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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowercase   =	logging.get_logger(__name__)

lowercase   =	"""▁"""

lowercase   =	{"""vocab_file""": """sentencepiece.bpe.model"""}

lowercase   =	{
    """vocab_file""": {
        """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model""",
        """xlm-roberta-large-finetuned-conll02-dutch""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll02-spanish""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-english""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"""
        ),
        """xlm-roberta-large-finetuned-conll03-german""": (
            """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

lowercase   =	{
    """xlm-roberta-base""": 5_1_2,
    """xlm-roberta-large""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-dutch""": 5_1_2,
    """xlm-roberta-large-finetuned-conll02-spanish""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-english""": 5_1_2,
    """xlm-roberta-large-finetuned-conll03-german""": 5_1_2,
}





class    __A(					_UpperCamelCase							):
					SCREAMING_SNAKE_CASE           =     VOCAB_FILES_NAMES
					SCREAMING_SNAKE_CASE           =     PRETRAINED_VOCAB_FILES_MAP
					SCREAMING_SNAKE_CASE           =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					SCREAMING_SNAKE_CASE           =     ['''input_ids''', '''attention_mask''']

					def __init__(						self       :  str ,       __UpperCamelCase       :  Tuple ,       __UpperCamelCase       :  Any="<s>" ,       __UpperCamelCase       :  List[str]="</s>" ,       __UpperCamelCase       :  Dict="</s>" ,       __UpperCamelCase       :  List[str]="<s>" ,       __UpperCamelCase       :  Union[str, Any]="<unk>" ,       __UpperCamelCase       :  List[Any]="<pad>" ,       __UpperCamelCase       :  str="<mask>" ,       __UpperCamelCase       :  Optional[Dict[str, Any]] = None ,       **__UpperCamelCase       :  Union[str, Any] ,       ):
												# Mask token behave like a normal word, i.e. include the space before it
												lowerCamelCase_					=       AddedToken(lowerCamelCase_ ,       lstrip=lowerCamelCase_ ,       rstrip=lowerCamelCase_ ) if isinstance(lowerCamelCase_ ,       lowerCamelCase_ ) else mask_token

												lowerCamelCase_					=       {} if sp_model_kwargs is None else sp_model_kwargs

												super().__init__(
												    bos_token=lowerCamelCase_ ,       eos_token=lowerCamelCase_ ,       unk_token=lowerCamelCase_ ,       sep_token=lowerCamelCase_ ,       cls_token=lowerCamelCase_ ,       pad_token=lowerCamelCase_ ,       mask_token=lowerCamelCase_ ,       sp_model_kwargs=self.sp_model_kwargs ,       **lowerCamelCase_ ,       )

												lowerCamelCase_					=       spm.SentencePieceProcessor(**self.sp_model_kwargs )
												self.sp_model.Load(str(lowerCamelCase_ ) )
												lowerCamelCase_					=       vocab_file

												# Original fairseq vocab and spm vocab must be "aligned":
												# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
												# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
												# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
												# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

												# Mimic fairseq token-to-id alignment for the first 4 token
												lowerCamelCase_					=       {'<s>': 0, '<pad>': 1, '</s>': 2, '<unk>': 3}

												# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
												lowerCamelCase_					=       1

												lowerCamelCase_					=       len(self.sp_model ) + self.fairseq_offset
												lowerCamelCase_					=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}

					def __getstate__(						self       :  Optional[int] ):
												lowerCamelCase_					=       self.__dict__.copy()
												lowerCamelCase_					=       None
												lowerCamelCase_					=       self.sp_model.serialized_model_proto()
												return state

					def __setstate__(						self       :  Any ,       __UpperCamelCase       :  List[Any] ):
												lowerCamelCase_					=       d

												# for backward compatibility
												if not hasattr(self ,       """sp_model_kwargs""" ):
																			lowerCamelCase_					=       {}

												lowerCamelCase_					=       spm.SentencePieceProcessor(**self.sp_model_kwargs )
												self.sp_model.LoadFromSerializedProto(self.sp_model_proto )

					def  lowercase__   (						self       :  Tuple ,       __UpperCamelCase       :  List[int] ,       __UpperCamelCase       :  Optional[List[int]] = None ):

												if token_ids_a is None:
																			return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												lowerCamelCase_					=       [self.cls_token_id]
												lowerCamelCase_					=       [self.sep_token_id]
												return cls + token_ids_a + sep + sep + token_ids_a + sep

					def  lowercase__   (						self       :  str ,       __UpperCamelCase       :  List[int] ,       __UpperCamelCase       :  Optional[List[int]] = None ,       __UpperCamelCase       :  bool = False ):

												if already_has_special_tokens:
																			return super().get_special_tokens_mask(
																			    token_ids_a=lowerCamelCase_ ,       token_ids_a=lowerCamelCase_ ,       already_has_special_tokens=lowerCamelCase_ )

												if token_ids_a is None:
																			return [1] + ([0] * len(lowerCamelCase_ )) + [1]
												return [1] + ([0] * len(lowerCamelCase_ )) + [1, 1] + ([0] * len(lowerCamelCase_ )) + [1]

					def  lowercase__   (						self       :  str ,       __UpperCamelCase       :  List[int] ,       __UpperCamelCase       :  Optional[List[int]] = None ):
												lowerCamelCase_					=       [self.sep_token_id]
												lowerCamelCase_					=       [self.cls_token_id]

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

					@property
					def  lowercase__   (						self       :  Tuple ):
												return len(self.sp_model ) + self.fairseq_offset + 1  # Add the <mask> token

