






import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


__A          = logging.get_logger(__name__)


__A          = {'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all MVP models at https://huggingface.co/models?filter=mvp
__A          = {
    'vocab_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/vocab.json',
    },
    'added_tokens.json': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/added_tokens.json',
    },
    'merges_file': {
        'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/merges.txt',
    },
}

__A          = {
    'RUCAIBox/mvp': 1024,
}




@lru_cache()
def    __A    (   ):

					'''simple docstring'''







					_A									=       (
					    list(range(ord('''!'''       )    ,	ord('''~'''       ) + 1       )       ) + list(range(ord('''¡'''       )    ,	ord('''¬'''       ) + 1       )       ) + list(range(ord('''®'''       )    ,	ord('''ÿ'''       ) + 1       )       )
					)
					_A									=       bs[:]
					_A									=       0
					for b in range(2**8       ):
										if b not in bs:
															bs.append(_lowercase       )
															cs.append(2**8 + n       )
															n += 1
					_A									=       [chr(_lowercase       ) for n in cs]
					return dict(zip(_lowercase    ,	_lowercase       )       )




def    __A    (   _lowercase       ):

					'''simple docstring'''







					_A									=       set()
					_A									=       word[0]
					for char in word[1:]:
										pairs.add((prev_char, char)       )
										_A									=       char
					return pairs





class   SCREAMING_SNAKE_CASE (       snake_case    ):





							"""simple docstring"""

							A_       =    VOCAB_FILES_NAMES
							A_       =    PRETRAINED_VOCAB_FILES_MAP
							A_       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							A_       =    ["input_ids", "attention_mask"]

							def __init__(     self:      Any						,   __A:      str						,   __A:      int						,   __A:      Union[str, Any]="replace"						,   __A:      Any="<s>"						,   __A:      Union[str, Any]="</s>"						,   __A:      List[str]="</s>"						,   __A:      str="<s>"						,   __A:      Optional[Any]="<unk>"						,   __A:      Tuple="<pad>"						,   __A:      Optional[Any]="<mask>"						,   __A:      Tuple=False						,   **__A:      Optional[Any]						,   )			-> Optional[Any]:
												_A									=       AddedToken(__A						,   lstrip=__A						,   rstrip=__A      ) if isinstance(__A						,   __A      ) else bos_token
												_A									=       AddedToken(__A						,   lstrip=__A						,   rstrip=__A      ) if isinstance(__A						,   __A      ) else eos_token
												_A									=       AddedToken(__A						,   lstrip=__A						,   rstrip=__A      ) if isinstance(__A						,   __A      ) else sep_token
												_A									=       AddedToken(__A						,   lstrip=__A						,   rstrip=__A      ) if isinstance(__A						,   __A      ) else cls_token
												_A									=       AddedToken(__A						,   lstrip=__A						,   rstrip=__A      ) if isinstance(__A						,   __A      ) else unk_token
												_A									=       AddedToken(__A						,   lstrip=__A						,   rstrip=__A      ) if isinstance(__A						,   __A      ) else pad_token

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

												super().__init__(
												    errors=__A						,   bos_token=__A						,   eos_token=__A						,   unk_token=__A						,   sep_token=__A						,   cls_token=__A						,   pad_token=__A						,   mask_token=__A						,   add_prefix_space=__A						,   **__A						,   )
												with open(__A						,   encoding='''utf-8'''      ) as vocab_handle:
																	_A									=       json.load(__A      )
												_A									=       {v: k for k, v in self.encoder.items()}
												_A									=       errors  # how to handle errors in decoding
												_A									=       bytes_to_unicode()
												_A									=       {v: k for k, v in self.byte_encoder.items()}
												with open(__A						,   encoding='''utf-8'''      ) as merges_handle:
																	_A									=       merges_handle.read().split('''\n'''      )[1:-1]
												_A									=       [tuple(merge.split()      ) for merge in bpe_merges]
												_A									=       dict(zip(__A						,   range(len(__A      )      )      )      )
												_A									=       {}
												_A									=       add_prefix_space

												# Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
												_A									=       re.compile(R'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+'''      )

							@property
							def 					__A       (     self:      List[Any]      )			-> Dict:
												return len(self.encoder      )

							def 					__A       (     self:      str      )			-> int:
												return dict(self.encoder						,   **self.added_tokens_encoder      )

							def 					__A       (     self:      Any						,   __A:      Optional[Any]      )			-> Dict:
												if token in self.cache:
																	return self.cache[token]
												_A									=       tuple(__A      )
												_A									=       get_pairs(__A      )

												if not pairs:
																	return token

												while True:
																	_A									=       min(__A						,   key=lambda __A      : self.bpe_ranks.get(__A						,   float('''inf'''      )      )      )
																	if bigram not in self.bpe_ranks:
																						break
																	_A							,_A									=       bigram
																	_A									=       []
																	_A									=       0
																	while i < len(__A      ):
																						try:
																											_A									=       word.index(__A						,   __A      )
																						except ValueError:
																											new_word.extend(word[i:]      )
																											break
																						else:
																											new_word.extend(word[i:j]      )
																											_A									=       j

																						if word[i] == first and i < len(__A      ) - 1 and word[i + 1] == second:
																											new_word.append(first + second      )
																											i += 2
																						else:
																											new_word.append(word[i]      )
																											i += 1
																	_A									=       tuple(__A      )
																	_A									=       new_word
																	if len(__A      ) == 1:
																						break
																	else:
																						_A									=       get_pairs(__A      )
												_A									=       ''' '''.join(__A      )
												_A									=       word
												return word

