Giorgio Arena | 93a690e | 2017-08-01 16:09:33 +0100 | [diff] [blame] | 1 | /* |
| 2 | * Copyright (c) 2017 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 | |
| 25 | #include "helpers.h" |
| 26 | |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 27 | #if defined(CONV_STRIDE_X) |
| 28 | |
Giorgio Arena | 93a690e | 2017-08-01 16:09:33 +0100 | [diff] [blame] | 29 | #if CONV_STRIDE_X == 1 |
| 30 | #define convolution1x3 convolution1x3_stride_1 |
| 31 | #elif CONV_STRIDE_X == 2 |
| 32 | #define convolution1x3 convolution1x3_stride_2 |
| 33 | #elif CONV_STRIDE_X == 3 |
| 34 | #define convolution1x3 convolution1x3_stride_3 |
| 35 | #else /* CONV_STRIDE_X */ |
| 36 | #error "Stride not supported" |
| 37 | #endif /* CONV_STRIDE_X */ |
| 38 | |
| 39 | /** Compute a 1D horizontal convolution of size 3 and stride 1 for floating point type. |
| 40 | * |
| 41 | * @param[in] left_pixel Pointer to the left pixel. |
| 42 | * @param[in] left_coeff Weight of the left pixel |
| 43 | * @param[in] middle_coeff Weight of the middle pixel |
| 44 | * @param[in] right_coeff Weight of the right pixel |
| 45 | * |
| 46 | * @return a float2 containing 2 convoluted values. |
| 47 | */ |
| 48 | inline float2 convolution1x3_stride_1(__global const uchar *left_pixel, |
| 49 | const float left_coeff, |
| 50 | const float middle_coeff, |
| 51 | const float right_coeff) |
| 52 | { |
| 53 | float4 temp = vload4(0, (__global float *)left_pixel); |
| 54 | |
| 55 | float2 left = CONVERT(temp.s01, float2); |
| 56 | float2 middle = CONVERT(temp.s12, float2); |
| 57 | float2 right = CONVERT(temp.s23, float2); |
| 58 | |
| 59 | return left * (float2)left_coeff + middle * (float2)middle_coeff + right * (float2)right_coeff; |
| 60 | } |
| 61 | |
| 62 | /** Compute a 1D horizontal convolution of size 3 and stride 2 for floating point type. |
| 63 | * |
| 64 | * @param[in] left_pixel Pointer to the left pixel. |
| 65 | * @param[in] left_coeff Weight of the left pixel |
| 66 | * @param[in] middle_coeff Weight of the middle pixel |
| 67 | * @param[in] right_coeff Weight of the right pixel |
| 68 | * |
| 69 | * @return a float2 containing 2 convoluted values. |
| 70 | */ |
| 71 | inline float2 convolution1x3_stride_2(__global const uchar *left_pixel, |
| 72 | const float left_coeff, |
| 73 | const float middle_coeff, |
| 74 | const float right_coeff) |
| 75 | { |
| 76 | float4 temp0 = vload4(0, (__global float *)left_pixel); |
| 77 | float temp1 = *((__global float *)(left_pixel + 4 * sizeof(float))); |
| 78 | |
| 79 | float2 left = CONVERT(temp0.s02, float2); |
| 80 | float2 middle = CONVERT(temp0.s13, float2); |
| 81 | float2 right = CONVERT((float2)(temp0.s2, temp1), float2); |
| 82 | |
| 83 | return left * (float2)left_coeff + middle * (float2)middle_coeff + right * (float2)right_coeff; |
| 84 | } |
| 85 | |
| 86 | /** Compute a 1D horizontal convolution of size 3 and stride 3 for floating point type. |
| 87 | * |
| 88 | * @param[in] left_pixel Pointer to the left pixel. |
| 89 | * @param[in] left_coeff Weight of the left pixel |
| 90 | * @param[in] middle_coeff Weight of the middle pixel |
| 91 | * @param[in] right_coeff Weight of the right pixel |
| 92 | * |
| 93 | * @return a float2 containing 2 convoluted values. |
| 94 | */ |
| 95 | inline float2 convolution1x3_stride_3(__global const uchar *left_pixel, |
| 96 | const float left_coeff, |
| 97 | const float middle_coeff, |
| 98 | const float right_coeff) |
| 99 | { |
| 100 | float4 temp0 = vload4(0, (__global float *)left_pixel); |
| 101 | float2 temp1 = vload2(0, (__global float *)(left_pixel + 4 * sizeof(float))); |
| 102 | |
| 103 | float2 left = CONVERT(temp0.s03, float2); |
| 104 | float2 middle = CONVERT((float2)(temp0.s1, temp1.s0), float2); |
| 105 | float2 right = CONVERT((float2)(temp0.s2, temp1.s1), float2); |
| 106 | |
| 107 | return left * (float2)left_coeff + middle * (float2)middle_coeff + right * (float2)right_coeff; |
| 108 | } |
| 109 | |
