Compute Library
 20.05
ITensorInfo.h
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24 #ifndef ARM_COMPUTE_ITENSORINFO_H
25 #define ARM_COMPUTE_ITENSORINFO_H
26 
30 #include "arm_compute/core/Types.h"
31 #include "arm_compute/core/Utils.h"
34 
35 #include <cstddef>
36 
37 namespace arm_compute
38 {
39 /** Store the tensor's metadata */
40 class ITensorInfo : public misc::ICloneable<ITensorInfo>
41 {
42 public:
43  /** Default virtual destructor */
44  virtual ~ITensorInfo() = default;
45  /** Set the data type to the specified value.
46  *
47  * @warning This resets the format to UNKNOWN.
48  *
49  * @param[in] data_type The new data type.
50  *
51  * @return Reference to this ITensorInfo object
52  */
54  /** Set the number of channels to the specified value.
55  *
56  * @warning This resets the format to UNKNOWN.
57  *
58  * @param[in] num_channels New number of channels.
59  *
60  * @return Reference to this ITensorInfo object
61  */
62  virtual ITensorInfo &set_num_channels(int num_channels) = 0;
63  /** Set the format of an already initialized tensor.
64  *
65  * @note If the data type has already been configured (i.e. not UNKNOWN) it
66  * must match the new format. If data type hasn't been configured it will
67  * be based on the format.
68  *
69  * @param[in] format Single-plane format of the tensor.
70  *
71  * @return Reference to this ITensorInfo object
72  */
73  virtual ITensorInfo &set_format(Format format) = 0;
74  /** Set the shape of an already initialized tensor.
75  *
76  * @warning Changing the shape requires to recompute the strides and is
77  * therefore only possible if the tensor hasn't been allocated yet.
78  *
79  * @param[in] shape New tensor shape.
80  *
81  * @return Reference to this ITensorInfo object
82  */
83  virtual ITensorInfo &set_tensor_shape(const TensorShape &shape) = 0;
84  /** Set the quantization settings (scale and offset) of the tensor.
85  *
86  * @param[in] quantization_info QuantizationInfo containing the scale and offset
87  *
88  * @return Reference to this ITensorInfo object
89  */
91  /** Set the data layout of the tensor.
92  *
93  * @param[in] data_layout DataLayout containing the layout data information.
94  *
95  * @return Reference to this ITensorInfo object
96  */
98  /** Resets the padding settings of the tensor.
99  *
100  * @return Reference to this ITensorInfo object
101  */
102  virtual ITensorInfo &reset_padding() = 0;
103  /** Update the offset to the first element and the strides to automatically computed values.
104  *
105  * @note The padding used by this method is really conservative so that the tensor can be used for most functions.
106  *
107  * @return True if the strides or the offset to the first element have changed.
108  */
109  virtual bool auto_padding() = 0;
110  /** Update the offset to the first element, the strides and the total size.
111  *
112  * @note This function can only increase the offset, strides and total size.
113  *
114  * @param[in] padding Padding around the XY plane in number of elements.
115  *
116  * @return True if the strides, offset and total size have changed.
117  */
118  virtual bool extend_padding(const PaddingSize &padding) = 0;
119  /** Return the size of the requested dimension
120  *
121  * @param[in] index Index of the dimension
122  *
123  * @return Dimension of the requested dimension
124  */
125  virtual size_t dimension(size_t index) const = 0;
126  /** Return the size of the requested data layout dimension
127  *
128  * @param[in] dimension DataLayoutDimension of the dimension
129  *
130  * @return Dimension of the requested dimension
131  */
132  virtual size_t dimension(DataLayoutDimension dimension) const = 0;
133  /** The strides in bytes for accessing each dimension of the tensor
134  *
135  * @return Strides in bytes for each tensor dimension
136  */
137  virtual const Strides &strides_in_bytes() const = 0;
138  /** The offset from the beginning of the memory allocation to the first element of the tensor.
139  * This can be used to access efficiently elements in a 2D tensor
140  *
141  * @return The offset in bytes to access the first element of the tensor.
142  */
143  virtual size_t offset_first_element_in_bytes() const = 0;
144  /** The offset in bytes from the beginning of the memory allocation to access the element at position (x, y, z ...)
145  *
146  * @param[in] pos Vector with the coordinates of the element to access.
147  * The size of this vector must be equal to the number of dimensions of the tensor
148  *
149  * @return Offset in bytes from the beginning of the memory allocation to access the element (x, y, z, ...)
