TFLite: adding tile and expand_dims ops.

PiperOrigin-RevId: 198913026

1 files changed, 256 insertions, 0 deletions

diff --git a/tensorflow/contrib/lite/kernels/tile_test.cc b/tensorflow/contrib/lite/kernels/tile_test.cc
new file mode 100644
index 0000000000..a134a75d56
--- /dev/null
+++ b/tensorflow/contrib/lite/kernels/tile_test.cc
@@ -0,0 +1,256 @@
+/* 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 <gtest/gtest.h>
+#include "tensorflow/contrib/lite/builtin_op_data.h"
+#include "tensorflow/contrib/lite/interpreter.h"
+#include "tensorflow/contrib/lite/kernels/register.h"
+#include "tensorflow/contrib/lite/kernels/test_util.h"
+#include "tensorflow/contrib/lite/model.h"
+
+namespace tflite {
+namespace {
+
+using ::testing::ElementsAreArray;
+class TileOpModel : public SingleOpModel {
+ public:
+  TileOpModel(std::initializer_list<int> input_shape, TensorType input_type,
+              TensorType multiply_type) {
+    input_ = AddInput(input_type);
+    multipliers_ = AddInput(TensorType_INT32);
+    output_ = AddOutput(input_type);
+    SetBuiltinOp(BuiltinOperator_TILE, BuiltinOptions_TileOptions, 0);
+    BuildInterpreter({input_shape, {static_cast<int>(input_shape.size())}});
+  }
+
+  void SetInputFloat(std::initializer_list<float> data) {
+    PopulateTensor<float>(input_, data);
+  }
+
+  void SetInputUInt8(std::initializer_list<uint8> data) {
+    PopulateTensor<uint8>(input_, data);
+  }
+
+  void SetInputInt32(std::initializer_list<int32> data) {
+    PopulateTensor<int32>(input_, data);
+  }
+
+  void SetInputInt64(std::initializer_list<int64_t> data) {
+    PopulateTensor<int64_t>(input_, data);
+  }
+
+  void SetMultipliers(std::initializer_list<int32> data) {
+    PopulateTensor<int32>(multipliers_, data);
+  }
+
+  std::vector<float> GetOutputFloat() { return ExtractVector<float>(output_); }
+
+  std::vector<uint8> GetOutputUInt8() { return ExtractVector<uint8>(output_); }
+
+  std::vector<int32> GetOutputInt32() { return ExtractVector<int32>(output_); }
+
+  std::vector<int64_t> GetOutputInt64() {
+    return ExtractVector<int64_t>(output_);
+  }
+
+  std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
+
+ protected:
+  int input_;
+  int multipliers_;
+  int output_;
+};
+
+TEST(TileTest, Float32Vector) {
+  TileOpModel m({3}, TensorType_FLOAT32, TensorType_INT32);
+  m.SetInputFloat({1.f, 2.f, 3.f});
+  m.SetMultipliers({2});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputFloat(),
+              ElementsAreArray({1.f, 2.f, 3.f, 1.f, 2.f, 3.f}));
+}
+
+TEST(TileTest, Float32Matrix) {
+  TileOpModel m({2, 3}, TensorType_FLOAT32, TensorType_INT32);
+  m.SetInputFloat({
+      11.f,
+      12.f,
+      13.f,
+      21.f,
+      22.f,
+      23.f,
+  });
+  m.SetMultipliers({2, 1});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputFloat(), ElementsAreArray({
+                                      11.f,
+                                      12.f,
+                                      13.f,
+                                      21.f,
+                                      22.f,
+                                      23.f,
+                                      11.f,
+                                      12.f,
+                                      13.f,
+                                      21.f,
+                                      22.f,
+                                      23.f,
+                                  }));
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4, 3}));
+}
+
+TEST(TileTest, Float32HighDimension) {
+  TileOpModel m({1, 2, 3}, TensorType_FLOAT32, TensorType_INT32);
+  m.SetInputFloat({
+      11.f,
+      12.f,
+      13.f,
+      21.f,
+      22.f,
+      23.f,
+  });
+  m.SetMultipliers({2, 3, 1});
+  m.Invoke();
+  EXPECT_THAT(
+      m.GetOutputFloat(),
+      ElementsAreArray({11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f, 13.f,
+                        21.f, 22.f, 23.f, 11.f, 12.f, 13.f, 21.f, 22.f, 23.f,
+                        11.f, 12.f, 13.f, 21.f, 22.f, 23.f, 11.f, 12.f, 13.f,
+                        21.f, 22.f, 23.f, 11.f, 12.f, 13.f, 21.f, 22.f, 23.f}));
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 6, 3}));
+}
+
+TEST(TileTest, Uint8Matrix) {
+  TileOpModel m({2, 3}, TensorType_UINT8, TensorType_INT32);
+  m.SetInputUInt8({
+      11,
+      12,
+      13,
+      21,
+      22,
+      23,
+  });
+  m.SetMultipliers({2, 1});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputUInt8(), ElementsAreArray({
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                  }));
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4, 3}));
+}
+
+TEST(TileTest, Int32Matrix) {
+  TileOpModel m({2, 3}, TensorType_INT32, TensorType_INT32);
+  m.SetInputInt32({
+      11,
+      12,
+      13,
+      21,
+      22,
+      23,
+  });
+  m.SetMultipliers({2, 1});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputInt32(), ElementsAreArray({
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                  }));
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4, 3}));
+}
+
+TEST(TileTest, Int64Matrix) {
+  TileOpModel m({2, 3}, TensorType_INT64, TensorType_INT32);
+  m.SetInputInt64({
+      11,
+      12,
+      13,
+      21,
+      22,
+      23,
+  });
+  m.SetMultipliers({2, 1});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputInt64(), ElementsAreArray({
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                  }));
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4, 3}));
+}
+
+TEST(TileTest, Int64Matrix64Multipliers) {
+  TileOpModel m({2, 3}, TensorType_INT64, TensorType_INT64);
+  m.SetInputInt64({
+      11,
+      12,
+      13,
+      21,
+      22,
+      23,
+  });
+  m.SetMultipliers({2, 1});
+  m.Invoke();
+  EXPECT_THAT(m.GetOutputInt64(), ElementsAreArray({
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                      11,
+                                      12,
+                                      13,
+                                      21,
+                                      22,
+                                      23,
+                                  }));
+  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({4, 3}));
+}
+}  // namespace
+}  // namespace tflite
+
+int main(int argc, char** argv) {
+  ::tflite::LogToStderr();
+  ::testing::InitGoogleTest(&argc, argv);
+  return RUN_ALL_TESTS();
+}