| /* |
| * Copyright (c) 2016-2021 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/NEON/kernels/NEGEMMTranspose1xWKernel.h" |
| |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| #include "src/core/AccessWindowStatic.h" |
| #include "src/core/NEON/INEKernel.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include <arm_neon.h> |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| TensorShape get_output_shape(const ITensorInfo *input) |
| { |
| TensorShape output_shape{ input->tensor_shape() }; |
| const size_t transpose_w = 16 / input->element_size(); |
| output_shape.set(0, input->dimension(1) * transpose_w); |
| output_shape.set(1, static_cast<size_t>(std::ceil((input->dimension(0) / static_cast<float>(transpose_w))))); |
| return output_shape; |
| } |
| |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); |
| //Note: ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input) is not needed here as this kernel doesn't use Neon FP16 instructions. |
| |
| if(output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), get_output_shape(input)); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| void NEGEMMTranspose1xWKernel::configure(const ITensor *input, ITensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| // Output tensor auto inizialitation if not yet initialized |
| auto_init_if_empty(*output->info(), get_output_shape(input->info()), 1, input->info()->data_type()); |
| |
| // Perform validate step |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info())); |
| |
| _input = input; |
| _output = output; |
| |
| const size_t vector_size = 16 / input->info()->element_size(); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps(vector_size)); |
| |
| Coordinates coord; |
| coord.set_num_dimensions(output->info()->num_dimensions()); |
| output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| Status NEGEMMTranspose1xWKernel::validate(const ITensorInfo *input, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output)); |
| |
| return Status{}; |
| } |
| |
| void NEGEMMTranspose1xWKernel::run(const Window &window, const ThreadInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INESimpleKernel::window(), window); |
| |
| /* |
| * Following an example of how the transposition1xW works when the input data type is F32 |
| * |
| * |a00 a01 a02 a03| |
| * |a10 a11 a12 a13| |
| * |a20 a21 a22 a23| = | a00 a01 a02 a03 || a10 a11 a12 a13 || a20 a21 a22 a23 || a30 a31 a32 a33 | |
| * |a30 a31 a32 a33| |
| * |
| * The output matrix will have the following shape: [ height * W, ceil(width / W) ], where W = (16 / element size of the tensor) |
| */ |
| |
| // Set window for output tensor. Set to 0 the X and Y dimensions in order to allow multi-threading implementation and future batched matrix multiplications |
| Window win_out(window); |
| win_out.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| win_out.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| |
| Iterator in(_input, window); |
| Iterator out(_output, win_out); |
| |
| const size_t in_width = _input->info()->dimension(0); |
| const size_t element_size = _input->info()->element_size(); |
| const size_t out_stride = _output->info()->strides_in_bytes()[1]; |
| const size_t vector_size = 16 / element_size; |
| |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const uint8_t *in_ptr = in.ptr(); |
| uint8_t *const out_ptr = out.ptr() + (id.y() * vector_size) * element_size + (id.x() / vector_size) * out_stride; |
| |
| for(size_t k = 0; k < vector_size; ++k) |
| { |
| // If the input width is not multiple of W, we fill the reference with 0s |
| if((id.x() + k) >= in_width) |
| { |
| std::memset(out_ptr + k * element_size, 0, element_size); |
| } |
| else |
| { |
| std::memcpy(out_ptr + k * element_size, in_ptr + k * element_size, element_size); |
| } |
| } |
| }, |
| in, out); |
| } |
| } // namespace arm_compute |