| 110 | /** Apply a 3x3 convolution matrix to a single channel F32 input image and return the result. |
| 111 | * |
| 112 | * Convolution matrix layout: |
| 113 | * |
| 114 | * [ mat0, mat1, mat2 ]\n |
| 115 | * [ mat3, mat4, mat5 ]\n |
| 116 | * [ mat6, mat7, mat8 ]\n |
| 117 | * |
| 118 | * @param[in] src A pointer to source Image structure |
| 119 | * @param[in] mat0 Coefficient from the convolution matrix |
| 120 | * @param[in] mat1 Coefficient from the convolution matrix |
| 121 | * @param[in] mat2 Coefficient from the convolution matrix |
| 122 | * @param[in] mat3 Coefficient from the convolution matrix |
| 123 | * @param[in] mat4 Coefficient from the convolution matrix |
| 124 | * @param[in] mat5 Coefficient from the convolution matrix |
| 125 | * @param[in] mat6 Coefficient from the convolution matrix |
| 126 | * @param[in] mat0 Coefficient from the convolution matrix |
| 127 | * @param[in] mat7 Coefficient from the convolution matrix |
| 128 | * @param[in] mat8 Coefficient from the convolution matrix |
| 129 | * |
| 130 | * @return a float2 containing 2 convoluted values. |
| 131 | */ |
| 132 | inline float2 convolution3x3( |
| 133 | Image *src, |
| 134 | const float mat0, const float mat1, const float mat2, |
| 135 | const float mat3, const float mat4, const float mat5, |
| 136 | const float mat6, const float mat7, const float mat8) |
| 137 | { |
| 138 | float2 pixels; |
| 139 | |
| 140 | pixels = convolution1x3(offset(src, 0, 0), mat0, mat1, mat2); |
| 141 | pixels += convolution1x3(offset(src, 0, 1), mat3, mat4, mat5); |
| 142 | pixels += convolution1x3(offset(src, 0, 2), mat6, mat7, mat8); |
| 143 | |
| 144 | return pixels; |
| 145 | } |
| 146 | |
| 147 | /** This function computes the horizontal integral of the image. |
Anthony Barbier | f202e50 | 2017-11-23 18:02:04 +0000 | [diff] [blame^] | 148 | * |
| 149 | * @param[in] src_ptr Pointer to the source image. Supported data types: U8 |
| 150 | * @param[in] src_stride_x Stride of the source image in X dimension (in bytes) |
| 151 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 152 | * @param[in] src_stride_y Stride of the source image in Y dimension (in bytes) |
| 153 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 154 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source image |
| 155 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 156 | * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes) |
| 157 | * @param[in] dst_ptr Pointer to the destination tensor. Supported data types: F16/F32 |
| 158 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 159 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 160 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 161 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 162 | * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| 163 | * @param[in] dst_step_z dst_stride_z * number of elements along Y processed per workitem(in bytes) |
| 164 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 165 | * @param[in] weights_ptr Pointer to the weights tensor. Supported data types: F16/F32 |
| 166 | * @param[in] weights_stride_x Stride of the weights tensor in X dimension (in bytes) |
| 167 | * @param[in] weights_step_x weights_stride_x * number of elements along X processed per workitem(in bytes) |
| 168 | * @param[in] weights_stride_y Stride of the weights tensor in Y dimension (in bytes) |
| 169 | * @param[in] weights_step_y weights_stride_y * number of elements along Y processed per workitem(in bytes) |
| 170 | * @param[in] weights_stride_z Stride of the weights tensor in Z dimension (in bytes) |
| 171 | * @param[in] weights_step_z weights_stride_z * number of elements along Y processed per workitem(in bytes) |
| 172 | * @param[in] weights_offset_first_element_in_bytes The offset of the first element in the biases vector |
| 173 | * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: F16/F32 |
| 174 | * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) |
| 175 | * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) |
