
import io
import os
import unicodedata
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': 'vocab.txt', 'sentencepiece_model_ckpt': 'sentencepiece.bpe.model'}

__a         =   {
    'sentencepiece_model_file': 'sentencepiece.bpe.model',
    'vocab_file': 'vocab.txt',
}

__a         =   {
    'vocab_file': {
        'ernie-m-base': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt',
        'ernie-m-large': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt',
    },
    'sentencepiece_model_file': {
        'ernie-m-base': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model',
        'ernie-m-large': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model',
    },
}

__a         =   {
    'ernie-m-base': 5_1_4,
    'ernie-m-large': 5_1_4,
}

__a         =   {
    'ernie-m-base': {'do_lower_case': False},
    'ernie-m-large': {'do_lower_case': False},
}
class 					lowercase__(							UpperCAmelCase				):



	"""simple docstring"""




	a     :List[str]       	=      ["input_ids"]

	a     :Dict       	=      VOCAB_FILES_NAMES
	a     :Union[str, Any]       	=      PRETRAINED_INIT_CONFIGURATION
	a     :Dict       	=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	a     :List[str]       	=      PRETRAINED_VOCAB_FILES_MAP
	a     :Tuple       	=      RESOURCE_FILES_NAMES
	def __init__(			self    :     str			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]			,				SCREAMING_SNAKE_CASE_    :     List[str]=None			,				SCREAMING_SNAKE_CASE_    :     List[Any]=False			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]="utf8"			,				SCREAMING_SNAKE_CASE_    :     List[Any]="[UNK]"			,				SCREAMING_SNAKE_CASE_    :     Dict="[SEP]"			,				SCREAMING_SNAKE_CASE_    :     Union[str, Any]="[PAD]"			,				SCREAMING_SNAKE_CASE_    :     Optional[int]="[CLS]"			,				SCREAMING_SNAKE_CASE_    :     Optional[int]="[MASK]"			,				SCREAMING_SNAKE_CASE_    :     Optional[Dict[str, Any]] = None			,				**SCREAMING_SNAKE_CASE_    :     Optional[int]			,				)			->	None:
					# Mask token behave like a normal word, i.e. include the space before it and
					# is included in the raw text, there should be a match in a non-normalized sentence.

					lowercase_	    =   {} if sp_model_kwargs is None else sp_model_kwargs
					super().__init__(
					    do_lower_case=SCREAMING_SNAKE_CASE_			,				unk_token=SCREAMING_SNAKE_CASE_			,				sep_token=SCREAMING_SNAKE_CASE_			,				pad_token=SCREAMING_SNAKE_CASE_			,				cls_token=SCREAMING_SNAKE_CASE_			,				mask_token=SCREAMING_SNAKE_CASE_			,				vocab_file=SCREAMING_SNAKE_CASE_			,				encoding=SCREAMING_SNAKE_CASE_			,				sp_model_kwargs=self.sp_model_kwargs			,				**SCREAMING_SNAKE_CASE_			,				)
					lowercase_	    =   do_lower_case
					lowercase_	    =   sentencepiece_model_ckpt
					lowercase_	    =   spm.SentencePieceProcessor(**self.sp_model_kwargs			)
					self.sp_model.Load(SCREAMING_SNAKE_CASE_			)

					# to mimic paddlenlp.transformers.ernie_m.tokenizer.ErnieMTokenizer functioning
					if vocab_file is not None:
									lowercase_	    =   self.load_vocab(filepath=SCREAMING_SNAKE_CASE_			)
					else:
									lowercase_	    =   {self.sp_model.id_to_piece(SCREAMING_SNAKE_CASE_			): id for id in range(self.sp_model.get_piece_size()			)}
					lowercase_	    =   {v: k for k, v in self.vocab.items()}
	def 		_lowercase    (			self    :     Dict			,				SCREAMING_SNAKE_CASE_    :     str			)			->	List[Any]:
					if text is None:
									return None

