

'''simple docstring'''

from collections.abc import Generator
from math import sin




def 							_UpperCamelCase				(   lowerCAmelCase__:					bytes   )      -> bytes:
							if len(lowerCAmelCase__   ) != 32:
														raise ValueError('Input must be of length 32'   )

							SCREAMING_SNAKE_CASE_				=				B''
							for i in [3, 2, 1, 0]:
														little_endian += string_aa[8 * i : 8 * i + 8]
							return little_endian




def 							_UpperCamelCase				(   lowerCAmelCase__:					int   )      -> bytes:
							if i < 0:
														raise ValueError('Input must be non-negative'   )

							SCREAMING_SNAKE_CASE_				=				format(lowerCAmelCase__		,'08x'   )[-8:]
							SCREAMING_SNAKE_CASE_				=				B''
							for i in [3, 2, 1, 0]:
														little_endian_hex += hex_rep[2 * i : 2 * i + 2].encode('utf-8'   )
							return little_endian_hex




def 							_UpperCamelCase				(   lowerCAmelCase__:					bytes   )      -> bytes:
							SCREAMING_SNAKE_CASE_				=				B''
							for char in message:
														bit_string += format(lowerCAmelCase__		,'08b'   ).encode('utf-8'   )
							SCREAMING_SNAKE_CASE_				=				format(len(lowerCAmelCase__   )		,'064b'   ).encode('utf-8'   )

							# Pad bit_string to a multiple of 512 chars
							bit_string += b"1"
							while len(lowerCAmelCase__   ) % 512 != 448:
														bit_string += b"0"
							bit_string += to_little_endian(start_len[32:]   ) + to_little_endian(start_len[:32]   )

							return bit_string




def 							_UpperCamelCase				(   lowerCAmelCase__:					bytes   )      -> Generator[list[int], None, None]:
							if len(lowerCAmelCase__   ) % 512 != 0:
														raise ValueError('Input must have length that\'s a multiple of 512'   )

							for pos in range(0		,len(lowerCAmelCase__   )		,512   ):
														SCREAMING_SNAKE_CASE_				=				bit_string[pos : pos + 512]
														SCREAMING_SNAKE_CASE_				=				[]
														for i in range(0		,512		,32   ):
																					block_words.append(int(to_little_endian(block[i : i + 32]   )		,2   )   )
														yield block_words




def 							_UpperCamelCase				(   lowerCAmelCase__:					int   )      -> int:
							if i < 0:
														raise ValueError('Input must be non-negative'   )

							SCREAMING_SNAKE_CASE_				=				format(lowerCAmelCase__		,'032b'   )
							SCREAMING_SNAKE_CASE_				=				''
							for c in i_str:
														new_str += "1" if c == "0" else "0"
							return int(lowerCAmelCase__		,2   )




def 							_UpperCamelCase				(   lowerCAmelCase__:					int		,lowerCAmelCase__:					int   )      -> int:
							return (a + b) % 2**32




def 							_UpperCamelCase				(   lowerCAmelCase__:					int		,lowerCAmelCase__:					int   )      -> int:
							if i < 0:
														raise ValueError('Input must be non-negative'   )
							if shift < 0:
														raise ValueError('Shift must be non-negative'   )
							return ((i << shift) ^ (i >> (32 - shift))) % 2**32




def 							_UpperCamelCase				(   lowerCAmelCase__:					bytes   )      -> bytes:
							SCREAMING_SNAKE_CASE_				=				preprocess(lowerCAmelCase__   )

							SCREAMING_SNAKE_CASE_				=				[int(2**32 * abs(sin(i + 1   )   )   ) for i in range(64   )]

							# Starting states
							SCREAMING_SNAKE_CASE_				=				0x67452301
							SCREAMING_SNAKE_CASE_				=				0xefcdab89
							SCREAMING_SNAKE_CASE_				=				0x98badcfe
							SCREAMING_SNAKE_CASE_				=				0x10325476

