

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

import sentencepiece as spm

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


a		=logging.get_logger(__name__)

a		="""▁"""

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

a		={
    """vocab_file""": {
        """facebook/mbart-large-50-one-to-many-mmt""": (
            """https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model"""
        ),
    }
}

a		={
    """facebook/mbart-large-50-one-to-many-mmt""": 1024,
}

# fmt: off
a		=["""ar_AR""", """cs_CZ""", """de_DE""", """en_XX""", """es_XX""", """et_EE""", """fi_FI""", """fr_XX""", """gu_IN""", """hi_IN""", """it_IT""", """ja_XX""", """kk_KZ""", """ko_KR""", """lt_LT""", """lv_LV""", """my_MM""", """ne_NP""", """nl_XX""", """ro_RO""", """ru_RU""", """si_LK""", """tr_TR""", """vi_VN""", """zh_CN""", """af_ZA""", """az_AZ""", """bn_IN""", """fa_IR""", """he_IL""", """hr_HR""", """id_ID""", """ka_GE""", """km_KH""", """mk_MK""", """ml_IN""", """mn_MN""", """mr_IN""", """pl_PL""", """ps_AF""", """pt_XX""", """sv_SE""", """sw_KE""", """ta_IN""", """te_IN""", """th_TH""", """tl_XX""", """uk_UA""", """ur_PK""", """xh_ZA""", """gl_ES""", """sl_SI"""]






class        A_		(       SCREAMING_SNAKE_CASE				):
							_UpperCAmelCase    :  str						      =      VOCAB_FILES_NAMES
							_UpperCAmelCase    :  Any						      =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_UpperCAmelCase    :  int						      =      PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase    :  Dict						      =      ['''input_ids''', '''attention_mask''']

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

								__lowerCamelCase				:				List[str]					       = {} if sp_model_kwargs is None else sp_model_kwargs

								__lowerCamelCase				:				Any					       = kwargs.get('additional_special_tokens'   ,[])
								kwargs["additional_special_tokens"] += [
								    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
								]

								super().__init__(
								    src_lang=SCREAMING_SNAKE_CASE__   ,tgt_lang=SCREAMING_SNAKE_CASE__   ,eos_token=SCREAMING_SNAKE_CASE__   ,unk_token=SCREAMING_SNAKE_CASE__   ,sep_token=SCREAMING_SNAKE_CASE__   ,cls_token=SCREAMING_SNAKE_CASE__   ,pad_token=SCREAMING_SNAKE_CASE__   ,mask_token=SCREAMING_SNAKE_CASE__   ,sp_model_kwargs=self.sp_model_kwargs   ,**SCREAMING_SNAKE_CASE__   ,)

								__lowerCamelCase				:				Union[str, Any]					       = spm.SentencePieceProcessor(**self.sp_model_kwargs)
								self.sp_model.Load(str(SCREAMING_SNAKE_CASE__))
								__lowerCamelCase				:				Tuple					       = 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				:				str					       = {'<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				:				Tuple					       = 1

								__lowerCamelCase				:				List[Any]					       = len(self.sp_model)
								__lowerCamelCase				:				List[Any]					       = {
								    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(SCREAMING_SNAKE_CASE__)
								}
								__lowerCamelCase				:				Tuple					       = {v: k for k, v in self.lang_code_to_id.items()}
								__lowerCamelCase				:				Tuple					       = len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

								self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
								__lowerCamelCase				:				Union[str, Any]					       = {v: k for k, v in self.fairseq_tokens_to_ids.items()}

