Compute Library
 21.08
SimpleTensor.h
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24 #ifndef ARM_COMPUTE_TEST_SIMPLE_TENSOR_H
25 #define ARM_COMPUTE_TEST_SIMPLE_TENSOR_H
26 
28 #include "arm_compute/core/Types.h"
29 #include "arm_compute/core/Utils.h"
30 #include "tests/IAccessor.h"
31 #include "tests/Utils.h"
32 
33 #include <algorithm>
34 #include <array>
35 #include <cstddef>
36 #include <cstdint>
37 #include <functional>
38 #include <memory>
39 #include <stdexcept>
40 #include <utility>
41 
42 namespace arm_compute
43 {
44 namespace test
45 {
46 class RawTensor;
47 
48 /** Simple tensor object that stores elements in a consecutive chunk of memory.
49  *
50  * It can be created by either loading an image from a file which also
51  * initialises the content of the tensor or by explcitly specifying the size.
52  * The latter leaves the content uninitialised.
53  *
54  * Furthermore, the class provides methods to convert the tensor's values into
55  * different image format.
56  */
57 template <typename T>
58 class SimpleTensor : public IAccessor
59 {
60 public:
61  /** Create an uninitialised tensor. */
62  SimpleTensor() = default;
63 
64  /** Create an uninitialised tensor of the given @p shape and @p format.
65  *
66  * @param[in] shape Shape of the new raw tensor.
67  * @param[in] format Format of the new raw tensor.
68  */
70 
71  /** Create an uninitialised tensor of the given @p shape and @p data type.
72  *
73  * @param[in] shape Shape of the new raw tensor.
74  * @param[in] data_type Data type of the new raw tensor.
75  * @param[in] num_channels (Optional) Number of channels (default = 1).
76  * @param[in] quantization_info (Optional) Quantization info for asymmetric quantization (default = empty).
77  * @param[in] data_layout (Optional) Data layout of the tensor (default = NCHW).
78  */
80  int num_channels = 1,
83 
84  /** Create a deep copy of the given @p tensor.
85  *
86  * @param[in] tensor To be copied tensor.
87  */
88  SimpleTensor(const SimpleTensor &tensor);
89 
90  /** Create a deep copy of the given @p tensor.
91  *
92  * @param[in] tensor To be copied tensor.
93  *
94  * @return a copy of the given tensor.
95  */
97  /** Allow instances of this class to be move constructed */
98  SimpleTensor(SimpleTensor &&) = default;
99  /** Default destructor. */
100  ~SimpleTensor() = default;
101 
102  /** Tensor value type */
103  using value_type = T;
104  /** Tensor buffer pointer type */
105  using Buffer = std::unique_ptr<value_type[]>;
106 
107  friend class RawTensor;
108 
109  /** Return value at @p offset in the buffer.
110  *
111  * @param[in] offset Offset within the buffer.
112  *
113  * @return value in the buffer.
114  */
115  T &operator[](size_t offset);
116 
117  /** Return constant value at @p offset in the buffer.
118  *
119  * @param[in] offset Offset within the buffer.
120  *
121  * @return constant value in the buffer.
122  */
123  const T &operator[](size_t offset) const;
124 
125  /** Shape of the tensor.
126  *
127  * @return the shape of the tensor.
128  */
129  TensorShape shape() const override;
130  /** Size of each element in the tensor in bytes.
131  *
132  * @return the size of each element in the tensor in bytes.
133  */
134  size_t element_size() const override;
135  /** Total size of the tensor in bytes.
136  *
137  * @return the total size of the tensor in bytes.
138  */
139  size_t size() const override;
140  /** Image format of the tensor.
141  *
142  * @return the format of the tensor.
143  */
144  Format format() const override;
145  /** Data layout of the tensor.
146  *
147  * @return the data layout of the tensor.
148  */
149  DataLayout data_layout() const override;
150  /** Data type of the tensor.
151  *
152  * @return the data type of the tensor.
153  */
154  DataType data_type() const override;
155  /** Number of channels of the tensor.
