Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2018 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 | |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 26 | #if defined(DATA_TYPE) && defined(ELEMENT_SIZE) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 27 | |
| 28 | #if ELEMENT_SIZE == 1 |
| 29 | #define COND_DATA_TYPE char |
| 30 | #elif ELEMENT_SIZE == 2 |
| 31 | #define COND_DATA_TYPE short |
| 32 | #elif ELEMENT_SIZE == 4 |
| 33 | #define COND_DATA_TYPE int |
| 34 | #else // ELEMENT_SIZE |
| 35 | #error "Element size not support" |
| 36 | #endif // ELEMENT_SIZE |
| 37 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 38 | #if defined(CONVOLVED_WIDTH) && defined(STRIDE_Y) && defined(SRC_DEPTH) |
| 39 | /** This opencl kernel performs im2col when the kernel size is 1x1, the stride_x = 1 and the data layout is NCHW |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 40 | * |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 41 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 42 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 43 | * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 44 | * @note The stride along the Y direction must be passed at compile time using -DSTRIDE_Y: e.g. -DSTRIDE_Y=1 |
| 45 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 46 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 47 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 48 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 49 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 50 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 51 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 52 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 53 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 54 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 55 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 56 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 57 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 58 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 59 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 60 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 61 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 62 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 63 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 64 | __kernel void im2col1x1_stridex1_nchw( |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 65 | TENSOR3D_DECLARATION(src), |
| 66 | IMAGE_DECLARATION(dst), |
| 67 | uint src_stride_w, |
| 68 | uint dst_stride_w) |
| 69 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 70 | const uint xc = get_global_id(0) * 4; // x coordinate in the convolved tensor |
| 71 | const uint yc = get_global_id(1); // y coordinate in the convolved tensor |
| 72 | const uint ch = get_global_id(2) % SRC_DEPTH; // input feature map |
| 73 | const uint batch = get_global_id(2) / SRC_DEPTH; // batch size |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 74 | |
| 75 | // Clamp xc |
| 76 | // The strategy clamps at "xc" as it will be a valid value for sure |
| 77 | uint4 xc_clamped = xc + (uint4)(0, 1, 2, 3); |
| 78 | |
| 79 | // Check which values are valid |
| 80 | const VEC_DATA_TYPE(COND_DATA_TYPE, 4) cond0 = CONVERT((xc_clamped < SRC_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, 4)); |
| 81 | |
| 82 | xc_clamped = select((uint4)xc, xc_clamped, convert_int4(cond0)); |
| 83 | |
| 84 | // Calculate input indices |
| 85 | const uint xi = xc; |
| 86 | const uint yi = yc * STRIDE_Y; |
| 87 | |
| 88 | // Calculate output indices |
| 89 | const uint xo = ch; |
| 90 | const uint4 yo = xc_clamped + yc * CONVOLVED_WIDTH; // Index of the convolution |
| 91 | |
| 92 | // Get input and output address |
| 93 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * src_stride_x + yi * src_stride_y + ch * src_stride_z + batch * src_stride_w; |
| 94 | |
| 95 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + batch * dst_stride_w; |
| 96 | |
| 97 | VEC_DATA_TYPE(DATA_TYPE, 4) |
| 98 | data = vload4(0, (__global DATA_TYPE *)input_ptr); |
| 99 | |
| 100 | // If out-of-bound, overwrite with the first element |
| 101 | data = select((VEC_DATA_TYPE(DATA_TYPE, 4))data.s0, data, cond0); |
| 102 | |
| 103 | *(__global DATA_TYPE *)(output_ptr + yo.s0 * dst_stride_y) = data.s0; |
| 104 | *(__global DATA_TYPE *)(output_ptr + yo.s1 * dst_stride_y) = data.s1; |
| 105 | *(__global DATA_TYPE *)(output_ptr + yo.s2 * dst_stride_y) = data.s2; |
| 106 | *(__global DATA_TYPE *)(output_ptr + yo.s3 * dst_stride_y) = data.s3; |
| 107 | |
| 108 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 109 | if(ch == (SRC_DEPTH - 1)) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 110 | { |
| 111 | *((__global DATA_TYPE *)(output_ptr + yo.s0 * dst_stride_y) + 1) = 1.0f; |
| 112 | *((__global DATA_TYPE *)(output_ptr + yo.s1 * dst_stride_y) + 1) = 1.0f; |
| 113 | *((__global DATA_TYPE *)(output_ptr + yo.s2 * dst_stride_y) + 1) = 1.0f; |
| 114 | *((__global DATA_TYPE *)(output_ptr + yo.s3 * dst_stride_y) + 1) = 1.0f; |
| 115 | } |
| 116 | #endif // HAS_BIAS |
| 117 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 118 | #endif // defined(CONVOLVED_WIDTH) && defined(STRIDE_Y) && defined(SRC_DEPTH) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 119 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 120 | #if defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) |
| 121 | #if defined(DILATION_X) && defined(DILATION_Y) |
| 122 | /** This opencl kernel performs a generic im2col implementation when the data layout is NCHW |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 123 | * |
| 124 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 125 | * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 |
| 126 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 127 | * @note The kernel width, height and depth must be passed at compile time using -DKERNEL_WIDTH, -DKERNEL_HEIGHT and -DSRC_DEPTH: e.g. -DKERNEL_WIDTH=3, -DKERNEL_HEIGHT=3 and -DSRC_DEPTH=64 |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 128 | * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 |
| 129 | * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 |
| 130 | * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 |
