/* Copyright 2019 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_GPU_CL_KERNELS_CONV_BUFFER_H_
#define TENSORFLOW_LITE_DELEGATES_GPU_CL_KERNELS_CONV_BUFFER_H_

#include <vector>

#include "tensorflow/lite/delegates/gpu/cl/buffer.h"
#include "tensorflow/lite/delegates/gpu/cl/kernels/gpu_operation.h"
#include "tensorflow/lite/delegates/gpu/cl/kernels/util.h"
#include "tensorflow/lite/delegates/gpu/cl/linear_storage.h"
#include "tensorflow/lite/delegates/gpu/cl/tensor.h"
#include "tensorflow/lite/delegates/gpu/cl/util.h"
#include "tensorflow/lite/delegates/gpu/common/data_type.h"
#include "tensorflow/lite/delegates/gpu/common/operations.h"
#include "tensorflow/lite/delegates/gpu/common/shape.h"
#include "tensorflow/lite/delegates/gpu/common/status.h"
#include "tensorflow/lite/delegates/gpu/common/tensor.h"
#include "tensorflow/lite/delegates/gpu/common/types.h"

namespace tflite {
namespace gpu {
namespace cl {

class ConvBuffer : public GPUOperation {
 public:
  ConvBuffer() = default;
  Status AddToQueue(CLCommandQueue* queue) override;
  Status Tune(const TuningParameters& params) override;

  Status Compile(const CreationContext& creation_context) override;

  // Move only
  ConvBuffer(ConvBuffer&& operation);
  ConvBuffer& operator=(ConvBuffer&& operation);
  ConvBuffer(const ConvBuffer&) = delete;
  ConvBuffer& operator=(const ConvBuffer&) = delete;

 private:
  friend Status CreateConvBuffer(const CreationContext& creation_context,
                                 const OperationDef& definition,
                                 const Convolution2DAttributes& attr,
                                 ConvBuffer* result);
  ConvBuffer(const OperationDef& definition,
             const Convolution2DAttributes& attr, int x_elements,
             int y_elements);
  template <DataType T>
  Status UploadWeights(const ::tflite::gpu::Tensor<OHWI, T>& weights,
                       CLContext* context);

  Status BindArguments();
  int3 GetGridSize() const;

  Buffer weights_;
  LinearStorage biases_;

  int2 kernel_size_;
  int2 stride_;
  int2 padding_;
  int2 dilation_;
  int x_elements_;
  int y_elements_;

  CLKernel kernel_;
  int3 work_group_size_;
};

template <DataType T>
Status ConvBuffer::UploadWeights(const ::tflite::gpu::Tensor<OHWI, T>& weights,
                                 CLContext* context) {
  const int dst_depth = IntegralDivideRoundUp(weights.shape.o, 4);
  const int src_depth = IntegralDivideRoundUp(weights.shape.i, 4);

  const int float4_size = definition_.precision == CalculationsPrecision::F32
                              ? sizeof(float4)
                              : sizeof(half4);

  const int elements_count =
      weights.shape.h * weights.shape.w * src_depth * dst_depth * 4;

  if (definition_.GetDataType() == DataType::FLOAT32) {
    std::vector<float4> gpu_data(elements_count);
    RearrangeWeightsToOHWI4I4O(weights, absl::MakeSpan(gpu_data));
    return CreateReadOnlyBuffer(float4_size * elements_count, gpu_data.data(),
                                context, &weights_);
  } else {
    std::vector<half4> gpu_data(elements_count);
    RearrangeWeightsToOHWI4I4O(weights, absl::MakeSpan(gpu_data));
    return CreateReadOnlyBuffer(float4_size * elements_count, gpu_data.data(),
                                context, &weights_);
  }
}

Status CreateConvBuffer(const CreationContext& creation_context,
                        const OperationDef& definition,
                        const Convolution2DAttributes& attr,
                        ConvBuffer* result);

}  // namespace cl
}  // namespace gpu
}  // namespace tflite

#endif  // TENSORFLOW_LITE_DELEGATES_GPU_CL_KERNELS_CONV_BUFFER_H_
