Compute Library
 19.08
TensorInfo.cpp
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25 
26 #include "arm_compute/core/Error.h"
32 
33 using namespace arm_compute;
34 
36  : _total_size(0), _offset_first_element_in_bytes(0), _strides_in_bytes(), _num_channels(0), _tensor_shape(), _data_type(DataType::UNKNOWN), _format(Format::UNKNOWN), _is_resizable{ true },
37  _valid_region{ Coordinates(), _tensor_shape }, _padding{ 0 }, _quantization_info(), _data_layout(DataLayout::NCHW)
38 {
39 }
40 
42  : TensorInfo()
43 {
44  _total_size = info.total_size();
45  _offset_first_element_in_bytes = info.offset_first_element_in_bytes();
46  _strides_in_bytes = info.strides_in_bytes();
47  _num_channels = info.num_channels();
48  _tensor_shape = info.tensor_shape();
49  _data_type = info.data_type();
50  _format = info.format();
51  _is_resizable = info.is_resizable();
52  _valid_region = info.valid_region();
53  _padding = info.padding();
54  _quantization_info = info.quantization_info();
55  _data_layout = info.data_layout();
56 }
57 
59  : TensorInfo(TensorShape(), format)
60 {
61 }
62 
63 TensorInfo::TensorInfo(unsigned int width, unsigned int height, Format format)
64  : TensorInfo(TensorShape(width, height), format)
65 {
66 }
67 
68 TensorInfo::TensorInfo(const TensorShape &tensor_shape, Format format)
69  : TensorInfo()
70 {
72 }
73 
75  : TensorInfo()
76 {
78 }
79 
80 TensorInfo::TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type)
81  : TensorInfo()
82 {
84 }
85 
86 TensorInfo::TensorInfo(const TensorShape &tensor_shape, size_t num_channels, DataType data_type, QuantizationInfo quantization_info)
87  : TensorInfo()
88 {
90  _quantization_info = std::move(quantization_info);
91 }
92 
93 TensorInfo::TensorInfo(const HOGInfo &hog_info, unsigned int width, unsigned int height)
94  : TensorInfo()
95 {
96  init(hog_info, width, height);
97 }
98 
100 {
101  init(TensorShape(), format);
102 }
103 
104 void TensorInfo::init(const TensorShape &tensor_shape, Format format)
105 {
107  const DataType type = data_type_from_format(format);
108 
110 
111  _format = format;
112 }
113 
114 void TensorInfo::init(const TensorShape &tensor_shape, Format format,
115  const Strides &strides_in_bytes, size_t offset_first_element_in_bytes,
116  size_t total_size_in_bytes)
117 {
119  const DataType type = data_type_from_format(format);
120 
122 
123  _format = format;
124 }
125 
126 void TensorInfo::init(size_t num_channels, DataType data_type)
127 {
129 }
130 
131 void TensorInfo::init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type)
132 {
134 
135  _data_type = data_type;
136  _num_channels = num_channels;
137  _format = Format::UNKNOWN;
138 
140 }
141 
142 void TensorInfo::init(const TensorShape &tensor_shape, size_t num_channels, DataType data_type,
143  const Strides &strides_in_bytes, size_t offset_first_element_in_bytes,
144  size_t total_size_in_bytes)
145 {
147 
148  _data_type = data_type;
149  _num_channels = num_channels;
150  _format = Format::UNKNOWN;
151  _tensor_shape = tensor_shape;
152  _offset_first_element_in_bytes = offset_first_element_in_bytes;
153  _strides_in_bytes = strides_in_bytes;
154  _total_size = total_size_in_bytes;
155 
156  _valid_region = ValidRegion{ Coordinates(), _tensor_shape };
157 }
158 
159 void TensorInfo::init(const HOGInfo &hog_info, unsigned int width, unsigned int height)
160 {
161  // Number of cells for each block
162  const Size2D num_cells_per_block = hog_info.num_cells_per_block();
163 
164  // Tensor Size = (Number of horizontal block positions) * (Number of vertical block positions)
165  const Size2D num_block_positions_per_img = hog_info.num_block_positions_per_image(Size2D(width, height));
166 
167  // Number of tensor channels = (Number of cells per block) * (Number of bins per cell)
168  const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins();
169 
170  init(TensorShape(num_block_positions_per_img.width, num_block_positions_per_img.height), num_channels, DataType::F32);
