wehub-resource-sync
81 lines
2.7 KiB
C++
81 lines
2.7 KiB
C++
/* Copyright 2025 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_REVERSE_H_
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#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_REVERSE_H_
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#include <algorithm>
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#include <array>
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#include <cstdint>
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#include "ruy/profiler/instrumentation.h" // from @ruy
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#include "tensorflow/lite/kernels/internal/runtime_shape.h"
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namespace tflite {
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namespace reference_ops {
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template <typename Scalar>
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void Reverse(std::array<int32_t, 8>& axes, int num_axes,
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const RuntimeShape& input_shape, const Scalar* input_data,
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Scalar* output_data) {
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ruy::profiler::ScopeLabel label("Reverse");
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bool is_upper = (axes[num_axes - 1] == input_shape.DimensionsCount() - 1);
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bool is_lower = (axes[0] == 0);
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int rank = input_shape.DimensionsCount();
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if (is_upper && is_lower) {
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std::reverse_copy(input_data, input_data + input_shape.FlatSize(),
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output_data);
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return;
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} else {
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int32_t min_dim = axes[0];
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int32_t max_dim = axes[num_axes - 1];
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int upper_size = 1;
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for (int i = 0; i < min_dim; ++i) {
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upper_size *= input_shape.Dims(i);
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}
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int lower_size = 1;
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for (int i = max_dim + 1; i < rank; ++i) {
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lower_size *= input_shape.Dims(i);
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}
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int middle_size = 1;
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for (int i = min_dim; i <= max_dim; ++i) {
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middle_size *= input_shape.Dims(i);
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}
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if (lower_size > 1) {
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for (int i = 0; i < upper_size; ++i) {
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for (int j = 0; j < middle_size; ++j) {
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Scalar* src =
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(Scalar*)input_data + (i * (middle_size) + j) * lower_size;
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Scalar* dst =
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(Scalar*)output_data +
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(i * (middle_size) + (middle_size - j - 1)) * lower_size;
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memcpy(dst, src, lower_size * sizeof(Scalar));
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}
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}
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} else {
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for (int i = 0; i < upper_size; ++i) {
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std::reverse_copy(input_data + i * (middle_size),
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input_data + i * middle_size + middle_size,
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output_data + i * (middle_size));
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}
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}
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}
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}
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} // namespace reference_ops
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} // namespace tflite
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#endif // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_REVERSE_H_
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