






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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


_UpperCamelCase			:	str								=logging.get_logger(__name__)

_UpperCamelCase			:	int								={
    'vocab_file': 'vocab.txt',
    'merges_file': 'bpe.codes',
}

_UpperCamelCase			:	int								={
    'vocab_file': {
        'vinai/phobert-base': 'https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt',
        'vinai/phobert-large': 'https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt',
    },
    'merges_file': {
        'vinai/phobert-base': 'https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes',
        'vinai/phobert-large': 'https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes',
    },
}

_UpperCamelCase			:	str								={
    'vinai/phobert-base': 256,
    'vinai/phobert-large': 256,
}



def  a__ (__lowercase							:List[str]   )		-> List[str]:
				_A	:				str   =      set()
				_A	:				Optional[int]   =      word[0]
				for char in word[1:]:
								pairs.add((prev_char, char)   )
								_A	:				Dict   =      char

				_A	:				Optional[Any]   =      set(__lowercase   )
				return pairs






class 						UpperCAmelCase__ (							__snake_case							):
		__snake_case      :       List[str]     =   VOCAB_FILES_NAMES
		__snake_case      :       Optional[Any]     =   PRETRAINED_VOCAB_FILES_MAP
		__snake_case      :       str     =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES







		def __init__(					self       ,A__       ,A__       ,A__="<s>"       ,A__="</s>"       ,A__="</s>"       ,A__="<s>"       ,A__="<unk>"       ,A__="<pad>"       ,A__="<mask>"       ,**A__       ,):
						super().__init__(
						    bos_token=A__       ,eos_token=A__       ,unk_token=A__       ,sep_token=A__       ,cls_token=A__       ,pad_token=A__       ,mask_token=A__       ,**A__       ,)

						_A	:				Tuple   =      vocab_file
						_A	:				Union[str, Any]   =      merges_file

						_A	:				List[Any]   =      {}
						_A	:				int   =      0
						_A	:				List[str]   =      1
						_A	:				Any   =      2
						_A	:				Tuple   =      3

						self.add_from_file(A__		)

						_A	:				List[Any]   =      {v: k for k, v in self.encoder.items()}

						with open(A__       ,encoding='''utf-8'''		) as merges_handle:
										_A	:				Dict   =      merges_handle.read().split('''\n'''		)[:-1]
						_A	:				Tuple   =      [tuple(merge.split()[:-1]		) for merge in merges]
						_A	:				Dict   =      dict(zip(A__       ,range(len(A__		)		)		)		)
						_A	:				Any   =      {}







		def  A__      (					self       ,A__       ,A__ = None		):

						if token_ids_a is None:
										return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
						_A	:				Union[str, Any]   =      [self.cls_token_id]
						_A	:				Union[str, Any]   =      [self.sep_token_id]
						return cls + token_ids_a + sep + sep + token_ids_a + sep







		def  A__      (					self       ,A__       ,A__ = None       ,A__ = False		):

						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       ,A__       ,A__ = None		):
						_A	:				Optional[int]   =      [self.sep_token_id]
						_A	:				Tuple   =      [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]







		@property
		def  A__      (					self		):
						return len(self.encoder		)







		def  A__      (					self		):
						return dict(self.encoder       ,**self.added_tokens_encoder		)







		def  A__      (					self       ,A__		):
						if token in self.cache:
										return self.cache[token]
						_A	:				Optional[Any]   =      tuple(A__		)
						_A	:				Optional[Any]   =      tuple(list(word[:-1]		) + [word[-1] + '''</w>''']		)
						_A	:				Union[str, Any]   =      get_pairs(A__		)

						if not pairs:
										return token

						while True:
										_A	:				List[Any]   =      min(A__       ,key=lambda A__		: self.bpe_ranks.get(A__       ,float('''inf'''		)		)		)
										if bigram not in self.bpe_ranks:
														break
										_A  ,				_A	:				Union[str, Any]   =      bigram
										_A	:				Union[str, Any]   =      []
										_A	:				str   =      0
										while i < len(A__		):
														try:
																		_A	:				Tuple   =      word.index(A__       ,A__		)
														except ValueError:
																		new_word.extend(word[i:]		)
																		break
														else:
																		new_word.extend(word[i:j]		)
																		_A	:				List[str]   =      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	:				List[Any]   =      tuple(A__		)
										_A	:				List[str]   =      new_word
										if len(A__		) == 1:
														break
										else:
														_A	:				Tuple   =      get_pairs(A__		)
						_A	:				Union[str, Any]   =      '''@@ '''.join(A__		)
						_A	:				Optional[Any]   =      word[:-4]
						_A	:				int   =      word
						return word







		def  A__      (					self       ,A__		):
						_A	:				List[str]   =      []