171 }
172 
173 size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, Format format)
174 {
176  const DataType type = data_type_from_format(format);
178 
179  _format = format;
180 
181  return total_size;
182 }
183 
184 size_t TensorInfo::init_auto_padding(const TensorShape &tensor_shape, size_t num_channels, DataType data_type)
185 {
187 
188  _data_type = data_type;
189  _num_channels = num_channels;
190  _format = Format::UNKNOWN;
191  _tensor_shape = tensor_shape;
192 
193  _valid_region = ValidRegion{ Coordinates(), _tensor_shape };
194 
195  auto_padding();
196 
197  return _total_size;
198 }
199 
200 size_t TensorInfo::init_auto_padding(const HOGInfo &hog_info, unsigned int width, unsigned int height)
201 {
202  // Number of cells for each block
203  const Size2D num_cells_per_block = hog_info.num_cells_per_block();
204 
205  // Tensor Size = (Number of horizontal block positions) * (Number of vertical block positions)
206  const Size2D num_block_positions_per_img = hog_info.num_block_positions_per_image(Size2D(width, height));
207 
208  // Number of tensor channels = (Number of cells per block) * (Number of bins per cell)
209  const size_t num_channels = num_cells_per_block.area() * hog_info.num_bins();
210 
211  return init_auto_padding(TensorShape(num_block_positions_per_img.width, num_block_positions_per_img.height), num_channels, DataType::F32);
212 }
213 
215 {
216  ARM_COMPUTE_ERROR_ON(!_is_resizable);
217 
218  // Some kernels compute 32 elements at the time, worst case scenario they
219  // will read 32 values after the last element
220  const size_t extra_pad_x = _tensor_shape.num_dimensions() < 1 ? 0 : 32;
221  const size_t pad_x = _tensor_shape.num_dimensions() < 1 ? 0 : 4;
222  const size_t pad_y = _tensor_shape.num_dimensions() < 2 ? 0 : 4;
223 
224  return extend_padding(PaddingSize(pad_y, pad_x + extra_pad_x, pad_y, pad_x));
225 }
226 
227 std::tuple<Strides, size_t, size_t> TensorInfo::calculate_padding_requirements(const PaddingSize &padding)
228 {
229  // Calculate resulting stride for the X, Y and Z dimension
230  const size_t stride_x = element_size();
231  const size_t stride_y = (padding.left + _tensor_shape[0] + padding.right) * stride_x;
232  const size_t stride_z = (padding.top + _tensor_shape[1] + padding.bottom) * stride_y;
233 
234  Strides required_strides;
235  size_t required_total_size = 0;
236  const size_t required_offset_first_element = padding.left * stride_x + padding.top * stride_y;
237 
238  switch(_tensor_shape.num_dimensions())
239  {
240  case 0:
241  {
242  if(_tensor_shape.total_size() > 0)
243  {
244  required_strides = Strides(stride_x, stride_x);
245  required_total_size = stride_z;
246  }
247  break;
248  }
249  case 1:
250  required_strides = compute_strides(*this, stride_x, stride_y);
251  required_total_size = stride_z;
252  break;
253  case 2:
254  required_strides = compute_strides(*this, stride_x, stride_y);
255  required_total_size = stride_z;
256  break;
257  default:
258  {
259  required_strides = compute_strides(*this, stride_x, stride_y, stride_z);
260 
261  const unsigned int idx_last_dimension = _tensor_shape.num_dimensions() - 1;
262 
263  required_total_size = _tensor_shape[idx_last_dimension] * required_strides[idx_last_dimension];
264  break;
265  }
266  }
267 
268  return std::make_tuple(required_strides, required_offset_first_element, required_total_size);
269 }
270 
272 {
273  ARM_COMPUTE_ERROR_ON(!_is_resizable);
274 
275  bool updated = false;
276 
277  if(padding.top > _padding.top)
278  {
279  _padding.top = padding.top;
280  updated = true;
281  }
282 
283  if(padding.right > _padding.right)
284  {
285  _padding.right = padding.right;
286  updated = true;
287  }
288 
289  if(padding.bottom > _padding.bottom)
290  {
291  _padding.bottom = padding.bottom;
292  updated = true;
293  }
294 
295  if(padding.left > _padding.left)
296  {
297  _padding.left = padding.left;
298  updated = true;
299  }
300 
