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Diffstat (limited to 'src/core/NEON/kernels/NEGEMMTranspose1xWKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEGEMMTranspose1xWKernel.cpp | 144 |
1 files changed, 0 insertions, 144 deletions
diff --git a/src/core/NEON/kernels/NEGEMMTranspose1xWKernel.cpp b/src/core/NEON/kernels/NEGEMMTranspose1xWKernel.cpp deleted file mode 100644 index 20b0cabd1f..0000000000 --- a/src/core/NEON/kernels/NEGEMMTranspose1xWKernel.cpp +++ /dev/null @@ -1,144 +0,0 @@ -/* - * 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/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 CPU 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)); - - 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 |