






"""simple docstring"""



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

from transformers.utils import is_jieba_available, requires_backends


if is_jieba_available():
						import jieba

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


A__	:    Union[str, Any]			 = logging.get_logger(__name__)

A__	:    Optional[Any]			 = {'vocab_file': 'vocab.txt'}

A__	:    Optional[int]			 = {
    'vocab_file': {
        'openbmb/cpm-ant-10b': 'https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt',
    },
}

A__	:    Tuple			 = {
    'openbmb/cpm-ant-10b': 1_024,
}

def 			_snake_case    (					lowerCamelCase__     :   Dict  )    ->     List[Any]:
							lowerCamelCase_	:							str									=collections.OrderedDict()
							with open(lowerCamelCase__    ,						"r"    ,						encoding="utf-8"  ) as reader:
														lowerCamelCase_	:							Any									=reader.readlines()
							for index, token in enumerate(lowerCamelCase__  ):
														lowerCamelCase_	:							int									=token.rstrip("\n"  )
														lowerCamelCase_	:							Any									=index
							return vocab







class        lowercase__      (							snake_case__       ):


			def __init__(				self					:  Any       ,	snake_case__					:  Dict       ,	snake_case__					:  Dict="<unk>"       ,	snake_case__					:  str=200 ):
										lowerCamelCase_	:							Dict									=vocab
										lowerCamelCase_	:							Optional[Any]									=unk_token
										lowerCamelCase_	:							Union[str, Any]									=max_input_chars_per_word


			def      UpperCAmelCase__						(				self					:  Union[str, Any]       ,	snake_case__					:  Optional[Any] ):
										lowerCamelCase_	:							List[Any]									=list(__UpperCAmelCase )
										if len(__UpperCAmelCase ) > self.max_input_chars_per_word:
																	return [self.unk_token]

										lowerCamelCase_	:							Optional[Any]									=0
										lowerCamelCase_	:							str									=[]
										while start < len(__UpperCAmelCase ):
																	lowerCamelCase_	:							List[str]									=len(__UpperCAmelCase )
																	lowerCamelCase_	:							str									=None
																	while start < end:
																								lowerCamelCase_	:							Optional[int]									="".join(chars[start:end] )
																								if substr in self.vocab:
																															lowerCamelCase_	:							List[Any]									=substr
																															break
																								end -= 1
																	if cur_substr is None:
																								sub_tokens.append(self.unk_token )
																								start += 1
																	else:
																								sub_tokens.append(__UpperCAmelCase )
																								lowerCamelCase_	:							str									=end

										return sub_tokens







class        lowercase__      (							snake_case__       ):
			_UpperCAmelCase		:Optional[int]             =			VOCAB_FILES_NAMES
			_UpperCAmelCase		:Dict             =			PRETRAINED_VOCAB_FILES_MAP
			_UpperCAmelCase		:Any             =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			_UpperCAmelCase		:List[str]             =			["input_ids", "attention_mask"]
			_UpperCAmelCase		:Optional[int]             =			False


			def __init__(				self					:  Tuple       ,	snake_case__					:  Union[str, Any]       ,	snake_case__					:  Optional[int]="<d>"       ,	snake_case__					:  int="</d>"       ,	snake_case__					:  Tuple="<s>"       ,	snake_case__					:  str="</s>"       ,	snake_case__					:  Dict="<pad>"       ,	snake_case__					:  int="<unk>"       ,	snake_case__					:  List[str]="</n>"       ,	snake_case__					:  Optional[int]="</_>"       ,	snake_case__					:  List[str]="left"       ,	**snake_case__					:  Optional[Any]       ,	):
										requires_backends(self       ,	["jieba"] )
										super().__init__(
										    bod_token=__UpperCAmelCase       ,	eod_token=__UpperCAmelCase       ,	bos_token=__UpperCAmelCase       ,	eos_token=__UpperCAmelCase       ,	pad_token=__UpperCAmelCase       ,	unk_token=__UpperCAmelCase       ,	line_token=__UpperCAmelCase       ,	space_token=__UpperCAmelCase       ,	padding_side=__UpperCAmelCase       ,	**__UpperCAmelCase       ,	)
										lowerCamelCase_	:							Optional[int]									=bod_token
										lowerCamelCase_	:							Dict									=eod_token
										lowerCamelCase_	:							str									=load_vocab(__UpperCAmelCase )
										lowerCamelCase_	:							Union[str, Any]									=self.encoder[space_token]
										lowerCamelCase_	:							List[Any]									=self.encoder[line_token]

										del self.encoder[space_token]
										del self.encoder[line_token]

										lowerCamelCase_	:							Optional[int]									=collections.OrderedDict(sorted(self.encoder.items()       ,	key=lambda snake_case__ : x[1] ) )
										lowerCamelCase_	:							Tuple									={v: k for k, v in self.encoder.items()}

										lowerCamelCase_	:							Any									=WordpieceTokenizer(vocab=self.encoder       ,	unk_token=self.unk_token )


