

"""simple docstring"""





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

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


__UpperCamelCase						:   Optional[Any]							   =	logging.get_logger(__name__)

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

__UpperCamelCase						:   str							   =	{
    '''vocab_file''': {
        '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/vocab.json''',
    },
    '''merges_file''': {'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/merges.txt'''},
}

__UpperCamelCase						:   Optional[Any]							   =	{
    '''microsoft/biogpt''': 1_0_2_4,
}

def 						__SCREAMING_SNAKE_CASE						(   A_				):
	lowerCAmelCase__			:		str						       =			set()
	lowerCAmelCase__			:		Optional[Any]						       =			word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)				)
		lowerCAmelCase__			:		str						       =			char
	return pairs







class        SCREAMING_SNAKE_CASE      (	a_ ):






					"""simple docstring"""



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







					def __init__( self    :       Tuple     ,lowercase_    :       List[str]     ,lowercase_    :       List[str]     ,lowercase_    :       List[str]="<unk>"     ,lowercase_    :       Dict="<s>"     ,lowercase_    :       Any="</s>"     ,lowercase_    :       Union[str, Any]="</s>"     ,lowercase_    :       Any="<pad>"     ,**lowercase_    :       Union[str, Any]     ,):
						super().__init__(
						    bos_token=lowercase_     ,eos_token=lowercase_     ,sep_token=lowercase_     ,unk_token=lowercase_     ,pad_token=lowercase_     ,**lowercase_     ,)

						try:
							import sacremoses
						except ImportError:
							raise ImportError(
							    '''You need to install sacremoses to use BioGptTokenizer. '''
							    '''See https://pypi.org/project/sacremoses/ for installation.'''	)

						lowerCAmelCase__			:		str						       =			'''en'''
						lowerCAmelCase__			:		Union[str, Any]						       =			sacremoses
						# cache of sm.MosesTokenizer instance
						lowerCAmelCase__			:		Tuple						       =			{}
						lowerCAmelCase__			:		Optional[Any]						       =			{}
						with open(lowercase_     ,encoding='''utf-8'''	) as vocab_handle:
							lowerCAmelCase__			:		Union[str, Any]						       =			json.load(lowercase_	)
						lowerCAmelCase__			:		List[str]						       =			{v: k for k, v in self.encoder.items()}
						with open(lowercase_     ,encoding='''utf-8'''	) as merges_handle:
							lowerCAmelCase__			:		Union[str, Any]						       =			merges_handle.read().split('''\n'''	)[:-1]
						lowerCAmelCase__			:		Optional[Any]						       =			[tuple(merge.split()[:2]	) for merge in merges]
						lowerCAmelCase__			:		Union[str, Any]						       =			dict(zip(lowercase_     ,range(len(lowercase_	)	)	)	)
						lowerCAmelCase__			:		Dict						       =			{}







					@property
					def  __lowerCAmelCase				( self    :       Optional[int]	):
						return len(self.encoder	)







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







					def  __lowerCAmelCase				( self    :       Dict     ,lowercase_    :       Optional[Any]     ,lowercase_    :       Optional[Any]	):
						if lang not in self.cache_moses_tokenizer:
							lowerCAmelCase__			:		Tuple						       =			self.sm.MosesTokenizer(lang=lowercase_	)
							lowerCAmelCase__			:		int						       =			moses_tokenizer
						return self.cache_moses_tokenizer[lang].tokenize(
						    lowercase_     ,aggressive_dash_splits=lowercase_     ,return_str=lowercase_     ,escape=lowercase_	)







					def  __lowerCAmelCase				( self    :       Dict     ,lowercase_    :       Dict     ,lowercase_    :       Optional[Any]	):
						if lang not in self.cache_moses_detokenizer:
							lowerCAmelCase__			:		List[Any]						       =			self.sm.MosesDetokenizer(lang=lowercase_	)
							lowerCAmelCase__			:		List[str]						       =			moses_detokenizer
						return self.cache_moses_detokenizer[lang].detokenize(lowercase_	)







					def  __lowerCAmelCase				( self    :       Tuple     ,lowercase_    :       int	):
						lowerCAmelCase__			:		Tuple						       =			tuple(token[:-1]	) + (token[-1] + '''</w>''',)
						if token in self.cache:
							return self.cache[token]
						lowerCAmelCase__			:		List[Any]						       =			get_pairs(lowercase_	)

						if not pairs:
							return token + "</w>"

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

								if word[i] == first and i < len(lowercase_	) - 1 and word[i + 1] == second:
									new_word.append(first + second	)
									i += 2
								else:
									new_word.append(word[i]	)
									i += 1
							lowerCAmelCase__			:		List[Any]						       =			tuple(lowercase_	)
							lowerCAmelCase__			:		Any						       =			new_word
							if len(lowercase_	) == 1:
								break
							else:
								lowerCAmelCase__			:		str						       =			get_pairs(lowercase_	)
						lowerCAmelCase__			:		Union[str, Any]						       =			''' '''.join(lowercase_	)
						if word == "\n  </w>":
							lowerCAmelCase__			:		Tuple						       =			'''\n</w>'''
						lowerCAmelCase__			:		Union[str, Any]						       =			word
						return word







					def  __lowerCAmelCase				( self    :       Optional[Any]     ,lowercase_    :       Optional[Any]     ,lowercase_    :       Any=False	):
						if bypass_tokenizer:
							lowerCAmelCase__			:		int						       =			text.split()
						else:
							lowerCAmelCase__			:		Union[str, Any]						       =			self.moses_tokenize(lowercase_     ,self.lang	)

						lowerCAmelCase__			:		Optional[Any]						       =			[]
						for token in text:
							if token:
								split_tokens.extend(list(self.bpe(lowercase_	).split(''' '''	)	)	)

