113 lines
4.6 KiB
C++
113 lines
4.6 KiB
C++
/*
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* Copyright (c) 2018-2020 Arm Limited.
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*
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* SPDX-License-Identifier: MIT
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*
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* Permission is hereby granted, free of charge, to any person obtaining a copy
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* of this software and associated documentation files (the "Software"), to
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* deal in the Software without restriction, including without limitation the
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* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
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* sell copies of the Software, and to permit persons to whom the Software is
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* furnished to do so, subject to the following conditions:
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*
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* The above copyright notice and this permission notice shall be included in all
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* copies or substantial portions of the Software.
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*
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* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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* SOFTWARE.
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*/
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#include "GEMMReshapeRHSMatrix.h"
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#include "arm_compute/core/Types.h"
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#include "tests/validation/Helpers.h"
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#include <algorithm>
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#include <cmath>
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#include <cstring>
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namespace arm_compute
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{
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namespace test
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{
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namespace validation
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{
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namespace reference
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{
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template <typename T>
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SimpleTensor<T> gemm_reshape_rhs_matrix(const SimpleTensor<T> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info)
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{
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ARM_COMPUTE_ERROR_ON(in.shape().num_dimensions() > 3);
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SimpleTensor<T> out{ output_shape, in.data_type() };
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// Initialize the output tensor with zero
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std::memset(&out[0], 0, out.num_elements() * sizeof(T));
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const unsigned int N = in.shape()[0];
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const unsigned int K = in.shape()[1];
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const unsigned int B = in.shape()[2];
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const unsigned int num_tiles_x = std::ceil(N / static_cast<float>(rhs_info.n0));
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const unsigned int num_tiles_y = std::ceil(K / static_cast<float>(rhs_info.k0));
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const TensorShape tile_dims(rhs_info.n0, rhs_info.k0);
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const TensorShape tile_dims_transposed(rhs_info.k0, rhs_info.n0);
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// Simple tensor for the input tile
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SimpleTensor<T> src_tile{ tile_dims, in.data_type() };
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// Simple tensor for the input tile
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SimpleTensor<T> src_tile_transposed{ tile_dims_transposed, in.data_type() };
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// Simple tensor to use when storing the values
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SimpleTensor<T> *tile_to_use = rhs_info.transpose ? &src_tile_transposed : &src_tile;
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const unsigned int offset_output_x = rhs_info.interleave ? tile_to_use->shape()[0] : tile_to_use->shape()[0] * tile_to_use->shape()[1];
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const unsigned int step_output_x = rhs_info.interleave ? tile_to_use->shape()[0] * rhs_info.h0 : tile_to_use->shape()[0];
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#ifdef ARM_COMPUTE_OPENMP
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#pragma omp parallel for schedule(dynamic, 1) collapse(3)
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#endif /* _OPENMP */
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for(unsigned int z = 0; z < B; ++z)
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{
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for(unsigned int y = 0; y < num_tiles_y; ++y)
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{
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for(unsigned int x = 0; x < num_tiles_x; ++x)
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{
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// Get the tile from the input tensor
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get_tile<T>(in, src_tile, Coordinates(x * rhs_info.n0, y * rhs_info.k0, z, 0));
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if(rhs_info.transpose)
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{
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// Transpose matrix
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transpose_matrix<T>(src_tile, src_tile_transposed);
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}
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// Store
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const unsigned int offset_output = (y * rhs_info.k0 * rhs_info.n0 * rhs_info.h0) + ((x % rhs_info.h0) * offset_output_x) + ((x / rhs_info.h0) * out.shape()[0]) + (z * out.shape()[0] * out.shape()[1]);
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for(unsigned int i = 0; i < tile_to_use->shape()[1]; ++i)
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{
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const unsigned int offset_tile = i * tile_to_use->shape()[0];
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// Copy per row
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std::copy(&(*tile_to_use)[offset_tile], &(*tile_to_use)[offset_tile + tile_to_use->shape()[0]], &out[offset_output + i * step_output_x]);
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}
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}
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}
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}
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return out;
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}
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template SimpleTensor<int> gemm_reshape_rhs_matrix(const SimpleTensor<int> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info);
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template SimpleTensor<short> gemm_reshape_rhs_matrix(const SimpleTensor<short> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info);
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template SimpleTensor<char> gemm_reshape_rhs_matrix(const SimpleTensor<char> &in, const TensorShape &output_shape, const GEMMRHSMatrixInfo &rhs_info);
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} // namespace reference
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} // namespace validation
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} // namespace test
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} // namespace arm_compute
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