blob: 2a0329d239d32ceeb09c35f7c729939982602c92 [file] [log] [blame]
Michalis Spyrou6c7c38e2018-08-29 16:28:11 +01001/*
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
26#if defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(LAYER_WIDTH) && defined(LAYER_HEIGHT) && defined(OFFSET) && defined(STEP_X) && defined(STEP_Y) && defined(NUM_PRIORS) && defined(VARIANCE_0) && defined(VARIANCE_1) && defined(VARIANCE_2) && defined(VARIANCE_3)
27
28/** Compute prior boxes and clip (NCHW)
29 *
30 * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
31 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
32 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
33 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
34 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
35 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
36 * @param[in] idx Index to write to
37 * @param[in] center_x Center value of the x axis
38 * @param[in] center_y Center value of the y axis
39 * @param[in] box_width Prior box width
40 * @param[in] box_height Prior box height
41 *
42 */
43inline void calculate_xy_min_max_nchw(Image *out, int idx, float center_x, float center_y, float box_width, float box_height)
44{
45 float xmin = (center_x - box_width / 2.f) / WIDTH;
46 float ymin = (center_y - box_height / 2.f) / HEIGHT;
47 float xmax = (center_x + box_width / 2.f) / WIDTH;
48 float ymax = (center_y + box_height / 2.f) / HEIGHT;
49
50#if defined(CLIP)
51 xmin = clamp(xmin, 0.f, 1.f);
52 ymin = clamp(ymin, 0.f, 1.f);
53 xmax = clamp(xmax, 0.f, 1.f);
54 ymax = clamp(ymax, 0.f, 1.f);
55#endif // defined(CLIP)
56
57 // Store result
58 vstore4((VEC_DATA_TYPE(DATA_TYPE, 4))(xmin, ymin, xmax, ymax), 0, ((__global DATA_TYPE *)offset(out, idx + 0, 0)));
59}
60
61/** Compute prior boxes (NCHW)
62 *
63 * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
64 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
65 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
66 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
67 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
68 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
69 * @param[in] min_size Prior box min size
70 * @param[in] min_idx Index of the min vector
71 * @param[in] idx Index to write to
72 *
73 * @return The updated index
74 */
75inline int calculate_min_nchw(Image *out, float *max, float *aspect_ratios, int max_size, int aspect_ratios_size, float min_size, int min_idx, int idx)
76{
77 const float center_x = ((float)(get_global_id(0) % LAYER_WIDTH) + OFFSET) * STEP_X;
78 const float center_y = ((float)(get_global_id(0) / LAYER_WIDTH) + OFFSET) * STEP_Y;
79
80 float box_width = min_size;
81 float box_height = min_size;
82 calculate_xy_min_max_nchw(out, idx, center_x, center_y, box_width, box_height);
83 idx += 4;
84
85 if(max_size > 0)
86 {
87 box_width = sqrt(min_size * max[min_idx]);
88 box_height = box_width;
89 calculate_xy_min_max_nchw(out, idx, center_x, center_y, box_width, box_height);
90 idx += 4;
91 }
92 for(unsigned int i = 0; i < aspect_ratios_size; ++i)
93 {
94 if(fabs(aspect_ratios[i] - 1.f) < 1e-6f)
95 {
96 continue;
97 }
98 box_width = min_size * sqrt(aspect_ratios[i]);
99 box_height = min_size * rsqrt(aspect_ratios[i]);
100
101 calculate_xy_min_max_nchw(out, idx, center_x, center_y, box_width, box_height);
102 idx += 4;
103 }
104
105 return idx;
106}
107
108/** Compute prior boxes and clip (NHWC)
109 *
110 * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
111 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
112 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
113 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
114 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
115 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
116 * @param[in] idx Index to write to
117 * @param[in] center_x Center value of the x axis
118 * @param[in] center_y Center value of the y axis
119 * @param[in] box_width Prior box width
120 * @param[in] box_height Prior box height
121 *
122 */
123inline void calculate_xy_min_max_nhwc(Tensor3D *out, int idx, float center_x, float center_y, float box_width, float box_height)
124{
125 float xmin = (center_x - box_width / 2.f) / WIDTH;
126 float ymin = (center_y - box_height / 2.f) / HEIGHT;
127 float xmax = (center_x + box_width / 2.f) / WIDTH;
128 float ymax = (center_y + box_height / 2.f) / HEIGHT;
129
130#if defined(CLIP)
131 xmin = clamp(xmin, 0.f, 1.f);
132 ymin = clamp(ymin, 0.f, 1.f);
133 xmax = clamp(xmax, 0.f, 1.f);
134 ymax = clamp(ymax, 0.f, 1.f);
135#endif // defined(CLIP)
136
137 *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 0, 0)) = xmin;
138 *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 1, 0)) = ymin;
139 *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 2, 0)) = xmax;
140 *((__global DATA_TYPE *)tensor3D_offset(out, 0, idx + 3, 0)) = ymax;
141}
142
143/** Compute prior boxes (NHWC)
144 *
