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


lowercase_     :   Dict 				=				logging.get_logger(__name__)

lowercase_     :   Tuple 				=				{'vocab_file': 'vocab.txt'}

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

lowercase_     :   Any 				=				{
    'openbmb/cpm-ant-10b': 1_0_2_4,
}







def 			A__      (	snake_case_ :		Any      ):
	SCREAMING_SNAKE_CASE__:   Any=      collections.OrderedDict()
	with open(SCREAMING_SNAKE_CASE_       ,				'''r'''       ,				encoding='''utf-8'''      ) as reader:
		SCREAMING_SNAKE_CASE__:   Union[str, Any]=      reader.readlines()
	for index, token in enumerate(SCREAMING_SNAKE_CASE_      ):
		SCREAMING_SNAKE_CASE__:   Dict=      token.rstrip('''\n'''      )
		SCREAMING_SNAKE_CASE__:   int=      index
	return vocab






class 		_lowerCamelCase		(   lowercase__    ):
				def __init__(  self , lowerCAmelCase , lowerCAmelCase="<unk>" , lowerCAmelCase=200   )       ->					str:
					SCREAMING_SNAKE_CASE__:   List[Any]=      vocab
					SCREAMING_SNAKE_CASE__:   str=      unk_token
					SCREAMING_SNAKE_CASE__:   Union[str, Any]=      max_input_chars_per_word



				def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					Any:
					SCREAMING_SNAKE_CASE__:   int=      list(__lowercase   )
					if len(__lowercase   ) > self.max_input_chars_per_word:
						return [self.unk_token]

					SCREAMING_SNAKE_CASE__:   str=      0
					SCREAMING_SNAKE_CASE__:   int=      []
					while start < len(__lowercase   ):
						SCREAMING_SNAKE_CASE__:   List[str]=      len(__lowercase   )
						SCREAMING_SNAKE_CASE__:   str=      None
						while start < end:
							SCREAMING_SNAKE_CASE__:   Any=      ''''''.join(chars[start:end]   )
							if substr in self.vocab:
								SCREAMING_SNAKE_CASE__:   Union[str, Any]=      substr
								break
							end -= 1
						if cur_substr is None:
							sub_tokens.append(self.unk_token   )
							start += 1
						else:
							sub_tokens.append(__lowercase   )
							SCREAMING_SNAKE_CASE__:   int=      end

					return sub_tokens






class 		_lowerCamelCase		(   lowercase__    ):
				__a  =      VOCAB_FILES_NAMES
				__a  =      PRETRAINED_VOCAB_FILES_MAP
				__a  =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__a  =      ["""input_ids""", """attention_mask"""]
				__a  =      False
				def __init__(  self , lowerCAmelCase , lowerCAmelCase="<d>" , lowerCAmelCase="</d>" , lowerCAmelCase="<s>" , lowerCAmelCase="</s>" , lowerCAmelCase="<pad>" , lowerCAmelCase="<unk>" , lowerCAmelCase="</n>" , lowerCAmelCase="</_>" , lowerCAmelCase="left" , **lowerCAmelCase , )       ->					Union[str, Any]:
					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 , )
					SCREAMING_SNAKE_CASE__:   Optional[Any]=      bod_token
					SCREAMING_SNAKE_CASE__:   Dict=      eod_token
					SCREAMING_SNAKE_CASE__:   Any=      load_vocab(__lowercase   )
					SCREAMING_SNAKE_CASE__:   str=      self.encoder[space_token]
					SCREAMING_SNAKE_CASE__:   Dict=      self.encoder[line_token]

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

					SCREAMING_SNAKE_CASE__:   Union[str, Any]=      collections.OrderedDict(sorted(self.encoder.items() , key=lambda lowerCAmelCase   : x[1]   )   )
					SCREAMING_SNAKE_CASE__:   List[Any]=      {v: k for k, v in self.encoder.items()}

