


import json
import os
import shutil
import tempfile
import unittest

from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin



class 			lowerCamelCase__						(   UpperCAmelCase_							,    unittest.TestCase			):
						lowerCAmelCase       =     CanineTokenizer
						lowerCAmelCase       =     False







						def __a						(							self   :    Optional[Any]		):
								super().setUp()
								A					       = CanineTokenizer()
								tokenizer.save_pretrained(self.tmpdirname		)







						@cached_property
						def __a						(							self   :    Optional[int]		):
								return CanineTokenizer.from_pretrained('google/canine-s'		)







						def __a						(							self   :    List[str]			,			**_lowercase   :    List[str]		):
								A					       = self.tokenizer_class.from_pretrained(self.tmpdirname			,			**_lowercase		)
								A					       = 1_024
								return tokenizer







						@require_torch
						def __a						(							self   :    str		):
								A					       = self.canine_tokenizer
								A					       = ['Life is like a box of chocolates.', 'You never know what you\'re gonna get.']
								# fmt: off
								A					       = [57_344, 76, 105, 102, 101, 32, 105, 115, 32, 108, 105, 107, 101, 32, 97, 32, 98, 111, 120, 32, 111, 102, 32, 99, 104, 111, 99, 111, 108, 97, 116, 101, 115, 46, 57_345, 0, 0, 0, 0]
								# fmt: on
								A					       = tokenizer(_lowercase			,			padding=_lowercase			,			return_tensors='pt'		)
								self.assertIsInstance(_lowercase			,			_lowercase		)

								A					       = list(batch.input_ids.numpy()[0]		)

								self.assertListEqual(_lowercase			,			_lowercase		)

								self.assertEqual((2, 39)			,			batch.input_ids.shape		)
								self.assertEqual((2, 39)			,			batch.attention_mask.shape		)







						@require_torch
						def __a						(							self   :    Union[str, Any]		):
								A					       = self.canine_tokenizer
								A					       = ['Once there was a man.', 'He wrote a test in HuggingFace Tranformers.']
								A					       = tokenizer(_lowercase			,			padding=_lowercase			,			return_tensors='pt'		)
								# check if input_ids, attention_mask and token_type_ids are returned
								self.assertIn('input_ids'			,			_lowercase		)
								self.assertIn('attention_mask'			,			_lowercase		)
								self.assertIn('token_type_ids'			,			_lowercase		)







						@require_torch
						def __a						(							self   :    List[Any]		):
								A					       = self.canine_tokenizer
								A					       = [
								    'What\'s the weater?',
								    'It\'s about 25 degrees.',
								]
								A					       = tokenizer(
								    text_target=_lowercase			,			max_length=32			,			padding='max_length'			,			truncation=_lowercase			,			return_tensors='pt'		)
								self.assertEqual(32			,			targets['input_ids'].shape[1]		)







						def __a						(							self   :    List[str]		):
								A					       = self.get_tokenizers()
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												self.assertNotEqual(tokenizer.model_max_length			,			42		)

        # Now let's start the test
								A					       = self.get_tokenizers()
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												# Isolate this from the other tests because we save additional tokens/etc
												A					       = tempfile.mkdtemp()

												A					       = ' He is very happy, UNwant\u00E9d,running'
												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												tokenizer.save_pretrained(_lowercase		)

												A					       = tokenizer.__class__.from_pretrained(_lowercase		)
												A					       = after_tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												self.assertListEqual(_lowercase			,			_lowercase		)

												shutil.rmtree(_lowercase		)

								A					       = self.get_tokenizers(model_max_length=42		)
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												# Isolate this from the other tests because we save additional tokens/etc
												A					       = tempfile.mkdtemp()

												A					       = ' He is very happy, UNwant\u00E9d,running'

												A					       = tokenizer.additional_special_tokens

												# We can add a new special token for Canine as follows:
												A					       = chr(0xe007		)
												additional_special_tokens.append(_lowercase		)
												tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}		)
												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												tokenizer.save_pretrained(_lowercase		)

												A					       = tokenizer.__class__.from_pretrained(_lowercase		)
												A					       = after_tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												self.assertListEqual(_lowercase			,			_lowercase		)
												self.assertIn(_lowercase			,			after_tokenizer.additional_special_tokens		)
												self.assertEqual(after_tokenizer.model_max_length			,			42		)