145 * @param[in,out] out Tensor output
146 * @param[in] max The maximum values
147 * @param[in] aspect_ratios The aspect ratio values
148 * @param[in] max_size The maximum values values size
149 * @param[in] aspect_ratios_size The aspect ratio values size
150 * @param[in] min_size The minimum values size
151 * @param[in] min_idx Index of the min vector
152 * @param[in] idx Index to write to
153 *
154 * @return The updated index
155 */
156inline int calculate_min_nhwc(Image *out, float *max, float *aspect_ratios, int max_size, int aspect_ratios_size, float min_size, int min_idx, int idx)
157{
158 const float center_x = ((float)(get_global_id(1) % LAYER_WIDTH) + OFFSET) * STEP_X;
159 const float center_y = ((float)(get_global_id(1) / LAYER_WIDTH) + OFFSET) * STEP_Y;
160
161 float box_width = min_size;
162 float box_height = min_size;
163
164 calculate_xy_min_max_nhwc(out, idx, center_x, center_y, box_width, box_height);
165 idx += 4;
166 if(max_size > 0)
167 {
168 box_width = sqrt(min_size * max[min_idx]);
169 box_height = box_width;
170 calculate_xy_min_max_nhwc(out, idx, center_x, center_y, box_width, box_height);
171 idx += 4;
172 }
173 for(unsigned int i = 0; i < aspect_ratios_size; ++i)
174 {
175 if(fabs(aspect_ratios[i] - 1.f) < 1e-6f)
176 {
177 continue;
178 }
179 box_width = min_size * sqrt(aspect_ratios[i]);
180 box_height = min_size * rsqrt(aspect_ratios[i]);
181
182 calculate_xy_min_max_nhwc(out, idx, center_x, center_y, box_width, box_height);
183 idx += 4;
184 }
185
186 return idx;
187}
188
189/** Calculate prior boxes with NCHW format.
190 *
191 * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
192 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
193 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
194 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
195 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
196 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
197 * @param[in] min The minimum values
198 * @param[in] max The maximum_values
199 * @param[in] aspect_ratios The aspect ratio values
200 * @param[in] min_size The minimum values size
201 * @param[in] max_size The maximum_values values size
202 * @param[in] aspect_ratios_size The aspect ratio values size
203 */
204__kernel void prior_box_layer_nchw(IMAGE_DECLARATION(output), __global float *min, __global float *max, __global float *aspect_ratios, unsigned int min_size, unsigned int max_size,
205 unsigned int aspect_ratios_size)
206{
207 Image out = CONVERT_TO_IMAGE_STRUCT(output);
208
209 int idx = 0;
210 for(unsigned int i = 0; i < min_size; ++i)
211 {
212 idx = calculate_min_nchw(&out, max, aspect_ratios, max_size, aspect_ratios_size, min[i], i, idx);
213 }
214
215 // Store variances
216 for(int i = 0; i < (NUM_PRIORS * 4); i += 4)
217 {
218 vstore4((VEC_DATA_TYPE(DATA_TYPE, 4))(VARIANCE_0, VARIANCE_1, VARIANCE_2, VARIANCE_3), 0, ((__global DATA_TYPE *)offset(&out, i, 1)));
219 }
220}
221
222/** Calculate prior boxes with NHWC format.
223 *
224 * @param[out] output_ptr Pointer to the destination tensor. Supported data types: F32
225 * @param[in] output_stride_x Stride of the destination tensor in X dimension (in bytes)
226 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
227 * @param[in] output_stride_y Stride of the destination tensor in Y dimension (in bytes)
228 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
229 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination tensor
230 * @param[in] min The minimum values
231 * @param[in] max The maximum_values
232 * @param[in] aspect_ratios The aspect ratio values
233 * @param[in] min_size The minimum values size
234 * @param[in] max_size The maximum_values values size
235 * @param[in] aspect_ratios_size The aspect ratio values size
236 */
237__kernel void prior_box_layer_nhwc(TENSOR3D_DECLARATION(output), __global float *min, __global float *max, __global float *aspect_ratios, unsigned int min_size, unsigned int max_size,
238 unsigned int aspect_ratios_size)
239{
240 Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT(output);
241
242 int idx = 0;
243 for(unsigned int i = 0; i < min_size; ++i)
244 {
245 idx = calculate_min_nhwc(&out, max, aspect_ratios, max_size, aspect_ratios_size, min[i], i, idx);
246 }
247
248 for(int i = 0; i < (NUM_PRIORS * 4); i += 4)
249 {
250 *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 0, 1)) = VARIANCE_0;
251 *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 1, 1)) = VARIANCE_1;
252 *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 2, 1)) = VARIANCE_2;
253 *((__global DATA_TYPE *)tensor3D_offset(&out, 0, i + 3, 1)) = VARIANCE_3;
254 }
255}
256#endif /* defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(LAYER_WIDTH) && defined(LAYER_HEIGHT) && defined(OFFSET) && defined(STEP_X) && defined(STEP_Y) && defined(NUM_PRIORS) && defined(VARIANCE_0) && defined(VARIANCE_1) && defined(VARIANCE_2) && defined(VARIANCE_3) */