								__lowerCamelCase				:				Optional[Any]					       = src_lang if src_lang is not None else 'en_XX'
								__lowerCamelCase				:				Tuple					       = self.lang_code_to_id[self._src_lang]
								__lowerCamelCase				:				Optional[Any]					       = tgt_lang
								self.set_src_lang_special_tokens(self._src_lang)
							@property
							def     lowerCAmelCase     (		self		:			Tuple):
								return len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset + 1  # Plus 1 for the mask token
							@property
							def     lowerCAmelCase     (		self		:			int):
								return self._src_lang
							@src_lang.setter
							def     lowerCAmelCase     (		self		:			Optional[Any]   ,SCREAMING_SNAKE_CASE__		:			str):
								__lowerCamelCase				:				str					       = new_src_lang
								self.set_src_lang_special_tokens(self._src_lang)
							def __getstate__(		self		:			Optional[int]):
								__lowerCamelCase				:				str					       = self.__dict__.copy()
								__lowerCamelCase				:				Union[str, Any]					       = None
								return state
							def __setstate__(		self		:			Optional[int]   ,SCREAMING_SNAKE_CASE__		:			Dict):
								__lowerCamelCase				:				Optional[Any]					       = d

								# for backward compatibility
								if not hasattr(self   ,'sp_model_kwargs'):
									__lowerCamelCase				:				List[str]					       = {}

								__lowerCamelCase				:				int					       = spm.SentencePieceProcessor(**self.sp_model_kwargs)
								self.sp_model.Load(self.vocab_file)
							def     lowerCAmelCase     (		self		:			List[Any]):
								__lowerCamelCase				:				str					       = {self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__): i for i in range(self.vocab_size)}
								vocab.update(self.added_tokens_encoder)
								return vocab
							def     lowerCAmelCase     (		self		:			Optional[Any]   ,SCREAMING_SNAKE_CASE__		:			str):
								return self.sp_model.encode(SCREAMING_SNAKE_CASE__   ,out_type=SCREAMING_SNAKE_CASE__)
							def     lowerCAmelCase     (		self		:			Dict   ,SCREAMING_SNAKE_CASE__		:			str):
								if token in self.fairseq_tokens_to_ids:
									return self.fairseq_tokens_to_ids[token]
								__lowerCamelCase				:				int					       = self.sp_model.PieceToId(SCREAMING_SNAKE_CASE__)

								# 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     lowerCAmelCase     (		self		:			List[Any]   ,SCREAMING_SNAKE_CASE__		:			int):
								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     lowerCAmelCase     (		self		:			List[str]   ,SCREAMING_SNAKE_CASE__		:			int):
								__lowerCamelCase				:				List[Any]					       = []
								__lowerCamelCase				:				Optional[int]					       = ''
								__lowerCamelCase				:				int					       = 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(SCREAMING_SNAKE_CASE__) + token
										__lowerCamelCase				:				Tuple					       = True
										__lowerCamelCase				:				str					       = []
									else:
										current_sub_tokens.append(SCREAMING_SNAKE_CASE__)
										__lowerCamelCase				:				Optional[int]					       = False
								out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__)
								return out_string.strip()
							def     lowerCAmelCase     (		self		:			Any   ,SCREAMING_SNAKE_CASE__		:			str   ,SCREAMING_SNAKE_CASE__		:			Optional[str] = None):
								if not os.path.isdir(SCREAMING_SNAKE_CASE__):
									logger.error(F"Vocabulary path ({save_directory}) should be a directory")
									return
								__lowerCamelCase				:				Union[str, Any]					       = os.path.join(
								    SCREAMING_SNAKE_CASE__   ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

								if os.path.abspath(self.vocab_file) != os.path.abspath(SCREAMING_SNAKE_CASE__) and os.path.isfile(self.vocab_file):
									copyfile(self.vocab_file   ,SCREAMING_SNAKE_CASE__)
								elif not os.path.isfile(self.vocab_file):
									with open(SCREAMING_SNAKE_CASE__   ,'wb') as fi:
										__lowerCamelCase				:				Optional[int]					       = self.sp_model.serialized_model_proto()
										fi.write(SCREAMING_SNAKE_CASE__)

								return (out_vocab_file,)
							def     lowerCAmelCase     (		self		:			Optional[Any]   ,SCREAMING_SNAKE_CASE__		:			List[int]   ,SCREAMING_SNAKE_CASE__		:			Optional[List[int]] = None   ,SCREAMING_SNAKE_CASE__		:			bool = False):