Georgios Pinitas | 19ea419 | 2018-06-19 13:09:53 +0100 | [diff] [blame] | 131 | * @note The dilation_x and dilation_y must be passed at compile time using -DDILATION_X and -DDILATION_Y: e.g. -DDILATION_X=1, -DDILATION_Y=1 |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 132 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 133 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 134 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 135 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 136 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 137 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 138 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 139 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 140 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 141 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 142 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 143 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 144 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 145 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 146 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 147 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 148 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 149 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 150 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 151 | __kernel void im2col_generic_nchw( |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 152 | TENSOR3D_DECLARATION(src), |
| 153 | IMAGE_DECLARATION(dst), |
| 154 | uint src_stride_w, |
| 155 | uint dst_stride_w) |
| 156 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 157 | const int xc = get_global_id(0); // x coordinate in the convolved tensor |
| 158 | const int yc = get_global_id(1); // y coordinate in the convolved tensor |
| 159 | const int ch = get_global_id(2) % SRC_DEPTH; // input feature map |
| 160 | const int batch = get_global_id(2) / SRC_DEPTH; // batch size |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 161 | |
| 162 | // Calculate input indices |
| 163 | const int xi = xc * STRIDE_X - PAD_LEFT; |
| 164 | const int yi = yc * STRIDE_Y - PAD_TOP; |
| 165 | |
| 166 | // Calculate output indices |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 167 | const int xo = ch * KERNEL_WIDTH * KERNEL_HEIGHT; |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 168 | const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution |
| 169 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 170 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * src_stride_z + batch * src_stride_w; |
| 171 | __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + yo * dst_stride_y + batch * dst_stride_w)) + xo; |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 172 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 173 | // Linearize convolution elements |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 174 | for(int yk = 0; yk < KERNEL_HEIGHT; ++yk) |
| 175 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 176 | int y = yi + yk * DILATION_Y; |
| 177 | for(int xk = 0; xk < KERNEL_WIDTH; ++xk, ++output_ptr) |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 178 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 179 | int x = xi + xk * DILATION_X; |
| 180 | #if PAD_LEFT == 0 && PAD_TOP == 0 && PAD_RIGHT == 0 && PAD_BOTTOM == 0 |
| 181 | *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); |
| 182 | #else // PAD_LEFT == 0 && PAD_TOP == 0 && PAD_RIGHT == 0 && PAD_BOTTOM == 0 |
| 183 | if(x < 0 || x >= SRC_WIDTH || y < 0 || y >= SRC_HEIGHT) |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 184 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 185 | *output_ptr = PAD_VALUE; |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 186 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 187 | else |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 188 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 189 | *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 190 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 191 | #endif // PAD_LEFT == 0 && PAD_TOP == 0 && PAD_RIGHT == 0 && PAD_BOTTOM == 0 |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 192 | } |
| 193 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 194 | |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 195 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 196 | if(ch == (SRC_DEPTH - 1)) |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 197 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 198 | *output_ptr = 1.0f; |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 199 | } |
| 200 | #endif // HAS_BIAS |
| 201 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 202 | #endif // defined(DILATION_X) && defined(DILATION_Y) |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 203 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 204 | /** This opencl kernel performs im2col when the kernel size is 3x3 and the data layout is NCHW |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 205 | * |
| 206 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 207 | * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 |
| 208 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 209 | * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 210 | * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 |
| 211 | * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 |
| 212 | * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 |
| 213 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 214 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 215 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 216 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 217 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 218 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 219 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 220 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 221 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 222 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 223 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 224 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 225 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 226 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 227 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 228 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 229 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 230 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 231 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 232 | __kernel void im2col3x3_nchw( |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 233 | TENSOR3D_DECLARATION(src), |
| 234 | IMAGE_DECLARATION(dst), |
| 235 | uint src_stride_w, |
| 236 | uint dst_stride_w) |
| 237 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 238 | const int xc = get_global_id(0); // x coordinate in the convolved tensor |
| 239 | const int yc = get_global_id(1); // y coordinate in the convolved tensor |
| 240 | const int ch = get_global_id(2) % SRC_DEPTH; // input feature map |
| 241 | const int batch = get_global_id(2) / SRC_DEPTH; // batch size |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 242 | |
| 243 | // Calculate input indices |
| 244 | const int xi = xc * STRIDE_X - PAD_LEFT; |
| 245 | const int yi = yc * STRIDE_Y - PAD_TOP; |
| 246 | |
| 247 | // Calculate output indices |
| 248 | const int xo = ch * 9; // 3x3 |
