/* Copyright 2017 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;
using ::testing::Matcher;

template <typename T>
class PadOpModel : public SingleOpModel {
 public:
  void SetInput(std::initializer_list<T> data) {
    PopulateTensor<T>(input_, data);
  }

  void SetQuantizedInput(std::initializer_list<float> data) {
    QuantizeAndPopulate<uint8_t>(input_, data);
  }

  void SetQuantizedPadValue(float data) {
    QuantizeAndPopulate<uint8_t>(constant_values_, {data});
  }

  void SetPaddings(std::initializer_list<int> paddings) {
    PopulateTensor<int>(paddings_, paddings);
  }

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

  std::vector<float> GetDequantizedOutput() {
    return Dequantize<uint8_t>(ExtractVector<uint8_t>(output_),
                               GetScale(output_), GetZeroPoint(output_));
  }

 protected:
  int input_;
  int output_;
  int paddings_;
  int constant_values_;
};

namespace {

// Returns the corresponding TensorType given the type T.
template <typename T>
TensorType GetTensorType() {
  if (std::is_same<T, float>::value) return TensorType_FLOAT32;
  if (std::is_same<T, int32_t>::value) return TensorType_INT32;
  if (std::is_same<T, uint8_t>::value) return TensorType_UINT8;
  return TensorType_MIN;  // default value
}

}  // namespace

// Tests case where paddings is a const tensor. Type T is the dtype.
template <typename T>
class PadV2OpConstModel : public PadOpModel<T> {
 public:
  PadV2OpConstModel(const TensorData& input,
                    std::initializer_list<int> paddings_shape,
                    std::initializer_list<int> paddings, T constant_values,
                    const TensorData& output) {
    this->input_ = this->AddInput(input);
    this->paddings_ =
        this->AddConstInput(TensorType_INT32, paddings, paddings_shape);
    this->constant_values_ =
        this->AddConstInput(GetTensorType<T>(), {constant_values}, {1});

    this->output_ = this->AddOutput(output);

    this->SetBuiltinOp(BuiltinOperator_PADV2, BuiltinOptions_PadV2Options,
                       CreatePadV2Options(this->builder_).Union());
    this->BuildInterpreter({input.shape});
  }

  PadV2OpConstModel(const TensorData& input,
                    std::initializer_list<int> paddings_shape,
                    std::initializer_list<int> paddings,
                    const TensorData& constant_values,
                    const TensorData& output) {
    this->input_ = this->AddInput(input);
    this->paddings_ =
        this->AddConstInput(TensorType_INT32, paddings, paddings_shape);
    this->constant_values_ = this->AddInput(constant_values);

    this->output_ = this->AddOutput(output);

    this->SetBuiltinOp(BuiltinOperator_PADV2, BuiltinOptions_PadV2Options,
                       CreatePadV2Options(this->builder_).Union());
    this->BuildInterpreter({input.shape});
  }
};

// Tests case where paddings is a const tensor.
//
// Example usage is as follows:
//    PadOpDynamicModel m(input_shape, paddings_shape, paddings_data);
//    m.SetInput(input_data);
//    m.Invoke();
class PadOpConstModel : public PadOpModel<float> {
 public:
  PadOpConstModel(const TensorData& input,
                  std::initializer_list<int> paddings_shape,
                  std::initializer_list<int> paddings,
                  const TensorData& output) {
    input_ = AddInput(input);
    paddings_ = AddConstInput(TensorType_INT32, paddings, paddings_shape);
    constant_values_ = AddNullInput();
    output_ = AddOutput(output);

    SetBuiltinOp(BuiltinOperator_PAD, BuiltinOptions_PadOptions,
                 CreatePadOptions(builder_).Union());
    BuildInterpreter({input.shape});
  }
};

// Test case where paddings is a non-const tensor.
template <typename T>
class PadV2OpDynamicModel : public PadOpModel<T> {
 public:
  PadV2OpDynamicModel(const TensorData& input,
                      std::initializer_list<int> paddings_shape,
                      T constant_values, const TensorData& output) {
    this->input_ = this->AddInput(input);
    this->paddings_ = this->AddInput(TensorType_INT32);
    this->constant_values_ =
        this->AddConstInput(GetTensorType<T>(), {constant_values}, {1});
    this->output_ = this->AddOutput(output);

