/* Copyright 2018 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_REFERENCE_INTEGER_OPS_DEQUANTIZE_H_
#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_DEQUANTIZE_H_

#include "tensorflow/lite/kernels/internal/common.h"
#include "tensorflow/lite/kernels/internal/types.h"

namespace tflite {
namespace reference_integer_ops {

template <typename T>
inline void Dequantize(const tflite::DequantizationParams& op_params,
                       const RuntimeShape& input_shape, const T* input_data,
                       const RuntimeShape& output_shape, float* output_data) {
  const int32_t zero_point = op_params.zero_point;
  const double scale = op_params.scale;
  const int flat_size = MatchingFlatSize(input_shape, output_shape);

  for (int i = 0; i < flat_size; i++) {
    const int32_t val = static_cast<int32_t>(input_data[i]);
    const float result = static_cast<float>(scale * (val - zero_point));
    output_data[i] = result;
  }
}

}  // namespace reference_integer_ops
}  // namespace tflite

#endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_INTEGER_OPS_DEQUANTIZE_H_
