chromium/third_party/tflite/src/tensorflow/lite/kernels/internal/optimized/integer_ops/lut.h

/* Copyright 2022 The TensorFlow Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_OPTIMIZED_INTEGER_OPS_LUT_H_
#define TENSORFLOW_LITE_KERNELS_INTERNAL_OPTIMIZED_INTEGER_OPS_LUT_H_

#include <cstdint>

#if __aarch64__ && __clang__
#include <arm_neon.h>
#endif

#include "tensorflow/lite/kernels/internal/optimized/optimized_ops.h"

namespace tflite {
namespace optimized_integer_ops {

inline void LookupTable(const uint8_t* input_data, int num_elements,
                        const uint8_t* lut, uint8_t* output_data) { … }

// LUTPopulate<int8_t> has ordered the LUT so that indexing it with an
// int8_t is just done by casting it to an uint8_t. We can thus reuse the uint8
// LookupTable function.
inline void LookupTable(const int8_t* input_data, int num_elements,
                        const int8_t* lut, int8_t* output_data) { … }

}  // namespace optimized_integer_ops
}  // namespace tflite

#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_OPTIMIZED_INTEGER_OPS_LUT_H_