    this->SetBuiltinOp(BuiltinOperator_PADV2, BuiltinOptions_PadV2Options,
                       CreatePadV2Options(this->builder_).Union());
    this->BuildInterpreter({input.shape, paddings_shape});
  }
  PadV2OpDynamicModel(const TensorData& input,
                      std::initializer_list<int> paddings_shape,
                      const TensorData& constant_values,
                      const TensorData& output) {
    this->input_ = this->AddInput(input);
    this->paddings_ = this->AddInput(TensorType_INT32);
    this->constant_values_ = this->AddInput(constant_values);
    this->output_ = this->AddOutput(output);

    this->SetBuiltinOp(BuiltinOperator_PADV2, BuiltinOptions_PadV2Options,
                       CreatePadV2Options(this->builder_).Union());
    this->BuildInterpreter({input.shape, paddings_shape});
  }
};

// Test case where paddings is a non-const tensor.
//
// Example usage is as follows:
//    PadOpDynamicModel m(input_shape, paddings_shape);
//    m.SetInput(input_data);
//    m.SetPaddings(paddings_data);
//    m.Invoke();
class PadOpDynamicModel : public PadOpModel<float> {
 public:
  PadOpDynamicModel(const TensorData& input,
                    std::initializer_list<int> paddings_shape,
                    const TensorData& output) {
    input_ = AddInput(input);
    paddings_ = AddInput(TensorType_INT32);
    constant_values_ = AddNullInput();
    output_ = AddOutput(output);

    SetBuiltinOp(BuiltinOperator_PAD, BuiltinOptions_PadOptions,
                 CreatePadOptions(builder_).Union());
    BuildInterpreter({input.shape, paddings_shape});
  }
};

TEST(PadOpTest, TooManyDimensions) {
  EXPECT_DEATH(
      PadOpConstModel({TensorType_FLOAT32, {1, 2, 3, 4, 5, 6, 7, 8, 9}}, {9, 2},
                      {1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9},
                      {TensorType_FLOAT32}),
      "dims <= 4");
}

TEST(PadOpTest, UnequalDimensions) {
  EXPECT_DEATH(PadOpConstModel({TensorType_FLOAT32, {1, 1, 2, 1}}, {3, 2},
                               {1, 1, 2, 2, 3, 3}, {TensorType_FLOAT32}),
               "3 != 4");
}

TEST(PadOpTest, InvalidPadValue) {
  EXPECT_DEATH(
      PadOpConstModel({TensorType_FLOAT32, {1, 1, 2, 1}}, {4, 2},
                      {0, 0, 1, -1, 2, -1, 0, 0}, {TensorType_FLOAT32}),
      "Pad value has to be greater than equal to 0.");
}

TEST(PadOpTest, SimpleConstTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadOpConstModel m({TensorType_FLOAT32, {1, 2, 2, 1}}, {4, 2},
                    {0, 0, 1, 1, 1, 1, 0, 0}, {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4,
                                               0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadOpTest, SimpleConst1DTest) {
  PadOpConstModel m({TensorType_FLOAT32, {2}}, {1, 2}, {1, 2},
                    {TensorType_FLOAT32});
  m.SetInput({2, 3});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 2, 3, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({5}));
}

TEST(PadOpTest, SimpleDynamicTest) {
  PadOpDynamicModel m({TensorType_FLOAT32, {1, 2, 2, 1}}, {4, 2},
                      {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4});
  m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4,
                                               0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadOpTest, AdvancedConstTest) {
  PadOpConstModel m({TensorType_FLOAT32, {1, 2, 3, 1}}, {4, 2},
                    {0, 0, 0, 2, 1, 3, 0, 0}, {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4, 5, 6});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(),
              ElementsAreArray({0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0,
                                0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST(PadOpTest, AdvancedDynamicTest) {
  PadOpDynamicModel m({TensorType_FLOAT32, {1, 2, 3, 1}}, {4, 2},
                      {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4, 5, 6});
  m.SetPaddings({0, 0, 0, 2, 1, 3, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(),
              ElementsAreArray({0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0,
                                0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

class QuantizedPadOpTest : public ::testing::Test {
 protected:
  std::vector<Matcher<float>> DequantizedArrayNear(
      const std::vector<float>& values, const float min, const float max) {
    const float quantization_tolerance = (max - min) / 255.0;
    return ArrayFloatNear(values, quantization_tolerance);
  }
};

