We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Use the bug snapshot transform in the "uplift" model
Depends on #5.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `bugbug/models/uplift.py`
Content:
```
1 # -*- coding: utf-8 -*-
2 # This Source Code Form is subject to the terms of the Mozilla Public
3 # License, v. 2.0. If a copy of the MPL was not distributed with this file,
4 # You can obtain one at http://mozilla.org/MPL/2.0/.
5 
6 import xgboost
7 from imblearn.under_sampling import RandomUnderSampler
8 from sklearn.compose import ColumnTransformer
9 from sklearn.feature_extraction import DictVectorizer
10 from sklearn.pipeline import Pipeline
11 
12 from bugbug import bug_features
13 from bugbug import bugzilla
14 from bugbug.model import Model
15 
16 
17 class UpliftModel(Model):
18     def __init__(self, lemmatization=False):
19         Model.__init__(self, lemmatization)
20 
21         self.sampler = RandomUnderSampler(random_state=0)
22 
23         feature_extractors = [
24             bug_features.has_str(),
25             bug_features.has_regression_range(),
26             bug_features.severity(),
27             bug_features.keywords(),
28             bug_features.is_coverity_issue(),
29             bug_features.has_crash_signature(),
30             bug_features.has_url(),
31             bug_features.has_w3c_url(),
32             bug_features.has_github_url(),
33             bug_features.whiteboard(),
34             bug_features.patches(),
35             bug_features.landings(),
36             bug_features.title(),
37         ]
38 
39         cleanup_functions = [
40             bug_features.cleanup_fileref,
41             bug_features.cleanup_url,
42             bug_features.cleanup_synonyms,
43         ]
44 
45         self.extraction_pipeline = Pipeline([
46             ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions)),
47             ('union', ColumnTransformer([
48                 ('data', DictVectorizer(), 'data'),
49 
50                 ('title', self.text_vectorizer(), 'title'),
51 
52                 ('comments', self.text_vectorizer(), 'comments'),
53             ])),
54         ])
55 
56         self.clf = xgboost.XGBClassifier(n_jobs=16)
57         self.clf.set_params(predictor='cpu_predictor')
58 
59     def get_labels(self):
60         classes = {}
61 
62         for bug_data in bugzilla.get_bugs():
63             bug_id = int(bug_data['id'])
64 
65             for attachment in bug_data['attachments']:
66                 for flag in attachment['flags']:
67                     if not flag['name'].startswith('approval-mozilla-') or flag['status'] not in ['+', '-']:
68                         continue
69 
70                     if flag['status'] == '+':
71                         classes[bug_id] = 1
72                     elif flag['status'] == '-':
73                         classes[bug_id] = 0
74 
75         return classes
76 
77     def get_feature_names(self):
78         return self.extraction_pipeline.named_steps['union'].get_feature_names()
79
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/bugbug/models/uplift.py b/bugbug/models/uplift.py
--- a/bugbug/models/uplift.py
+++ b/bugbug/models/uplift.py
@@ -43,7 +43,7 @@
         ]
 
         self.extraction_pipeline = Pipeline([
-            ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions)),
+            ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions, rollback=True, rollback_when=self.rollback)),
             ('union', ColumnTransformer([
                 ('data', DictVectorizer(), 'data'),
 
@@ -56,6 +56,9 @@
         self.clf = xgboost.XGBClassifier(n_jobs=16)
         self.clf.set_params(predictor='cpu_predictor')
 
+    def rollback(self, change):
+        return (change['field_name'] == 'flagtypes.name' and change['added'].startswith('approval-mozilla-') and (change['added'].endswith('+') or change['added'].endswith('-')))
+
     def get_labels(self):
         classes = {}

{"golden_diff": "diff --git a/bugbug/models/uplift.py b/bugbug/models/uplift.py\n--- a/bugbug/models/uplift.py\n+++ b/bugbug/models/uplift.py\n@@ -43,7 +43,7 @@\n         ]\n \n         self.extraction_pipeline = Pipeline([\n-            ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions)),\n+            ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions, rollback=True, rollback_when=self.rollback)),\n             ('union', ColumnTransformer([\n                 ('data', DictVectorizer(), 'data'),\n \n@@ -56,6 +56,9 @@\n         self.clf = xgboost.XGBClassifier(n_jobs=16)\n         self.clf.set_params(predictor='cpu_predictor')\n \n+    def rollback(self, change):\n+        return (change['field_name'] == 'flagtypes.name' and change['added'].startswith('approval-mozilla-') and (change['added'].endswith('+') or change['added'].endswith('-')))\n+\n     def get_labels(self):\n         classes = {}\n", "issue": "Use the bug snapshot transform in the \"uplift\" model\nDepends on #5.\n", "before_files": [{"content": "# -*- coding: utf-8 -*-\n# This Source Code Form is subject to the terms of the Mozilla Public\n# License, v. 2.0. If a copy of the MPL was not distributed with this file,\n# You can obtain one at http://mozilla.org/MPL/2.0/.