/***************************************************************************************************
 * Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 * SPDX-License-Identifier: BSD-3-Clause
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *
 * 1. Redistributions of source code must retain the above copyright notice, this
 * list of conditions and the following disclaimer.
 *
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 * this list of conditions and the following disclaimer in the documentation
 * and/or other materials provided with the distribution.
 *
 * 3. Neither the name of the copyright holder nor the names of its
 * contributors may be used to endorse or promote products derived from
 * this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
 * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
 * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
 * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
 * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
 * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
 * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 *
 **************************************************************************************************/
#pragma once

#include <stdexcept>
#include "cutlass/cutlass.h"
#include "cutlass/util/reference/device/kernel/tensor_foreach.h"

namespace cutlass  {
namespace reference {
namespace device {

///////////////////////////////////////////////////////////////////////////////////////////////////

/// Launches a kernel calling a functor for each element in a tensor's index space.
template <typename Func, int Rank, typename Params>
struct TensorForEach {

  /// Constructor performs the operation.
  TensorForEach(Coord<Rank> size, Params params = Params(), int grid_size = 0, int block_size = 0) {

    if (!grid_size || !block_size) {

      // if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API
      cudaError_t result = cudaOccupancyMaxPotentialBlockSize(
        &grid_size,
        &block_size,
        reinterpret_cast<void const *>(kernel::TensorForEach<Func, Rank, Params>));

      if (result != cudaSuccess) {
        throw std::runtime_error("Failed to query occupancy.");
      }

      // Limit block size. This has the effect of increasing the number of items processed by a
      // single thread and reduces the impact of initialization overhead.
      block_size = (block_size < 128 ? block_size : 128);
    }

    dim3 grid(grid_size, 1, 1);
    dim3 block(block_size, 1, 1);

    kernel::TensorForEach<Func, Rank, Params><<< grid, block >>>(size, params);
  }
};

///////////////////////////////////////////////////////////////////////////////////////////////////

/// Launches a kernel calling a functor for each element along a tensor's diagonal
template <typename Func, int Rank, typename Params>
struct TensorDiagonalForEach {

  /// Constructor performs the operation
  TensorDiagonalForEach(Coord<Rank> size, Params params = Params(), int start = 0, int end = -1, int block_size = 128) { 

    if (end < 0) {
      end = size.min();
    }

    dim3 block(block_size, 1, 1);
    dim3 grid((end - start + block_size - 1) / block_size, 1, 1);

    kernel::TensorDiagonalForEach<Func, Rank, Params><<< grid, block >>>(size, params, start, end);
  }
};


///////////////////////////////////////////////////////////////////////////////////////////////////

template <typename Element, typename Func>
struct BlockForEach {

  /// Constructor performs the operation.
  BlockForEach(
    Element *ptr, 
    size_t capacity,
    typename Func::Params params = typename Func::Params(),
    int grid_size = 0, 
    int block_size = 0) {

    if (!grid_size || !block_size) {

      // if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API
      cudaError_t result = cudaOccupancyMaxPotentialBlockSize(
        &grid_size,
        &block_size,
        reinterpret_cast<void const *>(kernel::BlockForEach<Element, Func>));

      if (result != cudaSuccess) {
        throw std::runtime_error("Failed to query occupancy.");
      }

      // Limit block size. This has the effect of increasing the number of items processed by a
      // single thread and reduces the impact of initialization overhead.
      block_size = (block_size < 128 ? block_size : 128);
    }

    dim3 grid(grid_size, 1, 1);
    dim3 block(block_size, 1, 1);

    kernel::BlockForEach<Element, Func><<< grid, block >>>(ptr, capacity, params);
  }
};

///////////////////////////////////////////////////////////////////////////////////////////////////

} // namespace device
} // namespace reference
} // namesace cutlass
