| /* |
| * Copyright (c) 2019-2021, 2023 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/CLInstanceNormalizationLayerKernel.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 "arm_compute/core/utils/StringUtils.h" |
| |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "support/StringSupport.h" |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, |
| const ITensorInfo *output, |
| const InstanceNormalizationLayerKernelInfo &info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(info.epsilon == 0.f, "Epsilon must be different than 0"); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32); |
| |
| 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_DATA_LAYOUT(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), |
| "Input and output have different number of channels"); |
| } |
| |
| return Status{}; |
| } |
| |
| Status validate_arguments_meanvar(const ITensorInfo *input, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(input, DataType::F16, DataType::F32); |
| |
| if (output != nullptr && output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_channels() != output->num_channels(), |
| "Input and output have different number of channels"); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| CLComputeMeanVariance::CLComputeMeanVariance() : _input(nullptr), _output(nullptr) |
| { |
| _type = CLKernelType::ELEMENTWISE; |
| } |
| |
| void CLComputeMeanVariance::configure(const CLCompileContext &compile_context, |
| ICLTensor *input, |
| ICLTensor *output, |
| bool use_mixed_precision) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input); |
| auto padding_info = get_padding_info({input, output}); |
| |
| _input = input; |
| _output = output == nullptr ? input : output; |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_meanvar(_input->info(), _output->info())); |
| const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); |
| |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DINTERNAL_DATA_TYPE=" + |
| (use_mixed_precision ? "float" : get_cl_type_from_data_type(input->info()->data_type()))); |
| 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("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0))); |
| build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1))); |
| build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2))); |
| build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC"); |
| // Create kernel |
| _kernel = create_kernel(compile_context, "compute_mean_var", build_opts.options()); |
| |
| // We handle the planes manually |
| Window win = calculate_max_window(*(input->info()), Steps(1)); |
| const auto data_layout = input->info()->data_layout(); |
| const unsigned int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); |
| const unsigned int batches_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES); |
| const unsigned int input_channel = input->info()->dimension(channel_idx); |
| const unsigned int input_batches = input->info()->dimension(batches_idx); |
| const TensorShape out_shape(input_channel, 2u, input_batches); |
| |
| // Output auto initialization if not yet initialized |
| if (use_mixed_precision) |
| { |
| auto_init_if_empty(*_output->info(), out_shape, 1, DataType::F32); |
| } |
| else |
| { |
| auto_init_if_empty(*_output->info(), out_shape, 1, input->info()->data_type()); |
| } |
| ICLKernel::configure_internal(win); |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| } |
| |
| Status CLComputeMeanVariance::validate(const ITensorInfo *input, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_meanvar(input, output)); |
| return Status{}; |
| } |
| |
| void CLComputeMeanVariance::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); |
| |
| Window collapsed_window = window.collapse(window, Window::DimZ); |
| |
| // We will process the planes together |
| if (_input->info()->data_layout() == DataLayout::NCHW) |
| { |
| collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| } |
| else |
| { |
| collapsed_window.set(Window::DimZ, Window::Dimension(0, 1, 1)); |
| collapsed_window.set(Window::DimY, Window::Dimension(0, _input->info()->dimension(3), 1)); |
| } |
| unsigned int idx = 0; |
| add_4D_tensor_argument(idx, _input, collapsed_window); |
| add_3D_tensor_argument(idx, _output, collapsed_window); |
| |
| enqueue(queue, *this, collapsed_window, lws_hint()); |
| } |
| |
| CLInstanceNormalizationLayerKernel::CLInstanceNormalizationLayerKernel() |
| : _input(nullptr), _output(nullptr), _mean(nullptr), _run_in_place(false) |
| { |
| _type = CLKernelType::ELEMENTWISE; |
| } |
| |
| void CLInstanceNormalizationLayerKernel::configure(const CLCompileContext &compile_context, |
| ICLTensor *input, |
| ICLTensor *mean_var, |
| ICLTensor *output, |
| const InstanceNormalizationLayerKernelInfo &info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input); |
| auto padding_info = get_padding_info({input, output}); |
| |
| _input = input; |
| _output = output == nullptr ? input : output; |
| _mean = mean_var; |
| |
| _run_in_place = (output == nullptr) || (output == input); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(_input->info(), _output->info(), info)); |
| const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size(); |
| |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); |
| build_opts.add_option("-DINTERNAL_DATA_TYPE=" + (info.use_mixed_precision |
| ? "float" |
| : 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("-DDIM_X=" + support::cpp11::to_string(input->info()->dimension(0))); |
| build_opts.add_option("-DDIM_Y=" + support::cpp11::to_string(input->info()->dimension(1))); |
| build_opts.add_option("-DDIM_Z=" + support::cpp11::to_string(input->info()->dimension(2))); |
| build_opts.add_option("-DGAMMA=" + float_to_string_with_full_precision(info.gamma)); |
| build_opts.add_option("-DBETA=" + float_to_string_with_full_precision(info.beta)); |
| build_opts.add_option("-DEPSILON=" + float_to_string_with_full_precision(info.epsilon)); |
| build_opts.add_option_if(_run_in_place, "-DIN_PLACE"); |
| build_opts.add_option_if(_input->info()->data_layout() == DataLayout::NHWC, "-DNHWC"); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, "instance_normalization", build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps(1)); |
| if (output != nullptr) |
| { |
| auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type()); |
| } |
| |
| ICLKernel::configure_internal(win); |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| } |
| |
| Status CLInstanceNormalizationLayerKernel::validate(const ITensorInfo *input, |
| const ITensorInfo *output, |
| const InstanceNormalizationLayerKernelInfo &info) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info)); |
| return Status{}; |
| } |
| |
| void CLInstanceNormalizationLayerKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); |
| |
| Window collapsed_window = window.collapse(window, Window::DimZ); |
| |
| // We will process the planes together |
| if (_input->info()->data_layout() == DataLayout::NCHW) |
| { |
| collapsed_window.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| } |
| else |
| { |
| collapsed_window.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| collapsed_window.set(Window::DimZ, Window::Dimension(0, _input->info()->dimension(3), 1)); |
| } |
| |
| unsigned int idx = 0; |
| add_4D_tensor_argument(idx, _input, collapsed_window); |
| add_3D_tensor_argument(idx, _mean, collapsed_window); |
| |
| if (!_run_in_place) |
| { |
| add_4D_tensor_argument(idx, _output, collapsed_window); |
| } |
| |
| enqueue(queue, *this, collapsed_window, lws_hint()); |
| } |
| } // namespace arm_compute |