/* Copyright 2024 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_DYNAMICALLY_QUANTIZED_TRANSPOSE_CONV_TESTER_H_
#define TENSORFLOW_LITE_DELEGATES_XNNPACK_DYNAMICALLY_QUANTIZED_TRANSPOSE_CONV_TESTER_H_

#include <cstdint>
#include <functional>
#include <random>
#include <vector>

#include <gtest/gtest.h>
#include "tensorflow/lite/c/c_api_types.h"
#include "tensorflow/lite/core/c/builtin_op_data.h"
#include "tensorflow/lite/delegates/xnnpack/xnnpack_delegate.h"
#include "tensorflow/lite/schema/schema_generated.h"

namespace tflite {
namespace xnnpack {

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

  inline DynamicallyQuantizedTransposeConvTester& BatchSize(
      int32_t batch_size) {
    EXPECT_GT(batch_size, 0);
    batch_size_ = batch_size;
    return *this;
  }

  inline int32_t BatchSize() const { return batch_size_; }

  inline DynamicallyQuantizedTransposeConvTester& InputChannels(
      int32_t input_channels) {
    EXPECT_GT(input_channels, 0);
    input_channels_ = input_channels;
    return *this;
  }

  inline int32_t InputChannels() const { return input_channels_; }

  inline DynamicallyQuantizedTransposeConvTester& OutputChannels(
      int32_t output_channels) {
    EXPECT_GT(output_channels, 0);
    output_channels_ = output_channels;
    return *this;
  }

  inline int32_t OutputChannels() const { return output_channels_; }

  inline DynamicallyQuantizedTransposeConvTester& OutputHeight(
      int32_t output_height) {
    EXPECT_GT(output_height, 0);
    output_height_ = output_height;
    return *this;
  }

  inline int32_t OutputHeight() const { return output_height_; }

  inline DynamicallyQuantizedTransposeConvTester& OutputWidth(
      int32_t output_width) {
    EXPECT_GT(output_width, 0);
    output_width_ = output_width;
    return *this;
  }

  inline int32_t OutputWidth() const { return output_width_; }

  inline DynamicallyQuantizedTransposeConvTester& KernelHeight(
      int32_t kernel_height) {
    EXPECT_GT(kernel_height, 0);
    kernel_height_ = kernel_height;
    return *this;
  }

  inline int32_t KernelHeight() const { return kernel_height_; }

  inline DynamicallyQuantizedTransposeConvTester& KernelWidth(
      int32_t kernel_width) {
    EXPECT_GT(kernel_width, 0);
    kernel_width_ = kernel_width;
    return *this;
  }

  inline int32_t KernelWidth() const { return kernel_width_; }

  inline DynamicallyQuantizedTransposeConvTester& StrideHeight(
      int32_t stride_height) {
    EXPECT_GT(stride_height, 0);
    stride_height_ = stride_height;
    return *this;
  }

  inline int32_t StrideHeight() const { return stride_height_; }

  inline DynamicallyQuantizedTransposeConvTester& StrideWidth(
      int32_t stride_width) {
    EXPECT_GT(stride_width, 0);
    stride_width_ = stride_width;
    return *this;
  }

  inline int32_t StrideWidth() const { return stride_width_; }
  inline DynamicallyQuantizedTransposeConvTester& DilationHeight(
      int32_t dilation_height) {
    EXPECT_GT(dilation_height, 0);
    dilation_height_ = dilation_height;
    return *this;
  }

  inline int32_t DilationHeight() const { return dilation_height_; }

  inline DynamicallyQuantizedTransposeConvTester& DilationWidth(
      int32_t dilation_width) {
    EXPECT_GT(dilation_width, 0);
    dilation_width_ = dilation_width;
    return *this;
  }

  inline int32_t DilationWidth() const { return dilation_width_; }

  inline DynamicallyQuantizedTransposeConvTester& SamePadding() {
    padding_ = ::tflite::Padding_SAME;
    return *this;
  }

  inline DynamicallyQuantizedTransposeConvTester& ValidPadding() {
    padding_ = ::tflite::Padding_VALID;
    return *this;
  }

  inline ::tflite::Padding Padding() const { return padding_; }

  inline int32_t InputWidth() const {
    return ComputeInputSize(OutputWidth(), KernelWidth(), StrideWidth());
  }

  inline int32_t InputHeight() const {
    return ComputeInputSize(OutputHeight(), KernelHeight(), StrideHeight());
  }

  inline DynamicallyQuantizedTransposeConvTester& WeightsCache(
      TfLiteXNNPackDelegateWeightsCache* weights_cache) {
    weights_cache_ = weights_cache;
    return *this;
  }

  void Test(TfLiteDelegate* delegate) const;

 private:
  int32_t ComputeInputSize(int32_t output_size, int32_t kernel_size,
                           int32_t stride) const {
    // Roughly follows TFLite's `ComputeOutSize`.
    switch (padding_) {
      case ::tflite::Padding_VALID:
        return (output_size + stride - kernel_size) / stride;
        break;
      case ::tflite::Padding_SAME:
        return (output_size + stride - 1) / stride;
        break;
      default:
        assert(false);
    }
  }

 private:
  std::vector<int8_t> GenerateKernelData() const;
  std::vector<float> GenerateBiasData() const;
  std::vector<float> GenerateKernelScaleData() const;
  std::vector<char> CreateTfLiteModel(
      const std::vector<int8_t>& filter_data,
      const std::vector<float>& bias_data,
      const std::vector<float>& kernel_scale) const;

  int32_t batch_size_ = 1;
  int32_t input_channels_ = 1;
  int32_t output_channels_ = 1;
  int32_t output_height_ = 1;
  int32_t output_width_ = 1;
  int32_t kernel_height_ = 1;
  int32_t kernel_width_ = 1;
  int32_t stride_height_ = 1;
  int32_t stride_width_ = 1;
  int32_t dilation_height_ = 1;
  int32_t dilation_width_ = 1;
  ::tflite::Padding padding_ = ::tflite::Padding_VALID;
  TfLiteXNNPackDelegateWeightsCache* weights_cache_ = nullptr;
};

}  // namespace xnnpack
}  // namespace tflite

#endif  // TENSORFLOW_LITE_DELEGATES_XNNPACK_DYNAMICALLY_QUANTIZED_TRANSPOSE_CONV_TESTER_H_
