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SiCong Li3e363692017-07-04 15:02:10 +01001/*
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#include "helpers.h"
25
26#if DATA_SIZE == 32
27#define VEC_SIZE 4
28#define VEC_MAX vec4_max
29#elif DATA_SIZE == 16
30#define VEC_SIZE 8
31#define VEC_MAX vec8_max
32#else /* DATA_SIZE not equals 32 or 16 */
33#error "Unsupported data size"
34#endif /* DATA_SIZE == 32 */
35
36inline DATA_TYPE vec4_max(VEC_DATA_TYPE(DATA_TYPE, 4) vec)
37{
38 VEC_DATA_TYPE(DATA_TYPE, 2)
39 temp = fmax(vec.lo, vec.hi);
40 return fmax(temp.x, temp.y);
41}
42
43inline DATA_TYPE vec8_max(VEC_DATA_TYPE(DATA_TYPE, 8) vec)
44{
45 VEC_DATA_TYPE(DATA_TYPE, 4)
46 temp = fmax(vec.lo, vec.hi);
47 return vec4_max(temp);
48}
49
50/** Performs a roi pooling on a single output pixel.
51 *
52 * @param[in] input Pointer to input Tensor3D struct.
53 * @param[in] region_start_x Start x index projected onto the input tensor.
54 * @param[in] region_end_x End x index projected onto the input tensor.
55 * @param[in] region_start_y Start y index projected onto the input tensor.
56 * @param[in] region_end_y End y index projected onto the input tensor.
57 * @param[in] pz z index of the input tensor.
58 *
59 * @return A max pooled value from the region specified in the input tensor.
60 */
61inline DATA_TYPE roi_pool_1x1(const Tensor3D *input, int region_start_x, int region_end_x, int region_start_y, int region_end_y, int pz)
62{
63 // Iterate through the pooling region
64 if((region_end_x <= region_start_x) || (region_end_y <= region_start_y))
65 {
66 return (DATA_TYPE)0;
67 }
68 else
69 {
70 int num_iter = (int)((region_end_x - region_start_x) / VEC_SIZE);
71 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
72 curr_max = (VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE))(-FLT_MAX);
73 for(int j = region_start_y; j < region_end_y; ++j)
74 {
75 int i = region_start_x;
76 for(; i < region_start_x + num_iter * VEC_SIZE; i += VEC_SIZE)
77 {
78 VEC_DATA_TYPE(DATA_TYPE, VEC_SIZE)
79 val = VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor3D_offset(input, i, j, pz));
80 curr_max = fmax(val, curr_max);
81 }
82 for(; i < region_end_x; ++i)
83 {
84 DATA_TYPE val = *(__global DATA_TYPE *)tensor3D_offset(input, i, j, pz);
85 curr_max = fmax(curr_max, val);
86 }
87 }
88 return (DATA_TYPE)VEC_MAX(curr_max);
89 }
90}
91
92/** Performs a roi pooling function.
93 *
94 * @note Datatype must be passed using -DDATA_TYPE e.g. -DDATA_TYPE=float. Supported data types are F16, F32;
95 * @note Datasize must be passed using -DDATA_SIZE e.g. -DDATA_SIZE=32;
96 * @note Input dimensions must be passed using -DMAX_DIM_X, -DMAX_DIM_Y and -DMAX_DIM_Z;
97 * @note Pooled region dimensions must be passed using -DPOOLED_DIM_X and -DPOOLED_DIM_Y;
98 * @note Spatial scale must be passed using -DSPATIAL_SCALE;
99 *
100 * @param[in] input_ptr Pointer to the source image. Supported data types: F16, F32
101 * @param[in] input_stride_x Stride of the source image in X dimension (in bytes)
102 * @param[in] input_step_x input_stride_x * number of elements along X processed per workitem(in bytes)
103 * @param[in] input_stride_y Stride of the source image in Y dimension (in bytes)
104 * @param[in] input_step_y input_stride_y * number of elements along Y processed per workitem(in bytes)
105 * @param[in] input_stride_z Stride of the source tensor in Z dimension (in bytes)
106 * @param[in] input_step_z input_stride_z * number of elements along Z processed per workitem(in bytes)
107 * @param[in] input_offset_first_element_in_bytes The offset of the first element in the pooled region of the source image as specifed by ROI