					SCREAMING_SNAKE_CASE__:   Union[str, Any]=      WordpieceTokenizer(vocab=self.encoder , unk_token=self.unk_token   )
				@property
				def 						UpperCamelCase_				(  self   )       ->					Dict:
					return self.encoder[self.bod_token]
				@property
				def 						UpperCamelCase_				(  self   )       ->					Dict:
					return self.encoder[self.eod_token]
				@property
				def 						UpperCamelCase_				(  self   )       ->					str:
					return self.encoder["\n"]
				@property
				def 						UpperCamelCase_				(  self   )       ->					List[Any]:
					return len(self.encoder   )
				def 						UpperCamelCase_				(  self   )       ->					Union[str, Any]:
					return dict(self.encoder , **self.added_tokens_encoder   )
				def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					str:
					SCREAMING_SNAKE_CASE__:   int=      []
					for x in jieba.cut(__lowercase , cut_all=__lowercase   ):
						output_tokens.extend(self.wordpiece_tokenizer.tokenize(__lowercase   )   )
					return output_tokens
				def 						UpperCamelCase_				(  self , lowerCAmelCase , **lowerCAmelCase   )       ->					Tuple:
					SCREAMING_SNAKE_CASE__:   Optional[Any]=      [i for i in token_ids if i >= 0]
					SCREAMING_SNAKE_CASE__:   List[Any]=      [
					    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 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					List[str]:
					return token in self.encoder
				def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					Tuple:
					return "".join(__lowercase   )
				def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					List[Any]:
					return self.encoder.get(__lowercase , self.encoder.get(self.unk_token   )   )
				def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					Tuple:
					return self.decoder.get(__lowercase , self.unk_token   )
				def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase = None   )       ->					List[str]:
					if os.path.isdir(__lowercase   ):
						SCREAMING_SNAKE_CASE__:   Tuple=      os.path.join(
						    __lowercase , (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']   )
					else:
						SCREAMING_SNAKE_CASE__:   List[str]=      (filename_prefix + '''-''' if filename_prefix else '''''') + save_directory
					SCREAMING_SNAKE_CASE__:   str=      0
					if " " in self.encoder:
						SCREAMING_SNAKE_CASE__:   Tuple=      self.encoder[''' ''']
						del self.encoder[" "]
					if "\n" in self.encoder:
						SCREAMING_SNAKE_CASE__:   List[Any]=      self.encoder['''\n''']
						del self.encoder["\n"]
					SCREAMING_SNAKE_CASE__:   int=      collections.OrderedDict(sorted(self.encoder.items() , key=lambda lowerCAmelCase   : 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!'''   )
								SCREAMING_SNAKE_CASE__:   Tuple=      token_index
							writer.write(token + '''\n'''   )
							index += 1
					return (vocab_file,)
				def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase = None   )       ->					List[str]:
					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 , lowerCAmelCase , lowerCAmelCase = None , lowerCAmelCase = False   )       ->					Tuple:

					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 collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase_     :   List[Any] 				=				logging.get_logger(__name__)

lowercase_     :   List[Any] 				=				{
    'facebook/xlm-roberta-xl': 'https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json',
    'facebook/xlm-roberta-xxl': 'https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}






class 		_lowerCamelCase		(   UpperCamelCase_    ):
    __a  =      "xlm-roberta-xl"
    def __init__(  self , lowerCAmelCase=250880 , lowerCAmelCase=2560 , lowerCAmelCase=36 , lowerCAmelCase=32 , lowerCAmelCase=10240 , lowerCAmelCase="gelu" , lowerCAmelCase=0.1 , lowerCAmelCase=0.1 , lowerCAmelCase=514 , lowerCAmelCase=1 , lowerCAmelCase=0.02 , lowerCAmelCase=1e-05 , lowerCAmelCase=1 , lowerCAmelCase=0 , lowerCAmelCase=2 , lowerCAmelCase="absolute" , lowerCAmelCase=True , lowerCAmelCase=None , **lowerCAmelCase , )       ->					Union[str, Any]:
     super().__init__(pad_token_id=lowerCAmelCase , bos_token_id=lowerCAmelCase , eos_token_id=lowerCAmelCase , **lowerCAmelCase   )
     SCREAMING_SNAKE_CASE__:   List[Any]=      vocab_size
     SCREAMING_SNAKE_CASE__:   Dict=      hidden_size
     SCREAMING_SNAKE_CASE__:   Tuple=      num_hidden_layers
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      num_attention_heads
     SCREAMING_SNAKE_CASE__:   int=      hidden_act
     SCREAMING_SNAKE_CASE__:   Any=      intermediate_size
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      hidden_dropout_prob
     SCREAMING_SNAKE_CASE__:   str=      attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE__:   List[Any]=      max_position_embeddings
     SCREAMING_SNAKE_CASE__:   Dict=      type_vocab_size
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      initializer_range
     SCREAMING_SNAKE_CASE__:   Dict=      layer_norm_eps
     SCREAMING_SNAKE_CASE__:   Dict=      position_embedding_type
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      use_cache
     SCREAMING_SNAKE_CASE__:   str=      classifier_dropout






class 		_lowerCamelCase		(   UpperCamelCase_    ):
    @property
    def 						UpperCamelCase_				(  self   )       ->					Mapping[str, Mapping[int, str]]:
     if self.task == "multiple-choice":
      SCREAMING_SNAKE_CASE__:   Dict=      {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
     else:
      SCREAMING_SNAKE_CASE__:   List[str]=      {0: '''batch''', 1: '''sequence'''}
     return OrderedDict(
         [
             ('''input_ids''', dynamic_axis),
             ('''attention_mask''', dynamic_axis),
         ]   )

