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/*
 * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
 * Copyright (c) 2016, 2017 ARM Limited.
 *
 * 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.
 */
#include "helpers.h"

#if defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(BATCH_IN) && defined(HEIGHT_IN) && defined(WIDTH_IN) && defined(ZERO_VALUE)
/** Perform space to batch with input of 4D and NCHW format
 *
 * @attention Data type can be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float
 * @attention Output tensor depth should be given as a preprocessor argument using -DDEPTH_OUT=size. e.g. -DDEPTH_OUT=16
 * @attention Input tensor batch should be given as a preprocessor argument using -DBATCH_IN=size. e.g. -DBATCH_IN=16
 * @attention Input tensor height should be given as a preprocessor argument using -DHEIGHT_IN=size. e.g. -DHEIGHT_IN=16
 * @attention Input tensor width should be given as a preprocessor argument using -DHEIGHT_IN=size. e.g. -DWIDTH_IN=16
 * @attention The value to be set by pad value using -DZERO_VALUE=value. e.g. -DZERO_VALUE=0
 *
 * @param[in]  input_ptr                                   Pointer to the source tensor. Supported data types: U8/S8/U16/S16/F16/U32/S32/F32
 * @param[in]  input_stride_x                              Stride of the source tensor 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 tensor 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_stride_w                              Stride of the destination tensor in W dimension (in bytes)
 * @param[in]  input_step_w                                input_stride_w * number of elements along W processed per workitem(in bytes)
 * @param[in]  input_offset_first_element_in_bytes         The offset of the first element in the source tensor
 * @param[out] output_ptr                                  Pointer to the destination tensor. Supported data types: same as @p input_ptr
 * @param[in]  output_stride_x                             Stride of the destination tensor 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 tensor 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 destination 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 destination 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 tensor
 * @param[in]  block_size_ptr                              Pointer to the source tensor. Supported data types: S32
 * @param[in]  block_size_stride_x                         Stride of the source tensor in X dimension (in bytes)
 * @param[in]  block_size_step_x                           block_size_stride_x * number of elements along X processed per workitem(in  bytes)
 * @param[in]  block_size_offset_first_element_in_bytes    The offset of the first element in the destination tensor
 * @param[in]  padding_size_ptr                            Pointer to the source tensor. Supported data types: S32
 * @param[in]  padding_size_stride_x                       Stride of the source tensor in X dimension (in bytes)
 * @param[in]  padding_size_step_x                         padding_size_stride_x * number of elements along X processed per workitem(in  bytes)
 * @param[in]  padding_size_stride_y                       Stride of the source tensor in Y dimension (in bytes)
 * @param[in]  padding_size_step_y                         padding_size_stride_y * number of elements along Y processed per workitem(in  bytes)
 * @param[in]  padding_size_offset_first_element_in_bytes  The offset of the first element in the destination tensor
 */
__kernel void space_to_batch_4d_nchw(TENSOR4D_DECLARATION(input),
                                     TENSOR4D_DECLARATION(output),
                                     VECTOR_DECLARATION(block_size),
                                     IMAGE_DECLARATION(padding_size))
{
    Tensor4D in  = CONVERT_TO_TENSOR4D_STRUCT(input, 0);
    Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, DEPTH_OUT);

    int block_size_x = *((__global int *)(block_size_ptr));
    int block_size_y = *((__global int *)(block_size_ptr + block_size_stride_x));
    int shift_x = (get_global_id(2) / DEPTH_OUT / BATCH_IN) % block_size_x;
    int shift_y = (get_global_id(2) / DEPTH_OUT / BATCH_IN) / block_size_x;

    int in_index[4] = {0, };
    in_index[0] = get_global_id(0) * block_size_x + shift_x - *((__global int *)(padding_size_ptr));
    in_index[1] = get_global_id(1) * block_size_y + shift_y - *((__global int *)(padding_size_ptr + padding_size_stride_y));
    in_index[2] = get_global_id(2) % DEPTH_OUT;
    in_index[3] = (get_global_id(2) / DEPTH_OUT) % BATCH_IN;

    if (in_index[0] < 0 || in_index[0] >= WIDTH_IN || in_index[1] < 0 || in_index[1] >= HEIGHT_IN)
    {
        *((__global DATA_TYPE *)out.ptr) = (DATA_TYPE)ZERO_VALUE;
    }
    else
    {
        *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, in_index[0], in_index[1], in_index[2], in_index[3]));
    }
}
#endif // defined(DATA_TYPE) && defined(DEPTH_OUT) && defined(BATCH_IN) && defined(HEIGHT_IN) && defined(WIDTH_IN) && defined(ZERO_VALUE)

