


'''simple docstring'''


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

import sentencepiece as spm

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


UpperCAmelCase_						:  Tuple				  =						logging.get_logger(__name__)

UpperCAmelCase_						:  List[Any]				  =						{'''vocab_file''': '''spiece.model'''}

UpperCAmelCase_						:  Optional[int]				  =						{
    '''vocab_file''': {
        '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model''',
        '''google/bigbird-roberta-large''': (
            '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model'''
        ),
        '''google/bigbird-base-trivia-itc''': (
            '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model'''
        ),
    }
}

UpperCAmelCase_						:  Any				  =						{
    '''google/bigbird-roberta-base''': 4096,
    '''google/bigbird-roberta-large''': 4096,
    '''google/bigbird-base-trivia-itc''': 4096,
}





class        lowercase__    (		_snake_case   ):





							'''simple docstring'''


							A_				: str       =    VOCAB_FILES_NAMES
							A_				: int       =    PRETRAINED_VOCAB_FILES_MAP
							A_				: Union[str, Any]       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							A_				: int       =    ['input_ids', 'attention_mask']
							A_				: List[int]       =    []






							def __init__(       self       ,   __snake_case       ,   __snake_case="<unk>"       ,   __snake_case="<s>"       ,   __snake_case="</s>"       ,   __snake_case="<pad>"       ,   __snake_case="[SEP]"       ,   __snake_case="[MASK]"       ,   __snake_case="[CLS]"       ,   __snake_case = None       ,   **__snake_case       ,   ):
											_SCREAMING_SNAKE_CASE					:			Tuple							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else bos_token
											_SCREAMING_SNAKE_CASE					:			str							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else eos_token
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else unk_token
											_SCREAMING_SNAKE_CASE					:			Dict							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else pad_token
											_SCREAMING_SNAKE_CASE					:			Tuple							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else cls_token
											_SCREAMING_SNAKE_CASE					:			Tuple							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else sep_token

											# Mask token behave like a normal word, i.e. include the space before it
											_SCREAMING_SNAKE_CASE					:			Any							= AddedToken(_SCREAMING_SNAKE_CASE       ,   lstrip=_SCREAMING_SNAKE_CASE       ,   rstrip=_SCREAMING_SNAKE_CASE    ) if isinstance(_SCREAMING_SNAKE_CASE       ,   _SCREAMING_SNAKE_CASE    ) else mask_token

											_SCREAMING_SNAKE_CASE					:			str							= {} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    bos_token=_SCREAMING_SNAKE_CASE       ,   eos_token=_SCREAMING_SNAKE_CASE       ,   unk_token=_SCREAMING_SNAKE_CASE       ,   pad_token=_SCREAMING_SNAKE_CASE       ,   sep_token=_SCREAMING_SNAKE_CASE       ,   mask_token=_SCREAMING_SNAKE_CASE       ,   cls_token=_SCREAMING_SNAKE_CASE       ,   sp_model_kwargs=self.sp_model_kwargs       ,   **_SCREAMING_SNAKE_CASE       ,   )

											_SCREAMING_SNAKE_CASE					:			int							= vocab_file

											_SCREAMING_SNAKE_CASE					:			str							= spm.SentencePieceProcessor(**self.sp_model_kwargs    )
											self.sp_model.Load(_SCREAMING_SNAKE_CASE    )






							@property
							def UpperCAmelCase_      (       self    ):
											return self.sp_model.get_piece_size()






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE					:			Dict							= {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 __getstate__(       self    ):
											_SCREAMING_SNAKE_CASE					:			Dict							= self.__dict__.copy()
											_SCREAMING_SNAKE_CASE					:			List[str]							= None
											return state






							def __setstate__(       self       ,   __snake_case    ):
											_SCREAMING_SNAKE_CASE					:			List[Any]							= d

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

											_SCREAMING_SNAKE_CASE					:			str							= spm.SentencePieceProcessor(**self.sp_model_kwargs    )
											self.sp_model.Load(self.vocab_file    )






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											return self.sp_model.encode(_SCREAMING_SNAKE_CASE       ,   out_type=_SCREAMING_SNAKE_CASE    )






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											return self.sp_model.piece_to_id(_SCREAMING_SNAKE_CASE    )






