| /* | |
| * 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<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); | |
| auto biases = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_BIAS)); | |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(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<cl_uint>(idx++, src->info()->dimension(0)); | |
| _kernel.setArg<cl_uint>(idx++, src->info()->dimension(1)); | |
| _kernel.setArg<cl_uint>(idx++, src->info()->dimension(2)); | |
| _kernel.setArg<cl_uint>(idx++, src->info()->dimension(3)); | |
| _kernel.setArg<cl_uint>(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 |