1 /*
2 * Copyright (c) 2017-2019 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_GC_HELPER_H
25 #define ARM_COMPUTE_TEST_GC_HELPER_H
26
27 #include "tests/Globals.h"
28
29 #include "arm_compute/core/ITensor.h"
30 #include "arm_compute/runtime/GLES_COMPUTE/GCTensor.h"
31
32 #include <iostream>
33
34 namespace arm_compute
35 {
36 namespace test
37 {
38 /** Helper to create an empty tensor.
39 *
40 * @param[in] shape Desired shape.
41 * @param[in] data_type Desired data type.
42 * @param[in] num_channels (Optional) It indicates the number of channels for each tensor element
43 *
44 * @return Empty @ref GCTensor with the specified shape and data type.
45 */
46 inline GCTensor create_tensor(const TensorShape &shape, DataType data_type, int num_channels = 1)
47 {
48 GCTensor tensor;
49 tensor.allocator()->init(TensorInfo(shape, num_channels, data_type));
50
51 return tensor;
52 }
53
54 /** Helper to create an empty tensor.
55 *
56 * @param[in] name File name from which to get the dimensions.
57 * @param[in] data_type Desired data type.
58 *
59 * @return Empty @ref GCTensor with the specified shape and data type.
60 */
create_tensor(const std::string & name,DataType data_type)61 inline GCTensor create_tensor(const std::string &name, DataType data_type)
62 {
63 constexpr unsigned int num_channels = 1;
64
65 const RawTensor &raw = library->get(name);
66
67 GCTensor tensor;
68 tensor.allocator()->init(TensorInfo(raw.shape(), num_channels, data_type));
69
70 return tensor;
71 }
72
73 /** Helper to print tensor.
74 *
75 * @param[in] tensor Tensor to print.
76 * @param[in] name Tensor name.
77 * @param[in] info Format information.
78 *
79 * @return Empty @ref GCTensor with the specified shape and data type.
80 */
81 inline void print_tensor(ITensor &tensor, const std::string &name, IOFormatInfo info = IOFormatInfo(IOFormatInfo::PrintRegion::Full))
82 {
83 std::ostringstream s;
84 IGCTensor &t = dynamic_cast<IGCTensor &>(tensor);
85 t.map();
86 t.print(s, info);
87
88 std::cout << name << ":" << std::endl;
89 std::cout << s.str().c_str();
90 t.unmap();
91 }
92 } // namespace test
93 } // namespace arm_compute
94 #endif /* ARM_COMPUTE_TEST_GC_HELPER_H */
95