blob: bb3ac6e35e56e2e8e5e2453b5aa7d1485282e698 [file] [log] [blame]
Anthony Barbier6ff3b192017-09-04 18:44:23 +01001/*
2 * Copyright (c) 2016, 2017 ARM Limited.
3 *
4 * SPDX-License-Identifier: MIT
5 *
6 * Permission is hereby granted, free of charge, to any person obtaining a copy
7 * of this software and associated documentation files (the "Software"), to
8 * deal in the Software without restriction, including without limitation the
9 * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
10 * sell copies of the Software, and to permit persons to whom the Software is
11 * furnished to do so, subject to the following conditions:
12 *
13 * The above copyright notice and this permission notice shall be included in all
14 * copies or substantial portions of the Software.
15 *
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,
18 * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
19 * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
20 * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
21 * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
22 * SOFTWARE.
23 */
24#ifndef __ARM_COMPUTE_ITENSORINFO_H__
25#define __ARM_COMPUTE_ITENSORINFO_H__
26
27#include "arm_compute/core/Coordinates.h"
28#include "arm_compute/core/Strides.h"
29#include "arm_compute/core/TensorShape.h"
30#include "arm_compute/core/Types.h"
31#include "arm_compute/core/Utils.h"
32
33#include <cstddef>
34
35namespace arm_compute
36{
37/** Store the tensor's metadata */
38class ITensorInfo
39{
40public:
41 /** Default virtual destructor */
42 virtual ~ITensorInfo() = default;
43 /** Set the data type to the specified value.
44 *
45 * @warning This resets the format to UNKNOWN.
46 *
47 * @param[in] data_type The new data type.
48 */
49 virtual void set_data_type(DataType data_type) = 0;
50 /** Set the number of channels to the specified value.
51 *
52 * @warning This resets the format to UNKNOWN.
53 *
54 * @param[in] num_channels New number of channels.
55 */
56 virtual void set_num_channels(int num_channels) = 0;
57 /** Set the format of an already initialized tensor.
58 *
59 * @note If the data type has already been configured (i.e. not UNKNOWN) it
60 * must match the new format. If data type hasn't been configured it will
61 * be based on the format.
62 *
63 * @param[in] format Single-plane format of the tensor.
64 */
65 virtual void set_format(Format format) = 0;
66 /** Set the shape of an already initialized tensor.
67 *
68 * @warning Changing the shape requires to recompute the strides and is
69 * therefore only possible if the tensor hasn't been allocated yet.
70 *
71 * @param[in] shape New tensor shape.
72 */
73 virtual void set_tensor_shape(TensorShape shape) = 0;
74 /** Set the fixed point position to the specified value
75 *
76 * @warning The fixed point position must be set once the data type has been configured
77 *
78 * @param[in] fixed_point_position The new fixed point position
79 */
80 virtual void set_fixed_point_position(int fixed_point_position) = 0;
81 /** Update the offset to the first element and the strides to automatically computed values.
82 *
83 * @note The padding used by this method is really conservative so that the tensor can be used for most functions.
84 *
85 * @return True if the strides or the offset to the first element have changed.
86 */
87 virtual bool auto_padding() = 0;
88 /** Update the offset to the first element, the strides and the total size.
89 *
90 * @note This function can only increase the offset, strides and total size.
91 *
92 * @param[in] padding Padding around the XY plane in number of elements.
93 *
94 * @return True if the strides, offset and total size have changed.
95 */
96 virtual bool extend_padding(const PaddingSize &padding) = 0;
97 /** Return the size of the requested dimension
98 *
99 * @param[in] index Index of the dimension
100 *
101 * @return Dimension of the requested dimension
102 */
103 virtual size_t dimension(size_t index) const = 0;
104 /** The strides in bytes for accessing each dimension of the tensor
105 *
106 * @return Strides in bytes for each tensor dimension
107 */
108 virtual const Strides &strides_in_bytes() const = 0;
109 /** The offset from the beginning of the memory allocation to the first element of the tensor.
110 * This can be used to access efficiently elements in a 2D tensor
111 *
112 * @return The offset in bytes to access the first element of the tensor.
113 */
114 virtual size_t offset_first_element_in_bytes() const = 0;
115 /** The offset in bytes from the beginning of the memory allocation to access the element at position (x, y, z ...)
116 *
117 * @param[in] pos Vector with the coordinates of the element to access.
118 * The size of this vector must be equal to the number of dimensions of the tensor
119 *
120 * @return Offset in bytes from the beginning of the memory allocation to access the element (x, y, z, ...)
121 */
122 virtual size_t offset_element_in_bytes(const Coordinates &pos) const = 0;
123 /** Fixed point position used when the tensor data type is QS8 or QS16
124 *
125 * @return The fixed point position that expresses the number of bits for the fractional part of the number
126 */
127 virtual int fixed_point_position() const = 0;
128 /** Element size in bytes calculated as data_size() * num_channels()
129 *
130 * @return The size of one element in bytes
131 */
132 virtual size_t element_size() const = 0;
133 /** The number of dimensions of the tensor (rank)
134 *
135 * @return The number of dimensions of the tensor (rank)
136 */
137 virtual size_t num_dimensions() const = 0;
138 /** The number of channels for each tensor element
139 *
140 * @return The number of channels for each tensor element
141 */
142 virtual size_t num_channels() const = 0;
143 /** Size for each dimension of the tensor
144 *
145 * @return A vector with the size for each dimension of the tensor
146 */
147 virtual const TensorShape &tensor_shape() const = 0;
148 /** Data type used for each element of the tensor
149 *
150 * @return Tensor data type
151 */
152 virtual DataType data_type() const = 0;
153 /** Colour format of the image
154 *
155 * @return Colour format of the image
156 */
157 virtual Format format() const = 0;
158 /** Returns the total size of the tensor in bytes.
159 *
160 * @return Total size of the tensor in bytes.
161 */
162 virtual size_t total_size() const = 0;
163 /** Padding of tensor.
164 *
165 * @return Padding.
166 */
167 virtual PaddingSize padding() const = 0;
168 /** Checks if the tensor has been allocated with padding or not.
169 *
170 * @return True if padding is allocated in the tensor, otherwise false.
171 */
172 virtual bool has_padding() const = 0;
173 /** Flag indicating whether the size of the tensor can be changed.
174 *
175 * @return True if the tensor size can be changed.
176 */
177 virtual bool is_resizable() const = 0;
178 /** Set the flag whether the tensor size can be changed.
179 *
180 * @param[in] is_resizable Flag that marks the tensor if it can be changed or not.
181 */
182 virtual void set_is_resizable(bool is_resizable) = 0;
183 /** Valid region of the tensor. All elements in the valid region have defined values, i.e. are not undefined.
184 *
185 * @return The valid region.
186 */
187 virtual ValidRegion valid_region() const = 0;
188 /** Set the valid region of the tensor.
189 *
190 * @param[in] valid_region Valid region to set.
191 */
192 virtual void set_valid_region(ValidRegion valid_region) = 0;
193};
194}
195#endif /*__ARM_COMPUTE_TENSORINFO_H__ */