| 249 | const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution |
| 250 | |
| 251 | // Get input and output address |
| 252 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * (int)src_stride_x + yi * (int)src_stride_y + ch * src_stride_z + batch * src_stride_w; |
| 253 | |
| 254 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + batch * dst_stride_w; |
| 255 | |
| 256 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 257 | row0 = vload3(0, (__global DATA_TYPE *)(input_ptr + 0 * src_stride_y)); |
| 258 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 259 | row1 = vload3(0, (__global DATA_TYPE *)(input_ptr + 1 * src_stride_y)); |
| 260 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 261 | row2 = vload3(0, (__global DATA_TYPE *)(input_ptr + 2 * src_stride_y)); |
| 262 | |
| 263 | #if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 264 | // Put 0 if the value is out-of-bound |
| 265 | int3 x = (int3)xi + (int3)(0, 1, 2); |
| 266 | int3 y = (int3)yi + (int3)(0, 1, 2); |
| 267 | |
| 268 | VEC_DATA_TYPE(COND_DATA_TYPE, 3) |
| 269 | cond0 = CONVERT((x >= (int3)0 && x < (int3)SRC_WIDTH && (int3)(y.s0 >= 0 && y.s0 < SRC_HEIGHT)), VEC_DATA_TYPE(COND_DATA_TYPE, 3)); |
| 270 | VEC_DATA_TYPE(COND_DATA_TYPE, 3) |
| 271 | cond1 = CONVERT((x >= (int3)0 && x < (int3)SRC_WIDTH && (int3)(y.s1 >= 0 && y.s1 < SRC_HEIGHT)), VEC_DATA_TYPE(COND_DATA_TYPE, 3)); |
| 272 | VEC_DATA_TYPE(COND_DATA_TYPE, 3) |
| 273 | cond2 = CONVERT((x >= (int3)0 && x < (int3)SRC_WIDTH && (int3)(y.s2 >= 0 && y.s2 < SRC_HEIGHT)), VEC_DATA_TYPE(COND_DATA_TYPE, 3)); |
| 274 | |
| 275 | row0 = select((VEC_DATA_TYPE(DATA_TYPE, 3))PAD_VALUE, row0, cond0); |
| 276 | row1 = select((VEC_DATA_TYPE(DATA_TYPE, 3))PAD_VALUE, row1, cond1); |
| 277 | row2 = select((VEC_DATA_TYPE(DATA_TYPE, 3))PAD_VALUE, row2, cond2); |
| 278 | #endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 279 | |
| 280 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row0.s012, row1.s012, row2.s01), 0, (__global DATA_TYPE *)output_ptr); |
| 281 | *((__global DATA_TYPE *)output_ptr + 8) = row2.s2; |
| 282 | |
| 283 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 284 | if(ch == (SRC_DEPTH - 1)) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 285 | { |
| 286 | *((__global DATA_TYPE *)output_ptr + 9) = 1.0f; |
| 287 | } |
| 288 | #endif // HAS_BIAS |
| 289 | } |
| 290 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 291 | /** This opencl kernel performs im2col when the kernel size is 5x5 and the data layout is NCHW |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 292 | * |
| 293 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 294 | * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 |
| 295 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 296 | * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 297 | * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 |
| 298 | * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 |
| 299 | * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 |
| 300 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 301 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 302 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 303 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 304 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 305 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 306 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 307 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 308 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 309 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 310 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 311 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 312 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 313 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 314 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 315 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 316 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 317 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 318 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 319 | __kernel void im2col5x5_nchw( |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 320 | TENSOR3D_DECLARATION(src), |
| 321 | IMAGE_DECLARATION(dst), |
| 322 | uint src_stride_w, |
| 323 | uint dst_stride_w) |
| 324 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 325 | const int xc = get_global_id(0); // x coordinate in the convolved tensor |
| 326 | const int yc = get_global_id(1); // y coordinate in the convolved tensor |
| 327 | const int ch = get_global_id(2) % SRC_DEPTH; // input feature map |
| 328 | const int batch = get_global_id(2) / SRC_DEPTH; // batch size |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 329 | |
| 330 | // Calculate input indices |
| 331 | const int xi = xc * STRIDE_X - PAD_LEFT; |
| 332 | const int yi = yc * STRIDE_Y - PAD_TOP; |
| 333 | |
| 334 | // Calculate output indices |
| 335 | const int xo = ch * 25; // 5x5 |
| 336 | const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution |
| 337 | |
| 338 | #if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 339 | // Put 0 if the value is out-of-bound |
| 340 | int4 x0 = (int4)xi + (int4)(0, 1, 2, 3); |
| 341 | int4 y0 = (int4)yi + (int4)(0, 1, 2, 3); |
| 342 | int x1 = xi + 4; |
| 343 | int y1 = yi + 4; |
| 344 | |
| 345 | // Check if we could have out-of-bounds elements in the x direction |
| 346 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 347 | x0_condition = CONVERT((x0 >= (int4)0 && x0 < (int4)SRC_WIDTH), VEC_DATA_TYPE(COND_DATA_TYPE, 4)); |
| 348 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 349 | y0_condition = CONVERT((y0 >= (int4)0 && y0 < (int4)SRC_HEIGHT), VEC_DATA_TYPE(COND_DATA_TYPE, 4)); |
| 350 | COND_DATA_TYPE x1_condition = (COND_DATA_TYPE)(x1 >= 0 && x1 < SRC_WIDTH); |
| 351 | COND_DATA_TYPE y1_condition = (COND_DATA_TYPE)(y1 >= 0 && y1 < SRC_HEIGHT); |
| 352 | #endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 353 | |
| 354 | // Get input and output address |
| 355 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * (int)src_stride_x + yi * (int)src_stride_y + ch * src_stride_z + batch * src_stride_w; |
| 356 | |
| 357 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + batch * dst_stride_w; |
| 358 | |
| 359 | { |
| 360 | VEC_DATA_TYPE(DATA_TYPE, 4) |
| 361 | row00 = vload4(0, (__global DATA_TYPE *)input_ptr); |
| 362 | DATA_TYPE |
| 363 | row01 = *((__global DATA_TYPE *)input_ptr + 4); |
| 364 | |
| 365 | input_ptr += src_stride_y; |
| 366 | |
| 367 | VEC_DATA_TYPE(DATA_TYPE, 4) |
| 368 | row10 = vload4(0, (__global DATA_TYPE *)input_ptr); |
| 369 | DATA_TYPE |
| 370 | row11 = *((__global DATA_TYPE *)input_ptr + 4); |
| 371 | |
| 372 | #if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 373 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 374 | cond00 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s0; |
