Automated rollback of change 137564676

Change: 137576487

1 files changed, 0 insertions, 320 deletions

diff --git a/tensorflow/core/kernels/scatter_nd_op_test.cc b/tensorflow/core/kernels/scatter_nd_op_test.cc
deleted file mode 100644
index d6743a6867..0000000000
--- a/tensorflow/core/kernels/scatter_nd_op_test.cc
+++ /dev/null
@@ -1,320 +0,0 @@
-/* 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.
-==============================================================================*/
-
-#include <functional>
-#include <memory>
-#include <vector>
-
-#include "tensorflow/core/framework/allocator.h"
-#include "tensorflow/core/framework/fake_input.h"
-#include "tensorflow/core/framework/graph.pb.h"
-#include "tensorflow/core/framework/node_def_builder.h"
-#include "tensorflow/core/framework/op_kernel.h"
-#include "tensorflow/core/framework/tensor.h"
-#include "tensorflow/core/framework/types.h"
-#include "tensorflow/core/framework/types.pb.h"
-#include "tensorflow/core/kernels/ops_testutil.h"
-#include "tensorflow/core/kernels/ops_util.h"
-#include "tensorflow/core/lib/core/status_test_util.h"
-#include "tensorflow/core/lib/random/simple_philox.h"
-#include "tensorflow/core/platform/logging.h"
-#include "tensorflow/core/platform/test.h"
-#include "tensorflow/core/platform/test_benchmark.h"
-
-namespace tensorflow {
-namespace {
-
-class ScatterNdUpdateOpTest : public OpsTestBase {
- protected:
-  void MakeOp(DataType variable_ref_type, DataType index_type) {
-    TF_ASSERT_OK(NodeDefBuilder("myop", "ScatterNdUpdate")
-                     .Input(FakeInput(variable_ref_type))
-                     .Input(FakeInput(index_type))
-                     .Input(FakeInput(RemoveRefType(variable_ref_type)))
-                     .Finalize(node_def()));
-    TF_ASSERT_OK(InitOp());
-  }
-};
-
-TEST_F(ScatterNdUpdateOpTest, Simple_StringType) {
-  MakeOp(DT_STRING_REF, DT_INT32);
-  AddInputFromArray<string>(TensorShape({1}), {"Brain"});
-  AddInputFromArray<int32>(TensorShape({1}), {0});
-  AddInputFromArray<string>(TensorShape({1}), {"TensorFlow"});
-  TF_ASSERT_OK(RunOpKernel());
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_STRING, TensorShape({1}));
-  test::FillValues<string>(&expected, {"TensorFlow"});
-  test::ExpectTensorEqual<string>(expected, params_tensor);
-}
-
-TEST_F(ScatterNdUpdateOpTest, Simple_BoolType) {
-  MakeOp(DT_BOOL_REF, DT_INT32);
-  AddInputFromArray<bool>(TensorShape({1}), {false});
-  AddInputFromArray<int32>(TensorShape({1}), {0});
-  AddInputFromArray<bool>(TensorShape({1}), {true});
-  TF_ASSERT_OK(RunOpKernel());
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_BOOL, TensorShape({1}));
-  test::FillValues<bool>(&expected, {true});
-  test::ExpectTensorEqual<bool>(expected, params_tensor);
-}
-
-TEST_F(ScatterNdUpdateOpTest, Simple_TwoD32) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5, 3}),
-                           {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({3, 1}), {0, 4, 2});
-  AddInputFromArray<float>(TensorShape({3, 3}),
-                           {100, 101, 102, 777, 778, 779, 10000, 10001, 10002});
-  TF_ASSERT_OK(RunOpKernel());
-
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_FLOAT, TensorShape({5, 3}));
-  test::FillValues<float>(&expected, {100, 101, 102, 0, 0, 0, 10000, 10001,
-                                      10002, 0, 0, 0, 777, 778, 779});
-  test::ExpectTensorEqual<float>(expected, params_tensor);
-}
-
-TEST_F(ScatterNdUpdateOpTest, Simple_Two64) {
-  MakeOp(DT_FLOAT_REF, DT_INT64);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5, 3}),
-                           {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int64>(TensorShape({3, 1}), {0, 4, 2});
-  AddInputFromArray<float>(TensorShape({3, 3}),
