Compute Library
 21.02
NEBoundingBoxTransformKernel.cpp
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1 /*
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25 
28 #include "arm_compute/core/Utils.h"
31 #include "src/core/CPP/Validate.h"
34 
35 #include <arm_neon.h>
36 
37 namespace arm_compute
38 {
39 namespace
40 {
41 Status validate_arguments(const ITensorInfo *boxes, const ITensorInfo *pred_boxes, const ITensorInfo *deltas, const BoundingBoxTransformInfo &info)
42 {
43  ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(boxes, pred_boxes, deltas);
47  ARM_COMPUTE_RETURN_ERROR_ON(deltas->tensor_shape()[1] != boxes->tensor_shape()[1]);
48  ARM_COMPUTE_RETURN_ERROR_ON(deltas->tensor_shape()[0] % 4 != 0);
49  ARM_COMPUTE_RETURN_ERROR_ON(boxes->tensor_shape()[0] != 4);
50  ARM_COMPUTE_RETURN_ERROR_ON(deltas->num_dimensions() > 2);
51  ARM_COMPUTE_RETURN_ERROR_ON(boxes->num_dimensions() > 2);
52  ARM_COMPUTE_RETURN_ERROR_ON(info.scale() <= 0);
53 
54  if(boxes->data_type() == DataType::QASYMM16)
55  {
57  const UniformQuantizationInfo deltas_qinfo = deltas->quantization_info().uniform();
58  ARM_COMPUTE_RETURN_ERROR_ON(deltas_qinfo.scale != 0.125f);
59  ARM_COMPUTE_RETURN_ERROR_ON(deltas_qinfo.offset != 0);
60  }
61  else
62  {
64  }
65 
66  if(pred_boxes->total_size() > 0)
67  {
68  ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(pred_boxes->tensor_shape(), deltas->tensor_shape());
70  ARM_COMPUTE_RETURN_ERROR_ON(pred_boxes->num_dimensions() > 2);
71  if(pred_boxes->data_type() == DataType::QASYMM16)
72  {
73  const UniformQuantizationInfo pred_qinfo = pred_boxes->quantization_info().uniform();
74  ARM_COMPUTE_RETURN_ERROR_ON(pred_qinfo.scale != 0.125f);
75  ARM_COMPUTE_RETURN_ERROR_ON(pred_qinfo.offset != 0);
76  }
77  }
78 
79  return Status{};
80 }
81 } // namespace
82 
84  : _boxes(nullptr), _pred_boxes(nullptr), _deltas(nullptr), _bbinfo(0, 0, 0)
85 {
86 }
87 
88 void NEBoundingBoxTransformKernel::configure(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, const BoundingBoxTransformInfo &info)
89 {
90  ARM_COMPUTE_ERROR_ON_NULLPTR(boxes, pred_boxes, deltas);
91  ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(boxes->info(), pred_boxes->info(), deltas->info(), info));
92 
93  // Configure kernel window
94  auto_init_if_empty(*pred_boxes->info(), deltas->info()->clone()->set_data_type(boxes->info()->data_type()).set_quantization_info(boxes->info()->quantization_info()));
95 
96  // Set instance variables
97  _boxes = boxes;
98  _pred_boxes = pred_boxes;
99  _deltas = deltas;
100  _bbinfo = info;
101 
102  const unsigned int num_boxes = boxes->info()->dimension(1);
103  Window win = calculate_max_window(*pred_boxes->info(), Steps());
104  Coordinates coord;
105  coord.set_num_dimensions(pred_boxes->info()->num_dimensions());
106  pred_boxes->info()->set_valid_region(ValidRegion(coord, pred_boxes->info()->tensor_shape()));
107  win.set(Window::DimX, Window::Dimension(0, 1u));
108  win.set(Window::DimY, Window::Dimension(0, num_boxes));
109 
110  INEKernel::configure(win);
111 }
112 
114 {
115  ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(boxes, pred_boxes, deltas, info));
116  return Status{};
117 }
118 
119 template <>
120 void NEBoundingBoxTransformKernel::internal_run<uint16_t>(const Window &window)
121 {
122  const size_t num_classes = _deltas->info()->tensor_shape()[0] >> 2;
123  const size_t deltas_width = _deltas->info()->tensor_shape()[0];
124  const int img_h = std::floor(_bbinfo.img_height() / _bbinfo.scale() + 0.5f);
125  const int img_w = std::floor(_bbinfo.img_width() / _bbinfo.scale() + 0.5f);
