broadcast_args_test.cc

/* Copyright 2021 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 <cstdint>
#include <vector>

#include <gtest/gtest.h>
#include "tensorflow/lite/core/interpreter.h"
#include "tensorflow/lite/core/kernels/register.h"
#include "tensorflow/lite/core/model.h"
#include "tensorflow/lite/kernels/test_util.h"

namespace tflite {
namespace {
using ::testing::ElementsAreArray;

template <class ShapeType = int32_t>
class BroadcastArgsOpModel : public SingleOpModel {
 public:
  BroadcastArgsOpModel(std::initializer_list<ShapeType> input1,
                       std::initializer_list<ShapeType> input2,
                       bool constant_tensor) {
    int input1_length = input1.size();
    int input2_length = input2.size();
    if (constant_tensor) {
      shape1_ =
          AddConstInput({GetTensorType<ShapeType>(), {input1_length}}, input1);
      shape2_ =
          AddConstInput({GetTensorType<ShapeType>(), {input2_length}}, input2);
    } else {
      shape1_ = AddInput({GetTensorType<ShapeType>(), {input1_length}});
      shape2_ = AddInput({GetTensorType<ShapeType>(), {input2_length}});
    }
    output_ = AddOutput(GetTensorType<ShapeType>());
    SetBuiltinOp(BuiltinOperator_BROADCAST_ARGS, BuiltinOptions_NONE, 0);
    BuildInterpreter({{input1_length}, {input2_length}});
    if (!constant_tensor) {
      if (input1.size() > 0) SetInput1(input1);
      if (input2.size() > 0) SetInput2(input2);
    }
  }

  void SetInput1(std::initializer_list<ShapeType> data) {
    PopulateTensor(shape1_, data);
  }

  void SetInput2(std::initializer_list<ShapeType> data) {
    PopulateTensor(shape2_, data);
  }

  std::vector<ShapeType> GetOutput() {
    return ExtractVector<ShapeType>(output_);
  }
  std::vector<int> GetOutputShape() { return GetTensorShape(output_); }

 protected:
  int shape1_;
  int shape2_;
  int output_;
};

template <typename T>
class BroadcastArgsOpTest : public ::testing::Test {};

using DataTypes = ::testing::Types<int64_t, int32_t>;
TYPED_TEST_SUITE(BroadcastArgsOpTest, DataTypes);

#if GTEST_HAS_DEATH_TEST
TYPED_TEST(BroadcastArgsOpTest, ShapeNotBroadcastableConstant) {
  EXPECT_DEATH(BroadcastArgsOpModel<TypeParam> m({2, 3, 4, 4}, {2, 2},
                                                 /*constant_tensor=*/true),
               "");
}

TYPED_TEST(BroadcastArgsOpTest, ShapeNotBroadcastable) {
  BroadcastArgsOpModel<TypeParam> m({2, 3, 4, 4}, {2, 2},
                                    /*constant_tensor=*/false);
  EXPECT_DEATH(ASSERT_EQ(m.Invoke(), kTfLiteOk), "");
}
#endif

TYPED_TEST(BroadcastArgsOpTest, BroadcastArgsWithScalar) {
  for (bool constant_tensor : {true, false}) {
    BroadcastArgsOpModel<TypeParam> m({}, {2, 4}, constant_tensor);
    ASSERT_EQ(m.Invoke(), kTfLiteOk);
    EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2}));
    EXPECT_THAT(m.GetOutput(), ElementsAreArray({2, 4}));
  }
}

TYPED_TEST(BroadcastArgsOpTest, BroadcastArgsDifferentDims) {
  for (bool constant_tensor : {true, false}) {
    BroadcastArgsOpModel<TypeParam> m({1}, {2, 4}, constant_tensor);
    ASSERT_EQ(m.Invoke(), kTfLiteOk);
    EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2}));
    EXPECT_THAT(m.GetOutput(), ElementsAreArray({2, 4}));
  }
}

TYPED_TEST(BroadcastArgsOpTest, BroadcastArgsSameDims) {
  for (bool constant_tensor : {true, false}) {
    BroadcastArgsOpModel<TypeParam> m({1, 4, 6, 3, 1, 5}, {4, 4, 1, 3, 4, 1},
                                      constant_tensor);
    ASSERT_EQ(m.Invoke(), kTfLiteOk);
    EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({6}));
    EXPECT_THAT(m.GetOutput(), ElementsAreArray({4, 4, 6, 3, 4, 5}));
  }
}

TYPED_TEST(BroadcastArgsOpTest, BroadcastArgsComplex) {
  for (bool constant_tensor : {true, false}) {
    BroadcastArgsOpModel<TypeParam> m({6, 3, 1, 5}, {4, 4, 1, 3, 4, 1},
                                      constant_tensor);
    ASSERT_EQ(m.Invoke(), kTfLiteOk);
    EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({6}));
    EXPECT_THAT(m.GetOutput(), ElementsAreArray({4, 4, 6, 3, 4, 5}));
  }
}

}  // namespace
}  // namespace tflite