| 375 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 376 | cond10 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s1; |
| 377 | COND_DATA_TYPE cond01 = (COND_DATA_TYPE)(x1_condition && y0_condition.s0); |
| 378 | COND_DATA_TYPE cond11 = (COND_DATA_TYPE)(x1_condition && y0_condition.s1); |
| 379 | |
| 380 | // Replace with 0 if the value is not valid |
| 381 | row00 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row00, cond00); |
| 382 | row10 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row10, cond10); |
| 383 | row01 = select((DATA_TYPE)PAD_VALUE, row01, cond01); |
| 384 | row11 = select((DATA_TYPE)PAD_VALUE, row11, cond11); |
| 385 | #endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 386 | |
| 387 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s0123, row01, |
| 388 | row10.s012), |
| 389 | 0, (__global DATA_TYPE *)output_ptr); |
| 390 | vstore2((VEC_DATA_TYPE(DATA_TYPE, 2))(row10.s3, row11), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 391 | |
| 392 | input_ptr += src_stride_y; |
| 393 | output_ptr += 10 * dst_stride_x; |
| 394 | } |
| 395 | |
| 396 | { |
| 397 | VEC_DATA_TYPE(DATA_TYPE, 4) |
| 398 | row00 = vload4(0, (__global DATA_TYPE *)input_ptr); |
| 399 | DATA_TYPE |
| 400 | row01 = *((__global DATA_TYPE *)input_ptr + 4); |
| 401 | |
| 402 | input_ptr += src_stride_y; |
| 403 | |
| 404 | VEC_DATA_TYPE(DATA_TYPE, 4) |
| 405 | row10 = vload4(0, (__global DATA_TYPE *)input_ptr); |
| 406 | DATA_TYPE |
| 407 | row11 = *((__global DATA_TYPE *)input_ptr + 4); |
| 408 | |
| 409 | #if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 410 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 411 | cond00 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s2; |
| 412 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 413 | cond10 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y0_condition.s3; |
| 414 | COND_DATA_TYPE cond01 = (COND_DATA_TYPE)(x1_condition && y0_condition.s2); |
| 415 | COND_DATA_TYPE cond11 = (COND_DATA_TYPE)(x1_condition && y0_condition.s3); |
| 416 | |
| 417 | // Replace with 0 if the value is not valid |
| 418 | row00 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row00, cond00); |
| 419 | row10 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row10, cond10); |
| 420 | row01 = select((DATA_TYPE)PAD_VALUE, row01, cond01); |
| 421 | row11 = select((DATA_TYPE)PAD_VALUE, row11, cond11); |
| 422 | #endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 423 | |
| 424 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s0123, row01, |
| 425 | row10.s012), |
| 426 | 0, (__global DATA_TYPE *)output_ptr); |
| 427 | vstore2((VEC_DATA_TYPE(DATA_TYPE, 2))(row10.s3, row11), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 428 | |
| 429 | input_ptr += src_stride_y; |
| 430 | output_ptr += 10 * dst_stride_x; |
| 431 | } |
| 432 | |
| 433 | { |
| 434 | VEC_DATA_TYPE(DATA_TYPE, 4) |
| 435 | row00 = vload4(0, (__global DATA_TYPE *)input_ptr); |
| 436 | DATA_TYPE |
| 437 | row01 = *((__global DATA_TYPE *)input_ptr + 4); |
| 438 | |
| 439 | input_ptr += src_stride_y; |
| 440 | |
| 441 | #if PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 442 | VEC_DATA_TYPE(COND_DATA_TYPE, 4) |
| 443 | cond00 = x0_condition && (VEC_DATA_TYPE(COND_DATA_TYPE, 4))y1_condition; |
| 444 | COND_DATA_TYPE cond01 = (COND_DATA_TYPE)(x1_condition && y1_condition); |
| 445 | |
| 446 | // Replace with 0 if the value is not valid |
| 447 | row00 = select((VEC_DATA_TYPE(DATA_TYPE, 4))PAD_VALUE, row00, cond00); |
| 448 | row01 = select((DATA_TYPE)PAD_VALUE, row01, cond01); |
| 449 | #endif // PAD_LEFT != 0 || PAD_TOP != 0 || PAD_RIGHT != 0 || PAD_BOTTOM != 0 |
| 450 | |
| 451 | vstore4(row00, 0, (__global DATA_TYPE *)output_ptr); |
| 452 | *((__global DATA_TYPE *)output_ptr + 4) = row01; |
| 453 | |
| 454 | output_ptr += 5 * dst_stride_x; |
| 455 | } |
| 456 | |
| 457 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 458 | if(ch == (SRC_DEPTH - 1)) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 459 | { |
| 460 | *((__global DATA_TYPE *)output_ptr) = 1.0f; |
| 461 | } |
| 462 | #endif // HAS_BIAS |
| 463 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 464 | #endif // defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 465 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 466 | #if defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) |
| 467 | /** This opencl kernel performs im2col when the kernel size is 11x11, we do not have paddings and the data layout is NCHW |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 468 | * |
| 469 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 470 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 471 | * @note The number of input channels must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 472 | * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 |
| 473 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 474 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 475 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 476 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 477 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 478 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 479 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 480 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 481 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 482 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 483 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 484 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 485 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 486 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 487 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 488 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 489 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 490 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 491 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 492 | __kernel void im2col11x11_padx0_pady0_nchw( |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 493 | TENSOR3D_DECLARATION(src), |
| 494 | IMAGE_DECLARATION(dst), |
| 495 | uint src_stride_w, |
| 496 | uint dst_stride_w) |
| 497 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 498 | const int xc = get_global_id(0); // x coordinate in the convolved tensor |
| 499 | const int yc = get_global_id(1); // y coordinate in the convolved tensor |
| 500 | const int ch = get_global_id(2) % SRC_DEPTH; // input feature map |
| 501 | const int batch = get_global_id(2) / SRC_DEPTH; // batch size |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 502 | |
| 503 | // Calculate input indices |
| 504 | const int xi = xc * STRIDE_X; |
| 505 | const int yi = yc * STRIDE_Y; |
| 506 | |
| 507 | // Calculate output indices |
