1/* 2 * Copyright (c) 2019-2021 Arm Limited. 3 * 4 * SPDX-License-Identifier: MIT 5 * 6 * Permission is hereby granted, free of charge, to any person obtaining a copy 7 * of this software and associated documentation files (the "Software"), to 8 * deal in the Software without restriction, including without limitation the 9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or 10 * sell copies of the Software, and to permit persons to whom the Software is 11 * furnished to do so, subject to the following conditions: 12 * 13 * The above copyright notice and this permission notice shall be included in all 14 * copies or substantial portions of the Software. 15 * 16 * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 * SOFTWARE. 23 */ 24#include "helpers.h" 25 26#if defined(DATA_TYPE) && defined(BLOCK_SHAPE) && defined(CHANNEL_SIZE) 27/** Depth to space transformation. (NHWC) 28 * 29 * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float 30 * @note The input tensor depth size must be passed at compile time using -DCHANNEL_SIZE. e.g. -DCHANNEL_SIZE=2 31 * @note The block shape must be passed at compile time using -DBLOCK_SHAPE. e.g. -DBLOCK_SHAPE=2 32 * 33 * @param[in] input_ptr Pointer to the source tensor. Supported data types: All. 34 * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) 35 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) 36 * @param[in] input_stride_y Stride of the source tensor in Y dimension (in bytes) 37 * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) 38 * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) 39 * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) 40 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source tensor 41 * @param[in] batch_id The input tensor batch id 42 * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr 43 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) 44 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) 45 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) 46 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) 47 * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes) 48 * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) 49 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor 50 */ 51__kernel void depth_to_space_nhwc( 52 TENSOR3D_DECLARATION(input), 53 const int batch_id, 54 TENSOR4D_DECLARATION(output)) 55{ 56 Tensor3D in = CONVERT_TO_TENSOR3D_STRUCT(input); 57 Tensor4D out = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(output, 0); 58 59 const int r = (CHANNEL_SIZE / (BLOCK_SHAPE * BLOCK_SHAPE)); 60 const int x = get_global_id(1); 61 const int y = get_global_id(2); 62 const int z = get_global_id(0) % r; 63 64 const int out_x = x * BLOCK_SHAPE + (get_global_id(0) / r) % BLOCK_SHAPE; 65 const int out_y = y * BLOCK_SHAPE + (get_global_id(0) / r) / BLOCK_SHAPE; 66 67 *((__global DATA_TYPE *)tensor4D_offset(&out, z, out_x, out_y, batch_id)) = *((__global DATA_TYPE *)in.ptr); 68} 69#endif // defined(DATA_TYPE) && defined(BLOCK_SHAPE) && defined(CHANNEL_SIZE)