#if defined(DATA_TYPE) && defined(HEIGHT_OUT) && defined(BATCH_IN) && defined(HEIGHT_IN) && defined(WIDTH_IN) && defined(ZERO_VALUE) && defined(VEC_SIZE)
/** Perform space to batch with input of 4D and NHWC format
 *
 * @attention Data type can be passed using the -DDATA_TYPE compile flag, e.g. -DDATA_TYPE=float
 * @attention Output tensor depth should be given as a preprocessor argument using -DHEIGHT_OUT=size. e.g. -DHEIGHT_OUT=16
 * @attention Input tensor batch should be given as a preprocessor argument using -DBATCH_IN=size. e.g. -DBATCH_IN=16
 * @attention Input tensor height should be given as a preprocessor argument using -DHEIGHT_IN=size. e.g. -DHEIGHT_IN=16
 * @attention Input tensor width should be given as a preprocessor argument using -DHEIGHT_IN=size. e.g. -DWIDTH_IN=16
 * @attention The value to be set by pad value using -DZERO_VALUE=value. e.g. -DZERO_VALUE=0
 * @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16
 *
 * @param[in]  input_ptr                                   Pointer to the source tensor. Supported data types: U8/S8/U16/S16/F16/U32/S32/F32
 * @param[in]  input_stride_x                              Stride of the source tensor 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 tensor 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_stride_w                              Stride of the destination tensor in W dimension (in bytes)
 * @param[in]  input_step_w                                input_stride_w * number of elements along W processed per workitem(in bytes)
 * @param[in]  input_offset_first_element_in_bytes         The offset of the first element in the source tensor
 * @param[out] output_ptr                                  Pointer to the destination tensor. Supported data types: same as @p input_ptr
 * @param[in]  output_stride_x                             Stride of the destination tensor 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 tensor 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 destination 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 destination 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 tensor
 * @param[in]  block_size_ptr                              Pointer to the source tensor. Supported data types: S32
 * @param[in]  block_size_stride_x                         Stride of the source tensor in X dimension (in bytes)
 * @param[in]  block_size_step_x                           block_size_stride_x * number of elements along X processed per workitem(in  bytes)
 * @param[in]  block_size_offset_first_element_in_bytes    The offset of the first element in the destination tensor
 * @param[in]  padding_size_ptr                            Pointer to the source tensor. Supported data types: S32
 * @param[in]  padding_size_stride_x                       Stride of the source tensor in X dimension (in bytes)
 * @param[in]  padding_size_step_x                         padding_size_stride_x * number of elements along X processed per workitem(in  bytes)
 * @param[in]  padding_size_stride_y                       Stride of the source tensor in Y dimension (in bytes)
 * @param[in]  padding_size_step_y                         padding_size_stride_y * number of elements along Y processed per workitem(in  bytes)
 * @param[in]  padding_size_offset_first_element_in_bytes  The offset of the first element in the destination tensor
 */
__kernel void space_to_batch_4d_nhwc(TENSOR4D_DECLARATION(input),
                                     TENSOR4D_DECLARATION(output),
                                     VECTOR_DECLARATION(block_size),
                                     IMAGE_DECLARATION(padding_size))
{
    Tensor4D in  = CONVERT_TO_TENSOR4D_STRUCT(input, 0);
    Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT(output, HEIGHT_OUT);

    int block_size_x = *((__global int *)(block_size_ptr));
    int block_size_y = *((__global int *)(block_size_ptr + block_size_stride_x));
    int shift_x = (get_global_id(2) / HEIGHT_OUT / BATCH_IN) % block_size_x;
    int shift_y = (get_global_id(2) / HEIGHT_OUT / BATCH_IN) / block_size_x;

    int in_index[4] = {0, };
    in_index[0] = get_global_id(0) * VEC_SIZE;
    in_index[1] = get_global_id(1) * block_size_x + shift_x - *((__global int *)(padding_size_ptr));
    in_index[2] = get_global_id(2) % HEIGHT_OUT * block_size_y + shift_y - *((__global int *)(padding_size_ptr + padding_size_stride_y));
    in_index[3] = (get_global_id(2) / HEIGHT_OUT) % BATCH_IN;

    if (in_index[1] < 0 || in_index[1] >= WIDTH_IN || in_index[2] < 0 || in_index[2] >= HEIGHT_IN)
    {
        VSTORE(VEC_SIZE)((VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))ZERO_VALUE, 0, (__global DATA_TYPE *)out.ptr);
    }
    else
    {
        VSTORE(VEC_SIZE)(CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, in_index[0], in_index[1], in_index[2], in_index[3])),
                                 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)),
                         0, (__global DATA_TYPE *)out.ptr);
    }
}

#endif // defined(DATA_TYPE) && defined(HEIGHT_OUT) && defined(BATCH_IN) && defined(HEIGHT_IN) && defined(WIDTH_IN) && defined(ZERO_VALUE) && defined(VEC_SIZE)