TEST_F(QuantizedPadOpTest, ZeroNotInQuantizationRange) {
  // The test_util and actual quantization code currently ensure that the range
  // must include zero, but if that ever changes, this test will catch it.
  EXPECT_DEATH(PadOpConstModel m({TensorType_UINT8, {1, 2, 2, 1}, 1.0, 2.0},
                                 {4, 2}, {0, 0, 1, 1, 1, 1, 0, 0},
                                 {TensorType_UINT8, {}, 1.0, 2.0}),
               ".*Check failed: f_min <= 0.*");
}

TEST_F(QuantizedPadOpTest, SimpleConstTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadOpConstModel m({TensorType_UINT8, {1, 2, 2, 1}, -1.0, 1.0}, {4, 2},
                    {0, 0, 1, 1, 1, 1, 0, 0},
                    {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, 0, 0, 0, 0, -0.8, 0.2, 0, 0, 0.9, 0.7, 0, 0, 0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST_F(QuantizedPadOpTest, SimpleDynamicTest) {
  PadOpDynamicModel m({TensorType_UINT8, {1, 2, 2, 1}, -1.0, 1.0}, {4, 2},
                      {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7});
  m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, 0, 0, 0, 0, -0.8, 0.2, 0, 0, 0.9, 0.7, 0, 0, 0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST_F(QuantizedPadOpTest, AdvancedConstTest) {
  PadOpConstModel m({TensorType_UINT8, {1, 2, 3, 1}, -1.0, 1.0}, {4, 2},
                    {0, 0, 0, 2, 1, 3, 0, 0},
                    {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7, 0.1, -0.3});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, -0.8, 0.2, 0.9, 0, 0, 0, 0, 0.7, 0.1, -0.3, 0, 0, 0,
                   0, 0,    0,   0,   0, 0, 0, 0, 0,   0,   0,    0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST_F(QuantizedPadOpTest, AdvancedDynamicTest) {
  PadOpDynamicModel m({TensorType_UINT8, {1, 2, 3, 1}, -1.0, 1.0}, {4, 2},
                      {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7, 0.1, -0.3});
  m.SetPaddings({0, 0, 0, 2, 1, 3, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, -0.8, 0.2, 0.9, 0, 0, 0, 0, 0.7, 0.1, -0.3, 0, 0, 0,
                   0, 0,    0,   0,   0, 0, 0, 0, 0,   0,   0,    0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST(PadV2OpTest, TooManyDimensions) {
  EXPECT_DEATH(PadV2OpConstModel<float>(
                   {TensorType_FLOAT32, {1, 2, 3, 4, 5, 6, 7, 8, 9}}, {9, 2},
                   {1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9}, 0.0,
                   {TensorType_FLOAT32}),
               "dims <= 4");
}

TEST(PadV2OpTest, UnequalDimensions) {
  EXPECT_DEATH(
      PadV2OpConstModel<float>({TensorType_FLOAT32, {1, 1, 2, 1}}, {3, 2},
                               {1, 1, 2, 2, 3, 3}, 0.0, {TensorType_FLOAT32}),
      "3 != 4");
}

TEST(PadV2OpTest, InvalidPadValue) {
  EXPECT_DEATH(PadV2OpConstModel<float>({TensorType_FLOAT32, {1, 1, 2, 1}},
                                        {4, 2}, {0, 0, 1, -1, 2, -1, 0, 0}, 0.0,
                                        {TensorType_FLOAT32}),
               "Pad value has to be greater than equal to 0.");
}

TEST(PadV2OpTest, SimpleConstTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadV2OpConstModel<float> m({TensorType_FLOAT32, {1, 2, 2, 1}}, {4, 2},
                             {0, 0, 1, 1, 1, 1, 0, 0}, 0.0,
                             {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4,
                                               0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadV2OpTest, SimpleConstFloat32ValuedTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadV2OpConstModel<float> m({TensorType_FLOAT32, {1, 2, 2, 1}}, {4, 2},
                             {0, 0, 1, 1, 1, 1, 0, 0}, 5, {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({5, 5, 5, 5, 5, 1, 2, 5, 5, 3, 4,
                                               5, 5, 5, 5, 5}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadV2OpTest, Simple4DConstFloat32ValuedTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadV2OpConstModel<float> m({TensorType_FLOAT32, {1, 1, 2, 1}}, {4, 2},
                             {0, 1, 0, 0, 0, 0, 0, 1}, 5, {TensorType_FLOAT32});
  m.SetInput({3, 3});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({3, 5, 3, 5, 5, 5, 5, 5}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({2, 1, 2, 2}));
}

