




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

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


__SCREAMING_SNAKE_CASE 						=logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE 						={
    """vocab_file""": """vocab.txt""",
    """merges_file""": """bpe.codes""",
}

__SCREAMING_SNAKE_CASE 						={
    """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""",
    },
}

__SCREAMING_SNAKE_CASE 						={
    """vinai/phobert-base""": 256,
    """vinai/phobert-large""": 256,
}

def 			a   (_lowerCAmelCase     ):
							SCREAMING_SNAKE_CASE_   	=    set()
							SCREAMING_SNAKE_CASE_   	=    word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)     )
														SCREAMING_SNAKE_CASE_   	=    char

							SCREAMING_SNAKE_CASE_   	=    set(_lowerCAmelCase     )
							return pairs






class  __magic_name__						(  __UpperCAmelCase):
				'''simple docstring'''







				SCREAMING_SNAKE_CASE__					:							int	      =					VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE__					:							List[str]	      =					PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE__					:							Union[str, Any]	      =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES


				def __init__(							self:   Tuple		,					_lowerCamelCase:   str		,					_lowerCamelCase:   Optional[int]		,					_lowerCamelCase:   Optional[Any]="<s>"		,					_lowerCamelCase:   Any="</s>"		,					_lowerCamelCase:   str="</s>"		,					_lowerCamelCase:   int="<s>"		,					_lowerCamelCase:   int="<unk>"		,					_lowerCamelCase:   Optional[Any]="<pad>"		,					_lowerCamelCase:   List[str]="<mask>"		,					**_lowerCamelCase:   int		,					):
											super().__init__(
											    bos_token=_lowerCamelCase		,					eos_token=_lowerCamelCase		,					unk_token=_lowerCamelCase		,					sep_token=_lowerCamelCase		,					cls_token=_lowerCamelCase		,					pad_token=_lowerCamelCase		,					mask_token=_lowerCamelCase		,					**_lowerCamelCase		,					)

											SCREAMING_SNAKE_CASE_   	=    vocab_file
											SCREAMING_SNAKE_CASE_   	=    merges_file

											SCREAMING_SNAKE_CASE_   	=    {}
											SCREAMING_SNAKE_CASE_   	=    0
											SCREAMING_SNAKE_CASE_   	=    1
											SCREAMING_SNAKE_CASE_   	=    2
											SCREAMING_SNAKE_CASE_   	=    3

											self.add_from_file(_lowerCamelCase		)

											SCREAMING_SNAKE_CASE_   	=    {v: k for k, v in self.encoder.items()}

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


				def     _A							(							self:   List[str]		,					_lowerCamelCase:   List[int]		,					_lowerCamelCase:   Optional[List[int]] = None		):

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


				def     _A							(							self:   Union[str, Any]		,					_lowerCamelCase:   List[int]		,					_lowerCamelCase:   Optional[List[int]] = None		,					_lowerCamelCase:   bool = False		):

											if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=_lowerCamelCase		,					token_ids_a=_lowerCamelCase		,					already_has_special_tokens=_lowerCamelCase		)

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


				def     _A							(							self:   List[Any]		,					_lowerCamelCase:   List[int]		,					_lowerCamelCase:   Optional[List[int]] = None		):
											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]


				@property
				def     _A							(							self:   Optional[Any]		):
											return len(self.encoder		)


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


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

											if not pairs:
																		return token

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

																									if word[i] == first and i < len(_lowerCamelCase		) - 1 and word[i + 1] == second:
																																new_word.append(first + second		)
																																i += 2
																									else:
																																new_word.append(word[i]		)
																																i += 1
																		SCREAMING_SNAKE_CASE_   	=    tuple(_lowerCamelCase		)
																		SCREAMING_SNAKE_CASE_   	=    new_word
																		if len(_lowerCamelCase		) == 1:
																									break
																		else:
																									SCREAMING_SNAKE_CASE_   	=    get_pairs(_lowerCamelCase		)
											SCREAMING_SNAKE_CASE_   	=    '''@@ '''.join(_lowerCamelCase		)
											SCREAMING_SNAKE_CASE_   	=    word[:-4]
											SCREAMING_SNAKE_CASE_   	=    word
											return word


				def     _A							(							self:   Union[str, Any]		,					_lowerCamelCase:   str		):
											SCREAMING_SNAKE_CASE_   	=    []

											SCREAMING_SNAKE_CASE_   	=    re.findall(R'''\S+\n?'''		,					_lowerCamelCase		)

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


				def     _A							(							self:   List[Any]		,					_lowerCamelCase:   Tuple		):
											return self.encoder.get(_lowerCamelCase		,					self.encoder.get(self.unk_token		)		)


				def     _A							(							self:   Optional[int]		,					_lowerCamelCase:   Optional[int]		):
											return self.decoder.get(_lowerCamelCase		,					self.unk_token		)


				def     _A							(							self:   Any		,					_lowerCamelCase:   List[Any]		):
											SCREAMING_SNAKE_CASE_   	=    ''' '''.join(_lowerCamelCase		).replace('''@@ '''		,					''''''		).strip()
											return out_string


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

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

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

											return out_vocab_file, out_merge_file





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

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








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE 						={
    """configuration_xlm_roberta_xl""": [
        """XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """XLMRobertaXLConfig""",
        """XLMRobertaXLOnnxConfig""",
    ],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__SCREAMING_SNAKE_CASE 						=[
			    """XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """XLMRobertaXLForCausalLM""",
			    """XLMRobertaXLForMaskedLM""",
			    """XLMRobertaXLForMultipleChoice""",
			    """XLMRobertaXLForQuestionAnswering""",
			    """XLMRobertaXLForSequenceClassification""",
			    """XLMRobertaXLForTokenClassification""",
			    """XLMRobertaXLModel""",
			    """XLMRobertaXLPreTrainedModel""",
			]

if TYPE_CHECKING:
			from .configuration_xlm_roberta_xl import (
			    XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    XLMRobertaXLConfig,
			    XLMRobertaXLOnnxConfig,
			)

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_xlm_roberta_xl import (
						    XLM_ROBERTA_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
						    XLMRobertaXLForCausalLM,
						    XLMRobertaXLForMaskedLM,
						    XLMRobertaXLForMultipleChoice,
						    XLMRobertaXLForQuestionAnswering,
						    XLMRobertaXLForSequenceClassification,
						    XLMRobertaXLForTokenClassification,
						    XLMRobertaXLModel,
						    XLMRobertaXLPreTrainedModel,
						)

else:
			import sys

			__SCREAMING_SNAKE_CASE 						=_LazyModule(__name__, globals()["""__file__"""], _import_structure)


