1 /*
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_SQUEEZENET_ACTIVATION_LAYER_DATASET
25 #define ARM_COMPUTE_TEST_SQUEEZENET_ACTIVATION_LAYER_DATASET
26 
27 #include "tests/framework/datasets/Datasets.h"
28 
29 #include "utils/TypePrinter.h"
30 
31 #include "arm_compute/core/TensorShape.h"
32 #include "arm_compute/core/Types.h"
33 
34 namespace arm_compute
35 {
36 namespace test
37 {
38 namespace datasets
39 {
40 class SqueezeNetActivationLayerDataset final : public
41     framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
42 {
43 public:
SqueezeNetActivationLayerDataset()44     SqueezeNetActivationLayerDataset()
45         : CartesianProductDataset
46     {
47         framework::dataset::make("Shape", { // relu_conv1
48             TensorShape(111U, 111U, 64U),
49             // fire2/relu_squeeze1x1, fire3/relu_squeeze1x1
50             TensorShape(55U, 55U, 16U),
51             // fire2/relu_expand1x1, fire2/relu_expand3x3, fire3/relu_expand1x1, fire3/relu_expand3x3
52             TensorShape(55U, 55U, 64U),
53             // fire4/relu_squeeze1x1, fire5/relu_squeeze1x1
54             TensorShape(27U, 27U, 32U),
55             // fire4/relu_expand1x1, fire4/relu_expand3x3, fire5/relu_expand1x1, fire5/relu_expand3x3
56             TensorShape(27U, 27U, 128U),
57             // fire6/relu_squeeze1x1, fire7/relu_squeeze1x1
58             TensorShape(13U, 13U, 48U),
59             // fire6/relu_expand1x1, fire6/relu_expand3x3, fire7/relu_expand1x1, fire7/relu_expand3x3
60             TensorShape(13U, 13U, 192U),
61             // fire8/relu_squeeze1x1, fire9/relu_squeeze1x1
62             TensorShape(13U, 13U, 64U),
63             // fire8/relu_expand1x1, fire8/relu_expand3x3, fire9/relu_expand1x1, fire9/relu_expand3x3
64             TensorShape(13U, 13U, 256U),
65             // relu_conv10
66             TensorShape(13U, 13U, 1000U) }),
67         framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
68     }
69     {
70     }
71     SqueezeNetActivationLayerDataset(SqueezeNetActivationLayerDataset &&) = default;
72     ~SqueezeNetActivationLayerDataset()                                   = default;
73 };
74 } // namespace datasets
75 } // namespace test
76 } // namespace arm_compute
77 #endif /* ARM_COMPUTE_TEST_SQUEEZENET_ACTIVATION_LAYER_DATASET */
78