301  std::tie(_strides_in_bytes, _offset_first_element_in_bytes, _total_size) = calculate_padding_requirements(_padding);
302 
303  return updated;
304 }
305 
306 std::unique_ptr<ITensorInfo> TensorInfo::clone() const
307 {
308  return support::cpp14::make_unique<TensorInfo>(*this);
309 }
310 
312 {
313  _data_type = data_type;
314  _format = Format::UNKNOWN;
315  return set_tensor_shape(tensor_shape()); // Force total size and strides to update
316 }
317 
319 {
320  _num_channels = num_channels;
321  _format = Format::UNKNOWN;
322  return *this;
323 }
324 
326 {
327  _format = format;
328 
329  if(_data_type == DataType::UNKNOWN)
330  {
331  _num_channels = num_channels_from_format(format);
332  _data_type = data_type_from_format(format);
333  }
334  else
335  {
338  }
339  return *this;
340 }
341 
343 {
344  _tensor_shape = shape;
345  _offset_first_element_in_bytes = 0;
346  _strides_in_bytes = compute_strides(*this);
347 
348  if(_tensor_shape.num_dimensions() == 0)
349  {
350  _total_size = _strides_in_bytes[0];
351  }
352  else
353  {
354  const unsigned int idx_last_dimension = _tensor_shape.num_dimensions() - 1;
355  _total_size = _tensor_shape[idx_last_dimension] * _strides_in_bytes[idx_last_dimension];
356  }
357 
358  std::tie(_strides_in_bytes, _offset_first_element_in_bytes, _total_size) = calculate_padding_requirements(_padding);
359 
360  _valid_region = ValidRegion{ Coordinates(), _tensor_shape };
361  return *this;
362 }
363 
365 {
366  _quantization_info = quantization_info;
367  return *this;
368 }
369 
371 {
372  _data_layout = data_layout;
373  return *this;
374 }
375 
377 {
378  _padding = PaddingSize();
379  if(((_format != Format::UNKNOWN) || (_data_type != DataType::UNKNOWN)) && _total_size != 0)
380  {
381  std::tie(_strides_in_bytes, _offset_first_element_in_bytes, _total_size) = calculate_padding_requirements(_padding);
382  }
383  return *this;
384 }
385 
387 {
389 
390  size_t offset = _offset_first_element_in_bytes;
391 
392  for(size_t i = 0; i < _tensor_shape.num_dimensions(); ++i)
393  {
394  offset += pos[i] * _strides_in_bytes[i];
395  }
396 
397  return offset;
398 }
ITensorInfo & set_format(Format format) override
Set the format of an already initialized tensor.
Definition: TensorInfo.cpp:325
__global uchar * offset(const Image *img, int x, int y)
Get the pointer position of a Image.
Definition: helpers.h:328
unsigned int top
top of the border
Definition: Types.h:339
size_t num_bins() const
The number of histogram bins for each cell.
Definition: HOGInfo.cpp:111
Shape of a tensor.
Definition: TensorShape.h:39
const DataLayout data_layout
Definition: Im2Col.cpp:146
size_t init_auto_padding(const TensorShape &tensor_shape, Format format)
Initialize the metadata structure for the given tensor shape and single-plane format,...
Definition: TensorInfo.cpp:173
std::unique_ptr< ITensorInfo > clone() const override
Provide a clone of the current object of class T.
Definition: TensorInfo.cpp:306
Container for 2D border size.
Definition: Types.h:259
size_t num_channels() const override
The number of channels for each tensor element.
Definition: TensorInfo.h:248
ITensorInfo & reset_padding() override
Resets the padding settings of the tensor.
Definition: TensorInfo.cpp:376
DataLayout data_layout() const override
Get the data layout of the tensor.
Definition: TensorInfo.h:297
Store the HOG's metadata.
Definition: HOGInfo.h:35
QuantizationInfo quantization_info() const override
Get the quantization settings (scale and offset) of the tensor.
Definition: TensorInfo.h:293
bool extend_padding(const PaddingSize &padding) override
Update the offset to the first element, the strides and the total size.
Definition: TensorInfo.cpp:271
1 channel, 1 F32 per channel
ITensorInfo & set_data_type(DataType data_type) override
Set the data type to the specified value.
Definition: TensorInfo.cpp:311
#define ARM_COMPUTE_ERROR_ON(cond)
If the condition is true then an error message is printed and an exception thrown.
