Adnan AlSinan | 7075fe2 | 2021-07-05 13:12:52 +0100 | [diff] [blame] | 1 | /* |
Viet-Hoa Do | 6829e02 | 2024-01-16 16:23:24 +0000 | [diff] [blame^] | 2 | * Copyright (c) 2018-2021, 2024 Arm Limited. |
Adnan AlSinan | 7075fe2 | 2021-07-05 13:12:52 +0100 | [diff] [blame] | 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(BATCH_SIZE) && defined(DATA_TYPE) && defined(WIDTH_IN) && defined(HEIGHT_IN) |
| 27 | /** Calculate the space to batch conversion. (NHWC) |
| 28 | * |
| 29 | * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float |
| 30 | * @note The block shape tensor rank must be passed at compile time using -DBLOCK_SHAPE_DIM. e.g. -DBLOCK_SHAPE_DIM=2 |
| 31 | * |
| 32 | * @param[in] input_ptr Pointer to the source tensor. Supported data types: All |
| 33 | * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) |
| 34 | * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) |
| 35 | * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes) |
| 36 | * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) |
| 37 | * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 38 | * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) |
| 39 | * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source image |
| 40 | * @param[in] paddings_ptr Pointer to the second source image. Supported data types: S32 |
| 41 | * @param[in] paddings_stride_x Stride of the paddinds tensor in X dimension (in bytes) |
| 42 | * @param[in] paddings_step_x paddings_stride_x * number of elements along X processed per workitem(in bytes) |
| 43 | * @param[in] paddings_stride_y Stride of the paddinds tensor in Y dimension (in bytes) |
| 44 | * @param[in] paddings_step_y paddings_stride_y * number of elements along Y processed per workitem(in bytes) |
| 45 | * @param[in] paddingse_offset_first_element_in_bytes The offset of the first element in the second source image |
| 46 | * @param[in] block_shape_ptr Pointer to the block shape tensor. Supported data types: S32 |
| 47 | * @param[in] block_shape_stride_x Stride of the block shape tensor in X dimension (in bytes) |
| 48 | * @param[in] block_shape_step_x block_shape_stride_x * number of elements along X processed per workitem(in bytes) |
| 49 | * @param[in] block_shape_offset_first_element_in_bytes The offset of the first element in the block shapetensor |
| 50 | * @param[in] batch_id The output tensor batch id |
| 51 | * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr |
| 52 | * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 53 | * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) |
| 54 | * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 55 | * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) |
| 56 | * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| 57 | * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) |
| 58 | * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image |
| 59 | */ |
| 60 | __kernel void space_to_batch_nhwc( |
| 61 | TENSOR4D_DECLARATION(input), |
| 62 | IMAGE_DECLARATION(paddings), |
| 63 | VECTOR_DECLARATION(block_shape), |
| 64 | const int batch_id, |
| 65 | TENSOR3D_DECLARATION(output)) |
| 66 | { |
Viet-Hoa Do | 6829e02 | 2024-01-16 16:23:24 +0000 | [diff] [blame^] | 67 | Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input); |
Adnan AlSinan | 7075fe2 | 2021-07-05 13:12:52 +0100 | [diff] [blame] | 68 | Image pad = CONVERT_TO_IMAGE_STRUCT_NO_STEP(paddings); |
| 69 | Vector block = CONVERT_TO_VECTOR_STRUCT_NO_STEP(block_shape); |
| 70 | Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); |
| 71 | |
| 72 | const int pad_left_x = *((__global int *)offset(&pad, 0, 0)); |
| 73 | const int pad_right_x = *((__global int *)offset(&pad, 1, 0)); |
| 74 | const int pad_left_y = *((__global int *)offset(&pad, 0, 1)); |
| 75 | const int pad_right_y = *((__global int *)offset(&pad, 1, 1)); |
| 76 | |
| 77 | int block_x = *((__global int *)vector_offset(&block, 0)); |
| 78 | int block_y = *((__global int *)vector_offset(&block, 1)); |
| 79 | |
| 80 | const int out_x = get_global_id(1); |
| 81 | const int out_y = get_global_id(2); |
| 82 | const int z = get_global_id(0); |
| 83 | |
| 84 | const int pos_x = out_x * block_x + ((batch_id / BATCH_IN) % block_x); |