\n\nimport xgboost\nfrom imblearn.under_sampling import RandomUnderSampler\nfrom sklearn.compose import ColumnTransformer\nfrom sklearn.feature_extraction import DictVectorizer\nfrom sklearn.pipeline import Pipeline\n\nfrom bugbug import bug_features\nfrom bugbug import bugzilla\nfrom bugbug.model import Model\n\n\nclass UpliftModel(Model):\n    def __init__(self, lemmatization=False):\n        Model.__init__(self, lemmatization)\n\n        self.sampler = RandomUnderSampler(random_state=0)\n\n        feature_extractors = [\n            bug_features.has_str(),\n            bug_features.has_regression_range(),\n            bug_features.severity(),\n            bug_features.keywords(),\n            bug_features.is_coverity_issue(),\n            bug_features.has_crash_signature(),\n            bug_features.has_url(),\n            bug_features.has_w3c_url(),\n            bug_features.has_github_url(),\n            bug_features.whiteboard(),\n            bug_features.patches(),\n            bug_features.landings(),\n            bug_features.title(),\n        ]\n\n        cleanup_functions = [\n            bug_features.cleanup_fileref,\n            bug_features.cleanup_url,\n            bug_features.cleanup_synonyms,\n        ]\n\n        self.extraction_pipeline = Pipeline([\n            ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions)),\n            ('union', ColumnTransformer([\n                ('data', DictVectorizer(), 'data'),\n\n                ('title', self.text_vectorizer(), 'title'),\n\n                ('comments', self.text_vectorizer(), 'comments'),\n            ])),\n        ])\n\n        self.clf = xgboost.XGBClassifier(n_jobs=16)\n        self.clf.set_params(predictor='cpu_predictor')\n\n    def get_labels(self):\n        classes = {}\n\n        for bug_data in bugzilla.get_bugs():\n            bug_id = int(bug_data['id'])\n\n            for attachment in bug_data['attachments']:\n                for flag in attachment['flags']:\n                    if not flag['name'].startswith('approval-mozilla-') or flag['status'] not in ['+', '-']:\n                        continue\n\n                    if flag['status'] == '+':\n                        classes[bug_id] = 1\n                    elif flag['status'] == '-':\n                        classes[bug_id] = 0\n\n        return classes\n\n    def get_feature_names(self):\n        return self.extraction_pipeline.named_steps['union'].get_feature_names()\n", "path": "bugbug/models/uplift.py"}], "after_files": [{"content": "# -*- coding: utf-8 -*-\n# This Source Code Form is subject to the terms of the Mozilla Public\n# License, v. 2.0. If a copy of the MPL was not distributed with this file,\n# You can obtain one at http://mozilla.org/MPL/2.0/.\n\nimport xgboost\nfrom imblearn.under_sampling import RandomUnderSampler\nfrom sklearn.compose import ColumnTransformer\nfrom sklearn.feature_extraction import DictVectorizer\nfrom sklearn.pipeline import Pipeline\n\nfrom bugbug import bug_features\nfrom bugbug import bugzilla\nfrom bugbug.model import Model\n\n\nclass UpliftModel(Model):\n    def __init__(self, lemmatization=False):\n        Model.__init__(self, lemmatization)\n\n        self.sampler = RandomUnderSampler(random_state=0)\n\n        feature_extractors = [\n            bug_features.has_str(),\n            bug_features.has_regression_range(),\n            bug_features.severity(),\n            bug_features.keywords(),\n            bug_features.is_coverity_issue(),\n            bug_features.has_crash_signature(),\n            bug_features.has_url(),\n            bug_features.has_w3c_url(),\n            bug_features.has_github_url(),\n            bug_features.whiteboard(),\n            bug_features.patches(),\n            bug_features.landings(),\n            bug_features.title(),\n        ]\n\n        cleanup_functions = [\n            bug_features.cleanup_fileref,\n            bug_features.cleanup_url,\n            bug_features.cleanup_synonyms,\n        ]\n\n        self.extraction_pipeline = Pipeline([\n            ('bug_extractor', bug_features.BugExtractor(feature_extractors, cleanup_functions, rollback=True, rollback_when=self.rollback)),\n            ('union', ColumnTransformer([\n                ('data', DictVectorizer(), 'data'),\n\n                ('title', self.text_vectorizer(), 'title'),\n\n                ('comments', self.text_vectorizer(), 'comments'),\n            ])),\n        ])\n\n        self.clf = xgboost.XGBClassifier(n_jobs=16)\n        self.clf.set_params(predictor='cpu_predictor')\n\n    def rollback(self, change):\n        return (change['field_name'] == 'flagtypes.name' and change['added'].startswith('approval-mozilla-') and (change['added'].endswith('+') or change['added'].endswith('-')))\n\n    def get_labels(self):\n        classes = {}\n\n        for bug_data in bugzilla.get_bugs():\n            bug_id = int(bug_data['id'])\n\n            for attachment in bug_data['attachments']:\n                for flag in attachment['flags']:\n                    if not flag['name'].startswith('approval-mozilla-') or flag['status'] not in ['+', '-']:\n                        continue\n\n                    if flag['status'] == '+':\n                        classes[bug_id] = 1\n                    elif flag['status'] == '-':\n                        classes[bug_id] = 0\n\n        return classes\n\n    def get_feature_names(self):\n        return self.extraction_pipeline.named_steps['union'].get_feature_names()\n", "path": "bugbug/models/uplift.py"}]}