
import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing


class     lowercase (		_SCREAMING_SNAKE_CASE       ):



		def __init__(			self    ,				A_ = "▁"    ,				A_ = True    ,				A_ = "<unk>"    ,				A_ = "</s>"    ,				A_ = "<pad>"    ,				)  -> Optional[int]:
				"""simple docstring"""
				UpperCamelCase          =					{
				    'pad': {'id': 0, 'token': pad_token},
				    'eos': {'id': 1, 'token': eos_token},
				    'unk': {'id': 2, 'token': unk_token},
				}

				UpperCamelCase          =					[None] * len(self.special_tokens	)
				for token_dict in self.special_tokens.values():
						UpperCamelCase          =					token_dict['token']

				UpperCamelCase          =					Tokenizer(Unigram()	)

				UpperCamelCase          =					normalizers.Sequence(
				    [
				        normalizers.Nmt(),
				        normalizers.NFKC(),
				        normalizers.Replace(Regex(' {2,}'	)    ,				' '	),
				        normalizers.Lowercase(),
				    ]	)
				UpperCamelCase          =					pre_tokenizers.Sequence(
				    [
				        pre_tokenizers.Metaspace(replacement=A_    ,				add_prefix_space=A_	),
				        pre_tokenizers.Digits(individual_digits=A_	),
				        pre_tokenizers.Punctuation(),
				    ]	)
				UpperCamelCase          =					decoders.Metaspace(replacement=A_    ,				add_prefix_space=A_	)

				UpperCamelCase          =					TemplateProcessing(
				    single=F'''$A {self.special_tokens['eos']['token']}'''    ,				special_tokens=[(self.special_tokens['eos']['token'], self.special_tokens['eos']['id'])]    ,				)

				UpperCamelCase          =					{
				    'model': 'SentencePieceUnigram',
				    'replacement': replacement,
				    'add_prefix_space': add_prefix_space,
				}

				super().__init__(A_    ,				A_	)



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = 8_000    ,				A_ = True    ,				)  -> List[str]:
				"""simple docstring"""
				UpperCamelCase          =					trainers.UnigramTrainer(
				    vocab_size=A_    ,				special_tokens=self.special_tokens_list    ,				show_progress=A_    ,				)

				if isinstance(A_    ,				A_	):
						UpperCamelCase          =					[files]
				self._tokenizer.train(A_    ,				trainer=A_	)

				self.add_unk_id()



		def __UpperCamelCase			(			self    ,				A_    ,				A_ = 8_000    ,				A_ = True    ,				)  -> Any:
				"""simple docstring"""
				UpperCamelCase          =					trainers.UnigramTrainer(
				    vocab_size=A_    ,				special_tokens=self.special_tokens_list    ,				show_progress=A_    ,				)

				self._tokenizer.train_from_iterator(A_    ,				trainer=A_	)

				self.add_unk_id()



		def __UpperCamelCase			(			self	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					json.loads(self._tokenizer.to_str()	)

				UpperCamelCase          =					self.special_tokens['unk']['id']

				UpperCamelCase          =					Tokenizer.from_str(json.dumps(A_	)	)


import logging
import os

from .state import PartialState


class     lowercase (		logging.LoggerAdapter       ):



		@staticmethod
		def __UpperCamelCase			(			A_	)  -> Optional[Any]:
				"""simple docstring"""
				UpperCamelCase          =					PartialState()
				return not main_process_only or (main_process_only and state.is_main_process)



		def __UpperCamelCase			(			self    ,				A_    ,				A_    ,				*A_    ,				**A_	)  -> Union[str, Any]:
				"""simple docstring"""
				if PartialState._shared_state == {}:
						raise RuntimeError(
						    'You must initialize the accelerate state by calling either `PartialState()` or `Accelerator()` before using the logging utility.'	)
				UpperCamelCase          =					kwargs.pop('main_process_only'    ,				A_	)
				UpperCamelCase          =					kwargs.pop('in_order'    ,				A_	)

				if self.isEnabledFor(A_	):
						if self._should_log(A_	):
								UpperCamelCase     ,  UpperCamelCase          =					self.process(A_    ,				A_	)
								self.logger.log(A_    ,				A_    ,				*A_    ,				**A_	)

						elif in_order:
								UpperCamelCase          =					PartialState()
								for i in range(state.num_processes	):
										if i == state.process_index:
												UpperCamelCase     ,  UpperCamelCase          =					self.process(A_    ,				A_	)
												self.logger.log(A_    ,				A_    ,				*A_    ,				**A_	)
										state.wait_for_everyone()






def 				A	( lowercase   ,	lowercase = None			)       ->  Dict:
		'''simple docstring'''

		if log_level is None:
				UpperCamelCase          =					os.environ.get('ACCELERATE_LOG_LEVEL'   ,	lowercase			)
		UpperCamelCase          =					logging.getLogger(lowercase			)
		if log_level is not None:
				logger.setLevel(log_level.upper()			)
				logger.root.setLevel(log_level.upper()			)
		return MultiProcessAdapter(lowercase   ,	{}			)