TEST(PadV2OpTest, SimpleConstInt32ValuedTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadV2OpConstModel<int32_t> m({TensorType_INT32, {1, 2, 2, 1}}, {4, 2},
                               {0, 0, 1, 1, 1, 1, 0, 0}, 5, {TensorType_INT32});
  m.SetInput({1, 2, 3, 4});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({5, 5, 5, 5, 5, 1, 2, 5, 5, 3, 4,
                                               5, 5, 5, 5, 5}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadV2OpTest, SimpleDynamicTest) {
  PadV2OpDynamicModel<float> m({TensorType_FLOAT32, {1, 2, 2, 1}}, {4, 2}, 0.0,
                               {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4});
  m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({0, 0, 0, 0, 0, 1, 2, 0, 0, 3, 4,
                                               0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadV2OpTest, SimpleDynamicValuedTest) {
  PadV2OpDynamicModel<float> m({TensorType_FLOAT32, {1, 2, 2, 1}}, {4, 2}, 5,
                               {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4});
  m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(), ElementsAreArray({5, 5, 5, 5, 5, 1, 2, 5, 5, 3, 4,
                                               5, 5, 5, 5, 5}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST(PadV2OpTest, AdvancedConstTest) {
  PadV2OpConstModel<float> m({TensorType_FLOAT32, {1, 2, 3, 1}}, {4, 2},
                             {0, 0, 0, 2, 1, 3, 0, 0}, 0, {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4, 5, 6});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(),
              ElementsAreArray({0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0,
                                0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST(PadV2OpTest, AdvancedDynamicTest) {
  PadV2OpDynamicModel<float> m({TensorType_FLOAT32, {1, 2, 3, 1}}, {4, 2}, 0,
                               {TensorType_FLOAT32});
  m.SetInput({1, 2, 3, 4, 5, 6});
  m.SetPaddings({0, 0, 0, 2, 1, 3, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetOutput(),
              ElementsAreArray({0, 1, 2, 3, 0, 0, 0, 0, 4, 5, 6, 0, 0, 0,
                                0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0}));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

class QuantizedPadV2OpTest : public ::testing::Test {
 protected:
  std::vector<Matcher<float>> DequantizedArrayNear(
      const std::vector<float>& values, const float min, const float max) {
    const float quantization_tolerance = (max - min) / 255.0;
    return ArrayFloatNear(values, quantization_tolerance);
  }
};

TEST_F(QuantizedPadV2OpTest, ZeroNotInQuantizationRange) {
  // The test_util and actual quantization code currently ensure that the range
  // must include zero, but if that ever changes, this test will catch it.
  EXPECT_DEATH(
      PadV2OpConstModel<float> m({TensorType_UINT8, {1, 2, 2, 1}, 1.0, 2.0},
                                 {4, 2}, {0, 0, 1, 1, 1, 1, 0, 0}, 0,
                                 {TensorType_UINT8, {}, 1.0, 2.0}),
      ".*Check failed: f_min <= 0.*");
}

