1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
|
/*
* Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
// TODO enable it
#if 0
#include "kernels/Softmax.h"
#include "kernels/TestUtils.h"
#include "luci_interpreter/TestMemoryManager.h"
namespace luci_interpreter
{
namespace kernels
{
namespace
{
using namespace testing;
template <typename T> constexpr loco::DataType toLocoDataType();
template <> constexpr loco::DataType toLocoDataType<float>() { return loco::DataType::FLOAT32; }
template <> constexpr loco::DataType toLocoDataType<uint8_t>() { return loco::DataType::U8; }
template <> constexpr loco::DataType toLocoDataType<int8_t>() { return loco::DataType::S8; }
template <typename T, std::enable_if_t<std::is_floating_point<T>::value, bool> = true>
void Check(std::initializer_list<int32_t> input_shape, std::initializer_list<int32_t> output_shape,
std::initializer_list<float> input_data, std::initializer_list<float> output_data)
{
std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
Tensor input_tensor =
makeInputTensor<toLocoDataType<T>()>(input_shape, input_data, memory_manager.get());
Tensor output_tensor = makeOutputTensor(toLocoDataType<T>());
SoftmaxParams params{};
params.beta = 0.1;
Softmax kernel(&input_tensor, &output_tensor, params);
kernel.configure();
memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorData<T>(output_tensor), FloatArrayNear(output_data));
EXPECT_THAT(extractTensorShape(output_tensor), output_shape);
}
template <typename T, std::enable_if_t<std::is_integral<T>::value, bool> = true>
void Check(std::initializer_list<int32_t> input_shape, std::initializer_list<int32_t> output_shape,
std::initializer_list<float> input_data, std::initializer_list<float> output_data)
{
std::unique_ptr<IMemoryManager> memory_manager = std::make_unique<TestMemoryManager>();
std::pair<float, int32_t> input_quant_param =
quantizationParams<T>(std::min<float>(std::min<float>(input_data), 0.f),
std::max<float>(std::max<float>(input_data), 0.f));
std::pair<float, int32_t> output_quant_param =
quantizationParams<T>(std::min<float>(std::min<float>(output_data), 0.f),
std::max<float>(std::max<float>(output_data), 0.f));
Tensor input_tensor = makeInputTensor<toLocoDataType<T>()>(input_shape, input_quant_param.first,
input_quant_param.second, input_data,
memory_manager.get());
Tensor output_tensor =
makeOutputTensor(toLocoDataType<T>(), output_quant_param.first, output_quant_param.second);
SoftmaxParams params{};
params.beta = 0.1;
Softmax kernel(&input_tensor, &output_tensor, params);
kernel.configure();
memory_manager->allocate_memory(output_tensor);
kernel.execute();
EXPECT_THAT(extractTensorShape(output_tensor), ::testing::ElementsAreArray(output_shape));
EXPECT_THAT(dequantizeTensorData(output_tensor),
FloatArrayNear(output_data, output_tensor.scale()));
}
template <typename T> class SoftmaxTest : public ::testing::Test
{
};
using DataTypes = ::testing::Types<float, uint8_t, int8_t>;
TYPED_TEST_SUITE(SoftmaxTest, DataTypes);
TYPED_TEST(SoftmaxTest, Simple)
{
Check<TypeParam>({2, 1, 2, 3}, {2, 1, 2, 3},
{
5, -9, 8, //
-7, 2, -4, //
1, -2, 9, //
3, -6, -1, //
},
{
0.38514, 0.09497, 0.51989, //
0.20792, 0.51141, 0.28067, //
0.25212, 0.18678, 0.56110, //
0.48149, 0.19576, 0.32275, //
});
}
} // namespace
} // namespace kernels
} // namespace luci_interpreter
#endif
|
