| /* |
| * Copyright (c) 2018-2021 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/core/gpu/cl/kernels/ClWidthConcatenate2TensorsKernel.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/Utils.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "src/core/CL/CLValidate.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| #include "src/core/utils/helpers/tensor_info.h" |
| #include "support/Cast.h" |
| |
| #include "support/StringSupport.h" |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| namespace kernels |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src1, src2, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(src1); |
| ARM_COMPUTE_RETURN_ERROR_ON(src1->data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src1, src2, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON(src1->dimension(0) + src2->dimension(0) > dst->dimension(0)); |
| |
| for(size_t i = 1; i < Coordinates::num_max_dimensions; ++i) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(src1->dimension(i) != dst->dimension(i)); |
| ARM_COMPUTE_RETURN_ERROR_ON(src2->dimension(i) != dst->dimension(i)); |
| } |
| ARM_COMPUTE_RETURN_ERROR_ON(src1->num_dimensions() > 4); |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| Status ClWidthConcatenate2TensorsKernel::validate(const ITensorInfo *src1, const ITensorInfo *src2, const ITensorInfo *dst) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src1, src2, dst)); |
| return Status{}; |
| } |
| |
| ClWidthConcatenate2TensorsKernel::ClWidthConcatenate2TensorsKernel() |
| { |
| _type = CLKernelType::ELEMENTWISE; |
| } |
| |
| void ClWidthConcatenate2TensorsKernel::configure(const CLCompileContext &compile_context, ITensorInfo *src1, ITensorInfo *src2, ITensorInfo *dst) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src1, src2, dst); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src1, src2, dst)); |
| |
| auto padding_info = get_padding_info({ src1, src2, dst }); |
| |
| const unsigned int min_dimension = std::min(src1->dimension(0), src2->dimension(0)); |
| const unsigned int num_elems_processed_per_iteration = adjust_vec_size(8, min_dimension); |
| const unsigned int vec_size_leftover = dst->dimension(0) % num_elems_processed_per_iteration; |
| |
| // Add build options |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(src1->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(vec_size_leftover)); |
| build_opts.add_option("-DDEPTH=" + support::cpp11::to_string(src1->dimension(2))); |
| build_opts.add_option("-DINPUT1_WIDTH=" + support::cpp11::to_string(src1->dimension(0))); |
| build_opts.add_option("-DINPUT2_WIDTH=" + support::cpp11::to_string(src2->dimension(0))); |
| build_opts.add_option("-DELEMENT_SIZE=" + support::cpp11::to_string(src1->element_size())); |
| build_opts.add_option("-DINPUT1_ROTATE_N=" + support::cpp11::to_string((src1->dimension(0) - vec_size_leftover) % num_elems_processed_per_iteration)); |
| |
| // If input have different quantization info set quantization parameters needed for the re-quantization process |
| const bool have_different_qinfo = helpers::tensor_info::tensors_have_different_quantization_info(dst, src1, src2); |
| if(is_data_type_quantized_asymmetric(src1->data_type()) && have_different_qinfo) |
| { |
| const UniformQuantizationInfo iq1_info = src1->quantization_info().uniform(); |
| const UniformQuantizationInfo iq2_info = src2->quantization_info().uniform(); |
| const UniformQuantizationInfo oq_info = dst->quantization_info().uniform(); |
| |
| build_opts.add_option("-DOFFSET_IN1=" + float_to_string_with_full_precision(iq1_info.offset)); |
| build_opts.add_option("-DSCALE_IN1=" + float_to_string_with_full_precision(iq1_info.scale)); |
| build_opts.add_option("-DOFFSET_IN2=" + float_to_string_with_full_precision(iq2_info.offset)); |
| build_opts.add_option("-DSCALE_IN2=" + float_to_string_with_full_precision(iq2_info.scale)); |
| build_opts.add_option("-DOFFSET_OUT=" + float_to_string_with_full_precision(oq_info.offset)); |
| build_opts.add_option("-DSCALE_OUT=" + float_to_string_with_full_precision(oq_info.scale)); |
| } |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, "concatenate_width_x2", build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration)); |
| ICLKernel::configure_internal(win.collapse(win, Window::DimZ)); |
| |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| |
| // Set config_id for enabling LWS tuning |
| _config_id = "concatenate_width_x2_"; |
| _config_id += lower_string(string_from_data_type(src1->data_type())); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(src1->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(src1->dimension(1)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(src2->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(src2->dimension(1)); |
| } |
| |
| void ClWidthConcatenate2TensorsKernel::run_op(ITensorPack &tensors, const Window &window, ::cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| Window slice = window.first_slice_window_4D(); |
| |
| const auto src0 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC)); |
| const auto src1 = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_VEC + 1)); |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_4D_tensor_argument(idx, src0, slice); |
| add_4D_tensor_argument(idx, src1, slice); |
| add_4D_tensor_argument(idx, dst, slice); |
| enqueue(queue, *this, window, lws_hint()); |
| } |
| while(window.slide_window_slice_4D(slice)); |
| } |
| } // namespace kernels |
| } // namespace opencl |
| } // namespace arm_compute |