Compute Library
 21.08
ROIPoolingLayer.cpp
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1 /*
2  * Copyright (c) 2021 Arm Limited.
3  *
4  * SPDX-License-Identifier: MIT
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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,
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22  * SOFTWARE.
23  */
24 
25 #include "ROIPoolingLayer.h"
26 #include "arm_compute/core/Types.h"
29 #include <algorithm>
30 
31 namespace arm_compute
32 {
33 namespace test
34 {
35 namespace validation
36 {
37 namespace reference
38 {
39 template <>
41 {
42  ARM_COMPUTE_UNUSED(output_qinfo);
43 
44  const size_t num_rois = rois.shape()[1];
45  const size_t values_per_roi = rois.shape()[0];
46  DataType output_data_type = src.data_type();
47 
49  TensorShape output_shape(pool_info.pooled_width(), pool_info.pooled_height(), src.shape()[2], num_rois);
50  SimpleTensor<float> output(output_shape, output_data_type);
51 
52  const int pooled_w = pool_info.pooled_width();
53  const int pooled_h = pool_info.pooled_height();
54  const float spatial_scale = pool_info.spatial_scale();
55 
56  // get sizes of x and y dimensions in src tensor
57  const int width = src.shape()[0];
58  const int height = src.shape()[1];
59 
60  // Move pointer across the fourth dimension
61  const size_t input_stride_w = input_shape[0] * input_shape[1] * input_shape[2];
62  const size_t output_stride_w = output_shape[0] * output_shape[1] * output_shape[2];
63 
64  const auto *rois_ptr = reinterpret_cast<const uint16_t *>(rois.data());
65 
66  // Iterate through pixel width (X-Axis)
67  for(size_t pw = 0; pw < num_rois; ++pw)
68  {
69  const unsigned int roi_batch = rois_ptr[values_per_roi * pw];
70  const auto x1 = rois_ptr[values_per_roi * pw + 1];
71  const auto y1 = rois_ptr[values_per_roi * pw + 2];
72  const auto x2 = rois_ptr[values_per_roi * pw + 3];
73  const auto y2 = rois_ptr[values_per_roi * pw + 4];
74 
75  //Iterate through pixel height (Y-Axis)
76  for(size_t fm = 0; fm < input_shape[2]; ++fm)
77  {
78  // Iterate through regions of interest index
79  for(size_t py = 0; py < pool_info.pooled_height(); ++py)
80  {
81  // Scale ROI
82  const int roi_anchor_x = support::cpp11::round(x1 * spatial_scale);
83  const int roi_anchor_y = support::cpp11::round(y1 * spatial_scale);
84  const int roi_width = std::max(support::cpp11::round((x2 - x1) * spatial_scale), 1.f);
85  const int roi_height = std::max(support::cpp11::round((y2 - y1) * spatial_scale), 1.f);
86 
87  // Iterate over feature map (Z axis)
88  for(size_t px = 0; px < pool_info.pooled_width(); ++px)
89  {
90  auto region_start_x = static_cast<int>(std::floor((static_cast<float>(px) / pooled_w) * roi_width));
91  auto region_end_x = static_cast<int>(std::floor((static_cast<float>(px + 1) / pooled_w) * roi_width));
92  auto region_start_y = static_cast<int>(std::floor((static_cast<float>(py) / pooled_h) * roi_height));
93  auto region_end_y = static_cast<int>(std::floor((static_cast<float>(py + 1) / pooled_h) * roi_height));
94 
95  region_start_x = std::min(std::max(region_start_x + roi_anchor_x, 0), width);
96  region_end_x = std::min(std::max(region_end_x + roi_anchor_x, 0), width);
97  region_start_y = std::min(std::max(region_start_y + roi_anchor_y, 0), height);
98  region_end_y = std::min(std::max(region_end_y + roi_anchor_y, 0), height);
99 
100  // Iterate through the pooling region
101  if((region_end_x <= region_start_x) || (region_end_y <= region_start_y))
102  {
103  /* Assign element in tensor 'output' at coordinates px, py, fm, roi_indx, to 0 */
104  auto out_ptr = output.data() + px + py * output_shape[0] + fm * output_shape[0] * output_shape[1] + pw * output_stride_w;
105  *out_ptr = 0;
106  }
107  else
108  {
109  float curr_max = -std::numeric_limits<float>::max();
110  for(int j = region_start_y; j < region_end_y; ++j)
111  {
112  for(int i = region_start_x; i < region_end_x; ++i)
113  {
114  /* Retrieve element from input tensor at coordinates(i, j, fm, roi_batch) */
115  float in_element = *(src.data() + i + j * input_shape[0] + fm * input_shape[0] * input_shape[1] + roi_batch * input_stride_w);
116  curr_max = std::max(in_element, curr_max);
117  }
118  }
119 
120  /* Assign element in tensor 'output' at coordinates px, py, fm, roi_indx, to curr_max */
121  auto out_ptr = output.data() + px + py * output_shape[0] + fm * output_shape[0] * output_shape[1] + pw * output_stride_w;
122  *out_ptr = curr_max;
123  }
124  }
125  }
126  }
127  }
128 
129  return output;
130 }
131 
132 /*
133  Template genericised method to allow calling of roi_pooling_layer with quantized 8 bit datatype
134 */
135 template <>
137 {
138  const SimpleTensor<float> src_tmp = convert_from_asymmetric(src);
139  SimpleTensor<float> dst_tmp = roi_pool_layer<float>(src_tmp, rois, pool_info, output_qinfo);
140  SimpleTensor<uint8_t> dst = convert_to_asymmetric<uint8_t>(dst_tmp, output_qinfo);
141  return dst;
142 }
143 
144 } // namespace reference
145 } // namespace validation
146 } // namespace test
147 } // namespace arm_compute
Shape of a tensor.
Definition: TensorShape.h:39
DataType data_type() const override
Data type of the tensor.
Definition: SimpleTensor.h:357
SimpleTensor< float > convert_from_asymmetric(const SimpleTensor< uint8_t > &src)
Definition: Helpers.cpp:36
TensorShape shape() const override
Shape of the tensor.
Definition: SimpleTensor.h:320
unsigned int pooled_width() const
Get the pooled width of the layer.
Definition: Types.h:1249
SimpleTensor< float > src
Definition: DFT.cpp:155
Copyright (c) 2017-2021 Arm Limited.
Quantization information.
TensorShape input_shape
Validate test suite is to test ARM_COMPUTE_RETURN_ON_* macros we use to check the validity of given a...
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
Simple tensor object that stores elements in a consecutive chunk of memory.
Definition: SimpleTensor.h:58
unsigned int pooled_height() const
Get the pooled height of the layer.
Definition: Types.h:1254
ROI Pooling Layer Information class.
Definition: Types.h:1234
T round(T value)
Round floating-point value with half value rounding away from zero.
float spatial_scale() const
Get the spatial scale.
Definition: Types.h:1259
SimpleTensor< float > roi_pool_layer(const SimpleTensor< float > &src, const SimpleTensor< uint16_t > &rois, const ROIPoolingLayerInfo &pool_info, const QuantizationInfo &output_qinfo)
DataType
Available data types.
Definition: Types.h:77
const T * data() const
Constant pointer to the underlying buffer.
Definition: SimpleTensor.h:418