


import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class        __lowercase       (							a_			,							unittest.TestCase  ):



		"""simple docstring"""

		UpperCamelCase     :					Optional[Any]			       =		RobertaTokenizer
		UpperCamelCase     :					List[str]			       =		RobertaTokenizerFast
		UpperCamelCase     :					str			       =		True
		UpperCamelCase     :					Optional[Any]			       =		{"cls_token": "<s>"}







		def 					__A   ( self	)  -> Union[str, Any]:







					'''simple docstring'''







					super().setUp()

					# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
					lowerCamelCase    		=  [
					    """l""",
					    """o""",
					    """w""",
					    """e""",
					    """r""",
					    """s""",
					    """t""",
					    """i""",
					    """d""",
					    """n""",
					    """\u0120""",
					    """\u0120l""",
					    """\u0120n""",
					    """\u0120lo""",
					    """\u0120low""",
					    """er""",
					    """\u0120lowest""",
					    """\u0120newer""",
					    """\u0120wider""",
					    """<unk>""",
					]
					lowerCamelCase    		=  dict(zip(A		,      range(len(A	)	)	)	)
					lowerCamelCase    		=  ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
					lowerCamelCase    		=  {"""unk_token""": """<unk>"""}

					lowerCamelCase    		=  os.path.join(self.tmpdirname		,      VOCAB_FILES_NAMES["""vocab_file"""]	)
					lowerCamelCase    		=  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	)  -> Tuple:







					'''simple docstring'''







					kwargs.update(self.special_tokens_map	)
					return self.tokenizer_class.from_pretrained(self.tmpdirname		,      **A	)







		def 					__A   ( self		,      **A	)  -> Tuple:







					'''simple docstring'''







					kwargs.update(self.special_tokens_map	)
					return RobertaTokenizerFast.from_pretrained(self.tmpdirname		,      **A	)







		def 					__A   ( self		,      A	)  -> int:







					'''simple docstring'''







					lowerCamelCase    		=  """lower newer"""
					lowerCamelCase    		=  """lower newer"""
					return input_text, output_text







		def 					__A   ( self	)  -> int:







					'''simple docstring'''







					lowerCamelCase    		=  self.tokenizer_class(self.vocab_file		,      self.merges_file		,      **self.special_tokens_map	)
					lowerCamelCase    		=  """lower newer"""
					lowerCamelCase    		=  ["""l""", """o""", """w""", """er""", """\u0120""", """n""", """e""", """w""", """er"""]
					lowerCamelCase    		=  tokenizer.tokenize(A	)  # , add_prefix_space=True)
					self.assertListEqual(A		,      A	)

					lowerCamelCase    		=  tokens + [tokenizer.unk_token]
					lowerCamelCase    		=  [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(A	)		,      A	)







		def 					__A   ( self	)  -> Union[str, Any]:







					'''simple docstring'''







					lowerCamelCase    		=  self.get_tokenizer()

					self.assertListEqual(tokenizer.encode("""Hello world!"""		,      add_special_tokens=A	)		,      [0, 3_14_14, 2_32, 3_28, 2]	)
					self.assertListEqual(
					    tokenizer.encode("""Hello world! cécé herlolip 418"""		,      add_special_tokens=A	)		,      [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]		,      )







		@slow
		def 					__A   ( self	)  -> Union[str, Any]:







					'''simple docstring'''







					lowerCamelCase    		=  self.tokenizer_class.from_pretrained("""roberta-base"""	)

					lowerCamelCase    		=  tokenizer.encode("""sequence builders"""		,      add_special_tokens=A	)
					lowerCamelCase    		=  tokenizer.encode("""multi-sequence build"""		,      add_special_tokens=A	)

					lowerCamelCase    		=  tokenizer.encode(
					    """sequence builders"""		,      add_special_tokens=A		,      add_prefix_space=A	)
					lowerCamelCase    		=  tokenizer.encode(
					    """sequence builders"""		,      """multi-sequence build"""		,      add_special_tokens=A		,      add_prefix_space=A	)

					lowerCamelCase    		=  tokenizer.build_inputs_with_special_tokens(A	)
					lowerCamelCase    		=  tokenizer.build_inputs_with_special_tokens(A		,      A	)

					assert encoded_sentence == encoded_text_from_decode
					assert encoded_pair == encoded_pair_from_decode







		def 					__A   ( self	)  -> int:







					'''simple docstring'''







					lowerCamelCase    		=  self.get_tokenizer()

					lowerCamelCase    		=  """Encode this sequence."""
					lowerCamelCase    		=  tokenizer.byte_encoder[""" """.encode("""utf-8"""	)[0]]

					# Testing encoder arguments
					lowerCamelCase    		=  tokenizer.encode(A		,      add_special_tokens=A		,      add_prefix_space=A	)
					lowerCamelCase    		=  tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
					self.assertNotEqual(A		,      A	)

					lowerCamelCase    		=  tokenizer.encode(A		,      add_special_tokens=A		,      add_prefix_space=A	)
					lowerCamelCase    		=  tokenizer.convert_ids_to_tokens(encoded[0]	)[0]
					self.assertEqual(A		,      A	)

					tokenizer.add_special_tokens({"""bos_token""": """<s>"""}	)
					lowerCamelCase    		=  tokenizer.encode(A		,      add_special_tokens=A	)
					lowerCamelCase    		=  tokenizer.convert_ids_to_tokens(encoded[1]	)[0]
					self.assertNotEqual(A		,      A	)