126 
127  const auto scale_after = (_bbinfo.apply_scale() ? _bbinfo.scale() : 1.f);
128  const auto scale_before = _bbinfo.scale();
129  const auto offset = (_bbinfo.correct_transform_coords() ? 1.f : 0.f);
130 
131  auto pred_ptr = reinterpret_cast<uint16_t *>(_pred_boxes->buffer() + _pred_boxes->info()->offset_first_element_in_bytes());
132  auto delta_ptr = reinterpret_cast<uint8_t *>(_deltas->buffer() + _deltas->info()->offset_first_element_in_bytes());
133 
134  const auto boxes_qinfo = _boxes->info()->quantization_info().uniform();
135  const auto deltas_qinfo = _deltas->info()->quantization_info().uniform();
136  const auto pred_qinfo = _pred_boxes->info()->quantization_info().uniform();
137 
138  Iterator box_it(_boxes, window);
139  execute_window_loop(window, [&](const Coordinates & id)
140  {
141  const auto ptr = reinterpret_cast<uint16_t *>(box_it.ptr());
142  const auto b0 = dequantize_qasymm16(*ptr, boxes_qinfo);
143  const auto b1 = dequantize_qasymm16(*(ptr + 1), boxes_qinfo);
144  const auto b2 = dequantize_qasymm16(*(ptr + 2), boxes_qinfo);
145  const auto b3 = dequantize_qasymm16(*(ptr + 3), boxes_qinfo);
146  const float width = (b2 / scale_before) - (b0 / scale_before) + 1.f;
147  const float height = (b3 / scale_before) - (b1 / scale_before) + 1.f;
148  const float ctr_x = (b0 / scale_before) + 0.5f * width;
149  const float ctr_y = (b1 / scale_before) + 0.5f * height;
150  for(size_t j = 0; j < num_classes; ++j)
151  {
152  // Extract deltas
153  const size_t delta_id = id.y() * deltas_width + 4u * j;
154  const float dx = dequantize_qasymm8(delta_ptr[delta_id], deltas_qinfo) / _bbinfo.weights()[0];
155  const float dy = dequantize_qasymm8(delta_ptr[delta_id + 1], deltas_qinfo) / _bbinfo.weights()[1];
156  float dw = dequantize_qasymm8(delta_ptr[delta_id + 2], deltas_qinfo) / _bbinfo.weights()[2];
157  float dh = dequantize_qasymm8(delta_ptr[delta_id + 3], deltas_qinfo) / _bbinfo.weights()[3];
158  // Clip dw and dh
159  dw = std::min(dw, _bbinfo.bbox_xform_clip());
160  dh = std::min(dh, _bbinfo.bbox_xform_clip());
161  // Determine the predictions
162  const float pred_ctr_x = dx * width + ctr_x;
163  const float pred_ctr_y = dy * height + ctr_y;
164  const float pred_w = std::exp(dw) * width;
165  const float pred_h = std::exp(dh) * height;
166  // Store the prediction into the output tensor
167  pred_ptr[delta_id] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_x - 0.5f * pred_w, 0.f, img_w - 1.f), pred_qinfo);
168  pred_ptr[delta_id + 1] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_y - 0.5f * pred_h, 0.f, img_h - 1.f), pred_qinfo);
169  pred_ptr[delta_id + 2] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_x + 0.5f * pred_w - offset, 0.f, img_w - 1.f), pred_qinfo);
170  pred_ptr[delta_id + 3] = quantize_qasymm16(scale_after * utility::clamp<float>(pred_ctr_y + 0.5f * pred_h - offset, 0.f, img_h - 1.f), pred_qinfo);
171  }
172  },
173  box_it);
174 }
175 
176 template <typename T>
177 void NEBoundingBoxTransformKernel::internal_run(const Window &window)
178 {
179  const size_t num_classes = _deltas->info()->tensor_shape()[0] >> 2;
180  const size_t deltas_width = _deltas->info()->tensor_shape()[0];
181  const int img_h = std::floor(_bbinfo.img_height() / _bbinfo.scale() + 0.5f);
182  const int img_w = std::floor(_bbinfo.img_width() / _bbinfo.scale() + 0.5f);
183 
184  const auto scale_after = (_bbinfo.apply_scale() ? T(_bbinfo.scale()) : T(1));
185  const auto scale_before = T(_bbinfo.scale());
186  ARM_COMPUTE_ERROR_ON(scale_before <= 0);
187  const auto offset = (_bbinfo.correct_transform_coords() ? T(1.f) : T(0.f));