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											_SCREAMING_SNAKE_CASE					:			List[Any]							= self.sp_model.IdToPiece(_SCREAMING_SNAKE_CASE    )
											return token






							def UpperCAmelCase_      (       self       ,   __snake_case    ):
											_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= []
											_SCREAMING_SNAKE_CASE					:			int							= """"""
											_SCREAMING_SNAKE_CASE					:			Tuple							= 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
																			_SCREAMING_SNAKE_CASE					:			Optional[int]							= True
																			_SCREAMING_SNAKE_CASE					:			List[str]							= []
															else:
																			current_sub_tokens.append(_SCREAMING_SNAKE_CASE    )
																			_SCREAMING_SNAKE_CASE					:			str							= False
											out_string += self.sp_model.decode(_SCREAMING_SNAKE_CASE    )
											return out_string.strip()






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = False       ,   __snake_case = None       ,   __snake_case = True       ,   **__snake_case       ,   ):
											_SCREAMING_SNAKE_CASE					:			Dict							= kwargs.pop("""use_source_tokenizer"""       ,   _SCREAMING_SNAKE_CASE    )

											_SCREAMING_SNAKE_CASE					:			Optional[int]							= self.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE       ,   skip_special_tokens=_SCREAMING_SNAKE_CASE    )

											# To avoid mixing byte-level and unicode for byte-level BPT
											# we need to build string separately for added tokens and byte-level tokens
											# cf. https://github.com/huggingface/transformers/issues/1133
											_SCREAMING_SNAKE_CASE					:			Tuple							= []
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= []
											for token in filtered_tokens:
															if skip_special_tokens and token in self.all_special_ids:
																			continue
															if token in self.added_tokens_encoder:
																			if current_sub_text:
																							sub_texts.append(self.convert_tokens_to_string(_SCREAMING_SNAKE_CASE    )    )
																							_SCREAMING_SNAKE_CASE					:			Dict							= []
																			sub_texts.append(_SCREAMING_SNAKE_CASE    )
															else:
																			current_sub_text.append(_SCREAMING_SNAKE_CASE    )
											if current_sub_text:
															sub_texts.append(self.convert_tokens_to_string(_SCREAMING_SNAKE_CASE    )    )

											# Mimic the behavior of the Rust tokenizer:
											# No space before [MASK] and [SEP]
											if spaces_between_special_tokens:
															_SCREAMING_SNAKE_CASE					:			List[str]							= re.sub(r""" (\[(MASK|SEP)\])"""       ,   r"""\1"""       ,   """ """.join(_SCREAMING_SNAKE_CASE    )    )
											else:
															_SCREAMING_SNAKE_CASE					:			Optional[int]							= """""".join(_SCREAMING_SNAKE_CASE    )

											_SCREAMING_SNAKE_CASE					:			Any							= (
											    clean_up_tokenization_spaces
											    if clean_up_tokenization_spaces is not None
											    else self.clean_up_tokenization_spaces
											)
											if clean_up_tokenization_spaces:
															_SCREAMING_SNAKE_CASE					:			int							= self.clean_up_tokenization(_SCREAMING_SNAKE_CASE    )
															return clean_text
											else:
															return text






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = None    ):





											if not os.path.isdir(_SCREAMING_SNAKE_CASE    ):
															logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""    )
															return
											_SCREAMING_SNAKE_CASE					:			List[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:
																			_SCREAMING_SNAKE_CASE					:			Any							= self.sp_model.serialized_model_proto()
																			fi.write(_SCREAMING_SNAKE_CASE    )

											return (out_vocab_file,)






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = None    ):





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






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = None       ,   __snake_case = 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    )

											if token_ids_a is None:
															return [1] + ([0] * len(_SCREAMING_SNAKE_CASE    )) + [1]
											return [1] + ([0] * len(_SCREAMING_SNAKE_CASE    )) + [1] + ([0] * len(_SCREAMING_SNAKE_CASE    )) + [1]






							def UpperCAmelCase_      (       self       ,   __snake_case       ,   __snake_case = None    ):
											_SCREAMING_SNAKE_CASE					:			int							= [self.sep_token_id]
											_SCREAMING_SNAKE_CASE					:			Optional[Any]							= [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]








from typing import Any

def 			lowerCAmelCase__					(     a__:						list     ,    a__:						list     ,    a__:						dict     ,    a__:						dict     ,    a__:						dict     ,    )    ->						list:


							'''simple docstring'''





							_validation(
							    a__     ,    a__     ,    a__     ,    a__     ,    a__     ,    )
							# Creates data structures and fill initial step
							_UpperCAmelCase											=     {}
							_UpperCAmelCase											=     {}
							for state in states_space:
														_UpperCAmelCase											=     observations_space[0]
														_UpperCAmelCase											=     (
														    initial_probabilities[state] * emission_probabilities[state][observation]
														)
														_UpperCAmelCase											=     None