						_A	:				Optional[Any]   =      re.findall(r'''\S+\n?'''       ,A__		)

						for token in words:
										split_tokens.extend(list(self.bpe(A__		).split(''' '''		)		)		)
						return split_tokens







		def  A__      (					self       ,A__		):
						return self.encoder.get(A__       ,self.encoder.get(self.unk_token		)		)







		def  A__      (					self       ,A__		):
						return self.decoder.get(A__       ,self.unk_token		)







		def  A__      (					self       ,A__		):
						_A	:				Optional[int]   =      ''' '''.join(A__		).replace('''@@ '''       ,''''''		).strip()
						return out_string







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

						if os.path.abspath(self.vocab_file		) != os.path.abspath(A__		):
										copyfile(self.vocab_file       ,A__		)

						if os.path.abspath(self.merges_file		) != os.path.abspath(A__		):
										copyfile(self.merges_file       ,A__		)

						return out_vocab_file, out_merge_file







		def  A__      (					self       ,A__		):
						if isinstance(A__       ,A__		):
										try:
														with open(A__       ,'''r'''       ,encoding='''utf-8'''		) as fd:
																		self.add_from_file(A__		)
										except FileNotFoundError as fnfe:
														raise fnfe
										except UnicodeError:
														raise Exception(f"""Incorrect encoding detected in {f}, please rebuild the dataset"""		)
										return

						_A	:				List[str]   =      f.readlines()
						for lineTmp in lines:
										_A	:				Tuple   =      lineTmp.strip()
										_A	:				List[Any]   =      line.rfind(''' '''		)
										if idx == -1:
														raise ValueError('''Incorrect dictionary format, expected \'<token> <cnt>\''''		)
										_A	:				int   =      line[:idx]
										_A	:				Any   =      len(self.encoder		)











from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class 						UpperCAmelCase__ (							__snake_case							):
		__snake_case      :       Optional[Any]     =   ["image_processor", "tokenizer"]
		__snake_case      :       Tuple     =   "BridgeTowerImageProcessor"
		__snake_case      :       List[str]     =   ("RobertaTokenizer", "RobertaTokenizerFast")







		def __init__(					self       ,A__       ,A__		):
						super().__init__(A__       ,A__		)







		def __call__(					self       ,A__       ,A__ = None       ,A__ = True       ,A__ = False       ,A__ = None       ,A__ = None       ,A__ = 0       ,A__ = None       ,A__ = None       ,A__ = None       ,A__ = False       ,A__ = False       ,A__ = False       ,A__ = False       ,A__ = True       ,A__ = None       ,**A__       ,):
						_A	:				List[Any]   =      self.tokenizer(
						    text=A__       ,add_special_tokens=A__       ,padding=A__       ,truncation=A__       ,max_length=A__       ,stride=A__       ,pad_to_multiple_of=A__       ,return_token_type_ids=A__       ,return_attention_mask=A__       ,return_overflowing_tokens=A__       ,return_special_tokens_mask=A__       ,return_offsets_mapping=A__       ,return_length=A__       ,verbose=A__       ,return_tensors=A__       ,**A__       ,)
						# add pixel_values + pixel_mask
						_A	:				Optional[Any]   =      self.image_processor(
						    A__       ,return_tensors=A__       ,do_normalize=A__       ,do_center_crop=A__       ,**A__		)
						encoding.update(A__		)

						return encoding







		def  A__      (					self       ,*A__       ,**A__		):
						return self.tokenizer.batch_decode(*A__       ,**A__		)







		def  A__      (					self       ,*A__       ,**A__		):
						return self.tokenizer.decode(*A__       ,**A__		)







		@property
		def  A__      (					self		):
						_A	:				Union[str, Any]   =      self.tokenizer.model_input_names
						_A	:				str   =      self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names		)		)



