Compute Library
 22.05
impl.cpp
Go to the documentation of this file.
1 /*
2  * Copyright (c) 2019-2022 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  */
26 namespace arm_compute
27 {
28 namespace cpu
29 {
30 /** Average pooling over an aligned window */
31 template <typename input_data_type>
32 inline input_data_type roi_align_1x1(const ITensor *input,
33  unsigned int roi_batch,
34  float region_start_x,
35  float bin_size_x,
36  int grid_size_x,
37  float region_end_x,
38  float region_start_y,
39  float bin_size_y,
40  int grid_size_y,
41  float region_end_y,
42  int pz)
43 {
44  if((region_end_x <= region_start_x) || (region_end_y <= region_start_y))
45  {
46  return input_data_type(0);
47  }
48  else
49  {
50  const DataLayout data_layout = input->info()->data_layout();
51  float avg = 0;
52  // Iterate through the aligned pooling region
53  for(int iy = 0; iy < grid_size_y; ++iy)
54  {
55  for(int ix = 0; ix < grid_size_x; ++ix)
56  {
57  // Align the window in the middle of every bin
58  float y = region_start_y + (iy + 0.5) * bin_size_y / float(grid_size_y);
59  float x = region_start_x + (ix + 0.5) * bin_size_x / float(grid_size_x);
60 
61  // Interpolation in the [0,0] [0,1] [1,0] [1,1] square
62  const int y_low = y;
63  const int x_low = x;
64  const int y_high = y_low + 1;
65  const int x_high = x_low + 1;
66 
67  const float ly = y - y_low;
68  const float lx = x - x_low;
69  const float hy = 1. - ly;
70  const float hx = 1. - lx;
71 
72  const float w1 = hy * hx;
73  const float w2 = hy * lx;
74  const float w3 = ly * hx;
75  const float w4 = ly * lx;
76  if(data_layout == DataLayout::NCHW)
77  {
78  const auto data1 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch)));
79  const auto data2 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch)));
80  const auto data3 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch)));
81  const auto data4 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch)));
82  avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
83  }
84  else
85  {
86  const auto data1 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch)));
87  const auto data2 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch)));
88  const auto data3 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch)));
89  const auto data4 = *reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch)));
90  avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
91  }
92  }
93  }
94 
95  avg /= grid_size_x * grid_size_y;
96  return input_data_type(avg);
97  }
98 }
99 
100 /** Average pooling over an aligned window */
101 template <typename input_data_type>
102 inline input_data_type roi_align_1x1_qasymm8(const ITensor *input,
103  unsigned int roi_batch,
104  float region_start_x,
105  float bin_size_x,
106  int grid_size_x,
107  float region_end_x,
108  float region_start_y,
109  float bin_size_y,
110  int grid_size_y,
111  float region_end_y,
112  int pz,
113  const QuantizationInfo &out_qinfo)
114 {
115  if((region_end_x <= region_start_x) || (region_end_y <= region_start_y))
116  {
117  return input_data_type(out_qinfo.uniform().offset);
118  }
119  else
120  {
121  float avg = 0;
122  const UniformQuantizationInfo input_qinfo = input->info()->quantization_info().uniform();
123  const bool is_qasymm_signed = is_data_type_quantized_asymmetric_signed(input->info()->data_type());
124  const DataLayout data_layout = input->info()->data_layout();
125 
126  // Iterate through the aligned pooling region
127  for(int iy = 0; iy < grid_size_y; ++iy)
128  {
129  for(int ix = 0; ix < grid_size_x; ++ix)
130  {
131  // Align the window in the middle of every bin
132  float y = region_start_y + (iy + 0.5) * bin_size_y / float(grid_size_y);
133  float x = region_start_x + (ix + 0.5) * bin_size_x / float(grid_size_x);
134 
135  // Interpolation in the [0,0] [0,1] [1,0] [1,1] square
136  const int y_low = y;
137  const int x_low = x;
138  const int y_high = y_low + 1;
139  const int x_high = x_low + 1;
140 
141  const float ly = y - y_low;