| 176 | * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector |
| 177 | */ |
Giorgio Arena | 93a690e | 2017-08-01 16:09:33 +0100 | [diff] [blame] | 178 | |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 179 | __kernel void depthwise_convolution_3x3( |
| 180 | TENSOR3D_DECLARATION(src), |
| 181 | TENSOR3D_DECLARATION(dst), |
| 182 | TENSOR3D_DECLARATION(weights) |
| 183 | #if defined(HAS_BIAS) |
| 184 | , |
| 185 | VECTOR_DECLARATION(biases) |
| 186 | #endif //defined(HAS_BIAS) |
| 187 | ) |
Giorgio Arena | 93a690e | 2017-08-01 16:09:33 +0100 | [diff] [blame] | 188 | { |
| 189 | Image src = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(src); |
| 190 | Image dst = CONVERT_TENSOR3D_TO_IMAGE_STRUCT(dst); |
| 191 | Tensor3D weights = CONVERT_TO_TENSOR3D_STRUCT(weights); |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 192 | #if defined(HAS_BIAS) |
| 193 | Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); |
| 194 | #endif //defined(HAS_BIAS) |
Giorgio Arena | 93a690e | 2017-08-01 16:09:33 +0100 | [diff] [blame] | 195 | |
| 196 | uchar3 offset = (uchar3)(0, 1, 2) * (uchar3)weights_stride_y; |
| 197 | float3 weights_values0 = vload3(0, (__global float *)(weights.ptr + offset.s0)); |
| 198 | float3 weights_values1 = vload3(0, (__global float *)(weights.ptr + offset.s1)); |
| 199 | float3 weights_values2 = vload3(0, (__global float *)(weights.ptr + offset.s2)); |
| 200 | |
| 201 | float2 pixels = convolution3x3(&src, weights_values0.s0, weights_values0.s1, weights_values0.s2, |
| 202 | weights_values1.s0, weights_values1.s1, weights_values1.s2, |
| 203 | weights_values2.s0, weights_values2.s1, weights_values2.s2); |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 204 | #if defined(HAS_BIAS) |
| 205 | pixels += (float2)(*((__global float *)(biases.ptr + get_global_id(2) * biases_stride_x))); |
| 206 | #endif //defined(HAS_BIAS) |
Giorgio Arena | 93a690e | 2017-08-01 16:09:33 +0100 | [diff] [blame] | 207 | |
| 208 | vstore2(pixels, 0, (__global float *)dst.ptr); |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 209 | } |
| 210 | |
| 211 | #endif //defined(CONV_STRIDE_X) |
| 212 | |
| 213 | #if defined(SRC_WIDTH) && defined(DATA_TYPE) |
| 214 | /** This kernel reshapes each of the tensor's low three dimensions to single rows. |
| 215 | * |
| 216 | * @note Datatype and source width should be given as a preprocessor argument using -DDATA_TYPE=type and -DSRC_WIDTH=width. e.g. -DSRC_WIDTH=128 |
| 217 | * |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 218 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: F16/F32 |
| 219 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 220 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 221 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 222 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 223 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 224 | * @param[in] src_step_z src_stride_z * number of elements along Y processed per workitem(in bytes) |
| 225 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 226 | * @param[out] dst_ptr Pointer to the destination tensor. Same as @p src_ptr |
| 227 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 228 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 229 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 230 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 231 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 232 | * @param[in] biases_ptr (Optional) Pointer to the biases vector. Supported data types: F16/F32 |
| 233 | * @param[in] biases_stride_x (Optional) Stride of the biases vector in X dimension (in bytes) |
| 234 | * @param[in] biases_step_x (Optional) biases_stride_x * number of elements along X processed per workitem(in bytes) |
| 235 | * @param[in] biases_offset_first_element_in_bytes (Optional) The offset of the first element in the biases vector |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 236 | */ |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 237 | __kernel void depthwise_weights_reshape( |
