/* 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_UTIL_H_
#define TENSORFLOW_LITE_DELEGATES_GPU_CL_UTIL_H_

#include <string>

#include "absl/types/span.h"
#include "tensorflow/lite/delegates/gpu/cl/opencl_wrapper.h"
#include "tensorflow/lite/delegates/gpu/common/data_type.h"
#include "tensorflow/lite/delegates/gpu/common/status.h"
#include "tensorflow/lite/delegates/gpu/common/tensor.h"
#include "tensorflow/lite/delegates/gpu/common/util.h"

namespace tflite {
namespace gpu {
namespace cl {

std::string CLErrorCodeToString(cl_int error_code);

int ChannelTypeToSizeInBytes(cl_channel_type type);

bool OpenCLSupported();

template <DataType S, typename T>
void CopyLinearFLT4(const tflite::gpu::Tensor<Linear, S>& src,
                    absl::Span<T> dst) {
  const int dst_depth = dst.size();
  for (int d = 0; d < dst_depth; ++d) {
    T val;
    for (int i = 0; i < 4; ++i) {
      const int dst_ch = d * 4 + i;
      val[i] = dst_ch >= src.shape.v ? 0.0f : src.data[dst_ch];
    }
    dst[d] = val;
  }
}

absl::Status CreateCLBuffer(cl_context context, int size_in_bytes,
                            bool read_only, void* data, cl_mem* result);

cl_channel_type DataTypeToChannelType(DataType type, bool normalized = false);
absl::Status CreateRGBAImage2D(cl_context context, int width, int height,
                               cl_channel_type channel_type, void* data,
                               cl_mem* result);
}  // namespace cl
}  // namespace gpu
}  // namespace tflite

#endif  // TENSORFLOW_LITE_DELEGATES_GPU_CL_UTIL_H_
