



import unittest

from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available

from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin


if is_bsa_available():
	from transformers import MarkupLMFeatureExtractor

class  __snake_case      (   unittest.TestCase):







							'''simple docstring'''






							def __init__(							self  ,  a_		):
											a__				      =		parent







							def _a      (							self		):
											return {}




def 			A_      (	):

				"""simple docstring"""
				a__				      =		"""<HTML>

    <HEAD>
    <TITLE>sample document</TITLE>
    </HEAD>

    <BODY BGCOLOR=\"FFFFFF\">
    <HR>
    <a href=\"http://google.com\">Goog</a>
    <H1>This is one header</H1>
    <H2>This is a another Header</H2>
    <P>Travel from
        <P>
        <B>SFO to JFK</B>
        <BR>
        <B><I>on May 2, 2015 at 2:00 pm. For details go to confirm.com </I></B>
        <HR>
        <div style=\"color:#0000FF\">
            <h3>Traveler <b> name </b> is
            <p> John Doe </p>
        </div>"""

				a__				      =		"""
    <!DOCTYPE html>
    <html>
    <body>

    <h1>My First Heading</h1>
    <p>My first paragraph.</p>

    </body>
    </html>
    """

				return [html_string_a, html_string_a]




@require_bsa
class  __snake_case      (   SCREAMING_SNAKE_CASE			,unittest.TestCase):







							'''simple docstring'''






							UpperCamelCase__				:      Dict         =					MarkupLMFeatureExtractor if is_bsa_available() else None


							def _a      (							self		):
											a__				      =		MarkupLMFeatureExtractionTester(self		)


							@property
							def _a      (							self		):
											return self.feature_extract_tester.prepare_feat_extract_dict()







							def _a      (							self		):
											# Initialize feature_extractor
											a__				      =		self.feature_extraction_class()

											# Test not batched input
											a__				      =		get_html_strings()[0]
											a__				      =		feature_extractor(a_		)

											# fmt: off
											a__				      =		[["""sample document""", """Goog""", """This is one header""", """This is a another Header""", """Travel from""", """SFO to JFK""", """on May 2, 2015 at 2:00 pm. For details go to confirm.com""", """Traveler""", """name""", """is""", """John Doe"""]]
											a__				      =		[["""/html/head/title""", """/html/body/a""", """/html/body/h1""", """/html/body/h2""", """/html/body/p""", """/html/body/p/p/b[1]""", """/html/body/p/p/b[2]/i""", """/html/body/p/p/div/h3""", """/html/body/p/p/div/h3/b""", """/html/body/p/p/div/h3""", """/html/body/p/p/div/h3/p"""]]
											# fmt: on

											self.assertEqual(encoding.nodes  ,  a_		)
											self.assertEqual(encoding.xpaths  ,  a_		)

											# Test batched
											a__				      =		get_html_strings()
											a__				      =		feature_extractor(a_		)

											# fmt: off
											a__				      =		expected_nodes + [["""My First Heading""", """My first paragraph."""]]
											a__				      =		expected_xpaths + [["""/html/body/h1""", """/html/body/p"""]]

											self.assertEqual(len(encoding.nodes		)  ,  2		)
											self.assertEqual(len(encoding.xpaths		)  ,  2		)

											self.assertEqual(encoding.nodes  ,  a_		)
											self.assertEqual(encoding.xpaths  ,  a_		)






import os
from datetime import datetime as dt

from github import Github


UpperCAmelCase							 =					[
    """good first issue""",
    """good second issue""",
    """good difficult issue""",
    """enhancement""",
    """new pipeline/model""",
    """new scheduler""",
    """wip""",
]

def 			A_      (	):

				"""simple docstring"""
				a__				      =		Github(os.environ["""GITHUB_TOKEN"""]		)
				a__				      =		g.get_repo("""huggingface/diffusers"""		)
				a__				      =		repo.get_issues(state="""open"""		)

				for issue in open_issues:
								a__				      =		sorted(issue.get_comments() ,		key=lambda __a		: i.created_at ,		reverse=__a		)
								a__				      =		comments[0] if len(__a		) > 0 else None
								if (
								    last_comment is not None
								    and last_comment.user.login == "github-actions[bot]"
								    and (dt.utcnow() - issue.updated_at).days > 7
								    and (dt.utcnow() - issue.created_at).days >= 30
								    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()		)
								):
												# Closes the issue after 7 days of inactivity since the Stalebot notification.
												issue.edit(state="""closed"""		)
								elif (
								    "stale" in issue.get_labels()
								    and last_comment is not None
								    and last_comment.user.login != "github-actions[bot]"
								):
												# Opens the issue if someone other than Stalebot commented.
												issue.edit(state="""open"""		)
												issue.remove_from_labels("""stale"""		)
								elif (
								    (dt.utcnow() - issue.updated_at).days > 23
								    and (dt.utcnow() - issue.created_at).days >= 30
								    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()		)
								):
												# Post a Stalebot notification after 23 days of inactivity.
												issue.create_comment(
												    """This issue has been automatically marked as stale because it has not had """
												    """recent activity. If you think this still needs to be addressed """
												    """please comment on this thread.\n\nPlease note that issues that do not follow the """
												    """[contributing guidelines](https://github.com/huggingface/diffusers/blob/main/CONTRIBUTING.md) """
												    """are likely to be ignored."""		)
												issue.add_to_labels("""stale"""		)


if __name__ == "__main__":
	main()

