| { |
| add_1D_tensor_argument(idx, _gamma, vector_slice); |
| } |
| |
| do |
| { |
| idx = 0; |
| add_3D_tensor_argument(idx, _input, slice); |
| if(!_run_in_place) |
| { |
| add_3D_tensor_argument(idx, _output, slice); |
| } |
| enqueue(queue, *this, slice, lws_hint()); |
| } |
| while(window.slide_window_slice_3D(slice)); |
| } |