Definition: Error.h:337
size_t num_channels_from_format(Format format)
Return the number of channels for a given single-planar pixel format.
Definition: Utils.h:478
Store the tensor's metadata.
Definition: ITensorInfo.h:40
unsigned int bottom
bottom of the border
Definition: Types.h:341
PaddingSize padding() const override
Padding of tensor.
Definition: TensorInfo.h:268
const Strides & strides_in_bytes() const override
The strides in bytes for accessing each dimension of the tensor.
Definition: TensorInfo.h:231
bool auto_padding() override
Update the offset to the first element and the strides to automatically computed values.
Definition: TensorInfo.cpp:214
Copyright (c) 2017-2018 ARM Limited.
size_t height
Height of the image region or rectangle.
Definition: Size2D.h:93
Strides compute_strides(const ITensorInfo &info, T stride_x, Ts &&... fixed_strides)
Create a strides object based on the provided strides and the tensor dimensions.
Definition: Helpers.h:535
Format format() const override
Colour format of the image.
Definition: TensorInfo.h:260
ITensorInfo & set_quantization_info(const QuantizationInfo &quantization_info) override
Set the quantization settings (scale and offset) of the tensor.
Definition: TensorInfo.cpp:364
DataType data_type() const override
Data type used for each element of the tensor.
Definition: TensorInfo.h:256
size_t offset_element_in_bytes(const Coordinates &pos) const override
The offset in bytes from the beginning of the memory allocation to access the element at position (x,...
Definition: TensorInfo.cpp:386
Quantization information.
ITensorInfo & set_data_layout(const DataLayout &data_layout) override
Set the data layout of the tensor.
Definition: TensorInfo.cpp:370
Format
Image colour formats.
Definition: Types.h:52
#define ARM_COMPUTE_ERROR_ON_COORDINATES_DIMENSIONS_GTE(p, md)
Definition: Validate.h:244
Size2D num_cells_per_block() const
Calculates the number of cells for each block.
Definition: HOGInfo.cpp:67
size_t total_size() const override
Returns the total size of the tensor in bytes.
Definition: TensorInfo.h:264
Coordinates of an item.
Definition: Coordinates.h:37
size_t total_size() const
Collapses all dimensions to a single linear total size.
Definition: TensorShape.h:171
BorderSize PaddingSize
Container for 2D padding size.
Definition: Types.h:346
unsigned int left
left of the border
Definition: Types.h:342
ITensorInfo & set_num_channels(int num_channels) override
Set the number of channels to the specified value.
Definition: TensorInfo.cpp:318
unsigned int right
right of the border
Definition: Types.h:340
Num samples, channels, height, width.
DataType data_type_from_format(Format format)
Return the data type used by a given single-planar pixel format.
Definition: Utils.h:215
void init(Format format)
Initialize the tensor info with just a format.
Definition: TensorInfo.cpp:99
Strides of an item in bytes.
Definition: Strides.h:37
size_t width
Width of the image region or rectangle.
Definition: Size2D.h:92
Size2D num_block_positions_per_image(const Size2D &image_size) const
Calculates the number of block positions for the given image size.
Definition: HOGInfo.cpp:83
Class for specifying the size of an image or rectangle.
Definition: Size2D.h:34
unsigned int num_dimensions() const
Returns the effective dimensionality of the tensor.
Definition: Dimensions.h:122
size_t offset_first_element_in_bytes() const override
The offset from the beginning of the memory allocation to the first element of the tensor.
Definition: TensorInfo.h:235
Store the tensor's metadata.
Definition: TensorInfo.h:45
ITensorInfo & set_tensor_shape(const TensorShape &shape) override
Set the shape of an already initialized tensor.
Definition: TensorInfo.cpp:342
TensorInfo()
Default constructor.
Definition: TensorInfo.cpp:35
Container for valid region of a window.
Definition: Types.h:174
const TensorShape & tensor_shape() const override
Size for each dimension of the tensor.
Definition: TensorInfo.h:252
DataType
Available data types.
Definition: Types.h:74
DataLayout
[DataLayout enum definition]
Definition: Types.h:114
size_t element_size() const override
Element size in bytes calculated as data_size() * num_channels()
Definition: TensorInfo.h:240
size_t area() const
The area of the image or rectangle calculated as (width * height)
Definition: Size2D.h:53