150  */
151  virtual int32_t offset_element_in_bytes(const Coordinates &pos) const = 0;
152 
153  /** Element size in bytes calculated as data_size() * num_channels()
154  *
155  * @return The size of one element in bytes
156  */
157  virtual size_t element_size() const = 0;
158  /** The number of dimensions of the tensor (rank)
159  *
160  * @return The number of dimensions of the tensor (rank)
161  */
162  virtual size_t num_dimensions() const = 0;
163  /** The number of channels for each tensor element
164  *
165  * @return The number of channels for each tensor element
166  */
167  virtual size_t num_channels() const = 0;
168  /** Size for each dimension of the tensor
169  *
170  * @return A vector with the size for each dimension of the tensor
171  */
172  virtual const TensorShape &tensor_shape() const = 0;
173  /** Data type used for each element of the tensor
174  *
175  * @return Tensor data type
176  */
177  virtual DataType data_type() const = 0;
178  /** Colour format of the image
179  *
180  * @return Colour format of the image
181  */
182  virtual Format format() const = 0;
183  /** Returns the total size of the tensor in bytes.
184  *
185  * @return Total size of the tensor in bytes.
186  */
187  virtual size_t total_size() const = 0;
188  /** Padding of tensor.
189  *
190  * @return Padding.
191  */
192  virtual PaddingSize padding() const = 0;
193  /** Checks if the tensor has been allocated with padding or not.
194  *
195  * @return True if padding is allocated in the tensor, otherwise false.
196  */
197  virtual bool has_padding() const = 0;
198  /** Flag indicating whether the size of the tensor can be changed.
199  *
200  * @return True if the tensor size can be changed.
201  */
202  virtual bool is_resizable() const = 0;
203  /** Flag indicating whether the shape of the tensor is dynamic, meaning that it can change on kernel/function execution.
204  *
205  * @return True if its dynamic else false
206  */
207  virtual bool is_dynamic() const = 0;
208  /** Set the flag whether the tensor size can be changed.
209  *
210  * @param[in] is_resizable Flag that marks the tensor if it can be changed or not.
211  *
212  * @return Reference to this ITensorInfo object
213  */
214  virtual ITensorInfo &set_is_resizable(bool is_resizable) = 0;
215  /** Set the flag whether the tensor size is dynamic.
216  *
217  * @param[in] is_dynamic Flag that marks the tensor if it's dynamic.
218  *
219  * @return Reference to this ITensorInfo object
220  */
221  virtual ITensorInfo &set_is_dynamic(bool is_dynamic) = 0;
222  /** Valid region of the tensor. All elements in the valid region have defined values, i.e. are not undefined.
223  *
224  * @return The valid region.
225  */
226  virtual ValidRegion valid_region() const = 0;
227  /** Set the valid region of the tensor.
228  *
229  * @param[in] valid_region Valid region to set.
230  */
231  virtual void set_valid_region(const ValidRegion &valid_region) = 0;
232 
233  /** Get the quantization settings (scale and offset) of the tensor.
234  *
235  * @return A QuantizationInfo containing the scale and offset.
236  */
237  virtual QuantizationInfo quantization_info() const = 0;
238  /** Get the data layout of the tensor.
239  *
240  * @return A DataLayout containing the layout data information.
241  */
242  virtual DataLayout data_layout() const = 0;
243 
244  /** If infos are broadcast compatible tensor info's, return the broadcasted shape and the intersection of
245  * the broadcasted valid regions of the tensors.
246  *
247  * Two tensor info's are broadcast compatible if their shapes are broadcast compatible.
248  *
249  * Two tensor shapes are broadcast compatible if for each dimension, they're equal or one of them is 1.
250  *
251  * If two shapes are compatible, each dimension in the broadcasted shape is the max of the original dimensions.
252  *
253  * @param[in] infos Tensor info's.
254  *
255  * @return The broadcasted shape and valid region, or an empty shape and valid region if the info's are
256  * not broadcast compatible.
257  */
258  template <typename... Infos>
259  static std::pair<TensorShape, ValidRegion> broadcast_shape_and_valid_region(const Infos &... infos)
260  {
261  TensorShape bc_shape = TensorShape::broadcast_shape(infos.tensor_shape()...);
262  ValidRegion bc_valid_region{ Coordinates(), bc_shape };
263 
264  auto broadcast_valid_region = [&bc_valid_region](const ITensorInfo & info)
265  {
266  if(info.num_dimensions() != 0)
267  {
268  for(size_t d = 0; d < bc_valid_region.shape.num_dimensions(); ++d)
269  {
270  const bool is_broadcast = (info.tensor_shape()[d] == 1);
271 
272  const int anchor_max = std::max(bc_valid_region.anchor[d], info.valid_region().anchor[d]);
273  const size_t valid_min = std::min(bc_valid_region.shape[d], info.valid_region().shape[d]);
274 
275  if(!is_broadcast || (valid_min == 0))
276  {
277  bc_valid_region.anchor.set(d, anchor_max);
278  bc_valid_region.shape.set(d, valid_min);
279  }
280  }
281  }
282  };
283 
284  utility::for_each(broadcast_valid_region, infos...);
285 
286  return std::pair<TensorShape, ValidRegion>(bc_shape, bc_valid_region);
287  }
288 };
289 } // namespace arm_compute
290 #endif /*ARM_COMPUTE_TENSORINFO_H */
virtual size_t num_dimensions() const =0
The number of dimensions of the tensor (rank)
virtual ITensorInfo & set_num_channels(int num_channels)=0
Set the number of channels to the specified value.
