

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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_albert import AlbertTokenizer
else:
				_a:    str 							=			None

_a:    str 							=			logging.get_logger(__name__)
_a:    str 							=			{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

_a:    Optional[int] 							=			{
    """vocab_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/spiece.model""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/spiece.model""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/spiece.model""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/spiece.model""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json""",
    },
}

_a:    Tuple 							=			{
    """albert-base-v1""": 512,
    """albert-large-v1""": 512,
    """albert-xlarge-v1""": 512,
    """albert-xxlarge-v1""": 512,
    """albert-base-v2""": 512,
    """albert-large-v2""": 512,
    """albert-xlarge-v2""": 512,
    """albert-xxlarge-v2""": 512,
}

_a:    List[Any] 							=			"""▁"""

class 						__UpperCamelCase    (					lowercase						):
	SCREAMING_SNAKE_CASE__    				=     VOCAB_FILES_NAMES
	SCREAMING_SNAKE_CASE__    				=     PRETRAINED_VOCAB_FILES_MAP
	SCREAMING_SNAKE_CASE__    				=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	SCREAMING_SNAKE_CASE__    				=     AlbertTokenizer




	def __init__(		self	:						Dict		,	lowerCAmelCase	:						Optional[Any]=None		,	lowerCAmelCase	:						int=None		,	lowerCAmelCase	:						int=True		,	lowerCAmelCase	:						str=True		,	lowerCAmelCase	:						Union[str, Any]=False		,	lowerCAmelCase	:						Tuple="[CLS]"		,	lowerCAmelCase	:						Union[str, Any]="[SEP]"		,	lowerCAmelCase	:						Union[str, Any]="<unk>"		,	lowerCAmelCase	:						List[str]="[SEP]"		,	lowerCAmelCase	:						Optional[Any]="<pad>"		,	lowerCAmelCase	:						str="[CLS]"		,	lowerCAmelCase	:						Any="[MASK]"		,	**lowerCAmelCase	:						Union[str, Any]		,	):


		'''simple docstring'''







		UpperCAmelCase_       				=			(
		    AddedToken(lowerCAmelCase		,	lstrip=lowerCAmelCase		,	rstrip=lowerCAmelCase		,	normalized=lowerCAmelCase							)
		    if isinstance(lowerCAmelCase		,	lowerCAmelCase							)
		    else mask_token
		)

		super().__init__(
		    lowerCAmelCase		,	tokenizer_file=lowerCAmelCase		,	do_lower_case=lowerCAmelCase		,	remove_space=lowerCAmelCase		,	keep_accents=lowerCAmelCase		,	bos_token=lowerCAmelCase		,	eos_token=lowerCAmelCase		,	unk_token=lowerCAmelCase		,	sep_token=lowerCAmelCase		,	pad_token=lowerCAmelCase		,	cls_token=lowerCAmelCase		,	mask_token=lowerCAmelCase		,	**lowerCAmelCase		,	)

		UpperCAmelCase_       				=			do_lower_case
		UpperCAmelCase_       				=			remove_space
		UpperCAmelCase_       				=			keep_accents
		UpperCAmelCase_       				=			vocab_file
		UpperCAmelCase_       				=			False if not self.vocab_file else True




	def       __A					(		self	:						Tuple		,	lowerCAmelCase	:						List[int]		,	lowerCAmelCase	:						Optional[List[int]] = None							):


		'''simple docstring'''







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




	def       __A					(		self	:						int		,	lowerCAmelCase	:						List[int]		,	lowerCAmelCase	:						Optional[List[int]] = None							):


		'''simple docstring'''







		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]




	def       __A					(		self	:						Optional[Any]		,	lowerCAmelCase	:						str		,	lowerCAmelCase	:						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(lowerCAmelCase							):
			logger.error(F"Vocabulary path ({save_directory}) should be a directory"							)
			return
		UpperCAmelCase_       				=			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							):
			copyfile(self.vocab_file		,	lowerCAmelCase							)

		return (out_vocab_file,)


from collections.abc import Sequence



def       __lowerCAmelCase      (						A       ,     A = False    ):
	if not arr:
		return 0

	UpperCAmelCase_       				=			0 if allow_empty_subarrays else float("-inf"    )
	UpperCAmelCase_       				=			0.0
	for num in arr:
		UpperCAmelCase_       				=			max(0 if allow_empty_subarrays else num       ,     curr_sum + num    )
		UpperCAmelCase_       				=			max(A       ,     A    )

	return max_sum


if __name__ == "__main__":
				from doctest import testmod

				testmod()

				_a:    Any 							=			[-2, 1, -3, 4, -1, 2, 1, -5, 4]
				print(F'{max_subarray_sum(nums) = }')