


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
							from .tokenization_xglm import XGLMTokenizer
else:
							snake_case_  :     str							  =							None


snake_case_  :     Optional[int]							  =							logging.get_logger(__name__)

snake_case_  :     int							  =							{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case_  :     Dict							  =							{
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/tokenizer.json''',
    },
}

snake_case_  :     str							  =							{
    '''facebook/xglm-564M''': 20_48,
}

class   A__							(						A__					):
						UpperCAmelCase     =  VOCAB_FILES_NAMES
						UpperCAmelCase     =  PRETRAINED_VOCAB_FILES_MAP
						UpperCAmelCase     =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCAmelCase     =  ["input_ids", "attention_mask"]
						UpperCAmelCase     =  XGLMTokenizer




						def __init__(    self   : Dict			,      _a   : int=None			,      _a   : Dict=None			,      _a   : Optional[Any]="<s>"			,      _a   : Optional[Any]="</s>"			,      _a   : Dict="</s>"			,      _a   : Union[str, Any]="<s>"			,      _a   : Tuple="<unk>"			,      _a   : int="<pad>"			,      **_a   : Dict			,      )							->       int:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=7
										_SCREAMING_SNAKE_CASE     					=[f"<madeupword{i}>" for i in range(self.num_madeup_words					)]

										_SCREAMING_SNAKE_CASE     					=kwargs.get('''additional_special_tokens'''			,      []					)
										kwargs["additional_special_tokens"] += [
										    word for word in madeup_words if word not in kwargs["additional_special_tokens"]
										]

										super().__init__(
										    _A			,      tokenizer_file=_A			,      bos_token=_A			,      eos_token=_A			,      sep_token=_A			,      cls_token=_A			,      unk_token=_A			,      pad_token=_A			,      **_A			,      )

										_SCREAMING_SNAKE_CASE     					=vocab_file
										_SCREAMING_SNAKE_CASE     					=False if not self.vocab_file else True




						def 							__UpperCamelCase			(    self   : List[str]			,      _a   : List[int]			,      _a   : Optional[List[int]] = None					)							->       Any:


										"""simple docstring"""





										if token_ids_a is None:
														return [self.sep_token_id] + token_ids_a
										_SCREAMING_SNAKE_CASE     					=[self.sep_token_id]
										return sep + token_ids_a + sep + sep + token_ids_a




						def 							__UpperCamelCase			(    self   : Dict			,      _a   : List[int]			,      _a   : Optional[List[int]] = None					)							->       str:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE     					=[self.sep_token_id]

										if token_ids_a is None:
														return len(sep + token_ids_a					) * [0]
										return len(sep + token_ids_a + sep + sep + token_ids_a					) * [0]




						def 							__UpperCamelCase			(    self   : str			,      _a   : str			,      _a   : Optional[str] = None					)							->       int:


										"""simple docstring"""





										if not self.can_save_slow_tokenizer:
														raise ValueError(
														    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
														    '''tokenizer.'''					)

										if not os.path.isdir(_A					):
														logger.error(f"Vocabulary path ({save_directory}) should be a directory."					)
														return
										_SCREAMING_SNAKE_CASE     					=os.path.join(
										    _A			,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

										if os.path.abspath(self.vocab_file					) != os.path.abspath(_A					):
														copyfile(self.vocab_file			,      _A					)

										return (out_vocab_file,)






from ..utils import DummyObject, requires_backends

class   A__							(						metaclass=UpperCamelCase__					):
						UpperCAmelCase     =  ["torch", "librosa"]




						def __init__(    self   : Dict			,      *_a   : Union[str, Any]			,      **_a   : List[str]					)							->       Optional[int]:


										"""simple docstring"""





										requires_backends(self			,      ['''torch''', '''librosa''']					)




						@classmethod
						def 							__UpperCamelCase			(    cls   : Dict			,      *_a   : Tuple			,      **_a   : Tuple					)							->       Optional[int]:


										"""simple docstring"""





										requires_backends(cls			,      ['''torch''', '''librosa''']					)




						@classmethod
						def 							__UpperCamelCase			(    cls   : List[Any]			,      *_a   : Any			,      **_a   : List[str]					)							->       Dict:


										"""simple docstring"""





										requires_backends(cls			,      ['''torch''', '''librosa''']					)

class   A__							(						metaclass=UpperCamelCase__					):
						UpperCAmelCase     =  ["torch", "librosa"]




						def __init__(    self   : List[Any]			,      *_a   : int			,      **_a   : int					)							->       Optional[Any]:


										"""simple docstring"""





										requires_backends(self			,      ['''torch''', '''librosa''']					)




						@classmethod
						def 							__UpperCamelCase			(    cls   : str			,      *_a   : Dict			,      **_a   : Optional[Any]					)							->       Union[str, Any]:


										"""simple docstring"""





										requires_backends(cls			,      ['''torch''', '''librosa''']					)




						@classmethod
						def 							__UpperCamelCase			(    cls   : List[str]			,      *_a   : Optional[int]			,      **_a   : Union[str, Any]					)							->       Optional[Any]:


										"""simple docstring"""





										requires_backends(cls			,      ['''torch''', '''librosa''']					)