78 lines
2.7 KiB
C++
78 lines
2.7 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 <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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class CeilOpModel : public SingleOpModel {
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public:
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CeilOpModel(std::initializer_list<int> input_shape, TensorType input_type) {
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input_ = AddInput(TensorType_FLOAT32);
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output_ = AddOutput(TensorType_FLOAT32);
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SetBuiltinOp(BuiltinOperator_CEIL, BuiltinOptions_NONE, 0);
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BuildInterpreter({
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input_shape,
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});
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}
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int input() { return input_; }
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std::vector<float> GetOutput() { return ExtractVector<float>(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(CeilOpTest, SingleDim) {
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CeilOpModel model({2}, TensorType_FLOAT32);
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model.PopulateTensor<float>(model.input(), {8.5, 0.0});
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model.Invoke();
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EXPECT_THAT(model.GetOutput(), ElementsAreArray({9, 0}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2}));
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}
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TEST(CeilOpTest, MultiDims) {
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CeilOpModel model({2, 1, 1, 5}, TensorType_FLOAT32);
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model.PopulateTensor<float>(model.input(), {
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0.0001,
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8.0001,
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0.9999,
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9.9999,
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0.5,
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-0.0001,
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-8.0001,
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-0.9999,
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-9.9999,
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-0.5,
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});
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model.Invoke();
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EXPECT_THAT(model.GetOutput(),
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ElementsAreArray({1, 9, 1, 10, 1, 0, -8, 0, -9, 0}));
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EXPECT_THAT(model.GetOutputShape(), ElementsAreArray({2, 1, 1, 5}));
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}
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} // namespace
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} // namespace tflite
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