1 /*
2 * Copyright (c) 2018 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 #include "arm_compute/core/Types.h"
25 #include "arm_compute/runtime/CL/CLTensor.h"
26 #include "arm_compute/runtime/CL/CLTensorAllocator.h"
27 #include "arm_compute/runtime/CL/functions/CLUnstack.h"
28
29 #include "tests/CL/CLAccessor.h"
30 #include "tests/datasets/ShapeDatasets.h"
31 #include "tests/framework/Asserts.h"
32 #include "tests/framework/Macros.h"
33 #include "tests/framework/datasets/Datasets.h"
34 #include "tests/validation/Validation.h"
35 #include "tests/validation/fixtures/UnstackFixture.h"
36
37 namespace arm_compute
38 {
39 namespace test
40 {
41 namespace validation
42 {
43 namespace
44 {
45 const auto unstack_axis_dataset = framework::dataset::make("Axis", -3, 3);
46 const auto unstack_num_dataset = framework::dataset::make("Num", 1, 3); // The length of the dimension axis
47 const auto unstack_dataset_small = datasets::Small3DShapes() * unstack_axis_dataset * unstack_num_dataset;
48 } //namespace
49
50 TEST_SUITE(CL)
TEST_SUITE(Unstack)51 TEST_SUITE(Unstack)
52
53 DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
54 framework::dataset::make("InputInfo",
55 {
56 TensorInfo(TensorShape(1U, 9U, 8U), 1, DataType::U8), // Passes, 1 slice on x axis
57 TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::U8), // fails because axis > input's rank
58 TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::S32), // fails axis < (- input's rank)
59 TensorInfo(TensorShape(3U, 7U, 5U), 1, DataType::S32), // passes, 3 slices along X
60 TensorInfo(TensorShape(13U, 7U, 5U), 1, DataType::S16), // fails, too few output slices
61 TensorInfo(TensorShape(1U, 2U, 3U), 1, DataType::U8), // fails mismatching data types
62 }),
63 framework::dataset::make("OutputInfo",
64 {
65 std::vector<TensorInfo>{ TensorInfo(TensorShape(9U, 8U), 1, DataType::U8) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(2U, 3U), 1, DataType::U8) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(2U, 3U), 1, DataType::S32) },
66
67 std::vector<TensorInfo>{ TensorInfo(TensorShape(7U, 5U), 1, DataType::S32), TensorInfo(TensorShape(7U, 5U), 1, DataType::S32), TensorInfo(TensorShape(7U, 5U), 1, DataType::S32) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(7U, 5U), 1, DataType::S16) }, std::vector<TensorInfo>{ TensorInfo(TensorShape(9U, 8U), 1, DataType::S32) },
68 })),
69 framework::dataset::make("Axis", { -3, 3, -4, -3, 1, 1 })),
70 framework::dataset::make("Num", { 1, 1, 1, 1, 0, 1 })),
71 framework::dataset::make("Expected", { true, false, false, true, false, false })),
72 input_info, output_info, axis, num, expected)
73 {
74 std::vector<TensorInfo> ti(output_info);
75 std::vector<ITensorInfo *> vec(num);
76 for(size_t j = 0; j < vec.size(); ++j)
77 {
78 vec[j] = &ti[j];
79 }
80 ARM_COMPUTE_EXPECT(bool(CLUnstack::validate(&input_info.clone()->set_is_resizable(false), vec, axis)) == expected, framework::LogLevel::ERRORS);
81 }
82
83 template <typename T>
84 using CLUnstackFixture = UnstackValidationFixture<CLTensor, ICLTensor, CLAccessor, CLUnstack, T>;
85
86 TEST_SUITE(F32)
87 FIXTURE_DATA_TEST_CASE(RunSmall, CLUnstackFixture<float>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::F32 }))
88 {
89 ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size());
90 // Validate output
91 for(size_t k = 0; k < _target.size(); ++k)
92 {
93 validate(CLAccessor(_target[k]), _reference[k]);
94 }
95 }
96 TEST_SUITE_END() // F32
97
TEST_SUITE(F16)98 TEST_SUITE(F16)
99 FIXTURE_DATA_TEST_CASE(RunSmall, CLUnstackFixture<half>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::F16 }))
100 {
101 ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size());
102 // Validate output
103 for(size_t k = 0; k < _target.size(); ++k)
104 {
105 validate(CLAccessor(_target[k]), _reference[k]);
106 }
107 }
108 TEST_SUITE_END() // F16
109
TEST_SUITE(Quantized)110 TEST_SUITE(Quantized)
111 FIXTURE_DATA_TEST_CASE(RunSmall, CLUnstackFixture<uint8_t>, framework::DatasetMode::PRECOMMIT, unstack_dataset_small * framework::dataset::make("DataType", { DataType::QASYMM8 }))
112 {
113 ARM_COMPUTE_ERROR_ON(_target.size() != _reference.size());
114 // Validate output
115 for(size_t k = 0; k < _target.size(); ++k)
116 {
117 validate(CLAccessor(_target[k]), _reference[k]);
118 }
119 }
120 TEST_SUITE_END() // QASYMM8
121
122 TEST_SUITE_END() // Unstack
123 TEST_SUITE_END() // CL
124 } // namespace validation
125 } // namespace test
126 } // namespace arm_compute
127