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author | 2018-08-23 21:50:34 -0700 | |
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committer | 2018-08-23 21:57:27 -0700 | |
commit | 4bc1d3e484c6eb3ea2ba4e6400722be32220c808 (patch) | |
tree | b6f760b3003355257f57b2441ac273e7349e3b03 /tensorflow/contrib/lite/kernels/unpack_test.cc | |
parent | 0c657f3b9f6ef6ee63b3eb54fe928f482c58dc80 (diff) |
Implementation of unpack op.
PiperOrigin-RevId: 210051131
Diffstat (limited to 'tensorflow/contrib/lite/kernels/unpack_test.cc')
-rw-r--r-- | tensorflow/contrib/lite/kernels/unpack_test.cc | 221 |
1 files changed, 221 insertions, 0 deletions
diff --git a/tensorflow/contrib/lite/kernels/unpack_test.cc b/tensorflow/contrib/lite/kernels/unpack_test.cc new file mode 100644 index 0000000000..96a20ac21b --- /dev/null +++ b/tensorflow/contrib/lite/kernels/unpack_test.cc @@ -0,0 +1,221 @@ +/* Copyright 2018 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 <gtest/gtest.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::ElementsAre; + +template <typename T> +class UnpackOpModel : public SingleOpModel { + public: + UnpackOpModel(const TensorData& input, int axis) { + CHECK_LE(axis, input.shape.size()); + const int num_outputs = input.shape[axis]; + input_ = AddInput(input); + for (int i = 0; i < num_outputs; ++i) { + outputs_.push_back(AddOutput(input.type)); + } + SetBuiltinOp(BuiltinOperator_UNPACK, BuiltinOptions_UnpackOptions, + CreatePackOptions(builder_, num_outputs, axis).Union()); + BuildInterpreter({GetShape(input_)}); + } + + void SetInput(std::initializer_list<T> data) { + PopulateTensor<T>(input_, data); + } + + std::vector<std::vector<T>> GetOutputDatas() { + std::vector<std::vector<T>> output_datas; + for (const int output : outputs_) { + std::cerr << "the output is " << output << std::endl; + output_datas.push_back(ExtractVector<T>(output)); + } + return output_datas; + } + + std::vector<std::vector<int>> GetOutputShapes() { + std::vector<std::vector<int>> output_shapes; + for (const int output : outputs_) { + output_shapes.push_back(GetTensorShape(output)); + } + return output_shapes; + } + + private: + int input_; + std::vector<int> outputs_; +}; + +// float32 tests. +TEST(UnpackOpTest, FloatThreeOutputs) { + UnpackOpModel<float> model({TensorType_FLOAT32, {3, 2}}, 0); + model.SetInput({1, 2, 3, 4, 5, 6}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 3); + EXPECT_THAT(output_shapes[0], ElementsAre(2)); + EXPECT_THAT(output_shapes[1], ElementsAre(2)); + EXPECT_THAT(output_shapes[2], ElementsAre(2)); + + // Check outputs values. + const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 3); + EXPECT_THAT(output_datas[0], ElementsAre(1, 2)); + EXPECT_THAT(output_datas[1], ElementsAre(3, 4)); + EXPECT_THAT(output_datas[2], ElementsAre(5, 6)); +} + +TEST(UnpackOpTest, FloatThreeOutputsAxisOne) { + UnpackOpModel<float> model({TensorType_FLOAT32, {3, 2}}, 1); + model.SetInput({1, 2, 3, 4, 5, 6}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 2); + EXPECT_THAT(output_shapes[0], ElementsAre(3)); + EXPECT_THAT(output_shapes[1], ElementsAre(3)); + + // Check outputs values. + const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 2); + EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5)); + EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6)); +} + +TEST(UnpackOpTest, FloatOneOutput) { + UnpackOpModel<float> model({TensorType_FLOAT32, {1, 6}}, 0); + model.SetInput({1, 2, 3, 4, 5, 6}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 1); + EXPECT_THAT(output_shapes[0], ElementsAre(6)); + + // Check outputs values. + const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 1); + EXPECT_THAT(output_datas[0], ElementsAre(1, 2, 3, 4, 5, 6)); +} + +TEST(UnpackOpTest, FloatThreeDimensionsOutputs) { + UnpackOpModel<float> model({TensorType_FLOAT32, {2, 2, 2}}, 2); + model.SetInput({1, 2, 3, 4, 5, 6, 7, 8}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 2); + EXPECT_THAT(output_shapes[0], ElementsAre(2, 2)); + EXPECT_THAT(output_shapes[1], ElementsAre(2, 2)); + + // Check outputs values. + const std::vector<std::vector<float>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 2); + EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5, 7)); + EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6, 8)); +} + +// int32 tests. +TEST(UnpackOpTest, IntThreeOutputs) { + UnpackOpModel<int32> model({TensorType_INT32, {3, 2}}, 0); + model.SetInput({1, 2, 3, 4, 5, 6}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 3); + EXPECT_THAT(output_shapes[0], ElementsAre(2)); + EXPECT_THAT(output_shapes[1], ElementsAre(2)); + EXPECT_THAT(output_shapes[2], ElementsAre(2)); + + // Check outputs values. + const std::vector<std::vector<int32>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 3); + EXPECT_THAT(output_datas[0], ElementsAre(1, 2)); + EXPECT_THAT(output_datas[1], ElementsAre(3, 4)); + EXPECT_THAT(output_datas[2], ElementsAre(5, 6)); +} + +TEST(UnpackOpTest, IntThreeOutputsAxisOne) { + UnpackOpModel<int32> model({TensorType_INT32, {3, 2}}, 1); + model.SetInput({1, 2, 3, 4, 5, 6}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 2); + EXPECT_THAT(output_shapes[0], ElementsAre(3)); + EXPECT_THAT(output_shapes[1], ElementsAre(3)); + + // Check outputs values. + const std::vector<std::vector<int32>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 2); + EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5)); + EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6)); +} + +TEST(UnpackOpTest, IntOneOutput) { + UnpackOpModel<int32> model({TensorType_INT32, {1, 6}}, 0); + model.SetInput({1, 2, 3, 4, 5, 6}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 1); + EXPECT_THAT(output_shapes[0], ElementsAre(6)); + + // Check outputs values. + const std::vector<std::vector<int32>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 1); + EXPECT_THAT(output_datas[0], ElementsAre(1, 2, 3, 4, 5, 6)); +} + +TEST(UnpackOpTest, IntThreeDimensionsOutputs) { + UnpackOpModel<int32> model({TensorType_INT32, {2, 2, 2}}, 2); + model.SetInput({1, 2, 3, 4, 5, 6, 7, 8}); + model.Invoke(); + + // Check outputs shapes. + const std::vector<std::vector<int>>& output_shapes = model.GetOutputShapes(); + EXPECT_EQ(output_shapes.size(), 2); + EXPECT_THAT(output_shapes[0], ElementsAre(2, 2)); + EXPECT_THAT(output_shapes[1], ElementsAre(2, 2)); + + // Check outputs values. + const std::vector<std::vector<int32>>& output_datas = model.GetOutputDatas(); + EXPECT_EQ(output_datas.size(), 2); + EXPECT_THAT(output_datas[0], ElementsAre(1, 3, 5, 7)); + EXPECT_THAT(output_datas[1], ElementsAre(2, 4, 6, 8)); +} + +} // namespace +} // namespace tflite + +int main(int argc, char** argv) { + ::tflite::LogToStderr(); + ::testing::InitGoogleTest(&argc, argv); + return RUN_ALL_TESTS(); +} |