												A					       = tokenizer.__class__.from_pretrained(_lowercase			,			model_max_length=43		)
												self.assertEqual(tokenizer.model_max_length			,			43		)

												shutil.rmtree(_lowercase		)







						def __a						(							self   :    Any		):
								A					       = self.get_tokenizers(do_lower_case=_lowercase		)
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												A					       = self.get_clean_sequence(_lowercase		)

												# a special token for Canine can be defined as follows:
												A					       = 0xe005
												A					       = chr(_lowercase		)

												tokenizer.add_special_tokens({'cls_token': special_token}		)
												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(len(_lowercase		)			,			1		)

												A					       = tokenizer.decode(ids + encoded_special_token			,			clean_up_tokenization_spaces=_lowercase		)
												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)

												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												self.assertEqual(_lowercase			,			input_encoded + special_token_id		)

												A					       = tokenizer.decode(_lowercase			,			skip_special_tokens=_lowercase		)
												self.assertTrue(special_token not in decoded		)







						def __a						(							self   :    Dict		):
								A					       = self.get_tokenizers(do_lower_case=_lowercase		)
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												A					       = chr(0xe005		)
												A					       = chr(0xe006		)

												# `add_tokens` method stores special tokens only in `tokenizer.unique_no_split_tokens`. (in tokenization_utils.py)
												tokenizer.add_tokens([SPECIAL_TOKEN_1]			,			special_tokens=_lowercase		)
												# `add_special_tokens` method stores special tokens in `tokenizer.additional_special_tokens`,
												# which also occur in `tokenizer.all_special_tokens`. (in tokenization_utils_base.py)
												tokenizer.add_special_tokens({'additional_special_tokens': [SPECIAL_TOKEN_2]}		)

												A					       = tokenizer.tokenize(_lowercase		)
												A					       = tokenizer.tokenize(_lowercase		)

												self.assertEqual(len(_lowercase		)			,			1		)
												self.assertEqual(len(_lowercase		)			,			1		)
												self.assertEqual(token_a[0]			,			_lowercase		)
												self.assertEqual(token_a[0]			,			_lowercase		)







						@require_tokenizers
						def __a						(							self   :    List[Any]		):
								A					       = self.get_tokenizers(do_lower_case=_lowercase		)
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												# a special token for Canine can be defined as follows:
												A					       = 0xe006
												A					       = chr(_lowercase		)

												A					       = AddedToken(_lowercase			,			lstrip=_lowercase		)
												tokenizer.add_special_tokens({'additional_special_tokens': [new_token]}		)

												with tempfile.TemporaryDirectory() as tmp_dir_name:
														tokenizer.save_pretrained(_lowercase		)
														tokenizer.from_pretrained(_lowercase		)







						def __a						(							self   :    Any		):
								A					       = []
								if self.test_slow_tokenizer:
										tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())		)

								if self.test_rust_tokenizer:
										tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())		)

								for tokenizer_class, tokenizer_utils in tokenizer_list:
										with tempfile.TemporaryDirectory() as tmp_dir:
												tokenizer_utils.save_pretrained(_lowercase		)

												with open(os.path.join(_lowercase			,			'special_tokens_map.json'		)			,			encoding='utf-8'		) as json_file:
														A					       = json.load(_lowercase		)

												with open(os.path.join(_lowercase			,			'tokenizer_config.json'		)			,			encoding='utf-8'		) as json_file:
														A					       = json.load(_lowercase		)

												# a special token for Canine can be defined as follows:
												A					       = 0xe006
												A					       = chr(_lowercase		)

												A					       = [new_token_a]
												A					       = [new_token_a]

												with open(os.path.join(_lowercase			,			'special_tokens_map.json'		)			,			'w'			,			encoding='utf-8'		) as outfile:
														json.dump(_lowercase			,			_lowercase		)
												with open(os.path.join(_lowercase			,			'tokenizer_config.json'		)			,			'w'			,			encoding='utf-8'		) as outfile:
														json.dump(_lowercase			,			_lowercase		)