TEST_F(QuantizedPadV2OpTest, SimpleConstTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadV2OpConstModel<uint8_t> m({TensorType_UINT8, {1, 2, 2, 1}, -1.0, 1.0},
                               {4, 2}, {0, 0, 1, 1, 1, 1, 0, 0},
                               {TensorType_UINT8, {1}, -1.0, 1.0},
                               {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7});
  m.SetQuantizedPadValue(0);
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, 0, 0, 0, 0, -0.8, 0.2, 0, 0, 0.9, 0.7, 0, 0, 0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST_F(QuantizedPadV2OpTest, SimpleDynamicTest) {
  PadV2OpDynamicModel<uint8_t> m({TensorType_UINT8, {1, 2, 2, 1}, -1.0, 1.0},
                                 {4, 2}, {TensorType_UINT8, {1}, -1.0, 1.0},
                                 {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7});
  m.SetQuantizedPadValue(0);
  m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, 0, 0, 0, 0, -0.8, 0.2, 0, 0, 0.9, 0.7, 0, 0, 0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST_F(QuantizedPadV2OpTest, AdvancedConstTest) {
  PadV2OpConstModel<uint8_t> m({TensorType_UINT8, {1, 2, 3, 1}, -1.0, 1.0},
                               {4, 2}, {0, 0, 0, 2, 1, 3, 0, 0},
                               {TensorType_UINT8, {1}, -1.0, 1.0},
                               {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7, 0.1, -0.3});
  m.SetQuantizedPadValue(0);
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, -0.8, 0.2, 0.9, 0, 0, 0, 0, 0.7, 0.1, -0.3, 0, 0, 0,
                   0, 0,    0,   0,   0, 0, 0, 0, 0,   0,   0,    0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST_F(QuantizedPadV2OpTest, AdvancedDynamicTest) {
  PadV2OpDynamicModel<uint8_t> m({TensorType_UINT8, {1, 2, 3, 1}, -1.0, 1.0},
                                 {4, 2}, {TensorType_UINT8, {1}, -1.0, 1.0},
                                 {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7, 0.1, -0.3});
  m.SetQuantizedPadValue(0);
  m.SetPaddings({0, 0, 0, 2, 1, 3, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {0, -0.8, 0.2, 0.9, 0, 0, 0, 0, 0.7, 0.1, -0.3, 0, 0, 0,
                   0, 0,    0,   0,   0, 0, 0, 0, 0,   0,   0,    0, 0, 0},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST_F(QuantizedPadV2OpTest, SimpleConstValuedTest) {
  // Padding is represented as four 2-D lists representing above padding and
  // below padding (i.e. {{0, 0}, {1, 1}, {1, 1}, {0, 0}}).
  PadV2OpConstModel<uint8_t> m({TensorType_UINT8, {1, 2, 2, 1}, -1.0, 1.0},
                               {4, 2}, {0, 0, 1, 1, 1, 1, 0, 0},
                               {TensorType_UINT8, {1}, -1.0, 1.0},
                               {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7});
  m.SetQuantizedPadValue(-0.5);
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {-0.5, -0.5, -0.5, -0.5, -0.5, -0.8, 0.2, -0.5, -0.5, 0.9,
                   0.7, -0.5, -0.5, -0.5, -0.5, -0.5},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST_F(QuantizedPadV2OpTest, SimpleDynamicValuedTest) {
  PadV2OpDynamicModel<uint8_t> m({TensorType_UINT8, {1, 2, 2, 1}, -1.0, 1.0},
                                 {4, 2}, {TensorType_UINT8, {1}, -1.0, 1.0},
                                 {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7});
  m.SetQuantizedPadValue(-0.5);
  m.SetPaddings({0, 0, 1, 1, 1, 1, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {-0.5, -0.5, -0.5, -0.5, -0.5, -0.8, 0.2, -0.5, -0.5, 0.9,
                   0.7, -0.5, -0.5, -0.5, -0.5, -0.5},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 4, 1}));
}

TEST_F(QuantizedPadV2OpTest, AdvancedConstValuedTest) {
  PadV2OpConstModel<uint8_t> m({TensorType_UINT8, {1, 2, 3, 1}, -1.0, 1.0},
                               {4, 2}, {0, 0, 0, 2, 1, 3, 0, 0},
                               {TensorType_UINT8, {1}, -1.0, 1.0},
                               {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7, 0.1, -0.3});
  m.SetQuantizedPadValue(-0.5);
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {-0.5, -0.8, 0.2,  0.9,  -0.5, -0.5, -0.5, -0.5, 0.7,  0.1,
                   -0.3, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5,
                   -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

TEST_F(QuantizedPadV2OpTest, AdvancedDynamicValuedTest) {
  PadV2OpDynamicModel<uint8_t> m({TensorType_UINT8, {1, 2, 3, 1}, -1.0, 1.0},
                                 {4, 2}, {TensorType_UINT8, {1}, -1.0, 1.0},
                                 {TensorType_UINT8, {}, -1.0, 1.0});
  m.SetQuantizedInput({-0.8, 0.2, 0.9, 0.7, 0.1, -0.3});
  m.SetQuantizedPadValue(-0.5);
  m.SetPaddings({0, 0, 0, 2, 1, 3, 0, 0});
  m.Invoke();
  EXPECT_THAT(m.GetDequantizedOutput(),
              ElementsAreArray(DequantizedArrayNear(
                  {-0.5, -0.8, 0.2,  0.9,  -0.5, -0.5, -0.5, -0.5, 0.7,  0.1,
                   -0.3, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5,
                   -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5, -0.5},
                  -1.0, 1.0)));
  EXPECT_THAT(m.GetOutputShape(), ElementsAreArray({1, 4, 7, 1}));
}

}  // namespace
}  // namespace tflite

int main(int argc, char** argv) {
  ::tflite::LogToStderr();
  ::testing::InitGoogleTest(&argc, argv);
  return RUN_ALL_TESTS();
}