| /* |
| * Copyright (c) 2019-2021 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/CL/gemm/CLGEMMHelpers.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/CLKernelLibrary.h" |
| #include "arm_compute/core/CL/OpenCL.h" |
| #include "arm_compute/core/ITensorInfo.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| |
| #include <utility> |
| |
| namespace arm_compute |
| { |
| namespace cl_gemm |
| { |
| using namespace arm_compute::misc::shape_calculator; |
| |
| std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> configure_lhs_rhs_info(unsigned int m, unsigned int n, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int v0, unsigned int h0, |
| bool lhs_interleave, bool rhs_interleave, bool lhs_transpose, bool rhs_transpose, bool export_to_cl_image) |
| { |
| ARM_COMPUTE_ERROR_ON(m0 == 0 || n0 == 0); |
| v0 = std::max(std::min(static_cast<int>(m / m0), static_cast<int>(v0)), static_cast<int>(1)); |
| h0 = std::max(std::min(static_cast<int>(n / n0), static_cast<int>(h0)), static_cast<int>(1)); |
| |
| const GEMMLHSMatrixInfo lhs_info(m0, k0, v0, lhs_transpose, lhs_interleave); |
| const GEMMRHSMatrixInfo rhs_info(n0, k0, h0, rhs_transpose, rhs_interleave, export_to_cl_image); |
| |
| return std::make_pair(lhs_info, rhs_info); |
| } |
| |
| std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> select_lhs_rhs_info(std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> info_img, |
| std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> info_buf, |
| unsigned int n, unsigned int k, unsigned int b, DataType data_type) |
| { |
| const TensorInfo tensor_rhs_info(TensorShape(n, k, b), 1, data_type); |
| const TensorShape shape = compute_rhs_reshaped_shape(tensor_rhs_info, info_img.second); |
| const TensorInfo tensor_reshaped_info(shape, 1, data_type); |
| |
| if(bool(validate_image2d_support_on_rhs(tensor_reshaped_info, info_img.second))) |
| { |
| return info_img; |
| } |
| else |
| { |
| return info_buf; |
| } |
| } |
| |
| void update_padding_for_cl_image(ITensorInfo *tensor) |
| { |
| constexpr unsigned int num_floats_per_pixel = 4; |
| |
| const unsigned int stride_y_in_elements = tensor->strides_in_bytes()[1] / tensor->element_size(); |
| const unsigned int pixel_alignment = get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()); |
| |
| ARM_COMPUTE_ERROR_ON_MSG(pixel_alignment == 0, "Cannot retrieve cl_image pitch alignment"); |
| if(pixel_alignment == 0) |
| { |
| return; |
| } |
| |
| const unsigned int row_pitch_alignment = pixel_alignment * num_floats_per_pixel; |
| const unsigned int round_up_width = ((stride_y_in_elements + row_pitch_alignment - 1) / row_pitch_alignment) * row_pitch_alignment; |
| const unsigned int padding = round_up_width - stride_y_in_elements; |
| |
| tensor->extend_padding(PaddingSize(0, padding, 0, 0)); |
| } |
| |
| Status validate_image2d_support_on_rhs(const ITensorInfo &tensor_reshaped_info, const GEMMRHSMatrixInfo &rhs_info) |
| { |
| if(rhs_info.export_to_cl_image) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.n0 == 2) || (rhs_info.n0 == 3), "Export to cl_image only supported with n0 = 4, 8 or 16"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG((rhs_info.k0 == 2) || (rhs_info.k0 == 3), "Export to cl_image only supported with k0 = 4, 8 or 16"); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(&tensor_reshaped_info, DataType::F32, DataType::F16); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(!image2d_from_buffer_supported(CLKernelLibrary::get().get_device()), "The extension cl_khr_image2d_from_buffer is not supported on the target platform"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(get_cl_image_pitch_alignment(CLKernelLibrary::get().get_device()) == 0, "Impossible to retrieve the cl_image pitch alignment"); |
| |
| // Check the width and height of the output tensor. |
| // Since we cannot create a 3d image from a buffer, the third dimension is collapsed on the second dimension |
| const size_t max_image_w = CLKernelLibrary::get().get_device().getInfo<CL_DEVICE_IMAGE2D_MAX_WIDTH>(); |
| const size_t max_image_h = CLKernelLibrary::get().get_device().getInfo<CL_DEVICE_IMAGE2D_MAX_HEIGHT>(); |
| |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(tensor_reshaped_info.tensor_shape()[0] > max_image_w * 4, "Not supported width for cl_image"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(tensor_reshaped_info.tensor_shape()[1] * tensor_reshaped_info.tensor_shape()[2] > max_image_h, "Not supported height for cl_image"); |
| } |
| |
| return Status{}; |
| } |
| } // namespace cl_gemm |
| } // namespace arm_compute |