												# the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
												# into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
												# "special_tokens_map.json" files
												A					       = tokenizer_class.from_pretrained(_lowercase			,			extra_ids=0		)
												self.assertIn(_lowercase			,			tokenizer_without_change_in_init.additional_special_tokens		)
												# self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
												self.assertEqual(
												    [new_token_a]			,			tokenizer_without_change_in_init.convert_ids_to_tokens(
												        tokenizer_without_change_in_init.convert_tokens_to_ids([new_token_a]		)		)			,			)

												A					       = 0xe007
												A					       = chr(_lowercase		)
												# Now we test that we can change the value of additional_special_tokens in the from_pretrained
												A					       = [AddedToken(_lowercase			,			lstrip=_lowercase		)]
												A					       = tokenizer_class.from_pretrained(
												    _lowercase			,			additional_special_tokens=_lowercase			,			extra_ids=0		)

												self.assertIn(_lowercase			,			tokenizer.additional_special_tokens		)
												# self.assertIn(new_token_2,tokenizer.get_vocab()) # ByT5Tokenization no vocab
												self.assertEqual(
												    [new_token_a]			,			tokenizer.convert_ids_to_tokens(tokenizer.convert_tokens_to_ids([new_token_a]		)		)		)







						@require_tokenizers
						def __a						(							self   :    Dict		):
								A					       = self.get_tokenizers(do_lower_case=_lowercase		)
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												A					       = 'hello world'
												if self.space_between_special_tokens:
														A					       = '[CLS] hello world [SEP]'
												else:
														A					       = input
												A					       = tokenizer.encode(_lowercase			,			add_special_tokens=_lowercase		)
												A					       = tokenizer.decode(_lowercase			,			spaces_between_special_tokens=self.space_between_special_tokens		)
												self.assertIn(_lowercase			,			[output, output.lower()]		)







						def __a						(							self   :    str		):
								A					       = self.get_tokenizers()
								for tokenizer in tokenizers:
										with self.subTest(f'{tokenizer.__class__.__name__}'		):
												A					       = [
												    'bos_token',
												    'eos_token',
												    'unk_token',
												    'sep_token',
												    'pad_token',
												    'cls_token',
												    'mask_token',
												]

								A					       = 'a'
								A					       = ord(_lowercase		)

								for attr in attributes_list:
										setattr(_lowercase			,			attr + '_id'			,			_lowercase		)
										self.assertEqual(getattr(_lowercase			,			_lowercase		)			,			_lowercase		)
										self.assertEqual(getattr(_lowercase			,			attr + '_id'		)			,			_lowercase		)

										setattr(_lowercase			,			attr + '_id'			,			_lowercase		)
										self.assertEqual(getattr(_lowercase			,			_lowercase		)			,			_lowercase		)
										self.assertEqual(getattr(_lowercase			,			attr + '_id'		)			,			_lowercase		)

								setattr(_lowercase			,			'additional_special_tokens_ids'			,			[]		)
								self.assertListEqual(getattr(_lowercase			,			'additional_special_tokens'		)			,			[]		)
								self.assertListEqual(getattr(_lowercase			,			'additional_special_tokens_ids'		)			,			[]		)

								A					       = 0xe006
								A					       = chr(_lowercase		)
								setattr(_lowercase			,			'additional_special_tokens_ids'			,			[additional_special_token_id]		)
								self.assertListEqual(getattr(_lowercase			,			'additional_special_tokens'		)			,			[additional_special_token]		)
								self.assertListEqual(getattr(_lowercase			,			'additional_special_tokens_ids'		)			,			[additional_special_token_id]		)







						def __a						(							self   :    Union[str, Any]		):
								pass







						def __a						(							self   :    List[Any]		):
								pass







						def __a						(							self   :    Optional[Any]		):
								pass







						def __a						(							self   :    Optional[int]		):
								pass







						def __a						(							self   :    Union[str, Any]		):
								pass







						def __a						(							self   :    Tuple		):
								pass







						def __a						(							self   :    Union[str, Any]		):
								pass







						def __a						(							self   :    List[str]		):
								pass









"""simple docstring"""


from datetime import datetime as dt
import os

from github import Github


UpperCamelCase						:				Union[str, Any]             =      [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "feature request",
    "new model",
    "wip",
]







def  __snake_case       (   )      ->		int:







		"""simple docstring"""





		A					       = Github(os.environ['GITHUB_TOKEN']	)
		A					       = g.get_repo('huggingface/transformers'	)
		A					       = repo.get_issues(state='open'	)

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





