




from random import randint, random


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A     ,	_A = False     ,	_A = False     ,	_A = 5     ,	):







	'''simple docstring'''





	snake_case_		    =     [[-1] * number_of_cells]  # Create a highway without any car
	snake_case_		    =     0
	snake_case_		    =     max(_A     ,	0							)
	while i < number_of_cells:
		snake_case_		    =     (
		    randint(0     ,	_A							) if random_speed else initial_speed
		)  # Place the cars
		i += (
		    randint(1     ,	max_speed * 2							) if random_frequency else frequency
		)  # Arbitrary number, may need tuning
	return highway


def 						lowerCamelCase__    (		_A     ,	_A							):







	'''simple docstring'''





	snake_case_		    =     0
	snake_case_		    =     highway_now[car_index + 1 :]
	for cell in range(len(_A							)							):  # May need a better name for this
		if cells[cell] != -1:  # If the cell is not empty then
			return distance  # we have the distance we wanted
		distance += 1
	# Here if the car is near the end of the highway
	return distance + get_distance(_A     ,	-1							)


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A							):







	'''simple docstring'''





	snake_case_		    =     len(_A							)
	# Beforce calculations, the highway is empty
	snake_case_		    =     [-1] * number_of_cells

	for car_index in range(_A							):
		if highway_now[car_index] != -1:
			# Add 1 to the current speed of the car and cap the speed
			snake_case_		    =     min(highway_now[car_index] + 1     ,	_A							)
			# Number of empty cell before the next car
			snake_case_		    =     get_distance(_A     ,	_A							) - 1
			# We can't have the car causing an accident
			snake_case_		    =     min(next_highway[car_index]     ,	_A							)
			if random() < probability:
				# Randomly, a driver will slow down
				snake_case_		    =     max(next_highway[car_index] - 1     ,	0							)
	return next_highway


def 						lowerCamelCase__    (		_A     ,	_A     ,	_A     ,	_A							):







	'''simple docstring'''





	snake_case_		    =     len(highway[0]							)

	for i in range(_A							):
		snake_case_		    =     update(highway[i]     ,	_A     ,	_A							)
		snake_case_		    =     [-1] * number_of_cells

		for car_index in range(_A							):
			snake_case_		    =     next_speeds_calculated[car_index]
			if speed != -1:
				# Change the position based on the speed (with % to create the loop)
				snake_case_		    =     (car_index + speed) % number_of_cells
				# Commit the change of position
				snake_case_		    =     speed
		highway.append(_A							)

	return highway


if __name__ == "__main__":
		import doctest

		doctest.testmod()






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


lowercase__				:     Optional[Any] 		=						logging.get_logger(__name__)

lowercase__				:     List[str] 		=						"▁"

lowercase__				:     Union[str, Any] 		=						{"vocab_file": "vocab.txt", "sentencepiece_model_ckpt": "sentencepiece.bpe.model"}

lowercase__				:     List[Any] 		=						{
    "sentencepiece_model_file": "sentencepiece.bpe.model",
    "vocab_file": "vocab.txt",
}

lowercase__				:     Tuple 		=						{
    "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",
    },
}

lowercase__				:     Optional[int] 		=						{
    "ernie-m-base": 514,
    "ernie-m-large": 514,
}

lowercase__				:     Dict 		=						{
    "ernie-m-base": {"do_lower_case": False},
    "ernie-m-large": {"do_lower_case": False},
}
class 		UpperCAmelCase   (				UpperCAmelCase__			):







						'''simple docstring'''





						lowerCAmelCase_     		=   ["input_ids"]

						lowerCAmelCase_     		=   VOCAB_FILES_NAMES
						lowerCAmelCase_     		=   PRETRAINED_INIT_CONFIGURATION
						lowerCAmelCase_     		=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						lowerCAmelCase_     		=   PRETRAINED_VOCAB_FILES_MAP
						lowerCAmelCase_     		=   RESOURCE_FILES_NAMES






						def __init__(						self							:     Dict       ,	__lowercase							:     List[Any]       ,	__lowercase							:     Tuple=None       ,	__lowercase							:     List[str]=False       ,	__lowercase							:     List[str]="utf8"       ,	__lowercase							:     Union[str, Any]="[UNK]"       ,	__lowercase							:     List[str]="[SEP]"       ,	__lowercase							:     Optional[Any]="[PAD]"       ,	__lowercase							:     Any="[CLS]"       ,	__lowercase							:     Any="[MASK]"       ,	__lowercase							:     Optional[Dict[str, Any]] = None       ,	**__lowercase							:     Tuple       ,	):






