



from typing import Dict, List, Optional

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


A__  :  List[str]								=					logging.get_logger(__name__)


A__  :  Tuple								=					{
    '''nielsr/canine-s''': 2048,
}

# Unicode defines 1,114,112 total “codepoints”
A__  :  Dict								=					111_4112

# Below: Constants defining canonical codepoints for special, pseudo-characters.
# Copied from https://github.com/google-research/language/blob/master/language/canine/special_codepoints.py
A__  :  List[Any]								=					0

A__  :  Optional[int]								=					0XE000
A__  :  Union[str, Any]								=					0XE001
A__  :  int								=					0XE002
A__  :  Optional[Any]								=					0XE003
A__  :  Dict								=					0XE004

# Maps special codepoints to human-readable names.
A__  :  Dict[int, str]								=					{
    # Special symbols are represented using codepoints values that are valid,
    # but designated as "Private Use", meaning that they will never be assigned
    # characters by the Unicode Consortium, and are thus safe for use here.
    #
    # NOTE: Do *NOT* add any sort of [UNK_CHAR] here. They are explicitly
    # excluded and should fail with a hard error.
    CLS: "[CLS]",
    SEP: "[SEP]",
    BOS: "[BOS]",
    MASK: "[MASK]",
    PAD: "[PAD]",
    RESERVED: "[RESERVED]",
}

# Maps special codepoint human-readable names to their codepoint values.
A__  :  Dict[str, int]								=					{name: codepoint for codepoint, name in SPECIAL_CODEPOINTS.items()}



class 				__snake_case						(     UpperCamelCase_						):
							_a			      = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES




							def __init__(       self     :       Dict				,				A_     :       List[str]=chr(A_)				,				A_     :       Union[str, Any]=chr(A_)				,				A_     :       List[Any]=chr(A_)				,				A_     :       Union[str, Any]=chr(A_)				,				A_     :       Tuple=chr(A_)				,				A_     :       Optional[int]=chr(A_)				,				A_     :       List[Any]=False				,				A_     :       Optional[Any]=2_0_4_8				,				**A_     :       Dict				,				):
									lowerCAmelCase_			:     List[str]									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else bos_token
									lowerCAmelCase_			:     str									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else eos_token
									lowerCAmelCase_			:     List[Any]									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else sep_token
									lowerCAmelCase_			:     int									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else cls_token
									lowerCAmelCase_			:     Tuple									= AddedToken(A_				,				lstrip=A_				,				rstrip=A_) if isinstance(A_				,				A_) else pad_token

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

									super().__init__(
									    bos_token=A_				,				eos_token=A_				,				sep_token=A_				,				cls_token=A_				,				pad_token=A_				,				mask_token=A_				,				add_prefix_space=A_				,				model_max_length=A_				,				**A_				,				)

									# Creates a mapping for looking up the IDs of special symbols.
									lowerCAmelCase_			:     Dict[str, int]									= {}
									for codepoint, name in SPECIAL_CODEPOINTS.items():
											lowerCAmelCase_			:     List[str]									= codepoint

									# Creates a mapping for looking up the string forms of special symbol IDs.
									lowerCAmelCase_			:     Dict[int, str]									= {
									    codepoint: name for name, codepoint in self._special_codepoints.items()
									}

									lowerCAmelCase_			:     Tuple									= UNICODE_VOCAB_SIZE
									lowerCAmelCase_			:     List[str]									= len(self._special_codepoints)




							@property
							def    UpperCAmelCase__			(       self     :       str):
									return self._unicode_vocab_size




							def    UpperCAmelCase__			(       self     :       List[str]				,				A_     :       str):
									return list(A_)




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       str):
									try:
											return ord(A_)
									except TypeError:
											raise ValueError(F"""invalid token: '{token}'""")




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       int):
									try:
											if index in SPECIAL_CODEPOINTS:
													return SPECIAL_CODEPOINTS[index]
											return chr(A_)
									except TypeError:
											raise ValueError(F"""invalid id: {index}""")




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       List[str]):
									return "".join(A_)




							def    UpperCAmelCase__			(       self     :       str				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None):
									lowerCAmelCase_			:     Optional[int]									= [self.sep_token_id]
									lowerCAmelCase_			:     Optional[int]									= [self.cls_token_id]

									lowerCAmelCase_			:     Dict									= cls + token_ids_a + sep
									if token_ids_a is not None:
											result += token_ids_a + sep
									return result




							def    UpperCAmelCase__			(       self     :       Dict				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None				,				A_     :       bool = False):
									if already_has_special_tokens:
											return super().get_special_tokens_mask(
											    token_ids_a=A_				,				token_ids_a=A_				,				already_has_special_tokens=A_)

									lowerCAmelCase_			:     Dict									= [1] + ([0] * len(A_)) + [1]
									if token_ids_a is not None:
											result += ([0] * len(A_)) + [1]
									return result




							def    UpperCAmelCase__			(       self     :       int				,				A_     :       List[int]				,				A_     :       Optional[List[int]] = None):
									lowerCAmelCase_			:     Any									= [self.sep_token_id]
									lowerCAmelCase_			:     int									= [self.cls_token_id]

									lowerCAmelCase_			:     Optional[int]									= len(cls + token_ids_a + sep) * [0]
									if token_ids_a is not None:
											result += len(token_ids_a + sep) * [1]
									return result







							def    UpperCAmelCase__			(       self     :       Optional[Any]				,				A_     :       str				,				A_     :       Optional[str] = None):
									return ()










import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp


def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     List[str]									= ArgumentParser(
		    description=(
		        '''PyTorch TPU distributed training launch '''
		        '''helper utility that will spawn up '''
		        '''multiple distributed processes'''
		    ) )

		# Optional arguments for the launch helper
		parser.add_argument('''--num_cores'''     ,type=__UpperCamelCase     ,default=1     ,help='''Number of TPU cores to use (1 or 8).''' )

		# positional
		parser.add_argument(
		    '''training_script'''     ,type=__UpperCamelCase     ,help=(
		        '''The full path to the single TPU training '''
		        '''program/script to be launched in parallel, '''
		        '''followed by all the arguments for the '''
		        '''training script'''
		    )     ,)

		# rest from the training program
		parser.add_argument('''training_script_args'''     ,nargs=__UpperCamelCase )

		return parser.parse_args()


def 			UpperCamelCase(  ):
		lowerCAmelCase_			:     str									= parse_args()

		# Import training_script as a module.
		lowerCAmelCase_			:     str									= Path(args.training_script )
		sys.path.append(str(script_fpath.parent.resolve() ) )
		lowerCAmelCase_			:     Tuple									= script_fpath.stem
		lowerCAmelCase_			:     Union[str, Any]									= importlib.import_module(__UpperCamelCase )

		# Patch sys.argv
		lowerCAmelCase_			:     Optional[int]									= [args.training_script] + args.training_script_args + ['''--tpu_num_cores''', str(args.num_cores )]
		xmp.spawn(mod._mp_fn     ,args=()     ,nprocs=args.num_cores )


if __name__ == "__main__":
						main()





