






'''simple docstring'''







import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
		from transformers.pipelines.conversational import Conversation


__lowerCAmelCase									=   logging.get_logger(__name__)

__lowerCAmelCase									=   {'tokenizer_file': 'tokenizer.json'}

__lowerCAmelCase									=   {
    'tokenizer_file': {
        'bigscience/tokenizer': 'https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json',
        'bigscience/bloom-560m': 'https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json',
        'bigscience/bloom-1b1': 'https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json',
        'bigscience/bloom-1b7': 'https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json',
        'bigscience/bloom-3b': 'https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json',
        'bigscience/bloom-7b1': 'https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json',
        'bigscience/bloom': 'https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json',
    },
}





class 						SCREAMING_SNAKE_CASE       (       SCREAMING_SNAKE_CASE_							):
			snake_case__	=					VOCAB_FILES_NAMES
			snake_case__	=					PRETRAINED_VOCAB_FILES_MAP
			snake_case__	=					["input_ids", "attention_mask"]
			snake_case__	=					None






			def __init__(			self   :      Dict	,    __SCREAMING_SNAKE_CASE   :      Tuple=None	,    __SCREAMING_SNAKE_CASE   :      Any=None	,    __SCREAMING_SNAKE_CASE   :      str=None	,    __SCREAMING_SNAKE_CASE   :      List[str]="<unk>"	,    __SCREAMING_SNAKE_CASE   :      str="<s>"	,    __SCREAMING_SNAKE_CASE   :      int="</s>"	,    __SCREAMING_SNAKE_CASE   :      Any="<pad>"	,    __SCREAMING_SNAKE_CASE   :      Optional[Any]=False	,    __SCREAMING_SNAKE_CASE   :      Optional[Any]=False	,    **__SCREAMING_SNAKE_CASE   :      Optional[int]	,    )      ->      Dict:
							super().__init__(
							    __SCREAMING_SNAKE_CASE	,    __SCREAMING_SNAKE_CASE	,    tokenizer_file=__SCREAMING_SNAKE_CASE	,    unk_token=__SCREAMING_SNAKE_CASE	,    bos_token=__SCREAMING_SNAKE_CASE	,    eos_token=__SCREAMING_SNAKE_CASE	,    pad_token=__SCREAMING_SNAKE_CASE	,    add_prefix_space=__SCREAMING_SNAKE_CASE	,    clean_up_tokenization_spaces=__SCREAMING_SNAKE_CASE	,    **__SCREAMING_SNAKE_CASE	,    )
							a_		:	Union[str, Any]									=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
							if pre_tok_state.get('''add_prefix_space'''	,    __SCREAMING_SNAKE_CASE       ) != add_prefix_space:
											a_		:	Tuple									=   getattr(__SCREAMING_SNAKE_CASE	,    pre_tok_state.pop('''type'''       )       )
											a_		:	Optional[Any]									=   add_prefix_space
											a_		:	Tuple									=   pre_tok_class(**__SCREAMING_SNAKE_CASE       )

							a_		:	Optional[int]									=   add_prefix_space






			def       SCREAMING_SNAKE_CASE   (			self   :      Tuple	,    *__SCREAMING_SNAKE_CASE   :      str	,    **__SCREAMING_SNAKE_CASE   :      Dict       )      ->      BatchEncoding:
							a_		:	List[Any]									=   kwargs.get('''is_split_into_words'''	,    __SCREAMING_SNAKE_CASE       )
							if not (self.add_prefix_space or not is_split_into_words):
											raise Exception(
											    f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'
											    ''' pretokenized inputs.'''       )

							return super()._batch_encode_plus(*__SCREAMING_SNAKE_CASE	,    **__SCREAMING_SNAKE_CASE       )






			def       SCREAMING_SNAKE_CASE   (			self   :      Any	,    *__SCREAMING_SNAKE_CASE   :      List[Any]	,    **__SCREAMING_SNAKE_CASE   :      List[str]       )      ->      BatchEncoding:
							a_		:	Any									=   kwargs.get('''is_split_into_words'''	,    __SCREAMING_SNAKE_CASE       )

							if not (self.add_prefix_space or not is_split_into_words):
											raise Exception(
											    f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'
											    ''' pretokenized inputs.'''       )

							return super()._encode_plus(*__SCREAMING_SNAKE_CASE	,    **__SCREAMING_SNAKE_CASE       )






			def       SCREAMING_SNAKE_CASE   (			self   :      Tuple	,    __SCREAMING_SNAKE_CASE   :      str	,    __SCREAMING_SNAKE_CASE   :      Optional[str] = None       )      ->      Tuple[str]:
							a_		:	int									=   self._tokenizer.model.save(__SCREAMING_SNAKE_CASE	,    name=__SCREAMING_SNAKE_CASE       )
							return tuple(__SCREAMING_SNAKE_CASE       )







			def       SCREAMING_SNAKE_CASE   (			self   :      int	,    __SCREAMING_SNAKE_CASE   :      "Conversation"       )      ->      List[int]:
							a_		:	str									=   []
							for is_user, text in conversation.iter_texts():
											input_ids.extend(self.encode(__SCREAMING_SNAKE_CASE	,    add_special_tokens=__SCREAMING_SNAKE_CASE       ) + [self.eos_token_id]       )

							if len(__SCREAMING_SNAKE_CASE       ) > self.model_max_length:
											a_		:	int									=   input_ids[-self.model_max_length :]
							return input_ids












'''simple docstring'''







import os
import time

import pytest

from datasets.utils.filelock import FileLock, Timeout





def 		_UpperCAmelCase (				__A				: int   ):
				a_		:	Optional[Any]									=   FileLock(str(tmpdir / '''foo.lock'''   )   )
				a_		:	Union[str, Any]									=   FileLock(str(tmpdir / '''foo.lock'''   )   )
				a_		:	List[Any]									=   0.01
				with locka.acquire():
								with pytest.raises(__A   ):
												a_		:	List[Any]									=   time.time()
												locka.acquire(__A   )
												assert time.time() - _start > timeout





def 		_UpperCAmelCase (				__A				: Tuple   ):
				a_		:	Tuple									=   '''a''' * 10_00 + '''.lock'''
				a_		:	List[Any]									=   FileLock(str(tmpdir / filename   )   )
				assert locka._lock_file.endswith('''.lock'''   )
				assert not locka._lock_file.endswith(__A   )
				assert len(os.path.basename(locka._lock_file   )   ) <= 2_55
				a_		:	Optional[int]									=   FileLock(tmpdir / filename   )
				with locka.acquire():
								with pytest.raises(__A   ):
												locka.acquire(0   )




