




import json
import os
import unittest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 		lowercase							(     UpperCamelCase__,unittest.TestCase	):
     _a											=		CLIPTokenizer
     _a											=		CLIPTokenizerFast
     _a											=		True
     _a											=		{}
     _a											=		False

     def       a__			(						self       )		->							Optional[Any]:
           super().setUp()

           # fmt: off
           _A							:  int    =		["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
           # fmt: on
           _A							:  str    =		dict(zip(_a	,  range(len(_a       )       )       )       )
           _A							:  Optional[int]    =		["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>"""]
           _A							:  str    =		{"""unk_token""": """<unk>"""}

           _A							:  Union[str, Any]    =		os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["""vocab_file"""]       )
           _A							:  Union[str, Any]    =		os.path.join(self.tmpdirname	,  VOCAB_FILES_NAMES["""merges_file"""]       )
           with open(self.vocab_file	,  """w"""	,  encoding="""utf-8"""       ) as fp:
                 fp.write(json.dumps(_a       ) + """\n"""       )
           with open(self.merges_file	,  """w"""	,  encoding="""utf-8"""       ) as fp:
                 fp.write("""\n""".join(_a       )       )

     def       a__			(						self	,  **_a       )		->							List[Any]:
           kwargs.update(self.special_tokens_map       )
           return CLIPTokenizer.from_pretrained(self.tmpdirname	,  **_a       )

     def       a__			(						self	,  **_a       )		->							Union[str, Any]:
           kwargs.update(self.special_tokens_map       )
           return CLIPTokenizerFast.from_pretrained(self.tmpdirname	,  **_a       )

     def       a__			(						self	,  _a       )		->							str:
           _A							:  Tuple    =		"""lower newer"""
           _A							:  Optional[Any]    =		"""lower newer"""
           return input_text, output_text

     def       a__			(						self       )		->							List[Any]:
           _A							:  Optional[int]    =		CLIPTokenizer(self.vocab_file	,  self.merges_file	,  **self.special_tokens_map       )
           _A							:  str    =		"""lower newer"""
           _A							:  List[str]    =		["""lo""", """w""", """er</w>""", """n""", """e""", """w""", """er</w>"""]
           _A							:  int    =		tokenizer.tokenize(_a       )
           self.assertListEqual(_a	,  _a       )

           _A							:  str    =		tokens + [tokenizer.unk_token]
           _A							:  Dict    =		[10, 2, 16, 9, 3, 2, 16, 20]
           self.assertListEqual(tokenizer.convert_tokens_to_ids(_a       )	,  _a       )

     @require_ftfy
     def       a__			(						self       )		->							Tuple:
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
                       _A							:  Dict    =		self.tokenizer_class.from_pretrained(_a	,  **_a       )
                       _A							:  str    =		self.rust_tokenizer_class.from_pretrained(_a	,  **_a       )

                       _A							:  List[str]    =		"""A\n'll 11p223RF☆ho!!to?'d'd''d of a cat to-$''d."""
                       _A							:  Dict    =		tokenizer_s.tokenize(_a       )
                       _A							:  Dict    =		tokenizer_r.tokenize(_a       )

                       self.assertListEqual(_a	,  _a       )

                       # Test that the tokenization is identical on an example containing a character (Latin Small Letter A
                       # with Tilde) encoded in 2 different ways
                       _A							:  Tuple    =		"""xa\u0303y""" + """ """ + """x\xe3y"""
                       _A							:  Dict    =		tokenizer_s.tokenize(_a       )
                       _A							:  Dict    =		tokenizer_r.tokenize(_a       )

                       self.assertListEqual(_a	,  _a       )

                       # Test that the tokenization is identical on unicode of space type
                       _A							:  Any    =		[
                           """\u0009""",  # (horizontal tab, '\t')
                           """\u000B""",  # (vertical tab)
                           """\u000C""",  # (form feed)
                           """\u0020""",  # (space, ' ')
                           """\u200E""",  # (left-to-right mark):w
                           """\u200F""",  # (right-to-left mark)
                       ]
                       for unicode_seq in spaces_unicodes:
                             _A							:  Optional[int]    =		tokenizer_s.tokenize(_a       )
                             _A							:  List[Any]    =		tokenizer_r.tokenize(_a       )

