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
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
|
import argparse
import os
import textwrap
from pathlib import Path
import common
# Imports for working with classi
from classifier import (
CategoryConfig,
CommitClassifier,
CommitClassifierInputs,
get_author_map,
get_file_map,
XLMR_BASE,
)
from commitlist import CommitList
from common import get_commit_data_cache, topics
import torch
class Categorizer:
def __init__(self, path, category="Uncategorized", use_classifier: bool = False):
self.cache = get_commit_data_cache()
self.commits = CommitList.from_existing(path)
if use_classifier:
print("Using a classifier to aid with categorization.")
device = "cuda" if torch.cuda.is_available() else "cpu"
classifier_config = CategoryConfig(common.categories)
author_map = get_author_map(
Path("results/classifier"), regen_data=False, assert_stored=True
)
file_map = get_file_map(
Path("results/classifier"), regen_data=False, assert_stored=True
)
self.classifier = CommitClassifier(
XLMR_BASE, author_map, file_map, classifier_config
).to(device)
self.classifier.load_state_dict(
torch.load(Path("results/classifier/commit_classifier.pt"))
)
self.classifier.eval()
else:
self.classifier = None
# Special categories: 'Uncategorized'
# All other categories must be real
self.category = category
def categorize(self):
commits = self.commits.filter(category=self.category)
total_commits = len(self.commits.commits)
already_done = total_commits - len(commits)
i = 0
while i < len(commits):
cur_commit = commits[i]
next_commit = commits[i + 1] if i + 1 < len(commits) else None
jump_to = self.handle_commit(
cur_commit, already_done + i + 1, total_commits, commits
)
# Increment counter
if jump_to is not None:
i = jump_to
elif next_commit is None:
i = len(commits)
else:
i = commits.index(next_commit)
def features(self, commit):
return self.cache.get(commit.commit_hash)
def potential_reverts_of(self, commit, commits):
submodule_update_str = [
"Update TensorPipe submodule",
"Updating submodules",
"Automated submodule update",
]
if any(a in commit.title for a in submodule_update_str):
return []
features = self.features(commit)
if "Reverted" in features.labels:
reasons = {"GithubBot": "Reverted"}
else:
reasons = {}
index = commits.index(commit)
# -8 to remove the (#35011)
cleaned_title = commit.title[:-10]
# NB: the index + 2 is sketch
reasons.update(
{
(index + 2 + delta): cand
for delta, cand in enumerate(commits[index + 1 :])
if cleaned_title in cand.title
and commit.commit_hash != cand.commit_hash
}
)
return reasons
def handle_commit(self, commit, i, total, commits):
potential_reverts = self.potential_reverts_of(commit, commits)
if potential_reverts:
potential_reverts = f"!!!POTENTIAL REVERTS!!!: {potential_reverts}"
else:
potential_reverts = ""
features = self.features(commit)
if self.classifier is not None:
# Some commits don't have authors:
author = features.author if features.author else "Unknown"
files = " ".join(features.files_changed)
classifier_input = CommitClassifierInputs(
title=[features.title], files=[files], author=[author]
)
classifier_category = self.classifier.get_most_likely_category_name(
classifier_input
)[0]
else:
classifier_category = commit.category
breaking_alarm = ""
if "module: bc-breaking" in features.labels:
breaking_alarm += "\n!!!!!! BC BREAKING !!!!!!"
if "module: deprecation" in features.labels:
breaking_alarm += "\n!!!!!! DEPRECATION !!!!!!"
os.system("clear")
view = textwrap.dedent(
f"""\
[{i}/{total}]
================================================================================
{features.title}
{potential_reverts} {breaking_alarm}
{features.body}
Files changed: {features.files_changed}
Labels: {features.labels}
Current category: {commit.category}
Select from: {', '.join(common.categories)}
"""
)
print(view)
cat_choice = None
while cat_choice is None:
print("Enter category: ")
value = input(f"{classifier_category} ").strip()
if len(value) == 0:
# The user just pressed enter and likes the default value
cat_choice = classifier_category
continue
choices = [cat for cat in common.categories if cat.startswith(value)]
if len(choices) != 1:
print(f"Possible matches: {choices}, try again")
continue
cat_choice = choices[0]
print(f"\nSelected: {cat_choice}")
print(f"\nCurrent topic: {commit.topic}")
print(f"""Select from: {', '.join(topics)}""")
topic_choice = None
while topic_choice is None:
value = input("topic> ").strip()
if len(value) == 0:
topic_choice = commit.topic
continue
choices = [cat for cat in topics if cat.startswith(value)]
if len(choices) != 1:
print(f"Possible matches: {choices}, try again")
continue
topic_choice = choices[0]
print(f"\nSelected: {topic_choice}")
self.update_commit(commit, cat_choice, topic_choice)
return None
def update_commit(self, commit, category, topic):
assert category in common.categories
assert topic in topics
commit.category = category
commit.topic = topic
self.commits.write_result()
def main():
parser = argparse.ArgumentParser(description="Tool to help categorize commits")
parser.add_argument(
"--category",
type=str,
default="Uncategorized",
help='Which category to filter by. "Uncategorized", None, or a category name',
)
parser.add_argument(
"--file",
help="The location of the commits CSV",
default="results/commitlist.csv",
)
parser.add_argument(
"--use_classifier",
action="store_true",
help="Whether or not to use a classifier to aid in categorization.",
)
args = parser.parse_args()
categorizer = Categorizer(args.file, args.category, args.use_classifier)
categorizer.categorize()
if __name__ == "__main__":
main()
|
