forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathtests_setup.py
88 lines (60 loc) · 1.72 KB
/
tests_setup.py
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
import sys
import os
import torch
class Setup(object):
def setup(self):
raise NotImplementedError()
def shutdown(self):
raise NotImplementedError()
class FileSetup(object):
path = None
def shutdown(self):
if os.path.exists(self.path):
os.remove(self.path)
pass
class EvalModeForLoadedModule(FileSetup):
path = 'dropout_model.pt'
def setup(self):
class Model(torch.jit.ScriptModule):
def __init__(self):
super(Model, self).__init__()
self.dropout = torch.nn.Dropout(0.1)
@torch.jit.script_method
def forward(self, x):
x = self.dropout(x)
return x
model = Model()
model = model.train()
model.save(self.path)
class SerializationInterop(FileSetup):
path = 'ivalue.pt'
def setup(self):
ones = torch.ones(2, 2)
twos = torch.ones(3, 5) * 2
value = (ones, twos)
torch.save(value, self.path, _use_new_zipfile_serialization=True)
# See testTorchSaveError in test/cpp/jit/tests.h for usage
class TorchSaveError(FileSetup):
path = 'eager_value.pt'
def setup(self):
ones = torch.ones(2, 2)
twos = torch.ones(3, 5) * 2
value = (ones, twos)
torch.save(value, self.path, _use_new_zipfile_serialization=False)
tests = [
EvalModeForLoadedModule(),
SerializationInterop(),
TorchSaveError(),
]
def setup():
for test in tests:
test.setup()
def shutdown():
for test in tests:
test.shutdown()
if __name__ == "__main__":
command = sys.argv[1]
if command == "setup":
setup()
elif command == "shutdown":
shutdown()