



"""simple docstring"""


import os
import re
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


snake_case_    					=	logging.get_logger(__name__)

snake_case_    					=	{"""vocab_file""": """spiece.model"""}

snake_case_    					=	{
    """vocab_file""": {
        """google/bigbird-roberta-base""": """https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model""",
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"""
        ),
    }
}

snake_case_    					=	{
    """google/bigbird-roberta-base""": 4096,
    """google/bigbird-roberta-large""": 4096,
    """google/bigbird-base-trivia-itc""": 4096,
}







class 				A_      (					SCREAMING_SNAKE_CASE_    ):



						"""simple docstring"""
						__UpperCamelCase		    =							VOCAB_FILES_NAMES
						__UpperCamelCase		    =							PRETRAINED_VOCAB_FILES_MAP
						__UpperCamelCase		    =							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__UpperCamelCase		    =							["""input_ids""", """attention_mask"""]
						__UpperCamelCase		    =							[]






						def __init__( self			:Optional[Any]       ,  lowercase_			:List[Any]       ,  lowercase_			:List[Any]="<unk>"       ,  lowercase_			:Optional[Any]="<s>"       ,  lowercase_			:Dict="</s>"       ,  lowercase_			:List[str]="<pad>"       ,  lowercase_			:Dict="[SEP]"       ,  lowercase_			:Optional[Any]="[MASK]"       ,  lowercase_			:Any="[CLS]"       ,  lowercase_			:Optional[Dict[str, Any]] = None       ,  **lowercase_			:Tuple       ,  )    ->      None:
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else bos_token
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else eos_token
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else unk_token
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else pad_token
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else cls_token
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else sep_token

												# Mask token behave like a normal word, i.e. include the space before it
												UpperCAmelCase					=			AddedToken(lowercase_       ,  lstrip=lowercase_       ,  rstrip=lowercase_ ) if isinstance(lowercase_       ,  lowercase_ ) else mask_token

												UpperCAmelCase					=			{} if sp_model_kwargs is None else sp_model_kwargs

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

												UpperCAmelCase					=			vocab_file

												UpperCAmelCase					=			spm.SentencePieceProcessor(**self.sp_model_kwargs )
												self.sp_model.Load(lowercase_ )






						@property
						def      UpperCAmelCase__					( self			:List[Any] )    ->      Dict:
												return self.sp_model.get_piece_size()






						def      UpperCAmelCase__					( self			:Dict )    ->      str:
												UpperCAmelCase					=			{self.convert_ids_to_tokens(lowercase_ ): i for i in range(self.vocab_size )}
												vocab.update(self.added_tokens_encoder )
												return vocab






						def __getstate__( self			:Tuple )    ->      Tuple:
												UpperCAmelCase					=			self.__dict__.copy()
												UpperCAmelCase					=			None
												return state






						def __setstate__( self			:Dict       ,  lowercase_			:Optional[int] )    ->      Dict:
												UpperCAmelCase					=			d

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

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






						def      UpperCAmelCase__					( self			:int       ,  lowercase_			:str )    ->      List[str]:
												return self.sp_model.encode(lowercase_       ,  out_type=lowercase_ )






						def      UpperCAmelCase__					( self			:Optional[int]       ,  lowercase_			:Any )    ->      str:
												return self.sp_model.piece_to_id(lowercase_ )






						def      UpperCAmelCase__					( self			:Optional[int]       ,  lowercase_			:Optional[Any] )    ->      str:
												UpperCAmelCase					=			self.sp_model.IdToPiece(lowercase_ )
												return token






						def      UpperCAmelCase__					( self			:Tuple       ,  lowercase_			:Any )    ->      Tuple:
												UpperCAmelCase					=			[]
												UpperCAmelCase					=			''
												UpperCAmelCase					=			False
												for token in tokens:
																		# make sure that special tokens are not decoded using sentencepiece model
																		if token in self.all_special_tokens:
																								if not prev_is_special:
																														out_string += " "
																								out_string += self.sp_model.decode(lowercase_ ) + token
																								UpperCAmelCase					=			True
																								UpperCAmelCase					=			[]
																		else:
																								current_sub_tokens.append(lowercase_ )
																								UpperCAmelCase					=			False
												out_string += self.sp_model.decode(lowercase_ )
												return out_string.strip()






						def      UpperCAmelCase__					( self			:str       ,  lowercase_			:List[int]       ,  lowercase_			:bool = False       ,  lowercase_			:bool = None       ,  lowercase_			:bool = True       ,  **lowercase_			:int       ,  )    ->      str:
												UpperCAmelCase					=			kwargs.pop('use_source_tokenizer'       ,  lowercase_ )

												UpperCAmelCase					=			self.convert_ids_to_tokens(lowercase_       ,  skip_special_tokens=lowercase_ )