-                           {100, 101, 102, 777, 778, 779, 10000, 10001, 10002});
-  TF_ASSERT_OK(RunOpKernel());
-
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_FLOAT, TensorShape({5, 3}));
-  test::FillValues<float>(&expected, {100, 101, 102, 0, 0, 0, 10000, 10001,
-                                      10002, 0, 0, 0, 777, 778, 779});
-  test::ExpectTensorEqual<float>(expected, params_tensor);
-}
-/*TEST_F(ScatterNdUpdateOpTest, Simple_ZeroElements) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({0}), {});
-  AddInputFromArray<int32>(TensorShape({0}), {});
-  AddInputFromArray<float>(TensorShape({0}), {});
-  Status s = RunOpKernel();
-  EXPECT_TRUE(StringPiece(s.ToString())
-                  .contains("Output must not have 0 elements, got shape: "))
-      << s;
-}*/
-
-TEST_F(ScatterNdUpdateOpTest, Simple_ZeroD) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5}), {0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({1}), {3});
-  AddInputFromArray<float>(TensorShape({1}), {101});
-  TF_ASSERT_OK(RunOpKernel());
-
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_FLOAT, TensorShape({5}));
-  test::FillValues<float>(&expected, {0, 0, 0, 101, 0});
-  test::ExpectTensorEqual<float>(expected, params_tensor);
-}
-
-TEST_F(ScatterNdUpdateOpTest, Simple_OneD) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5}), {0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({3, 1}), {0, 4, 2});
-  AddInputFromArray<float>(TensorShape({3}), {100, 101, 102});
-  TF_ASSERT_OK(RunOpKernel());
-
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_FLOAT, TensorShape({5}));
-  test::FillValues<float>(&expected, {100, 0, 102, 0, 101});
-  test::ExpectTensorEqual<float>(expected, params_tensor);
-}
-
-TEST_F(ScatterNdUpdateOpTest, HigherRank) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({8}), {0, 0, 0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({2, 3, 1}), {0, 4, 2, 1, 3, 6});
-  AddInputFromArray<float>(TensorShape({2, 3}), {10, 20, 30, 40, 50, 60});
-  TF_ASSERT_OK(RunOpKernel());
-
-  // Check the new state of the input
-  Tensor params_tensor = *mutable_input(0).tensor;
-  Tensor expected(allocator(), DT_FLOAT, TensorShape({8}));
-  test::FillValues<float>(&expected, {10, 40, 30, 50, 20, 0, 60, 0});
-  test::ExpectTensorEqual<float>(expected, params_tensor);
-}
-
-TEST_F(ScatterNdUpdateOpTest, Error_IndexOutOfRange) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5, 3}),
-                           {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({3, 1}), {0, 4, 99});
-  AddInputFromArray<float>(TensorShape({3, 3}),
-                           {100, 101, 102, 777, 778, 779, 10000, 10001, 10002});
-  Status s = RunOpKernel();
-  EXPECT_TRUE(StringPiece(s.ToString())
-                  .contains("Invalid indices: [2,0] = [99] is not in [0, 5)"))
-      << s;
-}
-
-TEST_F(ScatterNdUpdateOpTest, Error_WrongDimsIndices) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({2, 3}), {0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({1, 3, 1}), {0, 4, 99});
-  AddInputFromArray<float>(TensorShape({3, 3}),
-                           {100, 101, 102, 777, 778, 779, 10000, 10001, 10002});
-  Status s = RunOpKernel();
-  EXPECT_TRUE(StringPiece(s.ToString())
-                  .contains("The outermost dimension of updates and indices "
-                            "must match. Got indices.shape [1,3,1], "
-                            "updates.shape [3,3]"))
-      << s;
-}
-
-TEST_F(ScatterNdUpdateOpTest, Error_MismatchedParamsAndUpdateDimensions) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5, 3}),
-                           {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({3, 1}), {0, 4, 2});