					lowercase_	    =   self.tokenize(SCREAMING_SNAKE_CASE_			)
					lowercase_    ,      lowercase_	    =   '''''', []

					for i, ch in enumerate(SCREAMING_SNAKE_CASE_			):
									if ch in self.SP_CHAR_MAPPING:
													lowercase_	    =   self.SP_CHAR_MAPPING.get(SCREAMING_SNAKE_CASE_			)
									else:
													lowercase_	    =   unicodedata.normalize('''NFKC'''			,				SCREAMING_SNAKE_CASE_			)
									if self.is_whitespace(SCREAMING_SNAKE_CASE_			):
													continue
									normalized_text += ch
									char_mapping.extend([i] * len(SCREAMING_SNAKE_CASE_			)			)

					lowercase_    ,      lowercase_    ,      lowercase_	    =   normalized_text, [], 0

					if self.do_lower_case:
									lowercase_	    =   text.lower()

					for token in split_tokens:
									if token[:1] == "▁":
													lowercase_	    =   token[1:]
									lowercase_	    =   text[offset:].index(SCREAMING_SNAKE_CASE_			) + offset
									lowercase_	    =   start + len(SCREAMING_SNAKE_CASE_			)

									token_mapping.append((char_mapping[start], char_mapping[end - 1] + 1)			)
									lowercase_	    =   end
					return token_mapping
	@property
	def 		_lowercase    (			self    :     Union[str, Any]			)			->	Union[str, Any]:
					return len(self.vocab			)
	def 		_lowercase    (			self    :     Any			)			->	Optional[int]:
					return dict(self.vocab			,				**self.added_tokens_encoder			)
	def __getstate__(			self    :     Dict			)			->	int:
					lowercase_	    =   self.__dict__.copy()
					lowercase_	    =   None
					return state
	def __setstate__(			self    :     int			,				SCREAMING_SNAKE_CASE_    :     Any			)			->	List[Any]:
					lowercase_	    =   d

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

					lowercase_	    =   spm.SentencePieceProcessor(**self.sp_model_kwargs			)
					self.sp_model.Load(self.sentencepiece_model_ckpt			)
	def 		_lowercase    (			self    :     Optional[int]			,				SCREAMING_SNAKE_CASE_    :     Tuple			)			->	str:
					return "".join((self.SP_CHAR_MAPPING.get(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			) for c in text)			)
	def 		_lowercase    (			self    :     Dict			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]			,				SCREAMING_SNAKE_CASE_    :     List[Any]=False			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=6_4			,				SCREAMING_SNAKE_CASE_    :     List[str]=0.1			)			->	Any:

					if self.sp_model_kwargs.get('''enable_sampling'''			) is True:
									lowercase_	    =   True
					if self.sp_model_kwargs.get('''alpha'''			) is not None:
									lowercase_	    =   self.sp_model_kwargs.get('''alpha'''			)
					if self.sp_model_kwargs.get('''nbest_size'''			) is not None:
									lowercase_	    =   self.sp_model_kwargs.get('''nbest_size'''			)