| 85 | const int pos_y = out_y * block_y + ((batch_id / BATCH_IN) / block_x); |
| 86 | |
| 87 | 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))) |
| 88 | { |
| 89 | const int w = batch_id % BATCH_IN; |
| 90 | const int in_x = pos_x - pad_left_x; |
| 91 | const int in_y = pos_y - pad_left_y; |
| 92 | |
| 93 | *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, z, in_x, in_y, w)); |
| 94 | } |
| 95 | } |
| 96 | #endif // defined(BATCH_SIZE) && defined(DATA_TYPE) && defined(WIDTH_IN) && defined(HEIGHT_IN) |
| 97 | |
| 98 | #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) |
| 99 | /** Calculate the space to batch conversion. (NHWC) |
| 100 | * |
| 101 | * @note Datatype should be given as a preprocessor argument using -DDATA_TYPE=type. e.g. -DDATA_TYPE=float |
| 102 | * @note The input tensor batch size must be passed at compile time using -DBATCH_SIZE. e.g. -DBATCH_SIZE=2 |
| 103 | * @note The block shape x must be passed at compile time using -DBLOCK_SHAPE_X. e.g. -DBLOCK_SHAPE_X=2 |
| 104 | * @note The block shape y must be passed at compile time using -DBLOCK_SHAPE_Y. e.g. -DBLOCK_SHAPE_Y=2 |
| 105 | * @note The starting pad value of x must be passed at compile time using -DPAD_LEFT_X. e.g. -DPAD_LEFT_X=2 |
| 106 | * @note The ending pad value of x must be passed at compile time using -DPAD_RIGHT_X. e.g. -DPAD_RIGHT_X=2 |
| 107 | * @note The starting pad value of y must be passed at compile time using -DPAD_LEFT_Y. e.g. -DPAD_LEFT_Y=2 |
| 108 | * @note The ending pad value of y must be passed at compile time using -DPAD_RIGHT_Y. e.g. -DPAD_RIGHT_X=2 |
| 109 | * |
| 110 | * @param[in] input_ptr Pointer to the source tensor. Supported data types: All |
| 111 | * @param[in] input_stride_x Stride of the source tensor in X dimension (in bytes) |
| 112 | * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes) |
| 113 | * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes) |
| 114 | * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes) |
| 115 | * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 116 | * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes) |
| 117 | * @param[in] input_offset_first_element_in_bytes The offset of the first element in the first source image |
| 118 | * @param[in] batch_id The output tensor batch id |
| 119 | * @param[out] output_ptr Pointer to the destination tensor. Supported data types: same as @p input_ptr |
| 120 | * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 121 | * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes) |
| 122 | * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 123 | * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes) |
| 124 | * @param[in] output_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 125 | * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes) |
| 126 | * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image |
| 127 | */ |
| 128 | __kernel void space_to_batch_static_nhwc( |
| 129 | TENSOR4D_DECLARATION(input), |
| 130 | const int batch_id, |
| 131 | TENSOR3D_DECLARATION(output)) |
| 132 | { |
Viet-Hoa Do | 6829e02 | 2024-01-16 16:23:24 +0000 | [diff] [blame^] | 133 | Tensor4D in = CONVERT_TO_TENSOR4D_STRUCT_NO_STEP(input); |
Adnan AlSinan | 7075fe2 | 2021-07-05 13:12:52 +0100 | [diff] [blame] | 134 | Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output); |
| 135 | |
| 136 | int block_x = BLOCK_SHAPE_X; |
| 137 | int block_y = BLOCK_SHAPE_Y; |
| 138 | |
| 139 | const int out_x = get_global_id(1); |
| 140 | const int out_y = get_global_id(2); |
| 141 | const int z = get_global_id(0); |
| 142 | |
| 143 | const int pos_x = out_x * block_x + ((batch_id / BATCH_IN) % block_x); |
| 144 | const int pos_y = out_y * block_y + ((batch_id / BATCH_IN) / block_x); |
| 145 | |
| 146 | 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) |
| 147 | { |
| 148 | const int w = batch_id % BATCH_IN; |
| 149 | const int in_x = pos_x - PAD_LEFT_X; |
| 150 | const int in_y = pos_y - PAD_LEFT_Y; |
| 151 | |
| 152 | *((__global DATA_TYPE *)out.ptr) = *((__global DATA_TYPE *)tensor4D_offset(&in, z, in_x, in_y, w)); |
| 153 | } |
| 154 | } |
Viet-Hoa Do | 6829e02 | 2024-01-16 16:23:24 +0000 | [diff] [blame^] | 155 | #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) |