/* Copyright 2015 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.
==============================================================================*/

#if GOOGLE_CUDA

#define EIGEN_USE_GPU

#include "tensorflow/core/kernels/quantize_and_dequantize_op.h"

#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/platform/types.h"

namespace tensorflow {

typedef Eigen::GpuDevice GPUDevice;

namespace functor {
template <typename T>
struct QuantizeAndDequantizeOneScaleFunctor<GPUDevice, T> {
  void operator()(const GPUDevice& d, typename TTypes<T>::ConstVec input,
                  bool signed_input, int num_bits, bool range_given,
                  typename TTypes<T>::Scalar input_min,
                  typename TTypes<T>::Scalar input_max,
                  typename TTypes<T>::Vec out) {
    QuantizeAndDequantizeOneScaleImpl<GPUDevice, T>::Compute(
        d, input, signed_input, range_given, num_bits, input_min, input_max,
        out);
  }
};
}  // end namespace functor

// Instantiate the GPU implementation for float and double.
template struct functor::QuantizeAndDequantizeOneScaleFunctor<GPUDevice, float>;
template struct functor::QuantizeAndDequantizeOneScaleFunctor<GPUDevice,
                                                              double>;

}  // end namespace tensorflow

#endif  // GOOGLE_CUDA