							"""simple docstring"""






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

							# to mimic paddlenlp.transformers.ernie_m.tokenizer.ErnieMTokenizer functioning
							if vocab_file is not None:
								snake_case_		    =     self.load_vocab(filepath=__lowercase						)
							else:
								snake_case_		    =     {self.sp_model.id_to_piece(__lowercase						): id for id in range(self.sp_model.get_piece_size()						)}
							snake_case_		    =     {v: k for k, v in self.vocab.items()}






						def        snake_case__						(						self							:     Dict       ,	__lowercase							:     Optional[int]						):






							"""simple docstring"""






							if text is None:
								return None

							snake_case_		    =     self.tokenize(__lowercase						)
							snake_case_    ,      snake_case_		    =     "", []

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

							snake_case_    ,      snake_case_    ,      snake_case_		    =     normalized_text, [], 0

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

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

								token_mapping.append((char_mapping[start], char_mapping[end - 1] + 1)						)
								snake_case_		    =     end
							return token_mapping






						@property
						def        snake_case__						(						self							:     Optional[int]						):






							"""simple docstring"""






							return len(self.vocab						)






						def        snake_case__						(						self							:     Any						):






							"""simple docstring"""






							return dict(self.vocab       ,	**self.added_tokens_encoder						)






						def __getstate__(						self							:     List[str]						):






							"""simple docstring"""






							snake_case_		    =     self.__dict__.copy()
							snake_case_		    =     None
							return state






						def __setstate__(						self							:     str       ,	__lowercase							:     str						):






							"""simple docstring"""






							snake_case_		    =     d

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

							snake_case_		    =     spm.SentencePieceProcessor(**self.sp_model_kwargs						)
							self.sp_model.Load(self.sentencepiece_model_ckpt						)






						def        snake_case__						(						self							:     int       ,	__lowercase							:     Optional[Any]						):






							"""simple docstring"""






							return "".join((self.SP_CHAR_MAPPING.get(__lowercase       ,	__lowercase						) for c in text)						)






						def        snake_case__						(						self							:     List[str]       ,	__lowercase							:     int       ,	__lowercase							:     Any=False       ,	__lowercase							:     str=64       ,	__lowercase							:     Optional[Any]=0.1						):






							"""simple docstring"""






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

							if not enable_sampling:
								snake_case_		    =     self.sp_model.EncodeAsPieces(__lowercase						)
							else:
								snake_case_		    =     self.sp_model.SampleEncodeAsPieces(__lowercase       ,	__lowercase       ,	__lowercase						)
							snake_case_		    =     []
							for pi, piece in enumerate(__lowercase						):
								if piece == SPIECE_UNDERLINE:
									if not pieces[pi + 1].startswith(__lowercase						) and pi != 0:
										new_pieces.append(__lowercase						)
										continue
									else:
										continue
								snake_case_		    =     0
								for i, chunk in enumerate(__lowercase						):
									if chunk == SPIECE_UNDERLINE:
										continue
									if self.is_ch_char(__lowercase						) or self.is_punct(__lowercase						):
										if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
											new_pieces.append(piece[lst_i:i]						)
										new_pieces.append(__lowercase						)
										snake_case_		    =     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]						)
										snake_case_		    =     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]						)
										snake_case_		    =     i
								if len(__lowercase						) > lst_i:
									new_pieces.append(piece[lst_i:]						)
							return new_pieces






						def        snake_case__						(						self							:     List[Any]       ,	__lowercase							:     Dict						):






							"""simple docstring"""






							snake_case_		    =     "".join(__lowercase						).replace(__lowercase       ,	" "						).strip()
							return out_string






						def        snake_case__						(						self							:     int       ,	__lowercase							:     int						):






							"""simple docstring"""






							snake_case_		    =     self.convert_ids_to_tokens(__lowercase						)
							snake_case_		    =     "".join(__lowercase						).replace(__lowercase       ,	" "						).strip()
							return out_string






						def        snake_case__						(						self							:     Dict       ,	__lowercase							:     Any						):






