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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__A				=logging.get_logger(__name__)

__A				='''▁'''

__A				={'''vocab_file''': '''sentencepiece.bpe.model'''}

__A				={
    '''vocab_file''': {
        '''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model''',
    }
}

__A				={
    '''facebook/xglm-564M''': 2_0_4_8,
}




class     _SCREAMING_SNAKE_CASE     (      snake_case_						):
	lowerCAmelCase__         = VOCAB_FILES_NAMES
	lowerCAmelCase__         = PRETRAINED_VOCAB_FILES_MAP
	lowerCAmelCase__         = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	lowerCAmelCase__         = ['input_ids', 'attention_mask']



	def __init__(    self						,  lowercase						,  lowercase="<s>"						,  lowercase="</s>"						,  lowercase="</s>"						,  lowercase="<s>"						,  lowercase="<unk>"						,  lowercase="<pad>"						,  lowercase = None						,  **lowercase						,  )				->       None:
					lowerCamelCase_						=			{} if sp_model_kwargs is None else sp_model_kwargs

					# Compatibility with the original tokenizer
					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__(
					    bos_token=lowercase						,  eos_token=lowercase						,  unk_token=lowercase						,  sep_token=lowercase						,  cls_token=lowercase						,  pad_token=lowercase						,  sp_model_kwargs=self.sp_model_kwargs						,  **lowercase						,  )

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

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

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

					lowerCamelCase_						=			len(self.sp_model )
					lowerCamelCase_						=			{f'<madeupword{i}>': sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words )}
					self.fairseq_tokens_to_ids.update(lowercase )

					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						,  lowercase )				->       str:
					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     SCREAMING_SNAKE_CASE_(    self						,  lowercase						,  lowercase = None )				->       List[int]:

					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						,  lowercase						,  lowercase = None						,  lowercase = 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 ))
					return [1] + ([0] * len(lowercase )) + [1, 1] + ([0] * len(lowercase ))



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase						,  lowercase = None )				->       List[int]:
					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]



	@property
	def     SCREAMING_SNAKE_CASE_(    self )				->       List[Any]:
					return len(self.sp_model ) + self.fairseq_offset + self.num_madeup_words



	def     SCREAMING_SNAKE_CASE_(    self )				->       int:
					lowerCamelCase_						=			{self.convert_ids_to_tokens(lowercase ): i for i in range(self.vocab_size )}
					vocab.update(self.added_tokens_encoder )
					return vocab



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       List[str]:
					return self.sp_model.encode(lowercase						,  out_type=lowercase )



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       int:
					if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
					lowerCamelCase_						=			self.sp_model.PieceToId(lowercase )

					# 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     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       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     SCREAMING_SNAKE_CASE_(    self						,  lowercase )				->       List[str]:
					lowerCamelCase_						=			"".join(lowercase ).replace(lowercase						,  " " ).strip()
					return out_string



	def     SCREAMING_SNAKE_CASE_(    self						,  lowercase						,  lowercase = None )				->       Tuple[str]:
					if not os.path.isdir(lowercase ):
									logger.error(f'Vocabulary path ({save_directory}) should be a directory' )
									return
					lowerCamelCase_						=			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:
													lowerCamelCase_						=			self.sp_model.serialized_model_proto()
													fi.write(lowercase )

					return (out_vocab_file,)




import os
from math import logaa






def 							_lowercase							(     UpperCamelCase_ = "base_exp.txt"		)		->		int:
					'''simple docstring'''


					SCREAMING_SNAKE_CASE__													= 0
					SCREAMING_SNAKE_CASE__													= 0
					for i, line in enumerate(open(os.path.join(os.path.dirname(UpperCamelCase_		)	,	UpperCamelCase_		)		)		):
										SCREAMING_SNAKE_CASE__						, SCREAMING_SNAKE_CASE__													= list(map(UpperCamelCase_	,	line.split(','		)		)		)
										if x * logaa(UpperCamelCase_		) > largest:
															SCREAMING_SNAKE_CASE__													= x * logaa(UpperCamelCase_		)
															SCREAMING_SNAKE_CASE__													= i + 1
					return result


if __name__ == "__main__":
				print(solution())