| 508 | const int xo = ch * 121; // 11x11 |
| 509 | const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution |
| 510 | |
| 511 | // Get input and output address |
| 512 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + xi * src_stride_x + yi * src_stride_y + ch * src_stride_z + batch * src_stride_w; |
| 513 | |
| 514 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + xo * dst_stride_x + yo * dst_stride_y + batch * dst_stride_w; |
| 515 | { |
| 516 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 517 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 518 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 519 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 520 | |
| 521 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 522 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 523 | |
| 524 | input_ptr += src_stride_y; |
| 525 | output_ptr += 11 * src_stride_x; |
| 526 | } |
| 527 | |
| 528 | { |
| 529 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 530 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 531 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 532 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 533 | |
| 534 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 535 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 536 | |
| 537 | input_ptr += src_stride_y; |
| 538 | output_ptr += 11 * src_stride_x; |
| 539 | } |
| 540 | |
| 541 | { |
| 542 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 543 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 544 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 545 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 546 | |
| 547 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 548 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 549 | |
| 550 | input_ptr += src_stride_y; |
| 551 | output_ptr += 11 * src_stride_x; |
| 552 | } |
| 553 | |
| 554 | { |
| 555 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 556 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 557 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 558 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 559 | |
| 560 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 561 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 562 | |
| 563 | input_ptr += src_stride_y; |
| 564 | output_ptr += 11 * src_stride_x; |
| 565 | } |
| 566 | |
| 567 | { |
| 568 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 569 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 570 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 571 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 572 | |
| 573 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 574 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 575 | |
| 576 | input_ptr += src_stride_y; |
| 577 | output_ptr += 11 * src_stride_x; |
| 578 | } |
| 579 | |
| 580 | { |
| 581 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 582 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 583 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 584 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 585 | |
| 586 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 587 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 588 | |
| 589 | input_ptr += src_stride_y; |
| 590 | output_ptr += 11 * src_stride_x; |
| 591 | } |
| 592 | |
| 593 | { |
| 594 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 595 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 596 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 597 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 598 | |
| 599 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 600 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 601 | |
| 602 | input_ptr += src_stride_y; |
| 603 | output_ptr += 11 * src_stride_x; |
| 604 | } |
| 605 | |
| 606 | { |
| 607 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 608 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 609 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 610 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 611 | |
| 612 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 613 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 614 | |
| 615 | input_ptr += src_stride_y; |
| 616 | output_ptr += 11 * src_stride_x; |
| 617 | } |
| 618 | |
| 619 | { |
| 620 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 621 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 622 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 623 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 624 | |
| 625 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 626 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 627 | |
| 628 | input_ptr += src_stride_y; |
| 629 | output_ptr += 11 * src_stride_x; |
| 630 | } |
| 631 | |
| 632 | { |
| 633 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 634 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 635 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 636 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 637 | |
| 638 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 639 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 640 | |
| 641 | input_ptr += src_stride_y; |
| 642 | output_ptr += 11 * src_stride_x; |
| 643 | } |
| 644 | |
| 645 | { |
| 646 | VEC_DATA_TYPE(DATA_TYPE, 8) |
| 647 | row00 = vload8(0, (__global DATA_TYPE *)(input_ptr)); |
| 648 | VEC_DATA_TYPE(DATA_TYPE, 3) |
| 649 | row01 = vload3(0, (__global DATA_TYPE *)(input_ptr) + 8); |
| 650 | |
| 651 | vstore8((VEC_DATA_TYPE(DATA_TYPE, 8))(row00.s01234567), 0, (__global DATA_TYPE *)output_ptr); |
| 652 | vstore3((VEC_DATA_TYPE(DATA_TYPE, 3))(row01.s012), 0, (__global DATA_TYPE *)output_ptr + 8); |
| 653 | |
| 654 | output_ptr += 11 * src_stride_x; |
| 655 | } |
| 656 | |
| 657 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 658 | if(ch == (SRC_DEPTH - 1)) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 659 | { |
| 660 | *((__global DATA_TYPE *)output_ptr) = 1.0f; |
| 661 | } |
| 662 | #endif // HAS_BIAS |
| 663 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 664 | #endif // defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(SRC_DEPTH) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 665 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 666 | #if defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(VECTOR_SIZE) && defined(WIDTH_MOD_VECTOR_SIZE) |
| 667 | /** This opencl kernel performs im2col when the kernel size is greater than 1x1, we do not have paddings and the data layout is NCHW |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 668 | * |
| 669 | * @note The data type must be passed at compile time using -DDATA_TYPE e.g. -DDATA_TYPE=float. |
| 670 | * @note The vector size must be passed at compile time using -DVECTOR_SIZE e.g. -DVECTOR_SIZE=4. |
