
'''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:
		UpperCAmelCase__				:	Optional[int]					=						None


UpperCAmelCase__				:	Union[str, Any]					=						logging.get_logger(__name__)

UpperCAmelCase__				:	Optional[int]					=						{"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

UpperCAmelCase__				:	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",
    },
}

UpperCAmelCase__				:	Optional[int]					=						{
    "facebook/xglm-564M": 20_48,
}






class 				A       (		SCREAMING_SNAKE_CASE__      ):
	snake_case__ :Dict				       =       VOCAB_FILES_NAMES
	snake_case__ :Tuple				       =       PRETRAINED_VOCAB_FILES_MAP
	snake_case__ :Tuple				       =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	snake_case__ :Optional[int]				       =       ['input_ids', 'attention_mask']
	snake_case__ :Any				       =       XGLMTokenizer





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


				"""simple docstring"""

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

				lowerCAmelCase__									=							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__(
				    __magic_name__ ,							tokenizer_file=__magic_name__ ,							bos_token=__magic_name__ ,							eos_token=__magic_name__ ,							sep_token=__magic_name__ ,							cls_token=__magic_name__ ,							unk_token=__magic_name__ ,							pad_token=__magic_name__ ,							**__magic_name__ ,							)

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str ,							__magic_name__     :    List[int] ,							__magic_name__     :    Optional[List[int]] = None							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Union[str, Any] ,							__magic_name__     :    List[int] ,							__magic_name__     :    Optional[List[int]] = None							):


				"""simple docstring"""

				lowerCAmelCase__									=							[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 							__SCREAMING_SNAKE_CASE					(   self     :    List[str] ,							__magic_name__     :    str ,							__magic_name__     :    Optional[str] = None							):


				"""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(__magic_name__							):
							logger.error(f"""Vocabulary path ({save_directory}) should be a directory."""							)
							return
				lowerCAmelCase__									=							os.path.join(
				    __magic_name__ ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)

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

				return (out_vocab_file,)







'''simple docstring'''

UpperCAmelCase__				:	List[str]					=						"\n# Transformers installation\n! pip install transformers datasets evaluate\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"

UpperCAmelCase__				:	Any					=						[{"type": "code", "content": INSTALL_CONTENT}]
UpperCAmelCase__				:	Union[str, Any]					=						{
    "{processor_class}": "FakeProcessorClass",
    "{model_class}": "FakeModelClass",
    "{object_class}": "FakeObjectClass",
}