                             self.assertListEqual(_a	,  _a       )

                       # Test that the tokenization is identical on unicode of line break type
                       _A							:  int    =		[
                           """\u000A""",  # (line feed, '\n')
                           """\r\n""",  # (carriage return and line feed, '\r\n')
                           """\u000D""",  # (carriage return, '\r')
                           """\r""",  # (carriage return, '\r')
                           """\u000D""",  # (carriage return, '\r')
                           """\u2028""",  # (line separator)
                           """\u2029""",  # (paragraph separator)
                           # "\u0085", # (next line)
                       ]

                       # The tokenization is not identical for the character "\u0085" (next line). The slow version using ftfy transforms
                       # it into the Horizontal Ellipsis character "…" ("\u2026") while the fast version transforms it into a
                       # space (and thus into an empty list).

                       for unicode_seq in line_break_unicodes:
                             _A							:  Optional[Any]    =		tokenizer_s.tokenize(_a       )
                             _A							:  Tuple    =		tokenizer_r.tokenize(_a       )

                             self.assertListEqual(_a	,  _a       )

     def       a__			(						self       )		->							Any:
           # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space`
           for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                 with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''       ):
                       _A							:  List[Any]    =		"""hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
                       _A							:  str    =		F'''{text_of_1_token} {text_of_1_token}'''

                       _A							:  str    =		self.rust_tokenizer_class.from_pretrained(
                           _a	,  use_fast=_a	,  )
                       _A							:  Dict    =		tokenizer_r(_a	,  return_offsets_mapping=_a	,  add_special_tokens=_a       )
                       self.assertEqual(encoding.offset_mapping[0]	,  (0, len(_a       ))       )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,  (len(_a       ) + 1, len(_a       ) + 1 + len(_a       ))	,  )

                       _A							:  Any    =		F''' {text}'''

                       _A							:  List[Any]    =		self.rust_tokenizer_class.from_pretrained(
                           _a	,  use_fast=_a	,  )
                       _A							:  Optional[int]    =		tokenizer_r(_a	,  return_offsets_mapping=_a	,  add_special_tokens=_a       )
                       self.assertEqual(encoding.offset_mapping[0]	,  (1, 1 + len(_a       ))       )
                       self.assertEqual(
                           encoding.offset_mapping[1]	,  (1 + len(_a       ) + 1, 1 + len(_a       ) + 1 + len(_a       ))	,  )

     def       a__			(						self       )		->							List[Any]:
           # Test related to the breaking change introduced in transformers v4.17.0
           # We need to check that an error in raised when the user try to load a previous version of the tokenizer.
           with self.assertRaises(_a       ) as context:
                 self.rust_tokenizer_class.from_pretrained("""robot-test/old-clip-tokenizer"""       )

           self.assertTrue(
               context.exception.args[0].startswith(
                   """The `backend_tokenizer` provided does not match the expected format."""       )       )

     @require_ftfy
     def       a__			(						self       )		->							str:
           super().test_tokenization_python_rust_equals()



     def       a__			(						self       )		->							Union[str, Any]:
           # CLIP always lower cases letters
           pass







from datetime import datetime as dt
import os

from github import Github


_snake_case            = [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "feature request",
    "new model",
    "wip",
]







def        lowerCAmelCase_			(  ):
      _A							:  int    =		Github(os.environ["""GITHUB_TOKEN"""]  )
      _A							:  Tuple    =		g.get_repo("""huggingface/transformers"""  )
      _A							:  Dict    =		repo.get_issues(state="""open"""  )

      for issue in open_issues:
            _A							:  Optional[Any]    =		sorted([comment for comment in issue.get_comments()],key=lambda snake_case_  : i.created_at,reverse=snake_case_  )
            _A							:  Dict    =		comments[0] if len(snake_case_  ) > 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()  )
            ):
                  # print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
                  issue.edit(state="""closed"""  )
            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()  )
            ):
                  # print(f"Would add stale comment to {issue.number}")
                  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/transformers/blob/main/CONTRIBUTING.md) """
                      """are likely to be ignored."""  )


if __name__ == "__main__":
  main()