| 671 | * @note The width modulo vector size must be passed at compile time using -DWIDTH_MOD_VECTOR_SIZE e.g. -DWIDTH_MOD_VECTOR_SIZE=3. |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 672 | * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 673 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 674 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 675 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 676 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 677 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 678 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 679 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 680 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 681 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 682 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 683 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 684 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 685 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 686 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 687 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 688 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 689 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 690 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 691 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 692 | __kernel void im2col_generic_padx0_pady0_nchw( |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 693 | TENSOR3D_DECLARATION(src), |
| 694 | IMAGE_DECLARATION(dst), |
| 695 | uint src_stride_w, |
| 696 | uint dst_stride_w) |
| 697 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 698 | const int xc = get_global_id(0); // x coordinate in the convolved tensor |
| 699 | const int yc = get_global_id(1); // y coordinate in the convolved tensor |
| 700 | const int ch = get_global_id(2) % SRC_DEPTH; // input feature map |
| 701 | const int batch = get_global_id(2) / SRC_DEPTH; // batch size |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 702 | |
| 703 | // Calculate input indices |
| 704 | const int xi = xc * STRIDE_X; |
| 705 | const int yi = yc * STRIDE_Y; |
| 706 | // Calculate output indices |
| 707 | const int xo = ch * KERNEL_WIDTH * KERNEL_HEIGHT; |
| 708 | const int yo = xc + yc * CONVOLVED_WIDTH; // Index of the convolution |
| 709 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * src_stride_z + batch * src_stride_w; |
| 710 | __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst_ptr + dst_offset_first_element_in_bytes + yo * dst_stride_y + batch * dst_stride_w)) + xo; |
| 711 | // Linearize convolution elements |
| 712 | for(int y = yi, y_e = yi + KERNEL_HEIGHT; y < y_e; ++y) |
| 713 | { |
| 714 | int last_x = 0; |
| 715 | for(int x = xi, x_e = xi + KERNEL_WIDTH; x + VECTOR_SIZE <= x_e; x += VECTOR_SIZE, output_ptr += VECTOR_SIZE) |
| 716 | { |
| 717 | VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) |
| 718 | row = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); |
| 719 | VSTORE(VECTOR_SIZE) |
| 720 | (row, 0, output_ptr); |
| 721 | last_x = x; |
| 722 | } |
| 723 | // Copy the remainder of the row by doing VLOAD(WIDTH_MOD_VECTOR_SIZE) and VSTORE(WIDTH_MOD_VECTOR_SIZE). |
| 724 | // Note that x and output_ptr have already been incremented by VECTOR_SIZE by the loop just before exit. |
| 725 | #if WIDTH_MOD_VECTOR_SIZE == 1 |
| 726 | *output_ptr = *((__global DATA_TYPE *)(input_ptr + (last_x + VECTOR_SIZE) * src_stride_x + y * src_stride_y)); |
| 727 | #elif WIDTH_MOD_VECTOR_SIZE > 1 |
| 728 | VEC_DATA_TYPE(DATA_TYPE, WIDTH_MOD_VECTOR_SIZE) |
| 729 | row = VLOAD(WIDTH_MOD_VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + (last_x + VECTOR_SIZE) * src_stride_x + y * src_stride_y)); |
| 730 | VSTORE(WIDTH_MOD_VECTOR_SIZE) |
| 731 | (row, 0, output_ptr); |
| 732 | #endif /* WIDTH_MOD_VECTOR_SIZE */ |
| 733 | output_ptr += WIDTH_MOD_VECTOR_SIZE; |
| 734 | } /* End of loop over KERNEL_HEIGHT */ |
| 735 | |
| 736 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 737 | if(ch == (SRC_DEPTH - 1)) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 738 | { |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 739 | *output_ptr = 1.0f; |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 740 | } |
| 741 | #endif // HAS_BIAS |
| 742 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 743 | #endif //defined(CONVOLVED_WIDTH) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(PAD_LEFT) && defined(PAD_TOP) && defined(PAD_RIGHT) && defined(PAD_BOTTOM) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(VECTOR_SIZE) && defined(WIDTH_MOD_VECTOR_SIZE) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 744 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 745 | #if defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) && defined(VECTOR_SIZE) && defined(LAST_ACCESSED) |
| 746 | |
| 747 | #define VECTOR_N VEC_DATA_TYPE(DATA_TYPE, VECTOR_SIZE) |
| 748 | |
| 749 | /** This kernel performs im2col when the kernel size is 3x3 and the data layout is NHWC |
| 750 | * |
| 751 | * @note This kernel computes VECTOR_SIZE elements |
| 752 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 753 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
| 754 | * @note The kernel depth must be passed at compile time using -DSRC_DEPTH: e.g. -DSRC_DEPTH=3 |
| 755 | * @note The stride along the Y direction must be passed at compile time using -DSTRIDE_Y: e.g. -DSTRIDE_Y=1 |
| 756 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 757 | * |
| 758 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
| 759 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 760 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 761 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 762 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 763 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 764 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 765 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 766 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 767 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 768 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 769 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 770 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 771 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 772 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 773 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 774 | */ |
| 775 | __kernel void im2col3x3_nhwc( |
| 776 | TENSOR3D_DECLARATION(src), |
| 777 | IMAGE_DECLARATION(dst), |
| 778 | uint src_stride_w, |
| 779 | uint dst_stride_w) |
| 780 | { |
| 781 | const int ch = min((int)(get_global_id(0) * VECTOR_SIZE), LAST_ACCESSED); // input feature map |
| 782 | const int yo = get_global_id(1); |
| 783 | const int batch = get_global_id(2); // batch size |
| 784 | |
| 785 | // Calculate input indices |
| 786 | const int xi = (get_global_id(1) % CONVOLVED_WIDTH) * STRIDE_X; |
