text: /* Copyright 2015 Google Inc. 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_KERNELS_BATCH_MATRIX_DIAG_OP_H_
  #define TENSORFLOW_KERNELS_BATCH_MATRIX_DIAG_OP_H_
  
  // Generator definition for BatchMatrixDiagOp, must be compilable by nvcc.
  
  #include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
  #include "tensorflow/core/framework/tensor_types.h"
  #include "tensorflow/core/platform/types.h"
  
  namespace tensorflow {
  
  namespace generator {
  
  template <typename T>
  class BatchMatrixDiagPartGenerator {
   public:
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
        BatchMatrixDiagPartGenerator(typename TTypes<T, 3>::ConstTensor input)
        : input_(input) {}
  
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T
    operator()(const Eigen::array<Eigen::DenseIndex, 2>& coords) const {
      Eigen::array<Eigen::DenseIndex, 3> diag_from_coords(
          {coords[0], coords[1], coords[1]});
      return input_(diag_from_coords);
    }
  
   private:
    typename TTypes<T, 3>::ConstTensor input_;
  };
  
  template <typename T>
  class BatchMatrixDiagGenerator {
   public:
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
        BatchMatrixDiagGenerator(typename TTypes<T, 2>::ConstTensor input)
        : input_(input) {}
  
    EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T
    operator()(const Eigen::array<Eigen::DenseIndex, 3>& coords) const {
      if (coords[2] != coords[1]) return T();
  
      Eigen::array<Eigen::DenseIndex, 2> diag_coords({coords[0], coords[1]});
      return input_(diag_coords);
    }
  
   private:
    typename TTypes<T, 2>::ConstTensor input_;
  };
  
  }  // namespace generator
  
  namespace functor {
  
  template <typename Device, typename T>
  struct BatchMatrixDiagPart {
    EIGEN_ALWAYS_INLINE static void Compute(
        const Device& d, typename TTypes<T, 3>::ConstTensor input,
        typename TTypes<T, 2>::Tensor output) {
      generator::BatchMatrixDiagPartGenerator<T> generator(input);
      output.device(d) = output.generate(generator);
    }
  };
  
  template <typename Device, typename T>
  struct BatchMatrixDiag {
    EIGEN_ALWAYS_INLINE static void Compute(
        const Device& d, typename TTypes<T, 2>::ConstTensor input,
        typename TTypes<T, 3>::Tensor output) {
      generator::BatchMatrixDiagGenerator<T> generator(input);
      output.device(d) = output.generate(generator);
    }
  };
  
  }  // namespace functor
  
  }  // namespace tensorflow
  
  #endif  // TENSORFLOW_KERNELS_BATCH_MATRIX_DIAG_OP_H_
  