					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       {self.convert_ids_to_tokens(lowerCamelCase_ ): i for i in range(self.vocab_size )}
												vocab.update(self.added_tokens_encoder )
												return vocab

					def  lowercase__   (						self       :  str ,       __UpperCamelCase       :  str ):
												return self.sp_model.encode(lowerCamelCase_ ,       out_type=lowerCamelCase_ )

					def  lowercase__   (						self       :  Optional[Any] ,       __UpperCamelCase       :  Union[str, Any] ):
												if token in self.fairseq_tokens_to_ids:
																			return self.fairseq_tokens_to_ids[token]
												lowerCamelCase_					=       self.sp_model.PieceToId(lowerCamelCase_ )

												# Need to return unknown token if the SP model returned 0
												return spm_id + self.fairseq_offset if spm_id else self.unk_token_id

					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  Union[str, Any] ):
												if index in self.fairseq_ids_to_tokens:
																			return self.fairseq_ids_to_tokens[index]
												return self.sp_model.IdToPiece(index - self.fairseq_offset )

					def  lowercase__   (						self       :  List[Any] ,       __UpperCamelCase       :  int ):
												lowerCamelCase_					=       ''.join(lowerCamelCase_ ).replace(lowerCamelCase_ ,       """ """ ).strip()
												return out_string



					def  lowercase__   (						self       :  Dict ,       __UpperCamelCase       :  str ,       __UpperCamelCase       :  Optional[str] = None ):
												if not os.path.isdir(lowerCamelCase_ ):
																			logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
																			return
												lowerCamelCase_					=       os.path.join(
												    lowerCamelCase_ ,       (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )

												if os.path.abspath(self.vocab_file ) != os.path.abspath(lowerCamelCase_ ) and os.path.isfile(self.vocab_file ):
																			copyfile(self.vocab_file ,       lowerCamelCase_ )
												elif not os.path.isfile(self.vocab_file ):
																			with open(lowerCamelCase_ ,       """wb""" ) as fi:
																										lowerCamelCase_					=       self.sp_model.serialized_model_proto()
																										fi.write(lowerCamelCase_ )

												return (out_vocab_file,)












import argparse
import os
import re


__UpperCamelCase:	Any = """src/transformers/models/auto"""


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
__UpperCamelCase:	Dict = re.compile(r"""[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict""")
# re pattern that matches identifiers in mappings
__UpperCamelCase:	List[str] = re.compile(r"""\s*\(\s*\"(\S[^\"]+)\"""")


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : int   ,    _lowercase     : bool = False			)   ->							List[str]:




		'''simple docstring'''
		with open(_lowercase   ,    'r'   ,    encoding='utf-8'			) as f:
				lowercase__					:      Union[str, Any]      =		f.read()

		lowercase__					:      Optional[Any]      =		content.split('\n'			)
		lowercase__					:      Optional[int]      =		[]
		lowercase__					:      int      =		0
		while line_idx < len(_lowercase			):
				if _re_intro_mapping.search(lines[line_idx]			) is not None:
						lowercase__					:      Tuple      =		len(re.search(r'^(\s*)\S'   ,    lines[line_idx]			).groups()[0]			) + 8
						# Start of a new mapping!
						while not lines[line_idx].startswith(' ' * indent + '('			):
								new_lines.append(lines[line_idx]			)
								line_idx += 1

						lowercase__					:      Tuple      =		[]
						while lines[line_idx].strip() != "]":
								# Blocks either fit in one line or not
								if lines[line_idx].strip() == "(":
										lowercase__					:      Any      =		line_idx
										while not lines[line_idx].startswith(' ' * indent + ')'			):
												line_idx += 1
										blocks.append('\n'.join(lines[start_idx : line_idx + 1]			)			)
								else:
										blocks.append(lines[line_idx]			)
								line_idx += 1

						# Sort blocks by their identifiers
						lowercase__					:      List[str]      =		sorted(_lowercase   ,    key=lambda _lowercase			: _re_identifier.search(_lowercase			).groups()[0]			)
						new_lines += blocks
				else:
						new_lines.append(lines[line_idx]			)
						line_idx += 1

		if overwrite:
				with open(_lowercase   ,    'w'   ,    encoding='utf-8'			) as f:
						f.write('\n'.join(_lowercase			)			)
		elif "\n".join(_lowercase			) != content:
				return True


def       SCREAMING_SNAKE_CASE__  (       _lowercase     : bool = False			)   ->							List[Any]:




		'''simple docstring'''
		lowercase__					:      List[Any]      =		[os.path.join(_lowercase   ,    _lowercase			) for f in os.listdir(_lowercase			) if f.endswith('.py'			)]
		lowercase__					:      str      =		[sort_auto_mapping(_lowercase   ,    overwrite=_lowercase			) for fname in fnames]

		if not overwrite and any(_lowercase			):
				lowercase__					:      List[Any]      =		[f for f, d in zip(_lowercase   ,    _lowercase			) if d]
				raise ValueError(
				    f"""The following files have auto mappings that need sorting: {", ".join(_lowercase			)}. Run `make style` to fix"""
				    ' this.'			)


if __name__ == "__main__":
			__UpperCamelCase:	Tuple = argparse.ArgumentParser()
			parser.add_argument("""--check_only""", action="""store_true""", help="""Whether to only check or fix style.""")
			__UpperCamelCase:	List[Any] = parser.parse_args()

			sort_all_auto_mappings(not args.check_only)


