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/*
* 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(AXIS)
/** Performs the Gather operation along the chosen axis
* @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=short
* @note Axis should be given as a preprocessor argument using -DAXIS=axis. e.g. -DAXIS=1
* @attention Output tensor depth should be given as a preprocessor argument using -DOUTPUT_DIM_Z=size. e.g. -DOUTPUT_DIM_Z=16
* @attention Input tensor depth should be given as a preprocessor argument using -DINPUT_DIM_Z=size. e.g. -DINPUT_DIM_Z=16
*
*
* @param[in] input_ptr Pointer to the source tensor. Supported data types: All
* @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 work item (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 work item (in bytes)
* @param[in] input_stride_z Stride of the source tensor in Y dimension (in bytes)
* @param[in] input_step_z input_stride_z * number of elements along Z processed per work item (in bytes)
* @param[in] input_stride_w Stride of the source tensor in Z dimension (in bytes)
* @param[in] input_step_w input_stride_w * number of elements along W processed per work item (in bytes)
* @param[in] input_offset_first_element_in_bytes Offset of the first element in the source tensor
* @param[in] indices_ptr Pointer to the indices vector. Supported data types: S32/U32.
* @param[in] indices_stride_x Stride of the indices vector in X dimension (in bytes)
* @param[in] indices_step_x input_stride_x * number of elements along X processed per work item (in bytes)
* @param[in] indices_offset_first_element_in_bytes Offset of the first element in the indices vector
* @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 work item (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 work item (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 work item (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 work item (in bytes)
* @param[in] output_offset_first_element_in_bytes Offset of the first element in the destination tensor
*/
__kernel void gather(
TENSOR4D_DECLARATION(input),
VECTOR_DECLARATION(indices),
TENSOR4D_DECLARATION(output))
{
const int px = get_global_id(0);
const int py = get_global_id(1);
const int pz = get_global_id(2) % OUTPUT_DIM_Z;
const int pw = get_global_id(2) / OUTPUT_DIM_Z;
const Tensor4D input = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input, INPUT_DIM_Z);
const Vector indices = CONVERT_TO_VECTOR_STRUCT_NO_STEP(indices);
Tensor4D output = CONVERT_TO_TENSOR4D_STRUCT(output, OUTPUT_DIM_Z);
#if AXIS == 0
const uint index = *(__global const uint *)vector_offset(&indices, px);
__global const uchar *input_addr = tensor4D_offset(&input, index, py, pz, pw);
#elif AXIS == 1
const uint index = *(__global const uint *)vector_offset(&indices, py);
__global const uchar *input_addr = tensor4D_offset(&input, px, index, pz, pw);
#elif AXIS == 2
const uint index = *(__global const uint *)vector_offset(&indices, pz);
__global const uchar *input_addr = tensor4D_offset(&input, px, py, index, pw);
#elif AXIS == 3
const uint index = *(__global const uint *)vector_offset(&indices, pw);
__global const uchar *input_addr = tensor4D_offset(&input, px, py, pz, index);
#endif //AXIS
*(__global DATA_TYPE *)output.ptr = *((__global const DATA_TYPE *)input_addr);
}
#endif //defined(DATA_TYPE) && defined(AXIS)
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