Re-rollback of "TensorFlow: move eigen some NN code from our third_party/eigen3 copy

to being part of TF, add tests."
Change: 117608627

1 files changed, 0 insertions, 90 deletions

diff --git a/tensorflow/core/kernels/eigen_softmax.h b/tensorflow/core/kernels/eigen_softmax.h
deleted file mode 100644
index 49123e8062..0000000000
--- a/tensorflow/core/kernels/eigen_softmax.h
+++ /dev/null
@@ -1,90 +0,0 @@
-/* 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 THIRD_PARTY_TENSORFLOW_CORE_KERNELS_EIGEN_SOFTMAX_H_
-#define THIRD_PARTY_TENSORFLOW_CORE_KERNELS_EIGEN_SOFTMAX_H_
-
-#include "third_party/eigen3/unsupported/Eigen/CXX11/Tensor"
-
-namespace Eigen {
-
-/** SoftMax
-  * \ingroup CXX11_NeuralNetworks_Module
-  *
-  * \brief Applies a softmax
-  *
-  * The input parameter is expected to be a col-major tensor with a rank of 2 (depth and other).
-  *
-  * The result can be assigned to a tensor of rank and dimensions equal to that of the input. The result will be laid out in col-major order.
-  *
-*/
-
-namespace {
-struct SoftmaxOp {
-  SoftmaxOp(const float beta) : beta_(beta) { }
-
-  template <typename Input>
-  typename Input::Dimensions dimensions(const Input& input) const {
-    return input.dimensions();
-  }
-
-  template <typename Input, typename Output, typename Device>
-  void eval(const Input& input, Output& output, const Device& device) const
-  {
-#if !defined(EIGEN_HAS_INDEX_LIST)
-    // nvcc doesn't support cxx11
-    Eigen::array<typename internal::traits<Input>::Index, 1> depth_dim;
-    depth_dim[0] = 0;
-    Eigen::array<typename internal::traits<Input>::Index, 2> bcast;
-    bcast[0] = dimensions(input)[0];
-    bcast[1] = 1;
-    DSizes<typename internal::traits<Input>::Index, 2> dims2d;
-    dims2d[0] = 1;
-    dims2d[1] = dimensions(input)[1];
-#else
-    // Take advantage of cxx11 to give the compiler information it can use to
-    // optimize the code.
-    Eigen::IndexList<Eigen::type2index<0>> depth_dim;
-    Eigen::IndexList<int, Eigen::type2index<1>> bcast;
-    bcast.set(0, dimensions(input)[0]);
-    Eigen::IndexList<Eigen::type2index<1>, typename internal::traits<Input>::Index> dims2d;
-    dims2d.set(1, dimensions(input)[1]);
-#endif
-
-    output.device(device) = ((input - input.maximum(depth_dim).eval().reshape(dims2d).broadcast(bcast)) * beta_).exp();
-    output.device(device) = output / (output.sum(depth_dim).eval().reshape(dims2d).broadcast(bcast));
-  }
-
- private:
-  const float beta_;
-};
-}
-
-
-template <typename Input>
-EIGEN_ALWAYS_INLINE
-static const TensorCustomUnaryOp<const SoftmaxOp, const Input>
-SoftMax(const Input& input, const float beta)
-{
-  EIGEN_STATIC_ASSERT(internal::traits<Input>::Layout == ColMajor, YOU_MADE_A_PROGRAMMING_MISTAKE);
-  EIGEN_STATIC_ASSERT(internal::traits<Input>::NumDimensions == 2, YOU_MADE_A_PROGRAMMING_MISTAKE);
-
-  const SoftmaxOp op(beta);
-  return input.customOp(op);
-}
-
-} // end namespace Eigen
-
-#endif  // THIRD_PARTY_TENSORFLOW_CORE_KERNELS_EIGEN_SOFTMAX_H_