188 
189  auto pred_ptr = reinterpret_cast<T *>(_pred_boxes->buffer() + _pred_boxes->info()->offset_first_element_in_bytes());
190  auto delta_ptr = reinterpret_cast<T *>(_deltas->buffer() + _deltas->info()->offset_first_element_in_bytes());
191 
192  Iterator box_it(_boxes, window);
193  execute_window_loop(window, [&](const Coordinates & id)
194  {
195  const auto ptr = reinterpret_cast<T *>(box_it.ptr());
196  const auto b0 = *ptr;
197  const auto b1 = *(ptr + 1);
198  const auto b2 = *(ptr + 2);
199  const auto b3 = *(ptr + 3);
200  const T width = (b2 / scale_before) - (b0 / scale_before) + T(1.f);
201  const T height = (b3 / scale_before) - (b1 / scale_before) + T(1.f);
202  const T ctr_x = (b0 / scale_before) + T(0.5f) * width;
203  const T ctr_y = (b1 / scale_before) + T(0.5f) * height;
204  for(size_t j = 0; j < num_classes; ++j)
205  {
206  // Extract deltas
207  const size_t delta_id = id.y() * deltas_width + 4u * j;
208  const T dx = delta_ptr[delta_id] / T(_bbinfo.weights()[0]);
209  const T dy = delta_ptr[delta_id + 1] / T(_bbinfo.weights()[1]);
210  T dw = delta_ptr[delta_id + 2] / T(_bbinfo.weights()[2]);
211  T dh = delta_ptr[delta_id + 3] / T(_bbinfo.weights()[3]);
212  // Clip dw and dh
213  dw = std::min(dw, T(_bbinfo.bbox_xform_clip()));
214  dh = std::min(dh, T(_bbinfo.bbox_xform_clip()));
215  // Determine the predictions
216  const T pred_ctr_x = dx * width + ctr_x;
217  const T pred_ctr_y = dy * height + ctr_y;
218  const T pred_w = std::exp(dw) * width;
219  const T pred_h = std::exp(dh) * height;
220  // Store the prediction into the output tensor
221  pred_ptr[delta_id] = scale_after * utility::clamp<T>(pred_ctr_x - T(0.5f) * pred_w, T(0), T(img_w - 1));
222  pred_ptr[delta_id + 1] = scale_after * utility::clamp<T>(pred_ctr_y - T(0.5f) * pred_h, T(0), T(img_h - 1));
223  pred_ptr[delta_id + 2] = scale_after * utility::clamp<T>(pred_ctr_x + T(0.5f) * pred_w - offset, T(0), T(img_w - 1));
224  pred_ptr[delta_id + 3] = scale_after * utility::clamp<T>(pred_ctr_y + T(0.5f) * pred_h - offset, T(0), T(img_h - 1));
225  }
226  },
227  box_it);
228 }
229 
230 void NEBoundingBoxTransformKernel::run(const Window &window, const ThreadInfo &info)
231 {
232  ARM_COMPUTE_UNUSED(info);
235  switch(_boxes->info()->data_type())
236  {
237  case DataType::F32:
238  {
239  internal_run<float>(window);
240  break;
241  }
242  case DataType::QASYMM16:
243  {
244  internal_run<uint16_t>(window);
245  break;
246  }
247 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
248  case DataType::F16:
249  {
250  internal_run<float16_t>(window);
251  break;
252  }
253 #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
254  default:
255  {
256  ARM_COMPUTE_ERROR("Data type not supported");
257  }
258  }
259 }
260 } // namespace arm_compute
__global uchar * offset(const Image *img, int x, int y)
Get the pointer position of a Image.
Definition: helpers.h:846
virtual size_t num_dimensions() const =0
The number of dimensions of the tensor (rank)
Window calculate_max_window(const ValidRegion &valid_region, const Steps &steps, bool skip_border, BorderSize border_size)
const Window & window() const
The maximum window the kernel can be executed on.
Definition: IKernel.cpp:28
#define ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(tensor)
Definition: Validate.h:108
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.
#define ARM_COMPUTE_ERROR(msg)
Print the given message then throw an std::runtime_error.
Definition: Error.h:352
#define ARM_COMPUTE_RETURN_ON_ERROR(status)
Checks if a status contains an error and returns it.