					# Testing spaces after special tokens
					lowerCamelCase    		=  """<mask>"""
					tokenizer.add_special_tokens(
					    {"""mask_token""": AddedToken(A		,      lstrip=A		,      rstrip=A	)}	)  # mask token has a left space
					lowerCamelCase    		=  tokenizer.convert_tokens_to_ids(A	)

					lowerCamelCase    		=  """Encode <mask> sequence"""
					lowerCamelCase    		=  """Encode <mask>sequence"""

					lowerCamelCase    		=  tokenizer.encode(A	)
					lowerCamelCase    		=  encoded.index(A	)
					lowerCamelCase    		=  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
					self.assertEqual(A		,      A	)

					lowerCamelCase    		=  tokenizer.encode(A	)
					lowerCamelCase    		=  encoded.index(A	)
					lowerCamelCase    		=  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]	)[0]
					self.assertNotEqual(A		,      A	)







		def 					__A   ( self	)  -> Optional[int]:







					'''simple docstring'''







					pass







		def 					__A   ( self	)  -> Any:







					'''simple docstring'''







					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
								with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'	):
											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(A		,      **A	)
											lowerCamelCase    		=  self.tokenizer_class.from_pretrained(A		,      **A	)
											lowerCamelCase    		=  """A, <mask> AllenNLP sentence."""
											lowerCamelCase    		=  tokenizer_r.encode_plus(A		,      add_special_tokens=A		,      return_token_type_ids=A	)
											lowerCamelCase    		=  tokenizer_p.encode_plus(A		,      add_special_tokens=A		,      return_token_type_ids=A	)

											# token_type_ids should put 0 everywhere
											self.assertEqual(sum(tokens_r["""token_type_ids"""]	)		,      sum(tokens_p["""token_type_ids"""]	)	)

											# attention_mask should put 1 everywhere, so sum over length should be 1
											self.assertEqual(
											    sum(tokens_r["""attention_mask"""]	) / len(tokens_r["""attention_mask"""]	)		,      sum(tokens_p["""attention_mask"""]	) / len(tokens_p["""attention_mask"""]	)		,      )

											lowerCamelCase    		=  tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""]	)
											lowerCamelCase    		=  tokenizer_p.convert_ids_to_tokens(tokens_p["""input_ids"""]	)

											# Rust correctly handles the space before the mask while python doesnt
											self.assertSequenceEqual(tokens_p["""input_ids"""]		,      [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]	)
											self.assertSequenceEqual(tokens_r["""input_ids"""]		,      [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]	)

											self.assertSequenceEqual(
											    A		,      ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]	)
											self.assertSequenceEqual(
											    A		,      ["""<s>""", """A""", """,""", """<mask>""", """ĠAllen""", """N""", """LP""", """Ġsentence""", """.""", """</s>"""]	)







		def 					__A   ( self	)  -> Tuple:







					'''simple docstring'''







					for trim_offsets, add_prefix_space in itertools.product([True, False]		,      repeat=2	):
								lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
								    self.tmpdirname		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)

								lowerCamelCase    		=  json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()	)
								lowerCamelCase    		=  json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()	)

								self.assertEqual(pre_tokenizer_state["""add_prefix_space"""]		,      A	)

								self.assertEqual(post_processor_state["""add_prefix_space"""]		,      A	)
								self.assertEqual(post_processor_state["""trim_offsets"""]		,      A	)







		def 					__A   ( self	)  -> Optional[int]:







					'''simple docstring'''







					for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
								with self.subTest(F'{tokenizer.__class__.__name__} ({pretrained_name})'	):
											lowerCamelCase    		=  """hello"""  # `hello` is a token in the vocabulary of `pretrained_name`
											lowerCamelCase    		=  F'{text_of_1_token} {text_of_1_token}'

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  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	))		,      )

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  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	))		,      )

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  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	), len(A	) + 1 + len(A	))		,      )

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  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	), len(A	) + 1 + len(A	))		,      )

											lowerCamelCase    		=  F' {text}'

											# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
											#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
											# )
											# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
											# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
											# self.assertEqual(
											#     encoding.offset_mapping[1],
											#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
											# )

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  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	))		,      )

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  tokenizer_r(A		,      return_offsets_mapping=A		,      add_special_tokens=A	)
											self.assertEqual(encoding.offset_mapping[0]		,      (0, 1 + len(A	))	)
											self.assertEqual(
											    encoding.offset_mapping[1]		,      (1 + len(A	), 1 + len(A	) + 1 + len(A	))		,      )

											lowerCamelCase    		=  self.rust_tokenizer_class.from_pretrained(
											    A		,      use_fast=A		,      add_prefix_space=A		,      trim_offsets=A	)
											lowerCamelCase    		=  tokenizer_r(A		,      return_offsets_mapping=A		,      add_special_tokens=A	)
											self.assertEqual(encoding.offset_mapping[0]		,      (0, 1 + len(A	))	)
											self.assertEqual(
											    encoding.offset_mapping[1]		,      (1 + len(A	), 1 + len(A	) + 1 + len(A	))		,      )





import os
from datetime import datetime as dt

from github import Github


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






def 	__lowerCamelCase						(							):





			'''simple docstring'''




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

			for issue in open_issues:
						lowerCamelCase    		=  sorted(issue.get_comments()  ,							key=lambda lowerCamelCase__      : i.created_at  ,							reverse=lowerCamelCase__      )
						lowerCamelCase    		=  comments[0] if len(lowerCamelCase__      ) > 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()

