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Anthony Barbier6ff3b192017-09-04 18:44:23 +01001/*
2 * Copyright (c) 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_TEST_NEON_HELPER_H__
25#define __ARM_COMPUTE_TEST_NEON_HELPER_H__
26
27#include "Globals.h"
28#include "TensorLibrary.h"
29
Georgios Pinitas7b7858d2017-06-21 16:44:24 +010030#include "arm_compute/runtime/Array.h"
Anthony Barbier6ff3b192017-09-04 18:44:23 +010031#include "arm_compute/runtime/Tensor.h"
32
33namespace arm_compute
34{
35namespace test
36{
37namespace neon
38{
39/** Helper to create an empty tensor.
40 *
41 * @param[in] shape Desired shape.
42 * @param[in] data_type Desired data type.
43 * @param[in] num_channels (Optional) It indicates the number of channels for each tensor element
44 * @param[in] fixed_point_position (Optional) Fixed point position that expresses the number of bits for the fractional part of the number when the tensor's data type is QS8 or QS16.
45 *
46 * @return Empty @ref Tensor with the specified shape and data type.
47 */
48inline Tensor create_tensor(const TensorShape &shape, DataType data_type, int num_channels = 1, int fixed_point_position = 0)
49{
50 Tensor tensor;
51 tensor.allocator()->init(TensorInfo(shape, num_channels, data_type, fixed_point_position));
52
53 return tensor;
54}
55
56/** Helper to create an empty tensor.
57 *
58 * @param[in] name File name from which to get the dimensions.
59 * @param[in] data_type Desired data type.
60 * @param[in] fixed_point_position (Optional) Number of bits for the fractional part of the fixed point numbers
61 *
62 * @return Empty @ref Tensor with the specified shape and data type.
63 */
64inline Tensor create_tensor(const std::string &name, DataType data_type, int fixed_point_position = 0)
65{
66 constexpr unsigned int num_channels = 1;
67
68 const RawTensor &raw = library->get(name);
69
70 Tensor tensor;
71 tensor.allocator()->init(TensorInfo(raw.shape(), num_channels, data_type, fixed_point_position));
72
73 return tensor;
74}
Georgios Pinitas7b7858d2017-06-21 16:44:24 +010075
76template <typename T>
77Array<T> create_array(const std::vector<T> &v)
78{
79 const size_t v_size = v.size();
80 Array<T> array(v_size);
81
82 array.resize(v_size);
83 std::copy(v.begin(), v.end(), array.buffer());
84
85 return array;
86}
Anthony Barbier6ff3b192017-09-04 18:44:23 +010087} // namespace neon
88} // namespace test
89} // namespace arm_compute
90#endif