forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
check_backward_compatibility.py
186 lines (175 loc) · 7.75 KB
/
check_backward_compatibility.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
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
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
from __future__ import absolute_import, division, print_function, unicode_literals
import argparse
import datetime
import re
import sys
import torch
from torch._C import parse_schema
# The date specifies how long the whitelist exclusion should apply to.
#
# - If we NEVER give BC guarantee for an operator, you can put the
# date arbitrarily far in the future.
# - Otherwise, pick a date that is far enough in the future that you
# believe you can land your diff before then.
#
# Whitelist entries can be removed after the date listed on them passes.
white_list = [
('c10_experimental', datetime.date(2222, 1, 1)),
# We export some functions and classes for test_jit.py directly from libtorch.so,
# it's not important to have BC for them
('_TorchScriptTesting.*', datetime.date(9999, 1, 1)),
('aten::pop*', datetime.date(2020, 4, 1)),
('aten::insert*', datetime.date(2020, 4, 1)),
('aten::Delete*', datetime.date(2020, 4, 1)),
('aten::clear*', datetime.date(2020, 4, 1)),
('aten::_set_item*', datetime.date(2020, 4, 1)),
('aten::copy*', datetime.date(2020, 4, 1)),
('aten::extend*', datetime.date(2020, 4, 1)),
('aten::reverse*', datetime.date(2020, 4, 1)),
('aten::append*', datetime.date(2020, 4, 1)),
('aten::list*', datetime.date(2020, 4, 1)),
('aten::__getitem__*', datetime.date(2020, 4, 1)),
('aten::len*', datetime.date(2020, 4, 1)),
('aten::mul_*', datetime.date(2020, 4, 1)),
('aten::slice*', datetime.date(2020, 4, 1)),
('aten::add*', datetime.date(2020, 4, 1)),
('aten::mul*', datetime.date(2020, 4, 1)),
('aten::select*', datetime.date(2020, 4, 1)),
('aten::add_*', datetime.date(2020, 4, 1)),
# _like default change, see https://github.com/pytorch/pytorch/issues/33580
('aten::randn_like', datetime.date(2020, 3, 15)),
('aten::full_like', datetime.date(2020, 3, 15)),
('aten::empty_like', datetime.date(2020, 3, 15)),
('aten::rand_like', datetime.date(2020, 3, 15)),
('aten::ones_like', datetime.date(2020, 3, 15)),
('aten::randint_like', datetime.date(2020, 3, 15)),
('aten::zeros_like', datetime.date(2020, 3, 15)),
('aten::floor_divide', datetime.date(2020, 4, 1)),
('aten::Bool', datetime.date(2020, 4, 1)),
('aten::Float', datetime.date(2020, 4, 1)),
('aten::to', datetime.date(2020, 4, 1)),
('aten::backward', datetime.date(2020, 4, 1)),
('aten::len', datetime.date(2020, 4, 1)),
('aten::remove', datetime.date(2020, 4, 1)),
('aten::index', datetime.date(2020, 4, 1)),
('aten::count', datetime.date(2020, 4, 1)),
('aten::__contains__', datetime.date(2020, 4, 1)),
('aten::sort', datetime.date(2020, 4, 1)),
('aten::sorted', datetime.date(2020, 4, 1)),
('aten::eq', datetime.date(2020, 4, 1)),
('aten::ne', datetime.date(2020, 4, 1)),
('aten::lt', datetime.date(2020, 4, 1)),
('aten::gt', datetime.date(2020, 4, 1)),
('aten::le', datetime.date(2020, 4, 1)),
('aten::ge', datetime.date(2020, 4, 1)),
('aten::divmod', datetime.date(2020, 4, 1)),
('aten::__upsample_bilinear', datetime.date(2020, 4, 1)),
('aten::__upsample', datetime.date(2020, 4, 1)),
('aten::__upsample_nearest', datetime.date(2020, 4, 1)),
('aten::__interpolate', datetime.date(2020, 4, 1)),
('aten::fabs', datetime.date(2020, 4, 1)),
('aten::gamma', datetime.date(2020, 4, 1)),
('prim::abs', datetime.date(2020, 4, 1)),
('aten::factorial', datetime.date(2020, 4, 1)),
('aten::radians', datetime.date(2020, 4, 1)),