156  *
157  * @return the number of channels of the tensor.
158  */
159  int num_channels() const override;
160  /** Number of elements of the tensor.
161  *
162  * @return the number of elements of the tensor.
163  */
164  int num_elements() const override;
165  /** Available padding around the tensor.
166  *
167  * @return the available padding around the tensor.
168  */
169  PaddingSize padding() const override;
170  /** Quantization info in case of asymmetric quantized type
171  *
172  * @return
173  */
174  QuantizationInfo quantization_info() const override;
175 
176  /** Constant pointer to the underlying buffer.
177  *
178  * @return a constant pointer to the data.
179  */
180  const T *data() const;
181 
182  /** Pointer to the underlying buffer.
183  *
184  * @return a pointer to the data.
185  */
186  T *data();
187 
188  /** Read only access to the specified element.
189  *
190  * @param[in] coord Coordinates of the desired element.
191  *
192  * @return A pointer to the desired element.
193  */
194  const void *operator()(const Coordinates &coord) const override;
195 
196  /** Access to the specified element.
197  *
198  * @param[in] coord Coordinates of the desired element.
199  *
200  * @return A pointer to the desired element.
201  */
202  void *operator()(const Coordinates &coord) override;
203 
204  /** Swaps the content of the provided tensors.
205  *
206  * @param[in, out] tensor1 Tensor to be swapped.
207  * @param[in, out] tensor2 Tensor to be swapped.
208  */
209  template <typename U>
210  friend void swap(SimpleTensor<U> &tensor1, SimpleTensor<U> &tensor2);
211 
212 protected:
213  Buffer _buffer{ nullptr };
214  TensorShape _shape{};
215  Format _format{ Format::UNKNOWN };
216  DataType _data_type{ DataType::UNKNOWN };
217  int _num_channels{ 0 };
218  QuantizationInfo _quantization_info{};
219  DataLayout _data_layout{ DataLayout::UNKNOWN };
220 };
221 
222 template <typename T1, typename T2>
224 {
225  SimpleTensor<T1> st(tensor.shape(), tensor.data_type(),
226  tensor.num_channels(),
227  tensor.quantization_info(),
228  tensor.data_layout());
229  for(size_t n = 0; n < size_t(st.num_elements()); n++)
230  {
231  st.data()[n] = static_cast<T1>(tensor.data()[n]);
232  }
233  return st;
234 }
235 
236 template <typename T1, typename T2, typename std::enable_if<std::is_same<T1, T2>::value, int>::type = 0>
238 {
239  SimpleTensor<T1> st(tensor.shape(), tensor.data_type(),
240  tensor.num_channels(),
241  tensor.quantization_info(),
242  tensor.data_layout());
243  memcpy((void *)st.data(), (const void *)tensor.data(), size_t(st.num_elements() * sizeof(T1)));
244  return st;
245 }
246 
247 template < typename T1, typename T2, typename std::enable_if < (std::is_same<T1, half>::value || std::is_same<T2, half>::value), int >::type = 0 >
249 {
250  SimpleTensor<T1> st(tensor.shape(), tensor.data_type(),
251  tensor.num_channels(),
252  tensor.quantization_info(),
253  tensor.data_layout());
254  for(size_t n = 0; n < size_t(st.num_elements()); n++)
255  {
256  st.data()[n] = half_float::detail::half_cast<T1, T2>(tensor.data()[n]);
257  }
258  return st;
259 }
260 
261 template <typename T>
263  : _buffer(nullptr),
264  _shape(shape),
265  _format(format),
266  _quantization_info(),
267  _data_layout(DataLayout::NCHW)
268 {
269  _num_channels = num_channels();
270  _buffer = std::make_unique<T[]>(num_elements() * _num_channels);
271 }
272 
273 template <typename T>
275  : _buffer(nullptr),
276  _shape(shape),
277  _data_type(data_type),
278  _num_channels(num_channels),
279  _quantization_info(quantization_info),
280  _data_layout(data_layout)
281 {
282  _buffer = std::make_unique<T[]>(this->_shape.total_size() * _num_channels);
283 }
284 
