Rollback of "TensorFlow: move eigen some NN code from our third_party/eigen3 copy

to being part of TF, add tests."
Change: 117519243

1 files changed, 0 insertions, 65 deletions

diff --git a/tensorflow/core/kernels/eigen_softmax_test.cc b/tensorflow/core/kernels/eigen_softmax_test.cc
deleted file mode 100644
index 8623861518..0000000000
--- a/tensorflow/core/kernels/eigen_softmax_test.cc
+++ /dev/null
@@ -1,65 +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.
-==============================================================================*/
-
-#include "tensorflow/core/kernels/eigen_softmax.h"
-#include "tensorflow/core/framework/types.h"
-#include "tensorflow/core/platform/test.h"
-
-namespace Eigen {
-
-namespace {
-void EigenApprox(float a, float b) {
-  ASSERT_TRUE(std::abs(a - b) <= std::min(std::abs(a), std::abs(b)) * 1e-3);
-}
-}
-
-TEST(EigenSoftmaxTest, Simple) {
-  const int depth = 1024;
-  const int batch = 32;
-  const float beta = 1.2f;
-
-  Tensor<float, 2> input(depth, batch);
-  input = input.constant(11.0f) + input.random();
-
-  Tensor<float, 2> reference(depth, batch);
-  reference.setRandom();
-
-  Eigen::array<int, 1> depth_dim;
-  depth_dim[0] = 0;
-  Eigen::array<int, 2> bcast;
-  bcast[0] = depth;
-  bcast[1] = 1;
-  Tensor<float, 2>::Dimensions dims2d;
-  dims2d[0] = 1;
-  dims2d[1] = batch;
-  reference =
-      ((input -
-        input.maximum(depth_dim).eval().reshape(dims2d).broadcast(bcast)) *
-       beta)
-          .exp();
-  reference =
-      reference /
-      (reference.sum(depth_dim).eval().reshape(dims2d).broadcast(bcast));
-
-  Tensor<float, 2> result = SoftMax(input, beta);
-
-  for (int i = 0; i < depth; ++i) {
-    for (int j = 0; j < batch; ++j) {
-      EigenApprox(result(i, j), reference(i, j));
-    }
-  }
-}
-
-}  // namespace Eigen