							SCREAMING_SNAKE_CASE_				=				[
							    7,
							    12,
							    17,
							    22,
							    7,
							    12,
							    17,
							    22,
							    7,
							    12,
							    17,
							    22,
							    7,
							    12,
							    17,
							    22,
							    5,
							    9,
							    14,
							    20,
							    5,
							    9,
							    14,
							    20,
							    5,
							    9,
							    14,
							    20,
							    5,
							    9,
							    14,
							    20,
							    4,
							    11,
							    16,
							    23,
							    4,
							    11,
							    16,
							    23,
							    4,
							    11,
							    16,
							    23,
							    4,
							    11,
							    16,
							    23,
							    6,
							    10,
							    15,
							    21,
							    6,
							    10,
							    15,
							    21,
							    6,
							    10,
							    15,
							    21,
							    6,
							    10,
							    15,
							    21,
							]

							# Process bit string in chunks, each with 16 32-char words
							for block_words in get_block_words(lowerCAmelCase__   ):
														SCREAMING_SNAKE_CASE_				=				aa
														SCREAMING_SNAKE_CASE_				=				ba
														SCREAMING_SNAKE_CASE_				=				ca
														SCREAMING_SNAKE_CASE_				=				da

														# Hash current chunk
														for i in range(64   ):
																					if i <= 15:
																												# f = (b & c) | (not_32(b) & d)     # Alternate definition for f
																												SCREAMING_SNAKE_CASE_				=				d ^ (b & (c ^ d))
																												SCREAMING_SNAKE_CASE_				=				i
																					elif i <= 31:
																												# f = (d & b) | (not_32(d) & c)     # Alternate definition for f
																												SCREAMING_SNAKE_CASE_				=				c ^ (d & (b ^ c))
																												SCREAMING_SNAKE_CASE_				=				(5 * i + 1) % 16
																					elif i <= 47:
																												SCREAMING_SNAKE_CASE_				=				b ^ c ^ d
																												SCREAMING_SNAKE_CASE_				=				(3 * i + 5) % 16
																					else:
																												SCREAMING_SNAKE_CASE_				=				c ^ (b | not_aa(lowerCAmelCase__   ))
																												SCREAMING_SNAKE_CASE_				=				(7 * i) % 16
																					SCREAMING_SNAKE_CASE_				=				(f + a + added_consts[i] + block_words[g]) % 2**32
																					SCREAMING_SNAKE_CASE_				=				d
																					SCREAMING_SNAKE_CASE_				=				c
																					SCREAMING_SNAKE_CASE_				=				b
																					SCREAMING_SNAKE_CASE_				=				sum_aa(lowerCAmelCase__		,left_rotate_aa(lowerCAmelCase__		,shift_amounts[i]   )   )

														# Add hashed chunk to running total
														SCREAMING_SNAKE_CASE_				=				sum_aa(lowerCAmelCase__		,lowerCAmelCase__   )
														SCREAMING_SNAKE_CASE_				=				sum_aa(lowerCAmelCase__		,lowerCAmelCase__   )
														SCREAMING_SNAKE_CASE_				=				sum_aa(lowerCAmelCase__		,lowerCAmelCase__   )
														SCREAMING_SNAKE_CASE_				=				sum_aa(lowerCAmelCase__		,lowerCAmelCase__   )

							SCREAMING_SNAKE_CASE_				=				reformat_hex(lowerCAmelCase__   ) + reformat_hex(lowerCAmelCase__   ) + reformat_hex(lowerCAmelCase__   ) + reformat_hex(lowerCAmelCase__   )
							return digest


if __name__ == "__main__":
							import doctest

							doctest.testmod()








'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


SCREAMING_SNAKE_CASE							:				int     	=			logging.get_logger(__name__)


SCREAMING_SNAKE_CASE							:				Dict     	=			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE							:				str     	=			{
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json",
    },
}

SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			{
    "facebook/bart-base": 1024,
    "facebook/bart-large": 1024,
    "facebook/bart-large-mnli": 1024,
    "facebook/bart-large-cnn": 1024,
    "facebook/bart-large-xsum": 1024,
    "yjernite/bart_eli5": 1024,
}