Definition: Error.h:204
virtual DataType data_type() const =0
Data type used for each element of the tensor.
1 channel, 1 F32 per channel
void configure(const ITensor *boxes, ITensor *pred_boxes, const ITensor *deltas, const BoundingBoxTransformInfo &info)
Set the input and output tensors.
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:466
Store the tensor&#39;s metadata.
Definition: ITensorInfo.h:40
#define ARM_COMPUTE_ERROR_THROW_ON(status)
Definition: Error.h:455
Describe one of the image&#39;s dimensions with a start, end and step.
Definition: Window.h:77
quantized, asymmetric fixed-point 16-bit number
Status class.
Definition: Error.h:52
#define ARM_COMPUTE_RETURN_ERROR_ON(cond)
If the condition is true, an error is returned.
Definition: Error.h:296
Interface for Neon tensor.
Definition: ITensor.h:36
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(...)
Definition: Validate.h:288
Copyright (c) 2017-2021 Arm Limited.
virtual void set_valid_region(const ValidRegion &valid_region)=0
Set the valid region of the tensor.
1 channel, 1 F16 per channel
#define ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(...)
Definition: Validate.h:163
float dequantize_qasymm16(uint16_t value, const UniformQuantizationInfo &qinfo)
Dequantize a value given a 16-bit asymmetric quantization scheme.
static constexpr size_t DimX
Alias for dimension 0 also known as X dimension.
Definition: Window.h:43
#define ARM_COMPUTE_UNUSED(...)
To avoid unused variables warnings.
Definition: Error.h:152
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
quantized, asymmetric fixed-point 8-bit number unsigned
Class to describe a number of elements in each dimension.
Definition: Steps.h:40
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. ...
void run(const Window &window, const ThreadInfo &info) override
Execute the kernel on the passed window.
UniformQuantizationInfo uniform() const
Return per layer quantization info.
bool auto_init_if_empty(ITensorInfo &info, const TensorShape &shape, int num_channels, DataType data_type, QuantizationInfo quantization_info=QuantizationInfo())
Auto initialize the tensor info (shape, number of channels and data type) if the current assignment i...
virtual std::unique_ptr< T > clone() const =0
Provide a clone of the current object of class T.
virtual ITensorInfo * info() const =0
Interface to be implemented by the child class to return the tensor&#39;s metadata.
constexpr uint8_t * ptr() const
Return a pointer to the current pixel.
Definition: Helpers.inl:139
void set(size_t dimension, const Dimension &dim)
Set the values of a given dimension.
Definition: Window.inl:49
Bounding Box Transform information class.
Definition: Types.h:1483
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
#define ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(k)
Definition: Validate.h:941
static Status validate(const ITensorInfo *boxes, const ITensorInfo *pred_boxes, const ITensorInfo *deltas, const BoundingBoxTransformInfo &info)
Static function to check if given info will lead to a valid configuration of CLBoundingBoxTransform.
virtual size_t offset_first_element_in_bytes() const =0
The offset from the beginning of the memory allocation to the first element of the tensor...
static constexpr size_t DimY
Alias for dimension 1 also known as Y dimension.
Definition: Window.h:45
ScaleKernelInfo info(interpolation_policy, default_border_mode, PixelValue(), sampling_policy, false)
Information about executing thread and CPU.
Definition: CPPTypes.h:235
#define ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(...)
Definition: Validate.h:545
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)
Definition: Validate.h:792
Status validate_arguments(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo *output_stage)
std::array< float, 4 > weights() const
Definition: Types.h:1504
#define ARM_COMPUTE_ERROR_ON_NULLPTR(...)
Definition: Validate.h:161
void execute_window_loop(const Window &w, L &&lambda_function, Ts &&... iterators)
Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...
Definition: Helpers.inl:77
void set_num_dimensions(size_t num_dimensions)
Set number of dimensions.
Definition: Dimensions.h:149
Container for valid region of a window.
Definition: Types.h:188
#define ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(t,...)
Definition: Validate.h:694
Iterator updated by execute_window_loop for each window element.
Definition: Helpers.h:46
Describe a multidimensional execution window.
Definition: Window.h:39
uint16_t quantize_qasymm16(float value, const UniformQuantizationInfo &qinfo, RoundingPolicy rounding_policy=RoundingPolicy::TO_NEAREST_UP)
Quantize a value given a 16-bit asymmetric quantization scheme.
#define ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(f, s)
Definition: Validate.h:205