| 787 | const int yi = (get_global_id(1) / (int)CONVOLVED_WIDTH) * STRIDE_Y; |
| 788 | |
| 789 | // Get input and output address |
| 790 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + batch * (int)src_stride_w; |
| 791 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + yo * (int)dst_stride_y + batch * (int)dst_stride_w; |
| 792 | |
| 793 | int yi_coord = 0; |
| 794 | int3 offset = 0; |
| 795 | |
| 796 | // Clamp xi |
| 797 | int3 xi_offset = ((int3)xi + (int3)(0, 1, 2) * DILATION_X - (int3)PAD_LEFT); |
| 798 | #if PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 799 | #define CLAMP(x, min_val, max_val) min(max(x, min_val), max_val) |
| 800 | xi_offset = CLAMP(xi_offset, (int3)0, (int3)(SRC_WIDTH - 1)); |
| 801 | #endif // PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 802 | xi_offset *= (int3)src_stride_y; |
| 803 | |
| 804 | // Out-of-bound condition for X |
| 805 | int3 x_cond = (((int3)xi + (int3)(0, 1, 2) * DILATION_X - (int3)PAD_LEFT) < (int3)0) || (((int3)xi + (int3)(0, 1, 2) * DILATION_X - (int3)PAD_LEFT) >= (int3)SRC_WIDTH); |
| 806 | |
| 807 | // yi == 0 |
| 808 | // Clamp yi |
| 809 | // yi_coord is casted to unsigned int in order to use just a min() operation |
| 810 | // A "-1" 32 bit signed variable converted to unsigned gives 4294967295 |
| 811 | yi_coord = yi - (int)PAD_TOP; |
| 812 | |
| 813 | // Clamp only if PAD_TOP or PAD_BOTTOM is not equal to 0 |
| 814 | #if PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 815 | yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); |
| 816 | #endif // PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 817 | |
| 818 | // Compute offset |
| 819 | offset = xi_offset + (yi_coord * (int)src_stride_z); |
| 820 | |
| 821 | // Load input values |
| 822 | VECTOR_N values0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s0)); |
| 823 | VECTOR_N values1 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s1)); |
| 824 | VECTOR_N values2 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s2)); |
| 825 | |
| 826 | #if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 |
| 827 | // Replace invalid values with PAD_VALUE |
| 828 | int y_cond = (int)((uint)(yi - (int)PAD_TOP) >= (uint)(SRC_HEIGHT)); |
| 829 | values0 = select(values0, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s0)); |
| 830 | values1 = select(values1, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s1)); |
| 831 | values2 = select(values2, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s2)); |
| 832 | #endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 |
| 833 | |
| 834 | // yi == 1 |
| 835 | // Clamp yi_coord (it can be negative if PAD_TOP > 1) |
| 836 | yi_coord = yi - (int)PAD_TOP + 1 * DILATION_Y; |
| 837 | |
| 838 | // Clamp only if PAD_TOP or PAD_BOTTOM is not equal to 0 |
| 839 | #if PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 840 | yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); |
| 841 | #endif // PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 842 | |
| 843 | // Compute offset |
| 844 | offset = xi_offset + (yi_coord * (int)src_stride_z); |
| 845 | |
| 846 | // Load input values |
| 847 | VECTOR_N values3 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s0)); |
| 848 | VECTOR_N values4 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s1)); |
| 849 | VECTOR_N values5 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s2)); |
| 850 | |
| 851 | #if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 |
| 852 | // Replace invalid values with zeros |
| 853 | y_cond = (int)((uint)(yi - (int)PAD_TOP + 1) >= (uint)(SRC_HEIGHT)); |
| 854 | values3 = select(values3, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s0)); |
| 855 | values4 = select(values4, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s1)); |
| 856 | values5 = select(values5, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s2)); |
| 857 | #endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 |
| 858 | |
| 859 | // yi == 2 |
| 860 | // Clamp yi_coord |
| 861 | yi_coord = yi - (int)PAD_TOP + 2 * DILATION_Y; |
| 862 | |
| 863 | // Clamp only if PAD_TOP or PAD_BOTTOM is not equal to 0 |
| 864 | #if PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 865 | yi_coord = min((uint)yi_coord, (uint)(SRC_HEIGHT - 1)); |
| 866 | #endif // PAD_TOP != 0 || PAD_BOTTOM != 0 |
| 867 | |
| 868 | // Compute offset |
| 869 | offset = xi_offset + (yi_coord * (int)src_stride_z); |
| 870 | |
| 871 | // Load input values |
| 872 | VECTOR_N values6 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s0)); |
| 873 | VECTOR_N values7 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s1)); |
| 874 | VECTOR_N values8 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset.s2)); |
| 875 | |
| 876 | #if PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 |
| 877 | // Replace invalid values with PAD_VALUE |
| 878 | y_cond = (int)((uint)(yi - (int)PAD_TOP + 2) >= (uint)(SRC_HEIGHT)); |
| 879 | values6 = select(values6, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s0)); |
| 880 | values7 = select(values7, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s1)); |
| 881 | values8 = select(values8, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))y_cond || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(x_cond.s2)); |
| 882 | #endif // PAD_TOP != 0 || PAD_LEFT != 0 || PAD_BOTTOM != 0 || PAD_RIGHT != 0 |
| 883 | |
| 884 | // Store |
| 885 | VSTORE(VECTOR_SIZE) |
| 886 | (values0, 0, (__global DATA_TYPE *)(output_ptr) + 0 * SRC_DEPTH); |
| 887 | VSTORE(VECTOR_SIZE) |
| 888 | (values1, 0, (__global DATA_TYPE *)(output_ptr) + 1 * SRC_DEPTH); |
| 889 | VSTORE(VECTOR_SIZE) |
| 890 | (values2, 0, (__global DATA_TYPE *)(output_ptr) + 2 * SRC_DEPTH); |
| 891 | VSTORE(VECTOR_SIZE) |
| 892 | (values3, 0, (__global DATA_TYPE *)(output_ptr) + 3 * SRC_DEPTH); |
| 893 | VSTORE(VECTOR_SIZE) |
| 894 | (values4, 0, (__global DATA_TYPE *)(output_ptr) + 4 * SRC_DEPTH); |
| 895 | VSTORE(VECTOR_SIZE) |
| 896 | (values5, 0, (__global DATA_TYPE *)(output_ptr) + 5 * SRC_DEPTH); |
| 897 | VSTORE(VECTOR_SIZE) |
| 898 | (values6, 0, (__global DATA_TYPE *)(output_ptr) + 6 * SRC_DEPTH); |
| 899 | VSTORE(VECTOR_SIZE) |
| 900 | (values7, 0, (__global DATA_TYPE *)(output_ptr) + 7 * SRC_DEPTH); |
| 901 | VSTORE(VECTOR_SIZE) |
| 902 | (values8, 0, (__global DATA_TYPE *)(output_ptr) + 8 * SRC_DEPTH); |
| 903 | |
| 904 | #ifdef HAS_BIAS |
| 905 | if((ch + VECTOR_SIZE) >= SRC_DEPTH) |
| 906 | { |
| 907 | *((__global DATA_TYPE *)(output_ptr) - ch + SRC_DEPTH * 9) = 1.0f; |
| 908 | } |
| 909 | #endif // HAS_BIAS |
| 910 | } |
| 911 | |
| 912 | /** This opencl kernel performs a generic im2col implementation when the data layout is NHWC |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 913 | * |
| 914 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 915 | * @note The width and height of the input tensor must be passed at compile time using -DSRC_WIDTH and -DSRC_HEIGHT: e.g. -DSRC_WIDTH=128 and -DSRC_HEIGHT=128 |