						return split_tokens







					def  __lowerCAmelCase				( self    :       List[str]     ,lowercase_    :       int	):
						return self.encoder.get(lowercase_     ,self.encoder.get(self.unk_token	)	)







					def  __lowerCAmelCase				( self    :       str     ,lowercase_    :       Tuple	):
						return self.decoder.get(lowercase_     ,self.unk_token	)







					def  __lowerCAmelCase				( self    :       Dict     ,lowercase_    :       int	):
						lowerCAmelCase__			:		Union[str, Any]						       =			[t.replace(''' '''     ,''''''	).replace('''</w>'''     ,''' '''	) for t in tokens]
						lowerCAmelCase__			:		List[str]						       =			''''''.join(lowercase_	).split()
						# detokenize
						lowerCAmelCase__			:		int						       =			self.moses_detokenize(lowercase_     ,self.lang	)
						return text







					def  __lowerCAmelCase				( self    :       List[str]     ,lowercase_    :       List[int]     ,lowercase_    :       Optional[List[int]] = None	):
						if token_ids_a is None:
							return [self.sep_token_id] + token_ids_a
						lowerCAmelCase__			:		int						       =			[self.sep_token_id]
						return sep + token_ids_a + sep + token_ids_a







					def  __lowerCAmelCase				( self    :       List[Any]     ,lowercase_    :       List[int]     ,lowercase_    :       Optional[List[int]] = None     ,lowercase_    :       bool = False	):
						if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowercase_     ,token_ids_a=lowercase_     ,already_has_special_tokens=lowercase_	)
						# no bos used in fairseq
						if token_ids_a is not None:
							return [1] + ([0] * len(lowercase_	)) + [1] + ([0] * len(lowercase_	))
						return [1] + ([0] * len(lowercase_	))







					def  __lowerCAmelCase				( self    :       Optional[int]     ,lowercase_    :       List[int]     ,lowercase_    :       Optional[List[int]] = None	):
						lowerCAmelCase__			:		int						       =			[self.sep_token_id]

						# no bos used in fairseq
						if token_ids_a is None:
							return len(token_ids_a + sep	) * [0]
						return len(token_ids_a + sep	) * [0] + len(token_ids_a + sep	) * [1]







					def  __lowerCAmelCase				( self    :       List[Any]     ,lowercase_    :       str     ,lowercase_    :       Optional[str] = None	):
						if not os.path.isdir(lowercase_	):
							logger.error(F'Vocabulary path ({save_directory}) should be a directory'	)
							return
						lowerCAmelCase__			:		Any						       =			os.path.join(
						    lowercase_     ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']	)
						lowerCAmelCase__			:		Dict						       =			os.path.join(
						    lowercase_     ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']	)

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

						lowerCAmelCase__			:		int						       =			0
						with open(lowercase_     ,'''w'''     ,encoding='''utf-8'''	) as writer:
							for bpe_tokens, token_index in sorted(self.bpe_ranks.items()     ,key=lambda lowercase_	: 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!'''	)
									lowerCAmelCase__			:		List[Any]						       =			token_index
								writer.write(''' '''.join(lowercase_	) + '''\n'''	)
								index += 1

						return vocab_file, merge_file







					def __getstate__( self    :       Optional[int]	):
						lowerCAmelCase__			:		Any						       =			self.__dict__.copy()
						lowerCAmelCase__			:		Dict						       =			None
						return state







					def __setstate__( self    :       Dict     ,lowercase_    :       int	):
						lowerCAmelCase__			:		Optional[int]						       =			d

						try:
							import sacremoses
						except ImportError:
							raise ImportError(
							    '''You need to install sacremoses to use XLMTokenizer. '''
							    '''See https://pypi.org/project/sacremoses/ for installation.'''	)

						lowerCAmelCase__			:		int						       =			sacremoses







"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


__UpperCamelCase						:   Union[str, Any]							   =	{
    '''configuration_layoutlm''': ['''LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMConfig''', '''LayoutLMOnnxConfig'''],
    '''tokenization_layoutlm''': ['''LayoutLMTokenizer'''],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase						:   Union[str, Any]							   =	['''LayoutLMTokenizerFast''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase						:   Dict							   =	[
							    '''LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''LayoutLMForMaskedLM''',
							    '''LayoutLMForSequenceClassification''',
							    '''LayoutLMForTokenClassification''',
							    '''LayoutLMForQuestionAnswering''',
							    '''LayoutLMModel''',
							    '''LayoutLMPreTrainedModel''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__UpperCamelCase						:   str							   =	[
							    '''TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFLayoutLMForMaskedLM''',
							    '''TFLayoutLMForSequenceClassification''',
							    '''TFLayoutLMForTokenClassification''',
							    '''TFLayoutLMForQuestionAnswering''',
							    '''TFLayoutLMMainLayer''',
							    '''TFLayoutLMModel''',
							    '''TFLayoutLMPreTrainedModel''',
							]


if TYPE_CHECKING:
							from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
							from .tokenization_layoutlm import LayoutLMTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_layoutlm import (
														    LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    LayoutLMForMaskedLM,
														    LayoutLMForQuestionAnswering,
														    LayoutLMForSequenceClassification,
														    LayoutLMForTokenClassification,
														    LayoutLMModel,
														    LayoutLMPreTrainedModel,
														)
							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_layoutlm import (
														    TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFLayoutLMForMaskedLM,
														    TFLayoutLMForQuestionAnswering,
														    TFLayoutLMForSequenceClassification,
														    TFLayoutLMForTokenClassification,
														    TFLayoutLMMainLayer,
														    TFLayoutLMModel,
														    TFLayoutLMPreTrainedModel,
														)

else:
							import sys

							__UpperCamelCase						:   int							   =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