							def 					__A       (     self:      Dict						,   __A:      Optional[Any]      )			-> Tuple:
												_A									=       []
												for token in re.findall(self.pat						,   __A      ):
																	_A									=       ''''''.join(
																	    self.byte_encoder[b] for b in token.encode('''utf-8'''      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
																	bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__A      ).split(''' '''      )      )
												return bpe_tokens

							def 					__A       (     self:      Optional[Any]						,   __A:      Tuple      )			-> int:
												return self.encoder.get(__A						,   self.encoder.get(self.unk_token      )      )

							def 					__A       (     self:      Optional[Any]						,   __A:      str      )			-> List[str]:
												return self.decoder.get(__A      )

							def 					__A       (     self:      Tuple						,   __A:      str      )			-> List[Any]:
												_A									=       ''''''.join(__A      )
												_A									=       bytearray([self.byte_decoder[c] for c in text]      ).decode('''utf-8'''						,   errors=self.errors      )
												return text

							def 					__A       (     self:      Any						,   __A:      str						,   __A:      Optional[str] = None      )			-> Tuple[str]:
												if not os.path.isdir(__A      ):
																	logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""      )
																	return
												_A									=       os.path.join(
												    __A						,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
												_A									=       os.path.join(
												    __A						,   (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']      )

												with open(__A						,   '''w'''						,   encoding='''utf-8'''      ) as f:
																	f.write(json.dumps(self.encoder						,   indent=2						,   sort_keys=__A						,   ensure_ascii=__A      ) + '''\n'''      )

												_A									=       0
												with open(__A						,   '''w'''						,   encoding='''utf-8'''      ) as writer:
																	writer.write('''#version: 0.2\n'''      )
																	for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,   key=lambda __A      : kv[1]      ):
																						if index != token_index:
																											logger.warning(
																											    f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
																											    ''' Please check that the tokenizer is not corrupted!'''      )
																											_A									=       token_index
																						writer.write(''' '''.join(__A      ) + '''\n'''      )
																						index += 1

												return vocab_file, merge_file

							def 					__A       (     self:      Tuple						,   __A:      List[int]						,   __A:      Optional[List[int]] = None      )			-> List[int]:
												if token_ids_a is None:
																	return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
												_A									=       [self.cls_token_id]
												_A									=       [self.sep_token_id]
												return cls + token_ids_a + sep + sep + token_ids_a + sep

							def 					__A       (     self:      List[str]						,   __A:      List[int]						,   __A:      Optional[List[int]] = None						,   __A:      bool = False      )			-> List[int]:
												if already_has_special_tokens:
																	return super().get_special_tokens_mask(
																	    token_ids_a=__A						,   token_ids_a=__A						,   already_has_special_tokens=__A      )

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

							def 					__A       (     self:      Any						,   __A:      List[int]						,   __A:      Optional[List[int]] = None      )			-> List[int]:
												_A									=       [self.sep_token_id]
												_A									=       [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]



							def 					__A       (     self:      List[Any]						,   __A:      int						,   __A:      Any=False						,   **__A:      str      )			-> Optional[int]:
												_A									=       kwargs.pop('''add_prefix_space'''						,   self.add_prefix_space      )
												if (is_split_into_words or add_prefix_space) and (len(__A      ) > 0 and not text[0].isspace()):
																	_A									=       ''' ''' + text
												return (text, kwargs)











from ...configuration_utils import PretrainedConfig
from ...utils import logging


__A          = logging.get_logger(__name__)

__A          = {
    'uw-madison/nystromformer-512': 'https://huggingface.co/uw-madison/nystromformer-512/resolve/main/config.json',
    # See all Nystromformer models at https://huggingface.co/models?filter=nystromformer
}





class   SCREAMING_SNAKE_CASE (       snake_case    ):





							"""simple docstring"""

							A_       =    "nystromformer"

							def __init__(     self:      List[str]						,   __A:      Dict=3_00_00						,   __A:      int=7_68						,   __A:      int=12						,   __A:      Union[str, Any]=12						,   __A:      List[str]=30_72						,   __A:      Tuple="gelu_new"						,   __A:      Optional[Any]=0.1						,   __A:      Union[str, Any]=0.1						,   __A:      int=5_10						,   __A:      List[Any]=2						,   __A:      List[Any]=64						,   __A:      Optional[Any]=64						,   __A:      str=65						,   __A:      List[str]=False						,   __A:      Tuple=0.02						,   __A:      Dict=1e-5						,   __A:      int=1						,   __A:      str=0						,   __A:      int=2						,   **__A:      Union[str, Any]						,   )			-> int:
												_A									=       vocab_size
												_A									=       max_position_embeddings
												_A									=       hidden_size
												_A									=       num_hidden_layers
												_A									=       num_attention_heads
												_A									=       intermediate_size
												_A									=       hidden_act
												_A									=       hidden_dropout_prob
												_A									=       attention_probs_dropout_prob
												_A									=       initializer_range
												_A									=       type_vocab_size
												_A									=       segment_means_seq_len
												_A									=       num_landmarks
												_A									=       conv_kernel_size
												_A									=       inv_coeff_init_option
												_A									=       layer_norm_eps
												super().__init__(pad_token_id=__A						,   bos_token_id=__A						,   eos_token_id=__A						,   **__A      )