108 * @param[in] rois_ptr Pointer to the rois array. Layout: {x, y, width, height, batch_indx}
109 * @param[in] rois_stride_x Stride of the rois array in X dimension (in bytes)
110 * @param[in] rois_step_x rois_stride_x * number of elements along X processed per workitem(in bytes)
111 * @param[in] rois_offset_first_element_in_bytes The offset of the first element in the rois array
112 * @param[out] output_ptr Pointer to the destination image. Supported data types: F16, F32
113 * @param[in] output_stride_x Stride of the destination image in X dimension (in bytes)
114 * @param[in] output_step_x output_stride_x * number of elements along X processed per workitem(in bytes)
115 * @param[in] output_stride_y Stride of the destination image in Y dimension (in bytes)
116 * @param[in] output_step_y output_stride_y * number of elements along Y processed per workitem(in bytes)
117 * @param[in] output_stride_z Stride of the destination tensor in Z dimension (in bytes)
118 * @param[in] output_step_z output_stride_z * number of elements along Z processed per workitem(in bytes)
119 * @param[in] output_offset_first_element_in_bytes The offset of the first element in the destination image
120 * @param[in] input_stride_w Stride of the source image in W dimension (in bytes)
121 * @param[in] output_stride_w Stride of the destination image in W dimension (in bytes)
122 */
123__kernel void roi_pooling_layer(
124 TENSOR3D_DECLARATION(input),
125 VECTOR_DECLARATION(rois),
126 TENSOR3D_DECLARATION(output),
127 unsigned int input_stride_w, unsigned int output_stride_w)
128{
129 // Get pixels pointer
130 Tensor3D input = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(input);
131 Vector rois = CONVERT_TO_VECTOR_STRUCT_NO_STEP(rois);
132 Tensor3D output = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output);
133
134 const int px = get_global_id(0);
135 const int py = get_global_id(1);
136 const int pw = get_global_id(2);
137
138 // Load roi parameters
139 // roi is laid out as follows:
140 // { x, y, width, height, batch_index }
SiCong Licfb65532017-09-12 19:06:28 +0100141 const ushort4 roi = vload4(0, (__global ushort *)vector_offset(&rois, pw));
142 const ushort roi_batch = *((__global ushort *)vector_offset(&rois, pw) + 4);
143 const int2 roi_anchor = convert_int2_sat(round(convert_float2(roi.s01) * (float)SPATIAL_SCALE));
144 const int2 roi_dims = convert_int2_sat(fmax(round(convert_float2(roi.s23) * (float)SPATIAL_SCALE), 1.f));
SiCong Li3e363692017-07-04 15:02:10 +0100145
146 // Calculate pooled region start and end
147 const float2 spatial_indx = (float2)(px, py);
SiCong Licfb65532017-09-12 19:06:28 +0100148 const float2 pooled_dims = (float2)(POOLED_DIM_X, POOLED_DIM_Y);
SiCong Li3e363692017-07-04 15:02:10 +0100149 const int2 max_spatial_dims = (int2)(MAX_DIM_X, MAX_DIM_Y);
SiCong Licfb65532017-09-12 19:06:28 +0100150 int2 region_start = convert_int2_sat(floor(spatial_indx / pooled_dims * convert_float2(roi_dims))) + roi_anchor;
151 int2 region_end = convert_int2_sat(floor((spatial_indx + 1) / pooled_dims * convert_float2(roi_dims))) + roi_anchor;
SiCong Li3e363692017-07-04 15:02:10 +0100152
153 region_start = clamp(region_start, 0, max_spatial_dims);
154 region_end = clamp(region_end, 0, max_spatial_dims);
155
156 // Move input and output pointer across the fourth dimension
SiCong Licfb65532017-09-12 19:06:28 +0100157 input.ptr += roi_batch * input_stride_w;
SiCong Li3e363692017-07-04 15:02:10 +0100158 output.ptr += pw * output_stride_w;
159
160 for(int pz = 0; pz < MAX_DIM_Z; ++pz)
161 {
162 *(__global DATA_TYPE *)tensor3D_offset(&output, px, py, pz) = (__global DATA_TYPE)roi_pool_1x1(&input,
163 region_start.x,
164 region_end.x,
165 region_start.y,
166 region_end.y, pz);
167 }
168}