142  const float lx = x - x_low;
143  const float hy = 1. - ly;
144  const float hx = 1. - lx;
145 
146  const float w1 = hy * hx;
147  const float w2 = hy * lx;
148  const float w3 = ly * hx;
149  const float w4 = ly * lx;
150 
151  if(data_layout == DataLayout::NCHW)
152  {
153  if(is_qasymm_signed)
154  {
155  float data1 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))), input_qinfo);
156  float data2 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))), input_qinfo);
157  float data3 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))), input_qinfo);
158  float data4 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))), input_qinfo);
159  avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
160  }
161  else
162  {
163  float data1 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_low, y_low, pz, roi_batch))), input_qinfo);
164  float data2 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_high, y_low, pz, roi_batch))), input_qinfo);
165  float data3 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_low, y_high, pz, roi_batch))), input_qinfo);
166  float data4 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(x_high, y_high, pz, roi_batch))), input_qinfo);
167  avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
168  }
169  }
170  else
171  {
172  if(is_qasymm_signed)
173  {
174  const auto data1 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))), input_qinfo);
175  const auto data2 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))), input_qinfo);
176  const auto data3 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))), input_qinfo);
177  const auto data4 = dequantize_qasymm8_signed(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))), input_qinfo);
178  avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
179  }
180  else
181  {
182  const auto data1 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_low, y_low, roi_batch))), input_qinfo);
183  const auto data2 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_high, y_low, roi_batch))), input_qinfo);
184  const auto data3 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_low, y_high, roi_batch))), input_qinfo);
185  const auto data4 = dequantize_qasymm8(*reinterpret_cast<const input_data_type *>(input->ptr_to_element(Coordinates(pz, x_high, y_high, roi_batch))), input_qinfo);
186  avg += w1 * data1 + w2 * data2 + w3 * data3 + w4 * data4;
187  }
188  }
189  }
190  }
191 
192  avg /= grid_size_x * grid_size_y;
193 
194  input_data_type res = 0;
195  if(is_qasymm_signed)
196  {
197  res = quantize_qasymm8_signed(avg, out_qinfo);
198  }
199  else
200  {
201  res = quantize_qasymm8(avg, out_qinfo);
202  }
203  return res;
204  }
205 }
206 inline float compute_region_coordinate(int p, float bin_size, float roi_anchor, float max_value)
207 {
208  const float region_start = p * bin_size + roi_anchor;
209  return utility::clamp(region_start, 0.0f, max_value);
210 }
211 
212 template <typename input_data_type, typename roi_data_type>
213 void roi_align(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info)
214 {
215  ARM_COMPUTE_UNUSED(info);
216 
217  const DataLayout data_layout = input->info()->data_layout();
218  const size_t values_per_roi = rois->info()->dimension(0);
219 
220  const int roi_list_start = window.x().start();
221  const int roi_list_end = window.x().end();
222 
223  const unsigned int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
225  const unsigned int idx_depth = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL);
226 
227  const int input_width = input->info()->dimension(idx_width);
228  const int input_height = input->info()->dimension(idx_height);
229  const int input_chanels = input->info()->dimension(idx_depth);
230  const int pooled_w = pool_info.pooled_width();
231  const int pooled_h = pool_info.pooled_height();
232 
233  const DataType data_type = input->info()->data_type();
234  const bool is_qasymm = is_data_type_quantized_asymmetric(data_type);
235 
