| /* 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 <vector> |
| #include <gmock/gmock.h> |
| #include <gtest/gtest.h> |
| |
| #include "tensorflow/lite/c/c_api_internal.h" |
| #include "tensorflow/lite/util.h" |
| |
| namespace tflite { |
| namespace { |
| |
| TEST(ConvertVectorToTfLiteIntArray, TestWithVector) { |
| std::vector<int> input = {1, 2}; |
| TfLiteIntArray* output = ConvertVectorToTfLiteIntArray(input); |
| ASSERT_NE(output, nullptr); |
| EXPECT_EQ(output->size, 2); |
| EXPECT_EQ(output->data[0], 1); |
| EXPECT_EQ(output->data[1], 2); |
| TfLiteIntArrayFree(output); |
| } |
| |
| TEST(ConvertVectorToTfLiteIntArray, TestWithEmptyVector) { |
| std::vector<int> input; |
| TfLiteIntArray* output = ConvertVectorToTfLiteIntArray(input); |
| ASSERT_NE(output, nullptr); |
| EXPECT_EQ(output->size, 0); |
| TfLiteIntArrayFree(output); |
| } |
| |
| TEST(UtilTest, IsFlexOp) { |
| EXPECT_TRUE(IsFlexOp("Flex")); |
| EXPECT_TRUE(IsFlexOp("FlexOp")); |
| EXPECT_FALSE(IsFlexOp("flex")); |
| EXPECT_FALSE(IsFlexOp("Fle")); |
| EXPECT_FALSE(IsFlexOp("OpFlex")); |
| EXPECT_FALSE(IsFlexOp(nullptr)); |
| EXPECT_FALSE(IsFlexOp("")); |
| } |
| |
| } // namespace |
| } // namespace tflite |
| |
| int main(int argc, char** argv) { |
| ::testing::InitGoogleTest(&argc, argv); |
| return RUN_ALL_TESTS(); |
| } |