/* * Copyright (c) 2017-2021 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/gpu/cl/kernels/ClWeightsReshapeKernel.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" #include "support/Cast.h" #include "support/StringSupport.h" namespace arm_compute { using namespace misc::shape_calculator; namespace opencl { namespace kernels { namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output, unsigned int num_groups) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); ARM_COMPUTE_RETURN_ERROR_ON(num_groups == 0); ARM_COMPUTE_RETURN_ERROR_ON(input->data_layout() == DataLayout::NHWC && num_groups > 1); ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4 && num_groups > 1); ARM_COMPUTE_RETURN_ERROR_ON((input->dimension(3) % num_groups) != 0); if (biases != nullptr) { ARM_COMPUTE_RETURN_ERROR_ON(!is_data_type_float(input->data_type())); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, biases); ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) && (biases->num_dimensions() != 1)); ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 5) && (biases->num_dimensions() != 2)); ARM_COMPUTE_RETURN_ERROR_ON((input->num_dimensions() == 4) && (biases->dimension(0) != input->tensor_shape()[3])); ARM_COMPUTE_RETURN_ERROR_ON( (input->num_dimensions() == 5) && (biases->dimension(0) != input->tensor_shape()[3] || biases->dimension(1) != input->tensor_shape()[4])); } // Checks performed when output is configured if (output->total_size() != 0) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS( output->tensor_shape(), compute_weights_reshaped_shape(*input, biases != nullptr, num_groups)); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); } return Status{}; } } // namespace ClWeightsReshapeKernel::ClWeightsReshapeKernel() { _type = CLKernelType::ELEMENTWISE; } void ClWeightsReshapeKernel::configure(const ClCompileContext &compile_context, const ITensorInfo *src, const ITensorInfo *biases, ITensorInfo *dst, unsigned int num_groups) { ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); // Output tensor auto inizialitation if not yet initialized auto_init_if_empty( *dst, src->clone()->set_tensor_shape(compute_weights_reshaped_shape(*src, (biases != nullptr), num_groups))); // Perform validation step ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, biases, dst, num_groups)); auto padding_info = get_padding_info({src, biases, dst}); const DataType data_type = src->data_type(); // Create build options CLBuildOptions build_opts; build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(data_size_from_type(data_type))); build_opts.add_option("-DNUM_GROUPS=" + support::cpp11::to_string(num_groups)); build_opts.add_option_if(biases != nullptr, "-DHAS_BIAS"); // Create kernel _kernel = create_kernel(compile_context, "reshape_to_columns", build_opts.options()); // Configure window Window win = calculate_max_window(*src, Steps()); ICLKernel::configure_internal(win); ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); } Status ClWeightsReshapeKernel::validate(const ITensorInfo *src, const ITensorInfo *biases, const ITensorInfo *dst, unsigned int num_groups) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, biases, dst, num_groups)); return Status{}; } void ClWeightsReshapeKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window); auto src = utils::cast::polymorphic_downcast(tensors.get_const_tensor(TensorType::ACL_SRC)); auto biases = utils::cast::polymorphic_downcast(tensors.get_const_tensor(TensorType::ACL_BIAS)); auto dst = utils::cast::polymorphic_downcast(tensors.get_tensor(TensorType::ACL_DST)); Window out_window; out_window.use_tensor_dimensions(dst->info()->tensor_shape()); Window in_slice = window.first_slice_window_3D(); Window out_slice = out_window.first_slice_window_2D(); Window biases_window; Window biases_slice; unsigned int idx = num_arguments_per_3D_tensor() + num_arguments_per_2D_tensor(); idx += (biases != nullptr) ? num_arguments_per_1D_tensor() : 0; _kernel.setArg(idx++, src->info()->dimension(0)); _kernel.setArg(idx++, src->info()->dimension(1)); _kernel.setArg(idx++, src->info()->dimension(2)); _kernel.setArg(idx++, src->info()->dimension(3)); _kernel.setArg(idx++, dst->info()->strides_in_bytes().z()); if (biases != nullptr) { biases_window.use_tensor_dimensions(biases->info()->tensor_shape()); biases_slice = biases_window.first_slice_window_1D(); } do { // Set arguments unsigned idx = 0; add_3D_tensor_argument(idx, src, in_slice); add_2D_tensor_argument(idx, dst, out_slice); if (biases != nullptr) { add_1D_tensor_argument(idx, biases, biases_slice); ARM_COMPUTE_UNUSED(biases_window.slide_window_slice_1D(biases_slice)); } // Run kernel enqueue(queue, *this, in_slice, lws_hint()); } while (window.slide_window_slice_4D(in_slice) && out_window.slide_window_slice_2D(out_slice)); } } // namespace kernels } // namespace opencl } // namespace arm_compute