



"""simple docstring"""







import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


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

__snake_case	:				List[str]  					=			{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

__snake_case	:				Dict  					=			{
    'vocab_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'allenai/longformer-base-4096': 'https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt',
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'allenai/longformer-base-4096': (
            'https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096': (
            'https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096-finetuned-triviaqa': (
            'https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-base-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json'
        ),
        'allenai/longformer-large-4096-extra.pos.embd.only': (
            'https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json'
        ),
    },
}

__snake_case	:				Tuple  					=			{
    'allenai/longformer-base-4096': 4_096,
    'allenai/longformer-large-4096': 4_096,
    'allenai/longformer-large-4096-finetuned-triviaqa': 4_096,
    'allenai/longformer-base-4096-extra.pos.embd.only': 4_096,
    'allenai/longformer-large-4096-extra.pos.embd.only': 4_096,
}

class       UpperCamelCase  (					a				):





     """simple docstring"""






     _lowerCamelCase					: int				   =VOCAB_FILES_NAMES
     _lowerCamelCase					: Union[str, Any]				   =PRETRAINED_VOCAB_FILES_MAP
     _lowerCamelCase					: Dict				   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _lowerCamelCase					: str				   =["input_ids", "attention_mask"]
     _lowerCamelCase					: Optional[int]				   =LongformerTokenizer





     def __init__(					self :							int	,      _lowerCamelCase :							Dict=None	,      _lowerCamelCase :							str=None	,      _lowerCamelCase :							Optional[Any]=None	,      _lowerCamelCase :							Tuple="replace"	,      _lowerCamelCase :							List[Any]="<s>"	,      _lowerCamelCase :							Union[str, Any]="</s>"	,      _lowerCamelCase :							Any="</s>"	,      _lowerCamelCase :							List[str]="<s>"	,      _lowerCamelCase :							List[str]="<unk>"	,      _lowerCamelCase :							int="<pad>"	,      _lowerCamelCase :							str="<mask>"	,      _lowerCamelCase :							Optional[int]=False	,      _lowerCamelCase :							Optional[int]=True	,      **_lowerCamelCase :							int	,      ):
          super().__init__(
              _lowerCamelCase	,      _lowerCamelCase	,      tokenizer_file=_lowerCamelCase	,      errors=_lowerCamelCase	,      bos_token=_lowerCamelCase	,      eos_token=_lowerCamelCase	,      sep_token=_lowerCamelCase	,      cls_token=_lowerCamelCase	,      unk_token=_lowerCamelCase	,      pad_token=_lowerCamelCase	,      mask_token=_lowerCamelCase	,      add_prefix_space=_lowerCamelCase	,      trim_offsets=_lowerCamelCase	,      **_lowerCamelCase	,      )

          A__				=   json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
          if pre_tok_state.get('''add_prefix_space'''	,      _lowerCamelCase ) != add_prefix_space:
               A__				=   getattr(_lowerCamelCase	,      pre_tok_state.pop('''type''' ) )
               A__				=   add_prefix_space
               A__				=   pre_tok_class(**_lowerCamelCase )

          A__				=   add_prefix_space

          A__				=   '''post_processor'''
          A__				=   getattr(self.backend_tokenizer	,      _lowerCamelCase	,      _lowerCamelCase )
          if tokenizer_component_instance:
               A__				=   json.loads(tokenizer_component_instance.__getstate__() )

               # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
               if "sep" in state:
                    A__				=   tuple(state['''sep'''] )
               if "cls" in state:
                    A__				=   tuple(state['''cls'''] )

               A__				=   False

               if state.get('''add_prefix_space'''	,      _lowerCamelCase ) != add_prefix_space:
                    A__				=   add_prefix_space
                    A__				=   True

               if state.get('''trim_offsets'''	,      _lowerCamelCase ) != trim_offsets:
                    A__				=   trim_offsets
                    A__				=   True

               if changes_to_apply:
                    A__				=   getattr(_lowerCamelCase	,      state.pop('''type''' ) )
                    A__				=   component_class(**_lowerCamelCase )
                    setattr(self.backend_tokenizer	,      _lowerCamelCase	,      _lowerCamelCase )





     @property
     def 						A__  (					self :							Tuple ):
          if self._mask_token is None:
               if self.verbose:
                    logger.error('''Using mask_token, but it is not set yet.''' )
               return None
          return str(self._mask_token )





     @mask_token.setter
     def 						A__  (					self :							Optional[int]	,      _lowerCamelCase :							str ):
          A__				=   AddedToken(_lowerCamelCase	,      lstrip=_lowerCamelCase	,      rstrip=_lowerCamelCase ) if isinstance(_lowerCamelCase	,      _lowerCamelCase ) else value
          A__				=   value





     def 						A__  (					self :							Optional[int]	,      *_lowerCamelCase :							str	,      **_lowerCamelCase :							Any ):
          A__				=   kwargs.get('''is_split_into_words'''	,      _lowerCamelCase )
          assert self.add_prefix_space or not is_split_into_words, (
              F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
              "to use it with pretokenized inputs."
          )

          return super()._batch_encode_plus(*_lowerCamelCase	,      **_lowerCamelCase )





     def 						A__  (					self :							Dict	,      *_lowerCamelCase :							Dict	,      **_lowerCamelCase :							List[str] ):
          A__				=   kwargs.get('''is_split_into_words'''	,      _lowerCamelCase )

          assert self.add_prefix_space or not is_split_into_words, (
              F'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True '''
              "to use it with pretokenized inputs."
          )

          return super()._encode_plus(*_lowerCamelCase	,      **_lowerCamelCase )





     def 						A__  (					self :							str	,      _lowerCamelCase :							str	,      _lowerCamelCase :							Optional[str] = None ):
          A__				=   self._tokenizer.model.save(_lowerCamelCase	,      name=_lowerCamelCase )
          return tuple(_lowerCamelCase )





     def 						A__  (					self :							Any	,      _lowerCamelCase :							int	,      _lowerCamelCase :							Any=None ):
          A__				=   [self.bos_token_id] + token_ids_a + [self.eos_token_id]
          if token_ids_a is None:
               return output

          return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





     def 						A__  (					self :							Dict	,      _lowerCamelCase :							List[int]	,      _lowerCamelCase :							Optional[List[int]] = None ):
          A__				=   [self.sep_token_id]
          A__				=   [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]








"""simple docstring"""







import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_with_pabee

from transformers.testing_utils import TestCasePlus


logging.basicConfig(level=logging.DEBUG)

__snake_case	:				List[str]  					=			logging.getLogger()



def   a_	(			):
     A__				=   argparse.ArgumentParser()
     parser.add_argument('''-f'''      )
     A__				=   parser.parse_args()
     return args.f

class       UpperCamelCase  (					a				):





     """simple docstring"""






     def 						A__  (					self :							Optional[int] ):
          A__				=   logging.StreamHandler(sys.stdout )
          logger.addHandler(_lowerCamelCase )

          A__				=   self.get_auto_remove_tmp_dir()
          A__				=   F'''
            run_glue_with_pabee.py
            --model_type albert
            --model_name_or_path albert-base-v2
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --task_name mrpc
            --do_train
            --do_eval
            --per_gpu_train_batch_size=2
            --per_gpu_eval_batch_size=1
            --learning_rate=2e-5
            --max_steps=50
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            '''.split()

          with patch.object(_lowerCamelCase	,      '''argv'''	,      _lowerCamelCase ):
               A__				=   run_glue_with_pabee.main()
               for value in result.values():
                    self.assertGreaterEqual(_lowerCamelCase	,      0.75 )



