1 files changed, 0 insertions, 120 deletions
diff --git a/tensorflow/compiler/xla/tests/test_utils.cc b/tensorflow/compiler/xla/tests/test_utils.cc
deleted file mode 100644
index cdd3d66bbb..0000000000
--- a/tensorflow/compiler/xla/tests/test_utils.cc
+++ /dev/null
@@ -1,120 +0,0 @@
-/* Copyright 2017 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 "tensorflow/compiler/xla/tests/test_utils.h"
-
-#include "tensorflow/compiler/xla/primitive_util.h"
-
-namespace xla {
-
-namespace {
-
-template <typename FloatT>
-void PopulateWithRandomFloatingPointData(Literal* literal) {
-  CHECK_EQ(literal->shape().element_type(),
-           primitive_util::NativeToPrimitiveType<FloatT>());
-  std::minstd_rand0 engine;
-  std::uniform_real_distribution<FloatT> generator(0.0f, 1.0f);
-  TF_CHECK_OK(literal->Populate<FloatT>(
-      [&](tensorflow::gtl::ArraySlice<int64> /*indices*/) {
-        return generator(engine);
-      }));
-}
-
-template <typename IntT>
-void PopulateWithRandomIntegralData(Literal* literal) {
-  CHECK_EQ(literal->shape().element_type(),
-           primitive_util::NativeToPrimitiveType<IntT>());
-  std::minstd_rand0 engine;
-  std::uniform_int_distribution<IntT> generator(
-      std::numeric_limits<IntT>::lowest(), std::numeric_limits<IntT>::max());
-  TF_CHECK_OK(literal->Populate<IntT>(
-      [&](tensorflow::gtl::ArraySlice<int64> /*indices*/) {
-        return generator(engine);
-      }));
-}
-
-}  // namespace
-
-StatusOr<std::unique_ptr<Literal>> MakeFakeLiteral(const Shape& shape) {
-  if (ShapeUtil::IsTuple(shape)) {
-    std::vector<std::unique_ptr<Literal>> elements;
-    for (const Shape& element_shape : shape.tuple_shapes()) {
-      TF_ASSIGN_OR_RETURN(std::unique_ptr<Literal> element,
-                          MakeFakeLiteral(element_shape));
-      elements.push_back(std::move(element));
-    }
-    return Literal::MakeTupleOwned(std::move(elements));
-  }
-  std::unique_ptr<Literal> literal = Literal::CreateFromShape(shape);
-  switch (shape.element_type()) {
-    case F32:
-      PopulateWithRandomFloatingPointData<float>(literal.get());
-      break;
-    case F64:
-      PopulateWithRandomFloatingPointData<double>(literal.get());
-      break;
-    case S8:
-      PopulateWithRandomIntegralData<int8>(literal.get());
-      break;
-    case U8:
-      PopulateWithRandomIntegralData<uint8>(literal.get());
-      break;
-    case S16:
-      PopulateWithRandomIntegralData<int16>(literal.get());
-      break;
-    case U16:
-      PopulateWithRandomIntegralData<uint16>(literal.get());
-      break;
-    case S32:
-      PopulateWithRandomIntegralData<int32>(literal.get());
-      break;
-    case U32:
-      PopulateWithRandomIntegralData<uint32>(literal.get());
-      break;
-    case S64:
-      PopulateWithRandomIntegralData<int64>(literal.get());
-      break;
-    case U64:
-      PopulateWithRandomIntegralData<uint64>(literal.get());
-      break;
-    case PRED: {
-      std::uniform_int_distribution<int> generator(0, 1);
-      std::minstd_rand0 engine;
-      TF_CHECK_OK(literal->Populate<bool>(
-          [&](tensorflow::gtl::ArraySlice<int64> /*indices*/) {
-            return generator(engine);
-          }));
-      break;
-    }
-    default:
-      return Unimplemented("Unsupported type for fake literal generation: %s",
-                           ShapeUtil::HumanString(shape).c_str());
-  }
-  return std::move(literal);
-}
-
-StatusOr<std::vector<std::unique_ptr<Literal>>> MakeFakeArguments(
-    const HloModule& module) {
-  std::vector<std::unique_ptr<Literal>> arguments;
-  for (const ShapeLayout& shape_layout :
-       module.config().entry_computation_layout().parameter_layouts()) {
-    TF_ASSIGN_OR_RETURN(auto literal, MakeFakeLiteral(shape_layout.shape()));
-    arguments.push_back(std::move(literal));
-  }
-  return std::move(arguments);
-}
-
-}  // namespace xla