('aten::degrees', datetime.date(2020, 4, 1)),
('prim::acosh', datetime.date(2020, 4, 1)),
('prim::atanh', datetime.date(2020, 4, 1)),
('aten::asinh', datetime.date(2020, 4, 1)),
('aten::floordiv', datetime.date(2020, 4, 1)),
('prim::NumToTensor', datetime.date(2020, 4, 1)),
('aten::sin', datetime.date(2020, 4, 1)),
('aten::round', datetime.date(2020, 4, 1)),
('aten::remainder', datetime.date(2020, 4, 1)),
('aten::isfinite', datetime.date(2020, 4, 1)),
('aten::sub', datetime.date(2020, 4, 1)),
('aten::sqrt', datetime.date(2020, 4, 1)),
('aten::log1p', datetime.date(2020, 4, 1)),
('aten::acos', datetime.date(2020, 4, 1)),
('aten::floor', datetime.date(2020, 4, 1)),
('aten::exp', datetime.date(2020, 4, 1)),
('aten::tan', datetime.date(2020, 4, 1)),
('aten::sinh', datetime.date(2020, 4, 1)),
('aten::ceil', datetime.date(2020, 4, 1)),
('aten::atan', datetime.date(2020, 4, 1)),
('aten::erf', datetime.date(2020, 4, 1)),
('aten::erfc', datetime.date(2020, 4, 1)),
('aten::cosh', datetime.date(2020, 4, 1)),
('aten::expm1', datetime.date(2020, 4, 1)),
('aten::isinf', datetime.date(2020, 4, 1)),
('aten::lgamma', datetime.date(2020, 4, 1)),
('aten::asin', datetime.date(2020, 4, 1)),
('aten::log', datetime.date(2020, 4, 1)),
('aten::log10', datetime.date(2020, 4, 1)),
('aten::cos', datetime.date(2020, 4, 1)),
('aten::tanh', datetime.date(2020, 4, 1)),
('prim::min', datetime.date(2020, 4, 1)),
('prim::max', datetime.date(2020, 4, 1)),
('aten::_linear_packed', datetime.date(2020, 4, 1)),
('aten::_linear_prepack', datetime.date(2020, 4, 1)),
('aten::_conv2d_packed', datetime.date(2020, 4, 1)),
('aten::_conv2d_prepack', datetime.date(2020, 4, 1)),
('aten::confirmed_by_owner', datetime.date(2020, 3, 17)),
('aten::owner', datetime.date(2020, 3, 27)),
('aten::owner_name', datetime.date(2020, 3, 27)),
]
def white_listed(schema, white_list):
for item in white_list:
if item[1] < datetime.date.today():
continue
regexp = re.compile(item[0])
if regexp.search(schema.name):
return True
return False
def check_bc(new_schema_dict):
existing_schemas = torch._C._jit_get_all_schemas()
is_bc = True
broken_ops = []
for existing_schema in existing_schemas:
if white_listed(existing_schema, white_list):
print("skipping schema: ", str(existing_schema))
continue
print("processing existing schema: ", str(existing_schema))
new_schemas = new_schema_dict.get(existing_schema.name, [])
found = False
for new_schema in new_schemas:
if new_schema.is_backward_compatible_with(existing_schema):
found = True
break
if not found:
print('Can NOT find backward compatible schemas after changes '
'for schema {} from the following candidates:\n[\n{}\n]'
.format(
str(existing_schema),
"\n\t".join(str(s) for s in new_schemas)))
# TODO Print out more details about why candidates don't match.
broken_ops.append(str(existing_schema))
is_bc = False
if is_bc:
print('Found backward compatible schemas for all existing schemas')
else:
print('The PR is introducing backward incompatible changes to the '
'operator library. Please contact PyTorch team to confirm '
'whether this change is wanted or not. \n\nBroken ops: '
'[\n\t{}\n]'.format("\n\t".join(broken_ops)))
return is_bc
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Process some integers.')
parser.add_argument(
'--new-schemas',
help='filename to load new schemas',
type=str,
default='schemas.txt')
args = parser.parse_args()
new_schema_dict = dict()
with open(args.new_schemas, 'r') as f:
while True:
line = f.readline()
if not line:
break
s = parse_schema(line.strip())
slist = new_schema_dict.get(s.name, [])
slist.append(s)
new_schema_dict[s.name] = slist
if not check_bc(new_schema_dict):
sys.exit(1)