285 template <typename T>
287  : _buffer(nullptr),
288  _shape(tensor.shape()),
289  _format(tensor.format()),
290  _data_type(tensor.data_type()),
291  _num_channels(tensor.num_channels()),
292  _quantization_info(tensor.quantization_info()),
293  _data_layout(tensor.data_layout())
294 {
295  _buffer = std::make_unique<T[]>(tensor.num_elements() * _num_channels);
296  std::copy_n(tensor.data(), this->_shape.total_size() * _num_channels, _buffer.get());
297 }
298 
299 template <typename T>
301 {
302  swap(*this, tensor);
303 
304  return *this;
305 }
306 
307 template <typename T>
309 {
310  return _buffer[offset];
311 }
312 
313 template <typename T>
314 const T &SimpleTensor<T>::operator[](size_t offset) const
315 {
316  return _buffer[offset];
317 }
318 
319 template <typename T>
321 {
322  return _shape;
323 }
324 
325 template <typename T>
327 {
328  return num_channels() * element_size_from_data_type(data_type());
329 }
330 
331 template <typename T>
333 {
334  return _quantization_info;
335 }
336 
337 template <typename T>
338 size_t SimpleTensor<T>::size() const
339 {
340  const size_t size = std::accumulate(_shape.cbegin(), _shape.cend(), 1, std::multiplies<size_t>());
341  return size * element_size();
342 }
343 
344 template <typename T>
346 {
347  return _format;
348 }
349 
350 template <typename T>
352 {
353  return _data_layout;
354 }
355 
356 template <typename T>
358 {
359  if(_format != Format::UNKNOWN)
360  {
361  return data_type_from_format(_format);
362  }
363  else
364  {
365  return _data_type;
366  }
367 }
368 
369 template <typename T>
371 {
372  switch(_format)
373  {
374  case Format::U8:
375  case Format::U16:
376  case Format::S16:
377  case Format::U32:
378  case Format::S32:
379  case Format::F16:
380  case Format::F32:
381  return 1;
382  // Because the U and V channels are subsampled
383  // these formats appear like having only 2 channels:
384  case Format::YUYV422:
385  case Format::UYVY422:
386  return 2;
387  case Format::UV88:
388  return 2;
389  case Format::RGB888:
390  return 3;
391  case Format::RGBA8888:
392  return 4;
393  case Format::UNKNOWN:
394  return _num_channels;
395  //Doesn't make sense for planar formats:
396  case Format::NV12:
397  case Format::NV21:
398  case Format::IYUV:
399  case Format::YUV444:
400  default:
401  return 0;
402  }
403 }
404 
405 template <typename T>
407 {
408  return _shape.total_size();
409 }
410 
411 template <typename T>
413 {
414  return PaddingSize(0);
415 }
416 
417 template <typename T>
418 const T *SimpleTensor<T>::data() const
419 {
420  return _buffer.get();
421 }
422 
423 template <typename T>
425 {
426  return _buffer.get();
427 }
428 
429 template <typename T>
430 const void *SimpleTensor<T>::operator()(const Coordinates &coord) const
431 {
432  return _buffer.get() + coord2index(_shape, coord) * _num_channels;
433 }
434 
435 template <typename T>
437 {
438  return _buffer.get() + coord2index(_shape, coord) * _num_channels;
439 }
440 
441 template <typename U>
442 void swap(SimpleTensor<U> &tensor1, SimpleTensor<U> &tensor2)
443 {
444  // Use unqualified call to swap to enable ADL. But make std::swap available
445  // as backup.
446  using std::swap;
447  swap(tensor1._shape, tensor2._shape);
448  swap(tensor1._format, tensor2._format);
449  swap(tensor1._data_type, tensor2._data_type);
450  swap(tensor1._num_channels, tensor2._num_channels);
451  swap(tensor1._quantization_info, tensor2._quantization_info);
452  swap(tensor1._buffer, tensor2._buffer);
453 }
454 } // namespace test
455 } // namespace arm_compute
456 #endif /* ARM_COMPUTE_TEST_SIMPLE_TENSOR_H */
friend void swap(SimpleTensor< U > &tensor1, SimpleTensor< U > &tensor2)
Swaps the content of the provided tensors.