							# Fills the data structure with the probabilities of
							# different transitions and pointers to previous states
							for o in range(1     ,    len(a__			)			):
														_UpperCAmelCase											=     observations_space[o]
														_UpperCAmelCase											=     observations_space[o - 1]
														for state in states_space:
																					# Calculates the argmax for probability function
																					_UpperCAmelCase											=     ''
																					_UpperCAmelCase											=     -1
																					for k_state in states_space:
																												_UpperCAmelCase											=     (
																												    probabilities[(k_state, prior_observation)]
																												    * transition_probabilities[k_state][state]
																												    * emission_probabilities[state][observation]
																												)
																												if probability > max_probability:
																																			_UpperCAmelCase											=     probability
																																			_UpperCAmelCase											=     k_state

            # Update probabilities and pointers dicts
																					_UpperCAmelCase											=     (
																					    probabilities[(arg_max, prior_observation)]
																					    * transition_probabilities[arg_max][state]
																					    * emission_probabilities[state][observation]
																					)

																					_UpperCAmelCase											=     arg_max

    # The final observation
							_UpperCAmelCase											=     observations_space[len(a__			) - 1]

							# argmax for given final observation
							_UpperCAmelCase											=     ''
							_UpperCAmelCase											=     -1
							for k_state in states_space:
														_UpperCAmelCase											=     probabilities[(k_state, final_observation)]
														if probability > max_probability:
																					_UpperCAmelCase											=     probability
																					_UpperCAmelCase											=     k_state
							_UpperCAmelCase											=     arg_max

							# Process pointers backwards
							_UpperCAmelCase											=     last_state
							_UpperCAmelCase											=     []
							for o in range(len(a__			) - 1     ,    -1     ,    -1			):
														result.append(a__			)
														_UpperCAmelCase											=     pointers[previous, observations_space[o]]
							result.reverse()

							return result

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    )    ->						None:


							'''simple docstring'''





							_validate_not_empty(
							    a__     ,    a__     ,    a__     ,    a__     ,    a__     ,    )
							_validate_lists(a__     ,    a__			)
							_validate_dicts(
							    a__     ,    a__     ,    a__			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    )    ->						None:


							'''simple docstring'''





							if not all(
							    [
							        observations_space,
							        states_space,
							        initial_probabilities,
							        transition_probabilities,
							        emission_probabilities,
							    ]			):
														raise ValueError('There\'s an empty parameter'			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any			)    ->						None:


							'''simple docstring'''





							_validate_list(a__     ,    'observations_space'			)
							_validate_list(a__     ,    'states_space'			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str			)    ->						None:


							'''simple docstring'''





							if not isinstance(_object     ,    a__			):
														_UpperCAmelCase											=     F'''{var_name} must be a list'''
														raise ValueError(a__			)
							else:
														for x in _object:
																					if not isinstance(a__     ,    a__			):
																												_UpperCAmelCase											=     F'''{var_name} must be a list of strings'''
																												raise ValueError(a__			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						Any     ,    a__:						Any     ,    )    ->						None:


							'''simple docstring'''





							_validate_dict(a__     ,    'initial_probabilities'     ,    a__			)
							_validate_nested_dict(a__     ,    'transition_probabilities'			)
							_validate_nested_dict(a__     ,    'emission_probabilities'			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str			)    ->						None:


							'''simple docstring'''





							_validate_dict(_object     ,    a__     ,    a__			)
							for x in _object.values():
														_validate_dict(a__     ,    a__     ,    a__     ,    a__			)

def 			lowerCAmelCase__					(     a__:						Any     ,    a__:						str     ,    a__:						type     ,    a__:						bool = False			)    ->						None:


							'''simple docstring'''





							if not isinstance(_object     ,    a__			):
														_UpperCAmelCase											=     F'''{var_name} must be a dict'''
														raise ValueError(a__			)
							if not all(isinstance(a__     ,    a__			) for x in _object			):
														_UpperCAmelCase											=     F'''{var_name} all keys must be strings'''
														raise ValueError(a__			)
							if not all(isinstance(a__     ,    a__			) for x in _object.values()			):
														_UpperCAmelCase											=     'nested dictionary ' if nested else ''
														_UpperCAmelCase											=     F'''{var_name} {nested_text}all values must be {value_type.__name__}'''
														raise ValueError(a__			)


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

		testmod()