							"""simple docstring"""






							return self.vocab.get(__lowercase       ,	self.vocab.get(self.unk_token						)						)






						def        snake_case__						(						self							:     str       ,	__lowercase							:     List[Any]						):






							"""simple docstring"""






							return self.reverse_vocab.get(__lowercase       ,	self.unk_token						)






						def        snake_case__						(						self							:     Optional[Any]       ,	__lowercase							:     Union[str, Any]       ,	__lowercase							:     int=None						):






							"""simple docstring"""






							if token_ids_a is None:
								return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							snake_case_		    =     [self.cls_token_id]
							snake_case_		    =     [self.sep_token_id]
							return _cls + token_ids_a + _sep + _sep + token_ids_a + _sep






						def        snake_case__						(						self							:     str       ,	__lowercase							:     List[str]       ,	__lowercase							:     Any=None						):






							"""simple docstring"""






							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        snake_case__						(						self							:     Dict       ,	__lowercase							:     List[Any]       ,	__lowercase							:     List[Any]=None       ,	__lowercase							:     Dict=False						):






							"""simple docstring"""






							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(__lowercase						)) + [1, 1] + ([0] * len(__lowercase						)) + [1]
							return [1] + ([0] * len(__lowercase						)) + [1]






						def        snake_case__						(						self							:     Optional[int]       ,	__lowercase							:     List[int]       ,	__lowercase							:     Optional[List[int]] = None						):






							"""simple docstring"""






							if token_ids_a is None:
								# [CLS] X [SEP]
								return (len(__lowercase						) + 2) * [0]

							# [CLS] A [SEP] [SEP] B [SEP]
							return [0] * (len(__lowercase						) + 1) + [1] * (len(__lowercase						) + 3)






						def        snake_case__						(						self							:     Any       ,	__lowercase							:     Union[str, Any]						):






							"""simple docstring"""






							if "\u4e00" <= char <= "\u9fff":
								return True
							return False






						def        snake_case__						(						self							:     List[str]       ,	__lowercase							:     Any						):






							"""simple docstring"""






							if ("a" <= char <= "z") or ("A" <= char <= "Z"):
								return True
							return False






						def        snake_case__						(						self							:     int       ,	__lowercase							:     Dict						):






							"""simple docstring"""






							if char in ",;:.?!~，；：。？！《》【】":
								return True
							return False






						def        snake_case__						(						self							:     Union[str, Any]       ,	__lowercase							:     Union[str, Any]						):






							"""simple docstring"""






							if char == " " or char == "\t" or char == "\n" or char == "\r":
								return True
							if len(__lowercase						) == 1:
								snake_case_		    =     unicodedata.category(__lowercase						)
								if cat == "Zs":
									return True
							return False






						def        snake_case__						(						self							:     Dict       ,	__lowercase							:     Optional[Any]						):






							"""simple docstring"""






							snake_case_		    =     {}
							with io.open(__lowercase       ,	"r"       ,	encoding="utf-8"						) as f:
								for index, line in enumerate(__lowercase						):
									snake_case_		    =     line.rstrip("\n"						)
									snake_case_		    =     int(__lowercase						)

							return token_to_idx






						def        snake_case__						(						self							:     Dict       ,	__lowercase							:     str       ,	__lowercase							:     Optional[str] = None						):






							"""simple docstring"""






							snake_case_		    =     0
							if os.path.isdir(__lowercase						):
								snake_case_		    =     os.path.join(
								    __lowercase       ,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
							else:
								snake_case_		    =     (filename_prefix + "-" if filename_prefix else "") + save_directory
							with open(__lowercase       ,	"w"       ,	encoding="utf-8"						) as writer:
								for token, token_index in sorted(self.vocab.items()       ,	key=lambda __lowercase						: 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!"						)
										snake_case_		    =     token_index
									writer.write(token + "\n"						)
									index += 1

							snake_case_		    =     os.path.join(__lowercase       ,	"sentencepiece.bpe.model"						)
							with open(__lowercase       ,	"wb"						) as fi:
								snake_case_		    =     self.sp_model.serialized_model_proto()
								fi.write(__lowercase						)

							return (vocab_file,)