Definition: SimpleTensor.h:442
__global uchar * offset(const Image *img, int x, int y)
Get the pointer position of a Image.
Definition: helpers.h:861
size_t element_size() const override
Size of each element in the tensor in bytes.
Definition: SimpleTensor.h:326
Subclass of SimpleTensor using uint8_t as value type.
Definition: RawTensor.h:38
Shape of a tensor.
Definition: TensorShape.h:39
size_t size() const override
Total size of the tensor in bytes.
Definition: SimpleTensor.h:338
T & operator[](size_t offset)
Return value at offset in the buffer.
Definition: SimpleTensor.h:308
Unknown CL kernel type.
Definition: CLTypes.h:81
Container for 2D border size.
Definition: Types.h:264
size_t element_size_from_data_type(DataType dt)
The size in bytes of the data type.
Definition: Utils.h:185
Format format() const override
Image format of the tensor.
Definition: SimpleTensor.h:345
DataType data_type() const override
Data type of the tensor.
Definition: SimpleTensor.h:357
const DataLayout data_layout
Definition: Im2Col.cpp:151
void swap(SimpleTensor< U > &tensor1, SimpleTensor< U > &tensor2)
Definition: SimpleTensor.h:442
TensorShape shape() const override
Shape of the tensor.
Definition: SimpleTensor.h:320
decltype(strategy::transforms) typedef type
SimpleTensor< T2 > accumulate(const SimpleTensor< T1 > &src, DataType output_data_type)
Definition: Accumulate.cpp:38
SimpleTensor< T1 > copy_tensor(const SimpleTensor< T2 > &tensor)
Definition: SimpleTensor.h:223
Copyright (c) 2017-2021 Arm Limited.
int coord2index(const TensorShape &shape, const Coordinates &coord)
Linearise the given coordinate.
Definition: Utils.h:387
const DataType data_type
Definition: Im2Col.cpp:150
Quantization information.
Format
Image colour formats.
Definition: Types.h:54
~SimpleTensor()=default
Default destructor.
Coordinates of an item.
Definition: Coordinates.h:37
uint8_t value_type
Tensor value type.
Definition: SimpleTensor.h:103
PaddingSize padding() const override
Available padding around the tensor.
Definition: SimpleTensor.h:412
DataLayout data_layout() const override
Data layout of the tensor.
Definition: SimpleTensor.h:351
BorderSize PaddingSize
Container for 2D padding size.
Definition: Types.h:379
Num samples, channels, height, width.
SimpleTensor()=default
Create an uninitialised tensor.
const void * operator()(const Coordinates &coord) const override
Read only access to the specified element.
Definition: SimpleTensor.h:430
DataType data_type_from_format(Format format)
Return the data type used by a given single-planar pixel format.
Definition: Utils.h:219
std::unique_ptr< value_type[]> Buffer
Tensor buffer pointer type.
Definition: SimpleTensor.h:105
Simple tensor object that stores elements in a consecutive chunk of memory.
Definition: SimpleTensor.h:58
int num_channels() const override
Number of channels of the tensor.
Definition: SimpleTensor.h:370
SimpleTensor & operator=(SimpleTensor tensor)
Create a deep copy of the given tensor.
Definition: SimpleTensor.h:300
Common interface to provide information and access to tensor like structures.
Definition: IAccessor.h:37
int num_elements() const override
Number of elements of the tensor.
Definition: SimpleTensor.h:406
QuantizationInfo quantization_info() const override
Quantization info in case of asymmetric quantized type.
Definition: SimpleTensor.h:332
DataType
Available data types.
Definition: Types.h:77
DataLayout
[DataLayout enum definition]
Definition: Types.h:111
const T * data() const
Constant pointer to the underlying buffer.
Definition: SimpleTensor.h:418