90 lines
2.8 KiB
C++
90 lines
2.8 KiB
C++
/* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include <initializer_list>
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#include <gtest/gtest.h>
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#include "tensorflow/lite/interpreter.h"
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#include "tensorflow/lite/kernels/register.h"
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#include "tensorflow/lite/kernels/test_util.h"
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#include "tensorflow/lite/model.h"
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namespace tflite {
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namespace {
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using ::testing::ElementsAreArray;
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template <typename T>
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class ShapeOpModel : public SingleOpModel {
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public:
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ShapeOpModel(std::initializer_list<int> input_shape, TensorType input_type,
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TensorType output_type) {
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input_ = AddInput(input_type);
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output_ = AddOutput(output_type);
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SetBuiltinOp(BuiltinOperator_SHAPE, BuiltinOptions_ShapeOptions,
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CreateShapeOptions(builder_, output_type).Union());
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BuildInterpreter({input_shape});
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}
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TfLiteStatus InvokeWithResult() { return interpreter_->Invoke(); }
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int input() { return input_; }
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int32_t GetOutputSize() { return GetTensorSize(output_); }
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std::vector<T> GetOutput() { return ExtractVector<T>(output_); }
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std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
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private:
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int input_;
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int output_;
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};
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TEST(ShapeOpTest, OutTypeInt) {
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ShapeOpModel<int32_t> model({1, 3, 1, 3, 5}, TensorType_FLOAT32,
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TensorType_INT32);
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model.Invoke();
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EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 3, 1, 3, 5}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({5}));
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}
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TEST(ShapeOpTest, OutTypeInt64) {
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ShapeOpModel<int64_t> model({1, 3, 1, 3, 5}, TensorType_FLOAT32,
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TensorType_INT64);
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model.Invoke();
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EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 3, 1, 3, 5}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({5}));
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}
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TEST(ShapeOpTest, ScalarTensor) {
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ShapeOpModel<int32_t> model({}, TensorType_FLOAT32, TensorType_INT32);
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model.Invoke();
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EXPECT_EQ(model.GetOutputSize(), 0);
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({0}));
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}
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TEST(ShapeOpTest, EmptyTensor) {
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ShapeOpModel<int32_t> model({1, 0}, TensorType_FLOAT32, TensorType_INT32);
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model.Invoke();
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EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 0}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2}));
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}
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} // namespace
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} // namespace tflite
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