



'''simple docstring'''

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:
		_A					:     Union[str, Any]      =None


_A					:     str      =logging.get_logger(__name__)

_A					:     Optional[Any]      ={'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

_A					:     str      ={
    '''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''',
    },
}

_A					:     Union[str, Any]      ={
    '''facebook/xglm-564M''': 2_0_4_8,
}



class 		lowerCamelCase__   (    A  ):




					'''simple docstring'''



					A_         =    VOCAB_FILES_NAMES
					A_         =    PRETRAINED_VOCAB_FILES_MAP
					A_         =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					A_         =    ["""input_ids""", """attention_mask"""]
					A_         =    XGLMTokenizer




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



						'''simple docstring'''





						_lowercase       :							Union[str, Any]  	=		7
						_lowercase       :							Tuple  	=		[F'''<madeupword{i}>''' for i in range(self.num_madeup_words       )]

						_lowercase       :							Optional[int]  	=		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__(
						    UpperCamelCase_  ,	tokenizer_file=UpperCamelCase_  ,	bos_token=UpperCamelCase_  ,	eos_token=UpperCamelCase_  ,	sep_token=UpperCamelCase_  ,	cls_token=UpperCamelCase_  ,	unk_token=UpperCamelCase_  ,	pad_token=UpperCamelCase_  ,	**UpperCamelCase_  ,	)

						_lowercase       :							Tuple  	=		vocab_file
						_lowercase       :							List[str]  	=		False if not self.vocab_file else True




					def     __UpperCAmelCase  (	self					:						Any  ,	UpperCamelCase_					:						List[int]  ,	UpperCamelCase_					:						Optional[List[int]] = None       )	->							List[int]:



						'''simple docstring'''





						if token_ids_a is None:
							return [self.sep_token_id] + token_ids_a
						_lowercase       :							Optional[Any]  	=		[self.sep_token_id]
						return sep + token_ids_a + sep + sep + token_ids_a




					def     __UpperCAmelCase  (	self					:						Union[str, Any]  ,	UpperCamelCase_					:						List[int]  ,	UpperCamelCase_					:						Optional[List[int]] = None       )	->							List[int]:



						'''simple docstring'''





						_lowercase       :							int  	=		[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					:						int  ,	UpperCamelCase_					:						str  ,	UpperCamelCase_					:						Optional[str] = None       )	->							Tuple[str]:



						'''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(UpperCamelCase_       ):
							logger.error(F'''Vocabulary path ({save_directory}) should be a directory.'''       )
							return
						_lowercase       :							List[str]  	=		os.path.join(
						    UpperCamelCase_  ,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )

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

						return (out_vocab_file,)





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A					:     List[Any]      ={'''configuration_umt5''': ['''UMT5Config''', '''UMT5OnnxConfig''']}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_A					:     Optional[Any]      =[
		    '''UMT5EncoderModel''',
		    '''UMT5ForConditionalGeneration''',
		    '''UMT5ForQuestionAnswering''',
		    '''UMT5Model''',
		    '''UMT5PreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_umta import UMTaConfig, UMTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_umta import (
				    UMTaEncoderModel,
				    UMTaForConditionalGeneration,
				    UMTaForQuestionAnswering,
				    UMTaModel,
				    UMTaPreTrainedModel,
				)
else:
		import sys

		_A					:     Optional[int]      =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