												# To avoid mixing byte-level and unicode for byte-level BPT
												# we need to build string separately for added tokens and byte-level tokens
												# cf. https://github.com/huggingface/transformers/issues/1133
												UpperCAmelCase					=			[]
												UpperCAmelCase					=			[]
												for token in filtered_tokens:
																		if skip_special_tokens and token in self.all_special_ids:
																								continue
																		if token in self.added_tokens_encoder:
																								if current_sub_text:
																														sub_texts.append(self.convert_tokens_to_string(lowercase_ ) )
																														UpperCAmelCase					=			[]
																								sub_texts.append(lowercase_ )
																		else:
																								current_sub_text.append(lowercase_ )
												if current_sub_text:
																		sub_texts.append(self.convert_tokens_to_string(lowercase_ ) )

												# Mimic the behavior of the Rust tokenizer:
												# No space before [MASK] and [SEP]
												if spaces_between_special_tokens:
																		UpperCAmelCase					=			re.sub(R' (\[(MASK|SEP)\])'       ,  R'\1'       ,  ' '.join(lowercase_ ) )
												else:
																		UpperCAmelCase					=			''.join(lowercase_ )

												UpperCAmelCase					=			(
												    clean_up_tokenization_spaces
												    if clean_up_tokenization_spaces is not None
												    else self.clean_up_tokenization_spaces
												)
												if clean_up_tokenization_spaces:
																		UpperCAmelCase					=			self.clean_up_tokenization(lowercase_ )
																		return clean_text
												else:
																		return text






						def      UpperCAmelCase__					( self			:Any       ,  lowercase_			:str       ,  lowercase_			:Optional[str] = None )    ->      Tuple[str]:
												if not os.path.isdir(lowercase_ ):
																		logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
																		return
												UpperCAmelCase					=			os.path.join(
												    lowercase_       ,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )

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

												return (out_vocab_file,)






						def      UpperCAmelCase__					( self			:List[Any]       ,  lowercase_			:List[int]       ,  lowercase_			:Optional[List[int]] = None )    ->      List[int]:
												if token_ids_a is None:
																		return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												UpperCAmelCase					=			[self.cls_token_id]
												UpperCAmelCase					=			[self.sep_token_id]
												return cls + token_ids_a + sep + token_ids_a + sep






						def      UpperCAmelCase__					( self			:Any       ,  lowercase_			:List[int]       ,  lowercase_			:Optional[List[int]] = None       ,  lowercase_			:bool = False )    ->      List[int]:
												if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=lowercase_       ,  token_ids_a=lowercase_       ,  already_has_special_tokens=lowercase_ )

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






						def      UpperCAmelCase__					( self			:Union[str, Any]       ,  lowercase_			:List[int]       ,  lowercase_			:Optional[List[int]] = None )    ->      List[int]:
												UpperCAmelCase					=			[self.sep_token_id]
												UpperCAmelCase					=			[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 ) * [0] + len(token_ids_a + sep ) * [1]










"""simple docstring"""


import operator as op


snake_case_    					=	"""scaler.pt"""
snake_case_    					=	"""pytorch_model"""
snake_case_    					=	"""random_states"""
snake_case_    					=	"""optimizer"""
snake_case_    					=	"""scheduler"""
snake_case_    					=	"""pytorch_model.bin"""
snake_case_    					=	"""pytorch_model.bin.index.json"""
snake_case_    					=	"""model.safetensors"""
snake_case_    					=	"""model.safetensors.index.json"""
snake_case_    					=	"""1.10.2"""
snake_case_    					=	"""py38"""
snake_case_    					=	"""4.17.0"""
snake_case_    					=	["""ml.p3.16xlarge""", """ml.p3dn.24xlarge""", """ml.p4dn.24xlarge"""]
snake_case_    					=	["""FULL_SHARD""", """SHARD_GRAD_OP""", """NO_SHARD""", """HYBRID_SHARD""", """HYBRID_SHARD_ZERO2"""]
snake_case_    					=	["""TRANSFORMER_BASED_WRAP""", """SIZE_BASED_WRAP""", """NO_WRAP"""]
snake_case_    					=	["""BACKWARD_PRE""", """BACKWARD_POST""", """NO_PREFETCH"""]
snake_case_    					=	["""FULL_STATE_DICT""", """LOCAL_STATE_DICT""", """SHARDED_STATE_DICT"""]
snake_case_    					=	"""2.0.1"""
snake_case_    					=	["""pdsh""", """standard""", """openmpi""", """mvapich"""]
snake_case_    					=	["""default""", """reduce-overhead""", """max-autotune"""]

snake_case_    					=	{""">""": op.gt, """>=""": op.ge, """==""": op.eq, """!=""": op.ne, """<=""": op.le, """<""": op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
snake_case_    					=	[
    """nnodes""",
    """nproc_per_node""",
    """rdzv_backend""",
    """rdzv_endpoint""",
    """rdzv_id""",
    """rdzv_conf""",
    """standalone""",
    """max_restarts""",
    """monitor_interval""",
    """start_method""",
    """role""",
    """module""",
    """m""",
    """no_python""",
    """run_path""",
    """log_dir""",
    """r""",
    """redirects""",
    """t""",
    """tee""",
    """node_rank""",
    """master_addr""",
    """master_port""",
]

snake_case_    					=	["""DEEPSPEED""", """MULTI_GPU""", """FSDP""", """MEGATRON_LM"""]
snake_case_    					=	["""DEEPSPEED""", """MULTI_XPU""", """FSDP"""]





