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      1 /* Copyright 2018 The TensorFlow Authors. All Rights Reserved.
      2 
      3 Licensed under the Apache License, Version 2.0 (the "License");
      4 you may not use this file except in compliance with the License.
      5 You may obtain a copy of the License at
      6 
      7     http://www.apache.org/licenses/LICENSE-2.0
      8 
      9 Unless required by applicable law or agreed to in writing, software
     10 distributed under the License is distributed on an "AS IS" BASIS,
     11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     12 See the License for the specific language governing permissions and
     13 limitations under the License.
     14 ==============================================================================*/
     15 #include <gtest/gtest.h>
     16 #include "tensorflow/contrib/lite/interpreter.h"
     17 #include "tensorflow/contrib/lite/kernels/register.h"
     18 #include "tensorflow/contrib/lite/kernels/test_util.h"
     19 #include "tensorflow/contrib/lite/model.h"
     20 
     21 namespace tflite {
     22 namespace {
     23 
     24 using ::testing::ElementsAreArray;
     25 using ::testing::IsEmpty;
     26 
     27 class BaseSqueezeOpModel : public SingleOpModel {
     28  public:
     29   BaseSqueezeOpModel(const TensorData& input, const TensorData& output,
     30                      std::initializer_list<int> axis) {
     31     input_ = AddInput(input);
     32     output_ = AddOutput(output);
     33     SetBuiltinOp(
     34         BuiltinOperator_SQUEEZE, BuiltinOptions_SqueezeOptions,
     35         CreateSqueezeOptions(builder_, builder_.CreateVector<int>(axis))
     36             .Union());
     37     BuildInterpreter({GetShape(input_)});
     38   }
     39 
     40   int input() { return input_; }
     41 
     42  protected:
     43   int input_;
     44   int output_;
     45 };
     46 
     47 class FloatSqueezeOpModel : public BaseSqueezeOpModel {
     48  public:
     49   using BaseSqueezeOpModel::BaseSqueezeOpModel;
     50 
     51   void SetInput(std::initializer_list<float> data) {
     52     PopulateTensor(input_, data);
     53   }
     54 
     55   std::vector<float> GetOutput() { return ExtractVector<float>(output_); }
     56   std::vector<int> GetOutputShape() { return GetTensorShape(output_); }
     57 };
     58 
     59 TEST(FloatSqueezeOpTest, SqueezeAll) {
     60   std::initializer_list<float> data = {
     61       1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
     62       13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
     63   FloatSqueezeOpModel m({TensorType_FLOAT32, {1, 24, 1}},
     64                         {TensorType_FLOAT32, {24}}, {});
     65   m.SetInput(data);
     66   m.Invoke();
     67   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({24}));
     68   EXPECT_THAT(
     69       m.GetOutput(),
     70       ElementsAreArray({1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,
     71                         9.0,  10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0,
     72                         17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0}));
     73 }
     74 
     75 TEST(FloatSqueezeOpTest, SqueezeSelectedAxis) {
     76   std::initializer_list<float> data = {
     77       1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
     78       13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
     79   FloatSqueezeOpModel m({TensorType_FLOAT32, {1, 24, 1}},
     80                         {TensorType_FLOAT32, {24}}, {2});
     81   m.SetInput(data);
     82   m.Invoke();
     83   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 24}));
     84   EXPECT_THAT(
     85       m.GetOutput(),
     86       ElementsAreArray({1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,
     87                         9.0,  10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0,
     88                         17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0}));
     89 }
     90 
     91 TEST(FloatSqueezeOpTest, SqueezeNegativeAxis) {
     92   std::initializer_list<float> data = {
     93       1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,  9.0,  10.0, 11.0, 12.0,
     94       13.0, 14.0, 15.0, 16.0, 17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0};
     95   FloatSqueezeOpModel m({TensorType_FLOAT32, {1, 24, 1}},
     96                         {TensorType_FLOAT32, {24}}, {-1, 0});
     97   m.SetInput(data);
     98   m.Invoke();
     99   EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({24}));
    100   EXPECT_THAT(
    101       m.GetOutput(),
    102       ElementsAreArray({1.0,  2.0,  3.0,  4.0,  5.0,  6.0,  7.0,  8.0,
    103                         9.0,  10.0, 11.0, 12.0, 13.0, 14.0, 15.0, 16.0,
    104                         17.0, 18.0, 19.0, 20.0, 21.0, 22.0, 23.0, 24.0}));
    105 }
    106 
    107 TEST(FloatSqueezeOpTest, SqueezeAllDims) {
    108   std::initializer_list<float> data = {3.85};
    109   FloatSqueezeOpModel m({TensorType_FLOAT32, {1, 1, 1, 1, 1, 1, 1}},
    110                         {TensorType_FLOAT32, {1}}, {});
    111   m.SetInput(data);
    112   m.Invoke();
    113   EXPECT_THAT(m.GetOutputShape(), IsEmpty());
    114   EXPECT_THAT(m.GetOutput(), ElementsAreArray({3.85}));
    115 }
    116 
    117 }  // namespace
    118 }  // namespace tflite
    119 
    120 int main(int argc, char** argv) {
    121   ::tflite::LogToStderr();
    122   ::testing::InitGoogleTest(&argc, argv);
    123   return RUN_ALL_TESTS();
    124 }
    125