



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


UpperCAmelCase__       =	logging.get_logger(__name__)

UpperCAmelCase__       =	{"vocab_file": "vocab.txt"}

UpperCAmelCase__       =	{
    "vocab_file": {
        "openbmb/cpm-ant-10b": "https://huggingface.co/openbmb/cpm-ant-10b/blob/main/vocab.txt",
    },
}

UpperCAmelCase__       =	{
    "openbmb/cpm-ant-10b": 1024,
}





def 							A     (					_UpperCAmelCase    :       Tuple   )    ->			List[Any]:







			'''simple docstring'''
			_UpperCAmelCase			=       collections.OrderedDict()
			with open(a_							,       'r'							,       encoding='utf-8'   ) as reader:
						_UpperCAmelCase			=       reader.readlines()
			for index, token in enumerate(a_   ):
						_UpperCAmelCase			=       token.rstrip('\n'   )
						_UpperCAmelCase			=       index
			return vocab







class       __lowerCAmelCase   (      a_						):



			def __init__(						self       :  Optional[int]			,		A       :  List[Any]			,		A       :  Union[str, Any]="<unk>"			,		A       :  Tuple=2_00)       ->   Union[str, Any]:



						"""simple docstring"""






						_UpperCAmelCase			=       vocab
						_UpperCAmelCase			=       unk_token
						_UpperCAmelCase			=       max_input_chars_per_word



			def    _lowerCamelCase	(						self       :  Union[str, Any]			,		A       :  Union[str, Any])       ->   Optional[Any]:



						"""simple docstring"""






						_UpperCAmelCase			=       list(lowercase_)
						if len(lowercase_) > self.max_input_chars_per_word:
									return [self.unk_token]

						_UpperCAmelCase			=       0
						_UpperCAmelCase			=       []
						while start < len(lowercase_):
									_UpperCAmelCase			=       len(lowercase_)
									_UpperCAmelCase			=       None
									while start < end:
												_UpperCAmelCase			=       ''.join(chars[start:end])
												if substr in self.vocab:
															_UpperCAmelCase			=       substr
															break
												end -= 1
									if cur_substr is None:
												sub_tokens.append(self.unk_token)
												start += 1
									else:
												sub_tokens.append(lowercase_)
												_UpperCAmelCase			=       end

						return sub_tokens







class       __lowerCAmelCase   (      a_						):
			UpperCamelCase        =					VOCAB_FILES_NAMES
			UpperCamelCase        =					PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase        =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase        =					['''input_ids''', '''attention_mask''']
			UpperCamelCase        =					False



			def __init__(						self       :  List[Any]			,		A       :  List[Any]			,		A       :  Tuple="<d>"			,		A       :  Any="</d>"			,		A       :  List[Any]="<s>"			,		A       :  Dict="</s>"			,		A       :  Tuple="<pad>"			,		A       :  Union[str, Any]="<unk>"			,		A       :  Union[str, Any]="</n>"			,		A       :  List[Any]="</_>"			,		A       :  List[str]="left"			,		**A       :  Optional[Any]			,		)       ->   str:



						"""simple docstring"""






						requires_backends(self			,		['jieba'])
						super().__init__(
						    bod_token=lowercase_			,		eod_token=lowercase_			,		bos_token=lowercase_			,		eos_token=lowercase_			,		pad_token=lowercase_			,		unk_token=lowercase_			,		line_token=lowercase_			,		space_token=lowercase_			,		padding_side=lowercase_			,		**lowercase_			,		)
						_UpperCAmelCase			=       bod_token
						_UpperCAmelCase			=       eod_token
						_UpperCAmelCase			=       load_vocab(lowercase_)
						_UpperCAmelCase			=       self.encoder[space_token]
						_UpperCAmelCase			=       self.encoder[line_token]

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

						_UpperCAmelCase			=       collections.OrderedDict(sorted(self.encoder.items()			,		key=lambda A: x[1]))
						_UpperCAmelCase			=       {v: k for k, v in self.encoder.items()}

						_UpperCAmelCase			=       WordpieceTokenizer(vocab=self.encoder			,		unk_token=self.unk_token)



			@property
			def    _lowerCamelCase	(						self       :  Optional[int])       ->   List[str]:



						"""simple docstring"""






						return self.encoder[self.bod_token]



			@property
			def    _lowerCamelCase	(						self       :  Any)       ->   List[str]:



						"""simple docstring"""






						return self.encoder[self.eod_token]



			@property
			def    _lowerCamelCase	(						self       :  List[str])       ->   List[Any]:



						"""simple docstring"""






						return self.encoder["\n"]



			@property
			def    _lowerCamelCase	(						self       :  Optional[Any])       ->   int:



						"""simple docstring"""






						return len(self.encoder)



			def    _lowerCamelCase	(						self       :  Optional[int])       ->   int:



						"""simple docstring"""






						return dict(self.encoder			,		**self.added_tokens_encoder)



			def    _lowerCamelCase	(						self       :  int			,		A       :  Any)       ->   Tuple:



						"""simple docstring"""






						_UpperCAmelCase			=       []
						for x in jieba.cut(lowercase_			,		cut_all=lowercase_):
									output_tokens.extend(self.wordpiece_tokenizer.tokenize(lowercase_))
						return output_tokens



			def    _lowerCamelCase	(						self       :  Any			,		A       :  List[Any]			,		**A       :  Optional[Any])       ->   Dict:



						"""simple docstring"""






						_UpperCAmelCase			=       [i for i in token_ids if i >= 0]
						_UpperCAmelCase			=       [
						    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(lowercase_			,		**lowercase_)



			def    _lowerCamelCase	(						self       :  List[Any]			,		A       :  List[str])       ->   List[str]:



						"""simple docstring"""






						return token in self.encoder



			def    _lowerCamelCase	(						self       :  List[Any]			,		A       :  str)       ->   str:



						"""simple docstring"""






						return "".join(lowercase_)



			def    _lowerCamelCase	(						self       :  int			,		A       :  Optional[int])       ->   Optional[Any]:



						"""simple docstring"""






						return self.encoder.get(lowercase_			,		self.encoder.get(self.unk_token))



			def    _lowerCamelCase	(						self       :  str			,		A       :  List[Any])       ->   int:



						"""simple docstring"""






						return self.decoder.get(lowercase_			,		self.unk_token)



			def    _lowerCamelCase	(						self       :  Dict			,		A       :  List[str]			,		A       :  List[str] = None)       ->   Tuple[str]:



						"""simple docstring"""






						if os.path.isdir(lowercase_):
									_UpperCAmelCase			=       os.path.join(
									    lowercase_			,		(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])
						else:
									_UpperCAmelCase			=       (filename_prefix + '-' if filename_prefix else '') + save_directory
						_UpperCAmelCase			=       0
						if " " in self.encoder:
									_UpperCAmelCase			=       self.encoder[' ']
									del self.encoder[" "]
						if "\n" in self.encoder:
									_UpperCAmelCase			=       self.encoder['\n']
									del self.encoder["\n"]
						_UpperCAmelCase			=       collections.OrderedDict(sorted(self.encoder.items()			,		key=lambda A: x[1]))
						with open(lowercase_			,		'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!')
															_UpperCAmelCase			=       token_index
												writer.write(token + '\n')
												index += 1
						return (vocab_file,)



			def    _lowerCamelCase	(						self       :  Union[str, Any]			,		A       :  Dict			,		A       :  Tuple = None)       ->   List[int]:



						"""simple docstring"""






						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    _lowerCamelCase	(						self       :  Optional[Any]			,		A       :  Any			,		A       :  Union[str, Any] = None			,		A       :  str = False)       ->   List[int]:



						"""simple docstring"""






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

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




from typing import TYPE_CHECKING

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


UpperCAmelCase__       =	{
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	["LxmertTokenizerFast"]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "LxmertEncoder",
							    "LxmertForPreTraining",
							    "LxmertForQuestionAnswering",
							    "LxmertModel",
							    "LxmertPreTrainedModel",
							    "LxmertVisualFeatureEncoder",
							    "LxmertXLayer",
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__       =	[
							    "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "TFLxmertForPreTraining",
							    "TFLxmertMainLayer",
							    "TFLxmertModel",
							    "TFLxmertPreTrainedModel",
							    "TFLxmertVisualFeatureEncoder",
							]


if TYPE_CHECKING:
							from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
							from .tokenization_lxmert import LxmertTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_lxmert_fast import LxmertTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_lxmert import (
														    LxmertEncoder,
														    LxmertForPreTraining,
														    LxmertForQuestionAnswering,
														    LxmertModel,
														    LxmertPreTrainedModel,
														    LxmertVisualFeatureEncoder,
														    LxmertXLayer,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_lxmert import (
														    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFLxmertForPreTraining,
														    TFLxmertMainLayer,
														    TFLxmertModel,
														    TFLxmertPreTrainedModel,
														    TFLxmertVisualFeatureEncoder,
														)

else:
							import sys

							UpperCAmelCase__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