| 916 | * @note The width of output tensor after matrix multiplication must be passed at compile time using -DCONVOLVED_WIDTH: e.g. -DCONVOLVED_WIDTH=34 |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 917 | * @note The kernel width, height and depth must be passed at compile time using -DKERNEL_WIDTH, -DKERNEL_HEIGHT and -DSRC_DEPTH: e.g. -DKERNEL_WIDTH=3, -DKERNEL_HEIGHT=3 and -DSRC_DEPTH=64 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 918 | * @note The pad_left, pad_right, pad_top and pad_bottom must be passed at compile time using -DPAD_LEFT, -DPAD_RIGHT, -DPAD_TOP and -DPAD_BOTTOM: e.g. -DPAD_LEFT=1, -DPAD_RIGHT=2, -DPAD_TOP=3 and -DPAD_BOTTOM=2 |
| 919 | * @note The zero value to store in case we load values out-of-bounds must be passed at compile time using -DPAD_VALUE: e.g. -DPAD_VALUE=0.0 |
| 920 | * @note The stride along the X and Y directions must be passed at compile time using -DSTRIDE_X and -DSTRIDE_Y: e.g. -DSTRIDE_X=1 and -DSTRIDE_Y=1 |
Alex Gilday | 7da29b6 | 2018-03-23 14:16:00 +0000 | [diff] [blame] | 921 | * @note The dilation_x and dilation_y must be passed at compile time using -DDILATION_X and -DDILATION_Y: e.g. -DDILATION_X=1, -DDILATION_Y=1 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 922 | * @note In case biases will be added to the convolution -DHAS_BIAS has to be passed to append the final matrix with 1 in each row. |
| 923 | * |
Vidhya Sudhan Loganathan | 7485d5a | 2018-07-04 09:34:00 +0100 | [diff] [blame] | 924 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QASYMM8/F16/F32 |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 925 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 926 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 927 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 928 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 929 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 930 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 931 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 932 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 933 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 934 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 935 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 936 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 937 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 938 | * @param[in] src_stride_w Stride of the source tensor in W dimension (in bytes). |
| 939 | * @param[in] dst_stride_w Stride of the destination tensor in W dimension (in bytes). |
| 940 | */ |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 941 | __kernel void im2col_generic_nhwc( |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 942 | TENSOR3D_DECLARATION(src), |
| 943 | IMAGE_DECLARATION(dst), |
| 944 | uint src_stride_w, |
| 945 | uint dst_stride_w) |
| 946 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 947 | const int ch = min((int)(get_global_id(0) * VECTOR_SIZE), LAST_ACCESSED); // input feature map |
| 948 | const int yo = get_global_id(1); |
| 949 | const int batch = get_global_id(2); // batch size |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 950 | |
| 951 | // Calculate input indices |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 952 | const int xi = (get_global_id(1) % CONVOLVED_WIDTH) * STRIDE_X; |
| 953 | const int yi = (get_global_id(1) / (int)CONVOLVED_WIDTH) * STRIDE_Y; |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 954 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 955 | // Get input and output address |
| 956 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + batch * (int)src_stride_w; |
| 957 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + ch * sizeof(DATA_TYPE) + yo * (int)dst_stride_y + batch * (int)dst_stride_w; |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 958 | |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 959 | int i = 0; |
Alex Gilday | 7da29b6 | 2018-03-23 14:16:00 +0000 | [diff] [blame] | 960 | for(int yk = 0; yk < KERNEL_HEIGHT; ++yk) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 961 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 962 | // Clamp yi_coord |
| 963 | int yi_coord = yi + yk * DILATION_Y - (int)PAD_TOP; |
| 964 | yi_coord = CLAMP(yi_coord, (int)0, (int)(SRC_HEIGHT - 1)); |
| 965 | |
| 966 | // Out-of-bound condition for Y |
| 967 | int y_border_condition = ((yi + yk * DILATION_Y - (int)PAD_TOP) < (int)0) || ((yi + yk * DILATION_Y - (int)PAD_TOP) >= (int)SRC_HEIGHT); |
| 968 | |
| 969 | for(int xk = 0; xk < KERNEL_WIDTH; ++xk) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 970 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 971 | // Clamp xi_coord |
| 972 | int xi_coord = (xi + xk * DILATION_X - (int)PAD_LEFT); |
| 973 | xi_coord = CLAMP(xi_coord, (int)0, (int)(SRC_WIDTH - 1)); |
| 974 | |
| 975 | // Out-of-bound condition for X |
| 976 | int x_border_condition = ((xi + xk * DILATION_X - (int)PAD_LEFT) < (int)0) || ((xi + xk * DILATION_X - (int)PAD_LEFT) >= (int)SRC_WIDTH); |
| 977 | |
| 978 | int offset = xi_coord * (int)src_stride_y + (yi_coord * (int)src_stride_z); |
| 979 | |
| 980 | VECTOR_N values0 = VLOAD(VECTOR_SIZE)(0, (__global DATA_TYPE *)(input_ptr + offset)); |
| 981 | |
| 982 | // Replace with PAD_VALUE if the value is out-of-bound |
| 983 | values0 = select(values0, (VECTOR_N)PAD_VALUE, (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))x_border_condition || (VEC_DATA_TYPE(COND_DATA_TYPE, VECTOR_SIZE))(y_border_condition)); |
| 984 | |
| 985 | // Store |
| 986 | VSTORE(VECTOR_SIZE) |
| 987 | (values0, 0, (__global DATA_TYPE *)(output_ptr) + i * (int)SRC_DEPTH); |
| 988 | |
| 989 | i++; |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 990 | } |
| 991 | } |
| 992 | |
| 993 | #ifdef HAS_BIAS |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 994 | if((ch + VECTOR_SIZE) >= SRC_DEPTH) |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 995 | { |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 996 | *((__global DATA_TYPE *)(output_ptr) - ch + SRC_DEPTH * KERNEL_WIDTH * KERNEL_HEIGHT) = 1.0f; |
Gian Marco | 76faef8 | 2018-01-29 12:15:32 +0000 | [diff] [blame] | 997 | } |
| 998 | #endif // HAS_BIAS |
| 999 | } |
Gian Marco Iodice | 215b4ea | 2018-06-28 16:29:29 +0100 | [diff] [blame^] | 1000 | #endif // defined(CONVOLVED_WIDTH) && defined(SRC_WIDTH) && defined(SRC_HEIGHT) && defined(STRIDE_X) && defined(STRIDE_Y) && defined(KERNEL_WIDTH) && defined(KERNEL_HEIGHT) && defined(SRC_DEPTH) && defined(PAD_LEFT) && defined(PAD_RIGHT) && defined(PAD_TOP) && defined(PAD_BOTTOM) && defined(PAD_VALUE) && defined(VECTOR_SIZE) && defined(LAST_ACCESSED) |
Pablo Tello | 4a626a7 | 2018-04-04 10:01:14 +0100 | [diff] [blame] | 1001 | #endif // defined(DATA_TYPE) && defined(ELEMENT_SIZE) |