| 238 | TENSOR3D_DECLARATION(src), |
| 239 | IMAGE_DECLARATION(dst) |
| 240 | #ifdef HAS_BIAS |
| 241 | , |
| 242 | VECTOR_DECLARATION(biases) |
| 243 | #endif /* HAS_BIAS */ |
| 244 | ) |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 245 | { |
| 246 | Tensor3D src = CONVERT_TO_TENSOR3D_STRUCT(src); |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 247 | #ifdef HAS_BIAS |
| 248 | Vector biases = CONVERT_TO_VECTOR_STRUCT_NO_STEP(biases); |
| 249 | #endif /* HAS_BIAS */ |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 250 | |
| 251 | __global DATA_TYPE *input_ptr = (__global DATA_TYPE *)src.ptr; |
| 252 | __global uchar *output_ptr = dst_ptr + dst_offset_first_element_in_bytes + get_global_id(1) * SRC_WIDTH * dst_stride_x + get_global_id(2) * dst_stride_y; |
| 253 | |
| 254 | for(int i = 0; i < SRC_WIDTH; ++i, ++input_ptr) |
| 255 | { |
| 256 | *((__global DATA_TYPE *)(output_ptr + i * dst_stride_x)) = *input_ptr; |
| 257 | } |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 258 | |
| 259 | #if defined(HAS_BIAS) |
| 260 | if(get_global_id(1) == 0) |
| 261 | { |
| 262 | *((__global DATA_TYPE *)(output_ptr + SRC_WIDTH * get_global_size(1) * dst_stride_x)) = *((__global float *)(biases.ptr + get_global_id(2) * biases_stride_x)); |
| 263 | } |
| 264 | #endif // defined(HAS_BIAS) |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 265 | } |
| 266 | #endif //defined(SRC_WIDTH) && defined(DATA_TYPE) |
| 267 | |
Jaroslaw Rzepecki | a1ed41f | 2017-10-13 11:13:58 +0100 | [diff] [blame] | 268 | #if 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_WIDTH) && defined(SRC_HEIGHT) && defined(DATA_TYPE) |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 269 | /** This kernel performs a reshaping of the input tensor to a tensor used to perform depthwise convolution using vector to matrix multiplication. |
| 270 | * |
| 271 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
Jaroslaw Rzepecki | a1ed41f | 2017-10-13 11:13:58 +0100 | [diff] [blame] | 272 | * @note The convolution information must be passed at compile time using -DSTRIDE_X, -DSTRIDE_Y, -DPAD_LEFT, -DPAD_TOP, -DPAD_RIGHT, -DPAD_BOTTOM, -DKERNEL_WIDHT, -DKERNEL_HEIGHT, -DSRC_WIDTH, -DSRC_HEIGHT |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 273 | * |
| 274 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QS8/QS16/F16/F32 |
| 275 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 276 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 277 | * @param[in] src_stride_y Stride of the source tensor in Y dimension (in bytes) |
| 278 | * @param[in] src_step_y src_stride_y * number of elements along Y processed per workitem(in bytes) |
| 279 | * @param[in] src_stride_z Stride of the source tensor in Z dimension (in bytes) |
| 280 | * @param[in] src_step_z src_stride_z * number of elements along Z processed per workitem(in bytes) |
| 281 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 282 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 283 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 284 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 285 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 286 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 287 | * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| 288 | * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) |
| 289 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 290 | */ |
| 291 | |
| 292 | __kernel void depthwise_im2col(TENSOR3D_DECLARATION(src), TENSOR3D_DECLARATION(dst)) |
| 293 | { |
| 294 | Tensor3D dst = CONVERT_TO_TENSOR3D_STRUCT(dst); |
| 295 | |
| 296 | const int src_pixel_linear = get_global_id(1) * STRIDE_X; |
Jaroslaw Rzepecki | a1ed41f | 2017-10-13 11:13:58 +0100 | [diff] [blame] | 297 | const int full_length = SRC_WIDTH + PAD_LEFT + PAD_RIGHT; |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 298 | const int max_initial_x = STRIDE_X * (((full_length - KERNEL_WIDTH) / STRIDE_X) + 1); |
