142 lines
5.0 KiB
C++
142 lines
5.0 KiB
C++
/*
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* Copyright (c) 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 "tests/validation/reference/Logical.h"
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#include "src/core/KernelTypes.h"
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#include "tests/framework/Asserts.h"
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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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T logical_binary_op(arm_compute::kernels::LogicalOperation op, T src1, T src2)
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{
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switch(op)
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{
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case arm_compute::kernels::LogicalOperation::And:
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return src1 && src2;
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case arm_compute::kernels::LogicalOperation::Or:
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return src1 || src2;
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// The following operators are either invalid or not binary operator
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case arm_compute::kernels::LogicalOperation::Not:
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/* fall through */
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case arm_compute::kernels::LogicalOperation::Unknown:
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/* fall through */
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default:
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ARM_COMPUTE_ASSERT(true);
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}
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return T{};
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}
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template <size_t dim>
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struct BroadcastUnroll
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{
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template <typename T>
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static void unroll(arm_compute::kernels::LogicalOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst,
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Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst)
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{
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const bool src1_is_broadcast = (src1.shape()[dim - 1] != dst.shape()[dim - 1]);
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const bool src2_is_broadcast = (src2.shape()[dim - 1] != dst.shape()[dim - 1]);
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id_src1.set(dim - 1, 0);
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id_src2.set(dim - 1, 0);
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id_dst.set(dim - 1, 0);
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#if defined(_OPENMP)
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#pragma omp parallel for
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#endif /* _OPENMP */
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for(size_t i = 0; i < dst.shape()[dim - 1]; ++i)
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{
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BroadcastUnroll < dim - 1 >::unroll(op, src1, src2, dst, id_src1, id_src2, id_dst);
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id_src1[dim - 1] += !src1_is_broadcast;
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id_src2[dim - 1] += !src2_is_broadcast;
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++id_dst[dim - 1];
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}
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}
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};
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template <>
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struct BroadcastUnroll<0>
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{
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template <typename T>
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static void unroll(arm_compute::kernels::LogicalOperation op, const SimpleTensor<T> &src1, const SimpleTensor<T> &src2, SimpleTensor<T> &dst,
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Coordinates &id_src1, Coordinates &id_src2, Coordinates &id_dst)
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{
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dst[coord2index(dst.shape(), id_dst)] = logical_binary_op(op, src1[coord2index(src1.shape(), id_src1)], src2[coord2index(src2.shape(), id_src2)]);
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}
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};
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template <typename T>
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SimpleTensor<T> logical_or(const SimpleTensor<T> &src1, const SimpleTensor<T> &src2)
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{
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Coordinates id_src1{};
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Coordinates id_src2{};
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Coordinates id_dst{};
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SimpleTensor<T> dst{ TensorShape::broadcast_shape(src1.shape(), src2.shape()), src1.data_type() };
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BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(arm_compute::kernels::LogicalOperation::Or, src1, src2, dst, id_src1, id_src2, id_dst);
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return dst;
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}
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template <typename T>
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SimpleTensor<T> logical_and(const SimpleTensor<T> &src1, const SimpleTensor<T> &src2)
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{
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Coordinates id_src1{};
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Coordinates id_src2{};
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Coordinates id_dst{};
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SimpleTensor<T> dst{ TensorShape::broadcast_shape(src1.shape(), src2.shape()), src1.data_type() };
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BroadcastUnroll<Coordinates::num_max_dimensions>::unroll(arm_compute::kernels::LogicalOperation::And, src1, src2, dst, id_src1, id_src2, id_dst);
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return dst;
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}
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template <typename T>
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SimpleTensor<T> logical_not(const SimpleTensor<T> &src)
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{
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SimpleTensor<T> dst(src.shape(), src.data_type());
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#if defined(_OPENMP)
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#pragma omp parallel for
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#endif /* _OPENMP */
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for(int i = 0; i < src.num_elements(); ++i)
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{
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dst[i] = !src[i];
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}
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return dst;
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}
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template SimpleTensor<uint8_t> logical_or(const SimpleTensor<uint8_t> &src1, const SimpleTensor<uint8_t> &src2);
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template SimpleTensor<uint8_t> logical_and(const SimpleTensor<uint8_t> &src1, const SimpleTensor<uint8_t> &src2);
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template SimpleTensor<uint8_t> logical_not(const SimpleTensor<uint8_t> &src1);
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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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