					if not enable_sampling:
									lowercase_	    =   self.sp_model.EncodeAsPieces(SCREAMING_SNAKE_CASE_			)
					else:
									lowercase_	    =   self.sp_model.SampleEncodeAsPieces(SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			,				SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   []
					for pi, piece in enumerate(SCREAMING_SNAKE_CASE_			):
									if piece == SPIECE_UNDERLINE:
													if not pieces[pi + 1].startswith(SCREAMING_SNAKE_CASE_			) and pi != 0:
																	new_pieces.append(SCREAMING_SNAKE_CASE_			)
																	continue
													else:
																	continue
									lowercase_	    =   0
									for i, chunk in enumerate(SCREAMING_SNAKE_CASE_			):
													if chunk == SPIECE_UNDERLINE:
																	continue
													if self.is_ch_char(SCREAMING_SNAKE_CASE_			) or self.is_punct(SCREAMING_SNAKE_CASE_			):
																	if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
																					new_pieces.append(piece[lst_i:i]			)
																	new_pieces.append(SCREAMING_SNAKE_CASE_			)
																	lowercase_	    =   i + 1
													elif chunk.isdigit() and i > 0 and not piece[i - 1].isdigit():
																	if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
																					new_pieces.append(piece[lst_i:i]			)
																	lowercase_	    =   i
													elif not chunk.isdigit() and i > 0 and piece[i - 1].isdigit():
																	if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
																					new_pieces.append(piece[lst_i:i]			)
																	lowercase_	    =   i
									if len(SCREAMING_SNAKE_CASE_			) > lst_i:
													new_pieces.append(piece[lst_i:]			)
					return new_pieces
	def 		_lowercase    (			self    :     Tuple			,				SCREAMING_SNAKE_CASE_    :     Any			)			->	Optional[Any]:
					lowercase_	    =   ''''''.join(SCREAMING_SNAKE_CASE_			).replace(SCREAMING_SNAKE_CASE_			,				''' '''			).strip()
					return out_string
	def 		_lowercase    (			self    :     Optional[Any]			,				SCREAMING_SNAKE_CASE_    :     Tuple			)			->	Any:
					lowercase_	    =   self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE_			)
					lowercase_	    =   ''''''.join(SCREAMING_SNAKE_CASE_			).replace(SCREAMING_SNAKE_CASE_			,				''' '''			).strip()
					return out_string
	def 		_lowercase    (			self    :     str			,				SCREAMING_SNAKE_CASE_    :     List[str]			)			->	List[str]:
					return self.vocab.get(SCREAMING_SNAKE_CASE_			,				self.vocab.get(self.unk_token			)			)
	def 		_lowercase    (			self    :     str			,				SCREAMING_SNAKE_CASE_    :     List[Any]			)			->	List[Any]:
					return self.reverse_vocab.get(SCREAMING_SNAKE_CASE_			,				self.unk_token			)
	def 		_lowercase    (			self    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     Any			,				SCREAMING_SNAKE_CASE_    :     str=None			)			->	List[str]:
					if token_ids_a is None:
									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
					lowercase_	    =   [self.cls_token_id]
					lowercase_	    =   [self.sep_token_id]
					return _cls + token_ids_a + _sep + _sep + token_ids_a + _sep
	def 		_lowercase    (			self    :     Dict			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]			,				SCREAMING_SNAKE_CASE_    :     List[str]=None			)			->	int:
					if offset_mapping_a is None:
									return [(0, 0)] + offset_mapping_a + [(0, 0)]

					return [(0, 0)] + offset_mapping_a + [(0, 0), (0, 0)] + offset_mapping_a + [(0, 0)]
	def 		_lowercase    (			self    :     Tuple			,				SCREAMING_SNAKE_CASE_    :     Any			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=None			,				SCREAMING_SNAKE_CASE_    :     Optional[int]=False			)			->	Any:

					if already_has_special_tokens:
									if token_ids_a is not None:
													raise ValueError(
													    '''You should not supply a second sequence if the provided sequence of '''
													    '''ids is already formatted with special tokens for the model.'''			)
									return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

					if token_ids_a is not None:
									return [1] + ([0] * len(SCREAMING_SNAKE_CASE_			)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE_			)) + [1]
					return [1] + ([0] * len(SCREAMING_SNAKE_CASE_			)) + [1]
	def 		_lowercase    (			self    :     Dict			,				SCREAMING_SNAKE_CASE_    :     List[int]			,				SCREAMING_SNAKE_CASE_    :     Optional[List[int]] = None			)			->	List[int]:
					# called when `add_special_tokens` is True, so align with `build_inputs_with_special_tokens` method
					if token_ids_a is None:
									# [CLS] X [SEP]
									return (len(SCREAMING_SNAKE_CASE_			) + 2) * [0]

