/* 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. ==============================================================================*/ #ifndef TENSORFLOW_CORE_KERNELS_TILE_OPS_IMPL_H_ #define TENSORFLOW_CORE_KERNELS_TILE_OPS_IMPL_H_ #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor" #include "tensorflow/core/framework/tensor_types.h" #include "tensorflow/core/platform/types.h" namespace tensorflow { namespace functor { template struct TileGrad { void operator()(const Device& d, typename TTypes::Tensor out, typename TTypes::ConstTensor in, const Eigen::DSizes& indices, const Eigen::DSizes& sizes, bool first) const { if (first) { out.device(d) = in.slice(indices, sizes); } else { out.device(d) += in.slice(indices, sizes); } } }; template struct TileGrad { void operator()(const Device& d, typename TTypes::Tensor out, typename TTypes::ConstTensor in, const Eigen::DSizes&, const Eigen::DSizes&, bool first) const { if (first) { out.device(d) = in; } else { out.device(d) += in; } } }; template struct ReduceAndReshape { void operator()( const Device& d, typename TTypes::Tensor out, typename TTypes::ConstTensor in, const Eigen::DSizes& reduce_dim, const Eigen::DSizes& reshape_dim) const { out.device(d) = in.sum(reduce_dim).reshape(reshape_dim); } }; } // end namespace functor } // end namespace tensorflow #endif // TENSORFLOW_CORE_KERNELS_TILE_OPS_IMPL_H_