236  const auto *rois_ptr = reinterpret_cast<const roi_data_type *>(rois->buffer());
237  const QuantizationInfo &rois_qinfo = rois->info()->quantization_info();
238  for(int roi_indx = roi_list_start; roi_indx < roi_list_end; ++roi_indx)
239  {
240  const unsigned int roi_batch = rois_ptr[values_per_roi * roi_indx];
241 
242  roi_data_type qx1 = rois_ptr[values_per_roi * roi_indx + 1];
243  roi_data_type qy1 = rois_ptr[values_per_roi * roi_indx + 2];
244  roi_data_type qx2 = rois_ptr[values_per_roi * roi_indx + 3];
245  roi_data_type qy2 = rois_ptr[values_per_roi * roi_indx + 4];
246  float x1(qx1);
247  float x2(qx2);
248  float y1(qy1);
249  float y2(qy2);
250  if(is_qasymm)
251  {
252  x1 = dequantize_qasymm16(qx1, rois_qinfo);
253  x2 = dequantize_qasymm16(qx2, rois_qinfo);
254  y1 = dequantize_qasymm16(qy1, rois_qinfo);
255  y2 = dequantize_qasymm16(qy2, rois_qinfo);
256  }
257  const float roi_anchor_x = x1 * pool_info.spatial_scale();
258  const float roi_anchor_y = y1 * pool_info.spatial_scale();
259  const float roi_dims_x = std::max((x2 - x1) * pool_info.spatial_scale(), 1.0f);
260  const float roi_dims_y = std::max((y2 - y1) * pool_info.spatial_scale(), 1.0f);
261  float bin_size_x = roi_dims_x / pool_info.pooled_width();
262  float bin_size_y = roi_dims_y / pool_info.pooled_height();
263 
264  // Iterate through all feature maps
265  for(int ch = 0; ch < input_chanels; ++ch)
266  {
267  // Iterate through all output pixels
268  for(int py = 0; py < pooled_h; ++py)
269  {
270  for(int px = 0; px < pooled_w; ++px)
271  {
272  const float region_start_x = compute_region_coordinate(px, bin_size_x, roi_anchor_x, input_width);
273  const float region_start_y = compute_region_coordinate(py, bin_size_y, roi_anchor_y, input_height);
274  const float region_end_x = compute_region_coordinate(px + 1, bin_size_x, roi_anchor_x, input_width);
275  const float region_end_y = compute_region_coordinate(py + 1, bin_size_y, roi_anchor_y, input_height);
276  const int roi_bin_grid_x = (pool_info.sampling_ratio() > 0) ? pool_info.sampling_ratio() : int(ceil(bin_size_x));
277  const int roi_bin_grid_y = (pool_info.sampling_ratio() > 0) ? pool_info.sampling_ratio() : int(ceil(bin_size_y));
278  input_data_type out_val(0);
279  if(is_qasymm)
280  {
281  out_val = roi_align_1x1_qasymm8<input_data_type>(
282  input, roi_batch, region_start_x, bin_size_x,
283  roi_bin_grid_x, region_end_x, region_start_y, bin_size_y,
284  roi_bin_grid_y, region_end_y, ch, output->info()->quantization_info());
285  }
286  else
287  {
288  out_val = roi_align_1x1<input_data_type>(
289  input, roi_batch, region_start_x, bin_size_x,
290  roi_bin_grid_x, region_end_x, region_start_y, bin_size_y,
291  roi_bin_grid_y, region_end_y, ch);
292  }
293 
294  if(data_layout == DataLayout::NCHW)
295  {
296  auto out_ptr = reinterpret_cast<input_data_type *>(output->ptr_to_element(Coordinates(px, py, ch, roi_indx)));
297  *out_ptr = out_val;
298  }
299  else
300  {
301  auto out_ptr = reinterpret_cast<input_data_type *>(output->ptr_to_element(Coordinates(ch, px, py, roi_indx)));
302  *out_ptr = out_val;
303  }
304  }
305  }
306  }
307  }
308 }
309 template void roi_align<float, float>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
310 template void roi_align<uint8_t, uint16_t>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
311 template void roi_align<int8_t, uint16_t>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
312 #if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
313 template void roi_align<float16_t, float16_t>(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info);
314 #endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(ENABLE_FP16_KERNELS)
315 } // namespace cpu
316 } // namespace arm_compute
uint8_t * ptr_to_element(const Coordinates &id) const
Return a pointer to the element at the passed coordinates.
Definition: ITensor.h:63
float dequantize_qasymm8(uint8_t value, const INFO_TYPE &qinfo)
Dequantize a value given an unsigned 8-bit asymmetric quantization scheme.