-  AddInputFromArray<float>(
-      TensorShape({3, 4}),
-      {100, 101, 102, 103, 777, 778, 779, 780, 10000, 10001, 10002, 10004});
-  Status s = RunOpKernel();
-  EXPECT_TRUE(StringPiece(s.ToString())
-                  .contains("Must have updates.shape = indices.shape[0] + "
-                            "params_shape[IXDIM:], got"))
-
-      << s;
-}
-
-TEST_F(ScatterNdUpdateOpTest, Error_MismatchedIndicesAndUpdateDimensions) {
-  MakeOp(DT_FLOAT_REF, DT_INT32);
-
-  // Feed and run
-  AddInputFromArray<float>(TensorShape({5, 3}),
-                           {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0});
-  AddInputFromArray<int32>(TensorShape({3, 1}), {0, 4, 2});
-  AddInputFromArray<float>(TensorShape({2, 3}),
-                           {100, 101, 102, 10000, 10001, 10002});
-  Status s = RunOpKernel();
-  EXPECT_TRUE(StringPiece(s.ToString())
-                  .contains("The outermost dimension of updates and indices "
-                            "must match. Got "))
-      << s;
-}
-
-class ScatterNdUpdateBM : public ScatterNdUpdateOpTest {
- public:
-  virtual void TestBody() {}
-  void MakeBenchmarkOp(const char* op, DataType index_type) {
-    TF_ASSERT_OK(NodeDefBuilder("myop", op)
-                     .Input(FakeInput(DT_FLOAT_REF))
-                     .Input(FakeInput(index_type))
-                     .Input(FakeInput(DT_FLOAT))
-                     .Finalize(node_def()));
-    TF_CHECK_OK(InitOp());
-  }
-};
-
-template <typename Index>
-static void BM_ScatterNdHelper(int iters, int embedding_size, const char* op) {
-  testing::StopTiming();
-  const int kRows = 10000000 / embedding_size;
-  std::vector<float> values;
-  values.reserve(kRows);
-  for (int i = 0; i < kRows * embedding_size; i++) {
-    values.push_back(i);
-  }
-  const int kNumUpdates = 1000;
-  random::PhiloxRandom philox(301, 17);
-  random::SimplePhilox rnd(&philox);
-  std::vector<Index> indices;
-  std::vector<float> updates;
-  for (int i = 0; i < kNumUpdates; i++) {
-    indices.push_back(rnd.Uniform(kRows));
-    for (int j = 0; j < embedding_size; j++) {
-      updates.push_back(i * 10 + j);
-    }
-  }
-
-  ScatterNdUpdateBM bm;
-  bm.MakeBenchmarkOp(op, DataTypeToEnum<Index>::v());
-  bm.AddInputFromArray<float>(TensorShape({kRows, embedding_size}), values);
-  bm.AddInputFromArray<Index>(TensorShape({kNumUpdates}), indices);
-  bm.AddInputFromArray<float>(TensorShape({kNumUpdates, embedding_size}),
-                              updates);
-  testing::ItemsProcessed((static_cast<int64>(kNumUpdates) * embedding_size) *
-                          iters);
-  testing::StartTiming();
-  while (iters-- > 0) {
-    Status s = bm.RunOpKernel();
-  }
-  testing::StopTiming();
-}
-
-static void BM_ScatterNdUpdateInt32(int iters, int embedding_size) {
-  BM_ScatterNdHelper<int32>(iters, embedding_size, "ScatterNdUpdate");
-}
-static void BM_ScatterNdUpdateInt64(int iters, int embedding_size) {
-  BM_ScatterNdHelper<int64>(iters, embedding_size, "ScatterNdUpdate");
-}
-
-static void BM_ScatterNdAddInt32(int iters, int embedding_size) {
-  BM_ScatterNdHelper<int32>(iters, embedding_size, "ScatterNdAdd");
-}
-static void BM_ScatterNdAddInt64(int iters, int embedding_size) {
-  BM_ScatterNdHelper<int64>(iters, embedding_size, "ScatterNdAdd");
-}
-
-BENCHMARK(BM_ScatterNdUpdateInt32)
-    ->Arg(1)
-    ->Arg(10)
-    ->Arg(64)
-    ->Arg(256)
-    ->Arg(1024);
-BENCHMARK(BM_ScatterNdUpdateInt64)
-    ->Arg(1)
-    ->Arg(10)
-    ->Arg(64)
-    ->Arg(256)
-    ->Arg(1024);
-
-BENCHMARK(BM_ScatterNdAddInt32)->Arg(1)->Arg(10)->Arg(64)->Arg(256)->Arg(1024);
-BENCHMARK(BM_ScatterNdAddInt64)->Arg(1)->Arg(10)->Arg(64)->Arg(256)->Arg(1024);
-
-}  // namespace
-}  // namespace tensorflow