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author | A. Unique TensorFlower <gardener@tensorflow.org> | 2018-07-08 19:42:24 -0700 |
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committer | TensorFlower Gardener <gardener@tensorflow.org> | 2018-07-08 19:47:45 -0700 |
commit | ff83809afa9062e77809d2b65ffbaee3c0045241 (patch) | |
tree | 580ff678c025ceb10450c1b9391e944b0d65b82d /tensorflow/contrib/lite/kernels/arg_min_max_test.cc | |
parent | c1ce428a4499ad38916dd512f56a364859c9edd3 (diff) |
Refactoring ArgMax implementation in preparation for ArgMin.
PiperOrigin-RevId: 203698572
Diffstat (limited to 'tensorflow/contrib/lite/kernels/arg_min_max_test.cc')
-rw-r--r-- | tensorflow/contrib/lite/kernels/arg_min_max_test.cc | 106 |
1 files changed, 106 insertions, 0 deletions
diff --git a/tensorflow/contrib/lite/kernels/arg_min_max_test.cc b/tensorflow/contrib/lite/kernels/arg_min_max_test.cc new file mode 100644 index 0000000000..31b15fe19a --- /dev/null +++ b/tensorflow/contrib/lite/kernels/arg_min_max_test.cc @@ -0,0 +1,106 @@ +/* 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 <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::ElementsAreArray; + +template <typename T> +class ArgMaxOpModel : public SingleOpModel { + public: + ArgMaxOpModel(std::initializer_list<int> input_shape, TensorType input_type, + TensorType output_type, TensorType index_output_type) { + input_ = AddInput(input_type); + axis_ = AddInput(TensorType_INT32); + output_ = AddOutput(output_type); + SetBuiltinOp(BuiltinOperator_ARG_MAX, BuiltinOptions_ArgMaxOptions, + CreateArgMaxOptions(builder_, index_output_type).Union()); + BuildInterpreter({input_shape, {1, 1, 1, 1}}); + } + + int input() { return input_; } + int axis() { return axis_; } + + std::vector<T> GetOutput() { return ExtractVector<T>(output_); } + std::vector<int> GetOutputShape() { return GetTensorShape(output_); } + + private: + int input_; + int axis_; + int output_; +}; + +TEST(ArgMaxOpTest, GetMaxArgFloat) { + ArgMaxOpModel<int32_t> model({1, 1, 1, 4}, TensorType_FLOAT32, + TensorType_INT32, TensorType_INT32); + model.PopulateTensor<float>(model.input(), {0.1, 0.9, 0.7, 0.3}); + // Currently only support the last dimension. + model.PopulateTensor<int>(model.axis(), {3}); + model.Invoke(); + + EXPECT_THAT(model.GetOutput(), ElementsAreArray({1})); + EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 1, 1})); +} + +TEST(ArgMaxOpTest, GetMaxArgInt) { + ArgMaxOpModel<int32_t> model({1, 1, 1, 4}, TensorType_INT32, TensorType_INT32, + TensorType_INT32); + model.PopulateTensor<int>(model.input(), {1, 9, 7, 3}); + // Currently only support the last dimension. + model.PopulateTensor<int>(model.axis(), {3}); + model.Invoke(); + + EXPECT_THAT(model.GetOutput(), ElementsAreArray({1})); + EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 1, 1})); +} + +TEST(ArgMaxOpTest, GetMaxArgMulDimensions) { + ArgMaxOpModel<int32_t> model({1, 1, 2, 4}, TensorType_INT32, TensorType_INT32, + TensorType_INT32); + model.PopulateTensor<int>(model.input(), {1, 2, 7, 8, 1, 9, 7, 3}); + // Currently only support the last dimension. + model.PopulateTensor<int>(model.axis(), {3}); + model.Invoke(); + + EXPECT_THAT(model.GetOutput(), ElementsAreArray({3, 1})); + EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 2, 1})); +} + +TEST(ArgMaxOpTest, GetMaxArgOutput64) { + ArgMaxOpModel<int64_t> model({1, 1, 2, 4}, TensorType_INT32, TensorType_INT64, + TensorType_INT64); + model.PopulateTensor<int>(model.input(), {10, 2, 7, 8, 1, 9, 7, 3}); + // Currently only support the last dimension. + model.PopulateTensor<int>(model.axis(), {3}); + model.Invoke(); + + EXPECT_THAT(model.GetOutput(), ElementsAreArray({0, 1})); + EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({1, 1, 2, 1})); +} + +} // namespace +} // namespace tflite + +int main(int argc, char** argv) { + ::tflite::LogToStderr(); + ::testing::InitGoogleTest(&argc, argv); + return RUN_ALL_TESTS(); +} |