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

								__lowerCamelCase				:				Tuple					       = [1] * len(self.prefix_tokens)
								__lowerCamelCase				:				Tuple					       = [1] * len(self.suffix_tokens)
								if token_ids_a is None:
									return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE__)) + suffix_ones
								return prefix_ones + ([0] * len(SCREAMING_SNAKE_CASE__)) + ([0] * len(SCREAMING_SNAKE_CASE__)) + suffix_ones
							def     lowerCAmelCase     (		self		:			List[str]   ,SCREAMING_SNAKE_CASE__		:			List[int]   ,SCREAMING_SNAKE_CASE__		:			Optional[List[int]] = None):
								if token_ids_a is None:
									return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
							def     lowerCAmelCase     (		self		:			Tuple   ,SCREAMING_SNAKE_CASE__		:			int   ,SCREAMING_SNAKE_CASE__		:			str   ,SCREAMING_SNAKE_CASE__		:			Optional[str]   ,SCREAMING_SNAKE_CASE__		:			Optional[str]   ,**SCREAMING_SNAKE_CASE__		:			Dict):
								if src_lang is None or tgt_lang is None:
									raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model')
								__lowerCamelCase				:				List[str]					       = src_lang
								__lowerCamelCase				:				int					       = self(SCREAMING_SNAKE_CASE__   ,add_special_tokens=SCREAMING_SNAKE_CASE__   ,return_tensors=SCREAMING_SNAKE_CASE__   ,**SCREAMING_SNAKE_CASE__)
								__lowerCamelCase				:				Optional[Any]					       = self.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__)
								__lowerCamelCase				:				int					       = tgt_lang_id
								return inputs
							def     lowerCAmelCase     (		self		:			Dict   ,SCREAMING_SNAKE_CASE__		:			List[str]   ,SCREAMING_SNAKE_CASE__		:			str = "en_XX"   ,SCREAMING_SNAKE_CASE__		:			Optional[List[str]] = None   ,SCREAMING_SNAKE_CASE__		:			str = "ro_RO"   ,**SCREAMING_SNAKE_CASE__		:			Optional[Any]   ,):
								__lowerCamelCase				:				str					       = src_lang
								__lowerCamelCase				:				str					       = tgt_lang
								return super().prepare_seqaseq_batch(SCREAMING_SNAKE_CASE__   ,SCREAMING_SNAKE_CASE__   ,**SCREAMING_SNAKE_CASE__)
							def     lowerCAmelCase     (		self		:			Dict):
								return self.set_src_lang_special_tokens(self.src_lang)
							def     lowerCAmelCase     (		self		:			Tuple):
								return self.set_tgt_lang_special_tokens(self.tgt_lang)
							def     lowerCAmelCase     (		self		:			Tuple   ,SCREAMING_SNAKE_CASE__		:			str):
								__lowerCamelCase				:				int					       = self.lang_code_to_id[src_lang]
								__lowerCamelCase				:				str					       = [self.cur_lang_code_id]
								__lowerCamelCase				:				Dict					       = [self.eos_token_id]


							def     lowerCAmelCase     (		self		:			Optional[int]   ,SCREAMING_SNAKE_CASE__		:			str):
								__lowerCamelCase				:				Optional[Any]					       = self.lang_code_to_id[tgt_lang]
								__lowerCamelCase				:				List[Any]					       = [self.cur_lang_code_id]
								__lowerCamelCase				:				List[Any]					       = [self.eos_token_id]






def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''

					if edge <= 0 or not isinstance(lowerCAmelCase__ ,			lowerCAmelCase__		):
										raise ValueError('''Length must be a positive.'''		)
					return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)



def        UpperCamelCase    (							lowerCAmelCase__		):
					'''simple docstring'''

					if edge <= 0 or not isinstance(lowerCAmelCase__ ,			lowerCAmelCase__		):
										raise ValueError('''Length must be a positive.'''		)
					return ((15 + (7 * (5 ** (1 / 2)))) / 4) * (edge**3)


if __name__ == "__main__":
							import doctest

							doctest.testmod()