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     VOCAB_FILES_NAMES
				_a    	=     PRETRAINED_VOCAB_FILES_MAP
				_a    	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_a    	=     ["""input_ids""", """attention_mask"""]
				_a    	=     BartTokenizer



				def __init__(    self,     _lowercase=None,     _lowercase=None,     _lowercase=None,     _lowercase="replace",     _lowercase="<s>",     _lowercase="</s>",     _lowercase="</s>",     _lowercase="<s>",     _lowercase="<unk>",     _lowercase="<pad>",     _lowercase="<mask>",     _lowercase=False,     _lowercase=True,     **_lowercase,     )     ->							Dict:
											super().__init__(
											    _lowercase,     _lowercase,     tokenizer_file=_lowercase,     errors=_lowercase,     bos_token=_lowercase,     eos_token=_lowercase,     sep_token=_lowercase,     cls_token=_lowercase,     unk_token=_lowercase,     pad_token=_lowercase,     mask_token=_lowercase,     add_prefix_space=_lowercase,     trim_offsets=_lowercase,     **_lowercase,     )

											SCREAMING_SNAKE_CASE_				=				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
											if pre_tok_state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																		SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     pre_tok_state.pop('type'       )       )
																		SCREAMING_SNAKE_CASE_				=				add_prefix_space
																		SCREAMING_SNAKE_CASE_				=				pre_tok_class(**_lowercase       )

											SCREAMING_SNAKE_CASE_				=				add_prefix_space

											# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
											SCREAMING_SNAKE_CASE_				=				'post_processor'
											SCREAMING_SNAKE_CASE_				=				getattr(self.backend_tokenizer,     _lowercase,     _lowercase       )
											if tokenizer_component_instance:
																		SCREAMING_SNAKE_CASE_				=				json.loads(tokenizer_component_instance.__getstate__()       )

																		# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																		if "sep" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['sep']       )
																		if "cls" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['cls']       )

																		SCREAMING_SNAKE_CASE_				=				False

																		if state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																									SCREAMING_SNAKE_CASE_				=				add_prefix_space
																									SCREAMING_SNAKE_CASE_				=				True

																		if state.get('trim_offsets',     _lowercase       ) != trim_offsets:
																									SCREAMING_SNAKE_CASE_				=				trim_offsets
																									SCREAMING_SNAKE_CASE_				=				True

																		if changes_to_apply:
																									SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     state.pop('type'       )       )
																									SCREAMING_SNAKE_CASE_				=				component_class(**_lowercase       )
																									setattr(self.backend_tokenizer,     _lowercase,     _lowercase       )



				@property
				def   a__					(    self       )     ->							str:
											if self._mask_token is None:
																		if self.verbose:
																									logger.error('Using mask_token, but it is not set yet.'       )
																		return None
											return str(self._mask_token       )



				@mask_token.setter
				def   a__					(    self,     _lowercase       )     ->							Dict:
											SCREAMING_SNAKE_CASE_				=				AddedToken(_lowercase,     lstrip=_lowercase,     rstrip=_lowercase       ) if isinstance(_lowercase,     _lowercase       ) else value
											SCREAMING_SNAKE_CASE_				=				value



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

											return super()._batch_encode_plus(*_lowercase,     **_lowercase       )



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

											return super()._encode_plus(*_lowercase,     **_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							Tuple[str]:
											SCREAMING_SNAKE_CASE_				=				self._tokenizer.model.save(_lowercase,     name=_lowercase       )
											return tuple(_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase=None       )     ->							Optional[Any]:
											SCREAMING_SNAKE_CASE_				=				[self.bos_token_id] + token_ids_a + [self.eos_token_id]
											if token_ids_a is None:
																		return output

											return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							List[int]:
											SCREAMING_SNAKE_CASE_				=				[self.sep_token_id]
											SCREAMING_SNAKE_CASE_				=				[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 + sep + token_ids_a + sep       ) * [0]





