/*
 * Copyright (c) 2018-2020 Arm Limited.
 *
 * SPDX-License-Identifier: MIT
 *
 * Permission is hereby granted, free of charge, to any person obtaining a copy
 * of this software and associated documentation files (the "Software"), to
 * deal in the Software without restriction, including without limitation the
 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
 * sell copies of the Software, and to permit persons to whom the Software is
 * furnished to do so, subject to the following conditions:
 *
 * The above copyright notice and this permission notice shall be included in all
 * copies or substantial portions of the Software.
 *
 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
 * SOFTWARE.
 */
#include "helpers.h"

#if defined(DATA_TYPE) && defined(DEPTH_IN) && defined(P1) && defined(P2) && defined(P3) && defined(P4)
/**Perform a permute operation on an input tensor of Shape DCHW.
 *
 * @attention Data type can be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float
 * @attention Input tensor depth should be given as a preprocessor argument using -DDEPTH_IN=size. e.g. -DDEPTH_IN=16
 * @attention Permutation vector is passed as a preprocessor arguement using -DP1, -DP2, -DP3 and -DP4=int, e.g. -DP1=2, -DP2=1, -DP3=0 and -DP4=3.
 *
 * @param[in]  input_ptr                            Pointer to the source image. Supported data types: All
 * @param[in]  input_stride_x                       Stride of the source image in X dimension (in bytes)
 * @param[in]  input_step_x                         input_stride_x * number of elements along X processed per workitem(in bytes)
 * @param[in]  input_stride_y                       Stride of the source image in Y dimension (in bytes)
 * @param[in]  input_step_y                         input_stride_y * number of elements along Y processed per workitem(in bytes)
 * @param[in]  input_stride_z                       Stride of the source tensor in Z dimension (in bytes)
 * @param[in]  input_step_z                         input_stride_z * number of elements along Z processed per workitem(in bytes)
 * @param[in]  input_offset_first_element_in_bytes  The offset of the first element in the source image
 * @param[out] output_ptr                           Pointer to the destination image. Supported data types: same as @p input_ptr
 * @param[in]  output_stride_x                      Stride of the destination image in X dimension (in bytes)
 * @param[in]  output_step_x                        output_stride_x * number of elements along X processed per workitem(in bytes)
 * @param[in]  output_stride_y                      Stride of the destination image in Y dimension (in bytes)
 * @param[in]  output_step_y                        output_stride_y * number of elements along Y processed per workitem(in bytes)
 * @param[in]  output_stride_z                      Stride of the source tensor in Z dimension (in bytes)
 * @param[in]  output_step_z                        output_stride_z * number of elements along Z processed per workitem(in bytes)
 * @param[in]  output_stride_w                      Stride of the source tensor in W dimension (in bytes)
 * @param[in]  output_step_w                        output_stride_w * number of elements along W processed per workitem(in bytes)
 * @param[in]  output_offset_first_element_in_bytes The offset of the first element in the destination image
 */
__kernel void permute(TENSOR4D_DECLARATION(input),
                      TENSOR4D_DECLARATION(output))

{
    Tensor4D in  = CONVERT_TO_TENSOR4D_STRUCT(input, DEPTH_IN);
    Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0);

    int out_index[4] = { 0 };
    int in_index[4]  = { 0 };

    in_index[0] = get_global_id(0);            // W
    in_index[1] = get_global_id(1);            // H
    in_index[2] = get_global_id(2) % DEPTH_IN; // C
    in_index[3] = get_global_id(2) / DEPTH_IN; // B

    out_index[0] = in_index[P1];
    out_index[1] = in_index[P2];
    out_index[2] = in_index[P3];
    out_index[3] = in_index[P4];

    *((__global DATA_TYPE *)tensor4D_offset(&out, out_index[0], out_index[1], out_index[2], out_index[3])) = *((__global DATA_TYPE *)in.ptr);
}
#endif // defined(DATA_TYPE) && defined(DEPTH_IN) && defined(P1) && defined(P2) && defined(P3) && defined(P4)