					# [CLS] A [SEP] [SEP] B [SEP]
					return [0] * (len(SCREAMING_SNAKE_CASE_			) + 1) + [1] * (len(SCREAMING_SNAKE_CASE_			) + 3)
	def 		_lowercase    (			self    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     List[str]			)			->	Optional[int]:
					if "\u4e00" <= char <= "\u9fff":
									return True
					return False
	def 		_lowercase    (			self    :     List[Any]			,				SCREAMING_SNAKE_CASE_    :     Union[str, Any]			)			->	Tuple:
					if ("a" <= char <= "z") or ("A" <= char <= "Z"):
									return True
					return False
	def 		_lowercase    (			self    :     List[str]			,				SCREAMING_SNAKE_CASE_    :     int			)			->	List[Any]:
					if char in ",;:.?!~，；：。？！《》【】":
									return True
					return False
	def 		_lowercase    (			self    :     Optional[int]			,				SCREAMING_SNAKE_CASE_    :     Optional[Any]			)			->	Union[str, Any]:
					if char == " " or char == "\t" or char == "\n" or char == "\r":
									return True
					if len(SCREAMING_SNAKE_CASE_			) == 1:
									lowercase_	    =   unicodedata.category(SCREAMING_SNAKE_CASE_			)
									if cat == "Zs":
													return True
					return False
	def 		_lowercase    (			self    :     Any			,				SCREAMING_SNAKE_CASE_    :     Any			)			->	Tuple:
					lowercase_	    =   {}
					with io.open(SCREAMING_SNAKE_CASE_			,				'''r'''			,				encoding='''utf-8'''			) as f:
									for index, line in enumerate(SCREAMING_SNAKE_CASE_			):
													lowercase_	    =   line.rstrip('''\n'''			)
													lowercase_	    =   int(SCREAMING_SNAKE_CASE_			)

					return token_to_idx




	def 		_lowercase    (			self    :     Tuple			,				SCREAMING_SNAKE_CASE_    :     str			,				SCREAMING_SNAKE_CASE_    :     Optional[str] = None			)			->	Tuple[str]:
					lowercase_	    =   0
					if os.path.isdir(SCREAMING_SNAKE_CASE_			):
									lowercase_	    =   os.path.join(
									    SCREAMING_SNAKE_CASE_			,				(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)
					else:
									lowercase_	    =   (filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
					with open(SCREAMING_SNAKE_CASE_			,				'''w'''			,				encoding='''utf-8'''			) as writer:
									for token, token_index in sorted(self.vocab.items()			,				key=lambda SCREAMING_SNAKE_CASE_			: kv[1]			):
													if index != token_index:
																	logger.warning(
																	    f'''Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive.'''
																	    ''' Please check that the vocabulary is not corrupted!'''			)
																	lowercase_	    =   token_index
													writer.write(token + '''\n'''			)
													index += 1

					lowercase_	    =   os.path.join(SCREAMING_SNAKE_CASE_			,				'''sentencepiece.bpe.model'''			)
					with open(SCREAMING_SNAKE_CASE_			,				'''wb'''			) as fi:
									lowercase_	    =   self.sp_model.serialized_model_proto()
									fi.write(SCREAMING_SNAKE_CASE_			)

					return (vocab_file,)











'''simple docstring'''




import cmath
import math




def 						__lowerCamelCase			(	UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_					,				UpperCAmelCase_							)   ->complex:
	snake_case__	       =   math.radians(UpperCAmelCase_							)
	snake_case__	       =   math.radians(UpperCAmelCase_							)

	# Convert voltage and current to rectangular form
	snake_case__	       =   cmath.rect(UpperCAmelCase_					,				UpperCAmelCase_							)
	snake_case__	       =   cmath.rect(UpperCAmelCase_					,				UpperCAmelCase_							)

	# Calculate apparent power
	return voltage_rect * current_rect


if __name__ == "__main__":
			import doctest

			doctest.testmod()