Shape of a tensor.
Definition: TensorShape.h:39
virtual int32_t offset_element_in_bytes(const Coordinates &pos) const =0
The offset in bytes from the beginning of the memory allocation to access the element at position (x,...
virtual size_t dimension(size_t index) const =0
Return the size of the requested dimension.
Container for 2D border size.
Definition: Types.h:272
virtual ITensorInfo & set_tensor_shape(const TensorShape &shape)=0
Set the shape of an already initialized tensor.
DataLayoutDimension
[DataLayout enum definition]
Definition: Types.h:129
virtual DataType data_type() const =0
Data type used for each element of the tensor.
static TensorShape broadcast_shape(const Shapes &... shapes)
If shapes are broadcast compatible, return the broadcasted shape.
Definition: TensorShape.h:210
Store the tensor's metadata.
Definition: ITensorInfo.h:40
virtual bool is_dynamic() const =0
Flag indicating whether the shape of the tensor is dynamic, meaning that it can change on kernel/func...
virtual ITensorInfo & reset_padding()=0
Resets the padding settings of the tensor.
static std::pair< TensorShape, ValidRegion > broadcast_shape_and_valid_region(const Infos &... infos)
If infos are broadcast compatible tensor info's, return the broadcasted shape and the intersection of...
Definition: ITensorInfo.h:259
Copyright (c) 2017-2020 ARM Limited.
virtual void set_valid_region(const ValidRegion &valid_region)=0
Set the valid region of the tensor.
virtual ValidRegion valid_region() const =0
Valid region of the tensor.
virtual bool is_resizable() const =0
Flag indicating whether the size of the tensor can be changed.
Quantization information.
virtual Format format() const =0
Colour format of the image.
virtual bool auto_padding()=0
Update the offset to the first element and the strides to automatically computed values.
virtual const TensorShape & tensor_shape() const =0
Size for each dimension of the tensor.
virtual ITensorInfo & set_data_layout(const DataLayout &data_layout)=0
Set the data layout of the tensor.
Format
Image colour formats.
Definition: Types.h:54
Coordinates of an item.
Definition: Coordinates.h:37
virtual ITensorInfo & set_is_dynamic(bool is_dynamic)=0
Set the flag whether the tensor size is dynamic.
virtual size_t element_size() const =0
Element size in bytes calculated as data_size() * num_channels()
virtual PaddingSize padding() const =0
Padding of tensor.
virtual ITensorInfo & set_quantization_info(const QuantizationInfo &quantization_info)=0
Set the quantization settings (scale and offset) of the tensor.
virtual ITensorInfo & set_data_type(DataType data_type)=0
Set the data type to the specified value.
virtual QuantizationInfo quantization_info() const =0
Get the quantization settings (scale and offset) of the tensor.
void for_each(F &&)
Base case of for_each.
Definition: Utility.h:108
Strides of an item in bytes.
Definition: Strides.h:37
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.
virtual size_t total_size() const =0
Returns the total size of the tensor in bytes.
TensorShape & set(size_t dimension, size_t value, bool apply_dim_correction=true)
Accessor to set the value of one of the dimensions.
Definition: TensorShape.h:78
virtual const Strides & strides_in_bytes() const =0
The strides in bytes for accessing each dimension of the tensor.
Clonable Interface.
Definition: ICloneable.h:35
Container for valid region of a window.
Definition: Types.h:187
virtual ITensorInfo & set_format(Format format)=0
Set the format of an already initialized tensor.
DataType
Available data types.
Definition: Types.h:77
virtual ~ITensorInfo()=default
Default virtual destructor.
DataLayout
[DataLayout enum definition]
Definition: Types.h:120
virtual bool extend_padding(const PaddingSize &padding)=0
Update the offset to the first element, the strides and the total size.
virtual size_t num_channels() const =0
The number of channels for each tensor element.
virtual bool has_padding() const =0
Checks if the tensor has been allocated with padding or not.
virtual ITensorInfo & set_is_resizable(bool is_resizable)=0
Set the flag whether the tensor size can be changed.
virtual DataLayout data_layout() const =0
Get the data layout of the tensor.