/* Copyright 2020 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.
==============================================================================*/

#ifndef TENSORFLOW_LITE_DELEGATES_XNNPACK_REDUCE_TESTER_H_
#define TENSORFLOW_LITE_DELEGATES_XNNPACK_REDUCE_TESTER_H_

#include <cstdint>
#include <unordered_set>
#include <vector>

#include <gtest/gtest.h>
#include "tensorflow/lite/core/c/common.h"
#include "tensorflow/lite/schema/schema_generated.h"

namespace tflite {
namespace xnnpack {

class ReduceTester {
 public:
  ReduceTester() = default;
  ReduceTester(const ReduceTester&) = delete;
  ReduceTester& operator=(const ReduceTester&) = delete;

  inline ReduceTester& InputShape(std::initializer_list<int32_t> shape) {
    for (auto it = shape.begin(); it != shape.end(); ++it) {
      EXPECT_GT(*it, 0);
    }
    input_shape_ = std::vector<int32_t>(shape.begin(), shape.end());
    input_size_ = ReduceTester::ComputeSize(input_shape_);
    return *this;
  }

  inline const std::vector<int32_t>& InputShape() const { return input_shape_; }

  inline int32_t InputSize() const { return input_size_; }

  inline ReduceTester& Axes(std::initializer_list<int32_t> axes) {
    for (auto it = axes.begin(); it != axes.end(); ++it) {
      EXPECT_GE(*it, 0);
    }
    axes_ = std::vector<int32_t>(axes.begin(), axes.end());
    return *this;
  }

  inline const std::vector<int32_t>& Axes() const { return axes_; }

  inline ReduceTester& KeepDims(bool keep_dims) {
    keep_dims_ = keep_dims;
    return *this;
  }

  inline bool KeepDims() const { return keep_dims_; }

  inline std::vector<int32_t> OutputShape() const {
    std::vector<int32_t> output_shape;
    output_shape.reserve(InputShape().size());
    std::unordered_set<int32_t> axes_set(Axes().cbegin(), Axes().cend());
    for (int32_t i = 0; i < InputShape().size(); i++) {
      if (axes_set.count(i) != 0) {
        if (KeepDims()) {
          output_shape.push_back(1);
        }
      } else {
        output_shape.push_back(InputShape()[i]);
      }
    }
    return output_shape;
  }

  inline int32_t OutputSize() const {
    int32_t output_size = 1;
    std::unordered_set<int32_t> axes_set(Axes().cbegin(), Axes().cend());
    for (int32_t i = 0; i < InputShape().size(); i++) {
      if (axes_set.count(i) == 0) {
        output_size *= InputShape()[i];
      }
    }
    return output_size;
  }

  inline ReduceTester& RelativeTolerance(float relative_tolerance) {
    relative_tolerance_ = relative_tolerance;
    return *this;
  }

  inline float RelativeTolerance() const { return relative_tolerance_; }

  void Test(tflite::BuiltinOperator reduce_op, TfLiteDelegate* delegate) const;

 private:
  std::vector<char> CreateTfLiteModel(tflite::BuiltinOperator reduce_op) const;

  static int32_t ComputeSize(const std::vector<int32_t>& shape);

  std::vector<int32_t> input_shape_;
  std::vector<int32_t> axes_;
  int32_t input_size_;
  bool keep_dims_ = true;
  float relative_tolerance_ = 10.0f;
};

}  // namespace xnnpack
}  // namespace tflite

#endif  // TENSORFLOW_LITE_DELEGATES_XNNPACK_REDUCE_TESTER_H_