| 299 | |
Jaroslaw Rzepecki | a1ed41f | 2017-10-13 11:13:58 +0100 | [diff] [blame] | 300 | const int src_x = -PAD_LEFT + src_pixel_linear % max_initial_x; |
| 301 | const int src_y = -PAD_TOP + src_pixel_linear / max_initial_x * STRIDE_Y; |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 302 | const int src_z = get_global_id(2); |
| 303 | |
| 304 | __global uchar *input_ptr = src_ptr + src_offset_first_element_in_bytes + src_z * src_stride_z; |
| 305 | __global DATA_TYPE *output_ptr = ((__global DATA_TYPE *)(dst.ptr)); |
| 306 | |
| 307 | for(int y = src_y; y < src_y + KERNEL_HEIGHT; ++y) |
| 308 | { |
| 309 | for(int x = src_x; x < src_x + KERNEL_WIDTH; ++x, ++output_ptr) |
| 310 | { |
| 311 | if(x < 0 || x >= SRC_WIDTH || y < 0 || y >= SRC_HEIGHT) |
| 312 | { |
| 313 | *output_ptr = 0; |
| 314 | } |
| 315 | else |
| 316 | { |
| 317 | *output_ptr = *((__global DATA_TYPE *)(input_ptr + x * src_stride_x + y * src_stride_y)); |
| 318 | } |
| 319 | } |
| 320 | } |
Georgios Pinitas | 81a26ad | 2017-10-23 20:29:30 +0100 | [diff] [blame] | 321 | #if defined(HAS_BIAS) |
| 322 | *output_ptr = (DATA_TYPE)(1); |
| 323 | #endif // defined(HAS_BIAS) |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 324 | } |
| 325 | |
Jaroslaw Rzepecki | a1ed41f | 2017-10-13 11:13:58 +0100 | [diff] [blame] | 326 | #endif //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_WIDTH) && defined(DATA_TYPE) |
Giorgio Arena | 9fe4144 | 2017-08-23 16:36:24 +0100 | [diff] [blame] | 327 | |
| 328 | #if defined(CONV_WIDTH) && defined(CONV_HEIGHT) && defined(DATA_TYPE) |
| 329 | |
| 330 | /** This kernel performs a reshaping of the output of the depthwise generic convolution. |
| 331 | * |
| 332 | * @note The data type must be passed at compile time using -DDATA_TYPE: e.g. -DDATA_TYPE=float |
| 333 | * @note The convolution information must be passed at compile time using -DCONV_WIDTH, -DCONV_HEIGHT, e.g -DCONV_WIDTH=32, -DCONV_HEIGHT=42 |
| 334 | * |
| 335 | * @param[in] src_ptr Pointer to the source tensor. Supported data types: QS8/QS16/F16/F32 |
| 336 | * @param[in] src_stride_x Stride of the source tensor in X dimension (in bytes) |
| 337 | * @param[in] src_step_x src_stride_x * number of elements along X processed per workitem(in bytes) |
| 338 | * @param[in] src_offset_first_element_in_bytes The offset of the first element in the source tensor |
| 339 | * @param[out] dst_ptr Pointer to the destination tensor. Supported data types: same as @p src_ptr |
| 340 | * @param[in] dst_stride_x Stride of the destination tensor in X dimension (in bytes) |
| 341 | * @param[in] dst_step_x dst_stride_x * number of elements along X processed per workitem(in bytes) |
| 342 | * @param[in] dst_stride_y Stride of the destination tensor in Y dimension (in bytes) |
| 343 | * @param[in] dst_step_y dst_stride_y * number of elements along Y processed per workitem(in bytes) |
| 344 | * @param[in] dst_stride_z Stride of the destination tensor in Z dimension (in bytes) |
| 345 | * @param[in] dst_step_z dst_stride_z * number of elements along Z processed per workitem(in bytes) |
| 346 | * @param[in] dst_offset_first_element_in_bytes The offset of the first element in the destination tensor |
| 347 | */ |
| 348 | __kernel void depthwise_vector_to_tensor( |
| 349 | VECTOR_DECLARATION(src), |
| 350 | TENSOR3D_DECLARATION(dst)) |
| 351 | { |
| 352 | Vector src = CONVERT_TO_VECTOR_STRUCT(src); |
| 353 | |
| 354 | const int patch_size = CONV_WIDTH * CONV_HEIGHT; |
| 355 | const int id0 = get_global_id(0); |
| 356 | const int z = id0 / patch_size; |
| 357 | const int index2D = id0 - z * patch_size; |
| 358 | |
| 359 | __global uchar *out_ptr = dst_ptr + dst_offset_first_element_in_bytes + index2D % CONV_WIDTH * dst_stride_x + index2D / CONV_WIDTH * dst_stride_y + z * dst_stride_z; |
| 360 | *((__global DATA_TYPE *)out_ptr) = *((__global DATA_TYPE *)src.ptr); |
| 361 | } |
| 362 | |
| 363 | #endif //defined(CONV_WIDTH) && defined(CONV_HEIGHT) && defined(DATA_TYPE) |