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
uint8_t quantize_qasymm8(float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given an unsigned 8-bit asymmetric quantization scheme.
virtual DataType data_type() const =0
Data type used for each element of the tensor.
const size_t input_height
Definition: impl.cpp:61
input_data_type roi_align_1x1(const ITensor *input, unsigned int roi_batch, float region_start_x, float bin_size_x, int grid_size_x, float region_end_x, float region_start_y, float bin_size_y, int grid_size_y, float region_end_y, int pz)
Average pooling over an aligned window.
Definition: impl.cpp:32
Quantization info when assuming per layer quantization.
unsigned int pooled_width() const
Get the pooled width of the layer.
Definition: Types.h:1399
Interface for CPU tensor.
Definition: ITensor.h:36
const size_t input_width
Definition: impl.cpp:62
Copyright (c) 2017-2022 Arm Limited.
input_data_type roi_align_1x1_qasymm8(const ITensor *input, unsigned int roi_batch, float region_start_x, float bin_size_x, int grid_size_x, float region_end_x, float region_start_y, float bin_size_y, int grid_size_y, float region_end_y, int pz, const QuantizationInfo &out_qinfo)
Average pooling over an aligned window.
Definition: impl.cpp:102
DataType clamp(const DataType &n, const DataType &lower=std::numeric_limits< RangeType >::lowest(), const DataType &upper=std::numeric_limits< RangeType >::max())
Performs clamping among a lower and upper value.
Definition: Utility.h:101
float dequantize_qasymm16(uint16_t value, const UniformQuantizationInfo &qinfo)
Dequantize a value given a 16-bit asymmetric quantization scheme.
Quantization information.
float compute_region_coordinate(int p, float bin_size, float roi_anchor, float max_value)
Definition: impl.cpp:206
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
template void roi_align< float, float >(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info)
int8_t quantize_qasymm8_signed(float value, const INFO_TYPE &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given a signed 8-bit asymmetric quantization scheme.
Coordinates of an item.
Definition: Coordinates.h:37
virtual uint8_t * buffer() const =0
Interface to be implemented by the child class to return a pointer to CPU memory. ...
UniformQuantizationInfo uniform() const
Return per layer quantization info.
bool is_data_type_quantized_asymmetric_signed(DataType dt)
Check if a given data type is of asymmetric quantized signed type.
Definition: Utils.h:1071
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
unsigned int sampling_ratio() const
Get sampling ratio.
Definition: Types.h:1414
Num samples, channels, height, width.
bool is_data_type_quantized_asymmetric(DataType dt)
Check if a given data type is of asymmetric quantized type.
Definition: Utils.h:1052
template void roi_align< int8_t, uint16_t >(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info)
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
Information about executing thread and CPU.
Definition: CPPTypes.h:169
unsigned int pooled_height() const
Get the pooled height of the layer.
Definition: Types.h:1404
ROI Pooling Layer Information class.
Definition: Types.h:1384
size_t get_data_layout_dimension_index(const DataLayout &data_layout, const DataLayoutDimension &data_layout_dimension)
Get the index of the given dimension.
Definition: Helpers.inl:193
float spatial_scale() const
Get the spatial scale.
Definition: Types.h:1409
void roi_align(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info)
Definition: impl.cpp:213
float dequantize_qasymm8_signed(int8_t value, const INFO_TYPE &qinfo)
Dequantize a value given a signed 8-bit asymmetric quantization scheme.
constexpr int end() const
Return the end of the dimension.
Definition: Window.h:101
template void roi_align< uint8_t, uint16_t >(const ITensor *input, ITensor *output, const ITensor *rois, ROIPoolingLayerInfo pool_info, const Window &window, const ThreadInfo &info)
DataType
Available data types.
Definition: Types.h:79
DataLayout
[DataLayout enum definition]
Definition: Types.h:113
constexpr int start() const
Return the start of the dimension.
Definition: Window.h:96
Describe a multidimensional execution window.
Definition: Window.h:39
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.
constexpr const Dimension & x() const
Alias to access the first dimension of the window.
Definition: Window.h:158