| /* |
| * Copyright (c) 2018-2021, 2024 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(BATCH_SIZE) && defined(DATA_TYPE) && defined(WIDTH_IN) && defined(HEIGHT_IN) |
| /** Calculate the space to batch conversion. |
| * |
| * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float |
| * @note The block shape tensor rank must be passed at compile time using -DBLOCK_SHAPE_DIM. e.g. -DBLOCK_SHAPE_DIM=2 |
| * |
| * @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 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 first source image |
| * @param[in] paddings_ptr Pointer to the second source image. Supported data types: S32 |
| * @param[in] paddings_stride_x Stride of the paddinds tensor in X dimension (in bytes) |
| * @param[in] paddings_step_x paddings_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] paddings_stride_y Stride of the paddinds tensor in Y dimension (in bytes) |
| * @param[in] paddings_step_y paddings_stride_y * number of elements along Y processed per workitem(in bytes) |
| * @param[in] paddingse_offset_first_element_in_bytes The offset of the first element in the second source image |
| * @param[in] block_shape_ptr Pointer to the block shape tensor. Supported data types: S32 |
| * @param[in] block_shape_stride_x Stride of the block shape tensor in X dimension (in bytes) |
| * @param[in] block_shape_step_x block_shape_stride_x * number of elements along X processed per workitem(in bytes) |
| * @param[in] block_shape_offset_first_element_in_bytes The offset of the first element in the block shapetensor |
| * @param[in] batch_id The output tensor batch id |
| * @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_offset_first_element_in_bytes The offset of the first element in the destination image |
| */ |
| __kernel void space_to_batch_nchw( |
| TENSOR4D_DECLARATION(input), |
| IMAGE_DECLARATION(paddings), |
| VECTOR_DECLARATION(block_shape), |
| const int batch_id, |
| TENSOR3D_DECLARATION(output)) |
| { |
| Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input); |
| Image pad = CONVERT_TO_IMAGE_STRUCT_NO_STEP(paddings); |
| Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape); |
| Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); |
| |
| const int pad_left_x = *((__global int *)offset(&pad, 0, 0)); |
| const int pad_right_x = *((__global int *)offset(&pad, 1, 0)); |
| const int pad_left_y = *((__global int *)offset(&pad, 0, 1)); |
| const int pad_right_y = *((__global int *)offset(&pad, 1, 1)); |
| |
| int block_x = *((__global int *)vector_offset(&block, 0)); |
| int block_y = *((__global int *)vector_offset(&block, 1)); |
| |
| const int out_x = get_global_id(0); |
| const int out_y = get_global_id(1); |
| const int z = get_global_id(2); |
| |
| const int pos_x = out_x * block_x + ((batch_id / BATCH_IN) % block_x); |
| const int pos_y = out_y * block_y + ((batch_id / BATCH_IN) / block_x); |
| |
| if(((pos_y >= pad_left_y) && (pos_y < pad_left_y + HEIGHT_IN) && (pos_x >= pad_left_x) && (pos_x < pad_left_x + WIDTH_IN))) |
| { |
| const int w = batch_id % BATCH_IN; |
| const int in_x = pos_x - pad_left_x; |
| const int in_y = pos_y - pad_left_y; |
| |
| *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, in_x, in_y, z, w)); |
| } |
| } |
| |
| #endif // defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(WIDTH_IN) && defined(HEIGHT_IN) |
| |
| #if defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) && defined(PAD_LEFT_X) && defined(PAD_RIGHT_X) && defined(PAD_LEFT_Y) && defined(PAD_RIGHT_Y) && defined(WIDTH_IN) && defined(HEIGHT_IN) |
| /** Calculate the space to batch conversion. |
| * |
| * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float |
| * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 |
| * @note The block shape x must be passed at compile time using -DBLOCK_SHAPE_X. e.g. -DBLOCK_SHAPE_X=2 |
| * @note The block shape y must be passed at compile time using -DBLOCK_SHAPE_Y. e.g. -DBLOCK_SHAPE_Y=2 |
| * @note The starting pad value of x must be passed at compile time using -DPAD_LEFT_X. e.g. -DPAD_LEFT_X=2 |
| * @note The ending pad value of x must be passed at compile time using -DPAD_RIGHT_X. e.g. -DPAD_RIGHT_X=2 |
| * @note The starting pad value of y must be passed at compile time using -DPAD_LEFT_Y. e.g. -DPAD_LEFT_Y=2 |
| * @note The ending pad value of y must be passed at compile time using -DPAD_RIGHT_Y. e.g. -DPAD_RIGHT_X=2 |
| * |
| * @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 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 first source image |
| * @param[in] batch_id The output tensor batch id |
| * @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 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_offset_first_element_in_bytes The offset of the first element in the destination image |
| */ |
| __kernel void space_to_batch_static_nchw( |
| TENSOR4D_DECLARATION(input), |
| const int batch_id, |
| TENSOR3D_DECLARATION(output)) |
| { |
| Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input); |
| Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); |
| |
| int block_x = BLOCK_SHAPE_X; |
| int block_y = BLOCK_SHAPE_Y; |
| |
| const int out_x = get_global_id(0); |
| const int out_y = get_global_id(1); |
| const int z = get_global_id(2); |
| |
| const int pos_x = out_x * block_x + ((batch_id / BATCH_IN) % block_x); |
| const int pos_y = out_y * block_y + ((batch_id / BATCH_IN) / block_x); |
| |
| if(pos_y >= PAD_LEFT_Y && pos_y < PAD_LEFT_Y + HEIGHT_IN && pos_x >= PAD_LEFT_X && pos_x < PAD_LEFT_X + WIDTH_IN) |
| { |
| const int w = batch_id % BATCH_IN; |
| const int in_x = pos_x - PAD_LEFT_X; |
| const int in_y = pos_y - PAD_LEFT_Y; |
| |
| *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, in_x, in_y, z, w)); |
| } |
| } |
| #endif // defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(BLOCK_SHAPE_X) && defined(BLOCK_SHAPE_Y) && defined(PAD_LEFT_X) && defined(PAD_RIGHT_X) && defined(PAD_LEFT_Y) && defined(PAD_RIGHT_Y) && defined(WIDTH_IN) && defined(HEIGHT_IN) |