reduction_ops_gpu_float.cu.cc

/* 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 || TENSORFLOW_USE_ROCM

#define EIGEN_USE_GPU

#include "tensorflow/core/kernels/reduction_gpu_kernels.cu.h"

namespace tensorflow {
namespace functor {

typedef Eigen::GpuDevice GPUDevice;

// Derive Index type. int (32-bit) or long (64-bit) depending on the
// compile-time configuration. "float" here is not relevant.
// TODO(zhifengc): Moves the definition to TTypes.
typedef TTypes<float>::Tensor::Index Index;

// T: the data type
// REDUCER: the reducer functor
// NUM_AXES: the number of axes to reduce
// IN_DIMS: the number of dimensions of the input tensor
#define DEFINE(T, REDUCER, IN_DIMS, NUM_AXES)                          \
  template void ReduceFunctor<GPUDevice, REDUCER>::Reduce(             \
      OpKernelContext* ctx, TTypes<T, IN_DIMS - NUM_AXES>::Tensor out, \
      TTypes<T, IN_DIMS>::ConstTensor in,                              \
      const Eigen::array<Index, NUM_AXES>& reduction_axes,             \
      const REDUCER& reducer);

#define DEFINE_IDENTITY(T, REDUCER)                              \
  template void ReduceFunctor<GPUDevice, REDUCER>::FillIdentity( \
      const GPUDevice& d, TTypes<T>::Vec out, const REDUCER& reducer);

#define SINGLE_ARG(...) __VA_ARGS__

#define DEFINE_FOR_TYPE_AND_R(T, R) \
  DEFINE(T, SINGLE_ARG(R), 1, 1);   \
  DEFINE(T, SINGLE_ARG(R), 2, 1);   \
  DEFINE(T, SINGLE_ARG(R), 3, 1);   \
  DEFINE(T, SINGLE_ARG(R), 3, 2);   \
  DEFINE_IDENTITY(T, SINGLE_ARG(R))

#define DEFINE_FOR_ALL_REDUCERS(T)                                         \
  DEFINE_FOR_TYPE_AND_R(T, Eigen::internal::SumReducer<T>);                \
  DEFINE_FOR_TYPE_AND_R(T, functor::MeanReducer<T>);                       \
  DEFINE_FOR_TYPE_AND_R(T, functor::EuclideanNormReducer<T>);              \
  DEFINE_FOR_TYPE_AND_R(                                                   \
      T, SINGLE_ARG(Eigen::internal::MinReducer<T, Eigen::PropagateNaN>)); \
  DEFINE_FOR_TYPE_AND_R(                                                   \
      T, SINGLE_ARG(Eigen::internal::MaxReducer<T, Eigen::PropagateNaN>)); \
  DEFINE_FOR_TYPE_AND_R(T, Eigen::internal::ProdReducer<T>)

DEFINE_FOR_ALL_REDUCERS(float);
#undef SINGLE_ARG
#undef DEFINE_FOR_ALL_REDUCERS
#undef DEFINE_FOR_TYPE_AND_R
#undef DEFINE

}  // end namespace functor
}  // end namespace tensorflow

#endif  // GOOGLE_CUDA || TENSORFLOW_USE_ROCM