			@property
			def      UpperCAmelCase__						(				self					:  Any ):
										return self.encoder[self.bod_token]


			@property
			def      UpperCAmelCase__						(				self					:  Union[str, Any] ):
										return self.encoder[self.eod_token]


			@property
			def      UpperCAmelCase__						(				self					:  Any ):
										return self.encoder["\n"]


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


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


			def      UpperCAmelCase__						(				self					:  Optional[int]       ,	snake_case__					:  Optional[int] ):
										lowerCamelCase_	:							Any									=[]
										for x in jieba.cut(__UpperCAmelCase       ,	cut_all=__UpperCAmelCase ):
																	output_tokens.extend(self.wordpiece_tokenizer.tokenize(__UpperCAmelCase ) )
										return output_tokens


			def      UpperCAmelCase__						(				self					:  Any       ,	snake_case__					:  List[Any]       ,	**snake_case__					:  Optional[Any] ):
										lowerCamelCase_	:							Tuple									=[i for i in token_ids if i >= 0]
										lowerCamelCase_	:							str									=[
										    x for x in token_ids if x != self.pad_token_id and x != self.eos_token_id and x != self.bos_token_id
										]
										return super()._decode(__UpperCAmelCase       ,	**__UpperCAmelCase )


			def      UpperCAmelCase__						(				self					:  Union[str, Any]       ,	snake_case__					:  List[str] ):
										return token in self.encoder


			def      UpperCAmelCase__						(				self					:  Union[str, Any]       ,	snake_case__					:  List[str] ):
										return "".join(__UpperCAmelCase )


			def      UpperCAmelCase__						(				self					:  Union[str, Any]       ,	snake_case__					:  int ):
										return self.encoder.get(__UpperCAmelCase       ,	self.encoder.get(self.unk_token ) )


			def      UpperCAmelCase__						(				self					:  List[str]       ,	snake_case__					:  Optional[int] ):
										return self.decoder.get(__UpperCAmelCase       ,	self.unk_token )


			def      UpperCAmelCase__						(				self					:  str       ,	snake_case__					:  str       ,	snake_case__					:  Optional[str] = None ):


										if os.path.isdir(__UpperCAmelCase ):
																	lowerCamelCase_	:							List[Any]									=os.path.join(
																	    __UpperCAmelCase       ,	(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
										else:
																	lowerCamelCase_	:							Tuple									=(filename_prefix + "-" if filename_prefix else "") + save_directory
										lowerCamelCase_	:							str									=0
										if " " in self.encoder:
																	lowerCamelCase_	:							int									=self.encoder[" "]
																	del self.encoder[" "]
										if "\n" in self.encoder:
																	lowerCamelCase_	:							str									=self.encoder["\n"]
																	del self.encoder["\n"]
										lowerCamelCase_	:							List[str]									=collections.OrderedDict(sorted(self.encoder.items()       ,	key=lambda snake_case__ : x[1] ) )
										with open(__UpperCAmelCase       ,	"w"       ,	encoding="utf-8" ) as writer:
																	for token, token_index in self.encoder.items():
																								if index != token_index:
																															logger.warning(
																															    F"""Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."""
																															    " Please check that the vocabulary is not corrupted!" )
																															lowerCamelCase_	:							Any									=token_index
																								writer.write(token + "\n" )
																								index += 1
										return (vocab_file,)


			def      UpperCAmelCase__						(				self					:  Optional[Any]       ,	snake_case__					:  List[int]       ,	snake_case__					:  List[int] = None ):


										if token_ids_a is None:
																	return [self.bos_token_id] + token_ids_a
										return [self.bos_token_id] + token_ids_a + [self.bos_token_id] + token_ids_a


			def      UpperCAmelCase__						(				self					:  Dict       ,	snake_case__					:  List[int]       ,	snake_case__					:  Optional[List[int]] = None       ,	snake_case__					:  bool = False ):


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

										if token_ids_a is not None:
																	return [1] + ([0] * len(__UpperCAmelCase )) + [1] + ([0] * len(__UpperCAmelCase ))
										return [1] + ([0] * len(__UpperCAmelCase ))












"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


A__	:    List[Any]			 = {
    'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__	:    List[str]			 = [
						    'LILT_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'LiltForQuestionAnswering',
						    'LiltForSequenceClassification',
						    'LiltForTokenClassification',
						    'LiltModel',
						    'LiltPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_lilt import LILT_PRETRAINED_CONFIG_ARCHIVE_MAP, LiltConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_lilt import (
												    LILT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    LiltForQuestionAnswering,
												    LiltForSequenceClassification,
												    LiltForTokenClassification,
												    LiltModel,
												    LiltPreTrainedModel,
												)

else:
						import sys

						A__	:    Optional[Any]			 = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



