






"""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)

_UpperCamelCase						:    int		=						logging.getLogger()
def 		_SCREAMING_SNAKE_CASE					(       ):





  '''simple docstring'''





  lowercase				       =			argparse.ArgumentParser()
  parser.add_argument('-f'       )
  lowercase				       =			parser.parse_args()
  return args.f



class 			a	(  a_      ):







    def      UpperCamelCase_ (     self			):
      lowercase				       =			logging.StreamHandler(sys.stdout			)
      logger.addHandler(_lowerCamelCase			)

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

      with patch.object(_lowerCamelCase				,						'argv'				,						_lowerCamelCase			):
        lowercase				       =			run_glue_with_pabee.main()
        for value in result.values():
          self.assertGreaterEqual(_lowerCamelCase				,						0.7_5			)







"""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


_lowercase					:					str 		=		logging.get_logger(__name__)

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

_lowercase					:					Tuple 		=		{
    "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"
        ),
    },
}

_lowercase					:					str 		=		{
    "allenai/longformer-base-4096": 4_0_9_6,
    "allenai/longformer-large-4096": 4_0_9_6,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_0_9_6,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_0_9_6,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_0_9_6,
}

class 			__SCREAMING_SNAKE_CASE      ( lowerCAmelCase_  ):


					'''simple docstring'''





					_a       =				VOCAB_FILES_NAMES
					_a       =				PRETRAINED_VOCAB_FILES_MAP
					_a       =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_a       =				['input_ids', 'attention_mask']
					_a       =				LongformerTokenizer



					def __init__(			self				:    Dict,    lowerCamelCase				:    Any=None,    lowerCamelCase				:    List[Any]=None,    lowerCamelCase				:    List[Any]=None,    lowerCamelCase				:    Optional[Any]="replace",    lowerCamelCase				:    List[str]="<s>",    lowerCamelCase				:    Tuple="</s>",    lowerCamelCase				:    Union[str, Any]="</s>",    lowerCamelCase				:    str="<s>",    lowerCamelCase				:    Union[str, Any]="<unk>",    lowerCamelCase				:    Optional[Any]="<pad>",    lowerCamelCase				:    Optional[Any]="<mask>",    lowerCamelCase				:    int=False,    lowerCamelCase				:    Optional[Any]=True,    **lowerCamelCase				:    Union[str, Any],    )->   List[str]:
								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,    )

								lowerCamelCase__						:						List[str]						      =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
								if pre_tok_state.get('''add_prefix_space''',    lowerCamelCase	) != add_prefix_space:
											lowerCamelCase__						:						Dict						      =getattr(lowerCamelCase,    pre_tok_state.pop('''type'''	)	)
											lowerCamelCase__						:						int						      =add_prefix_space
											lowerCamelCase__						:						int						      =pre_tok_class(**lowerCamelCase	)

								lowerCamelCase__						:						Optional[int]						      =add_prefix_space

								lowerCamelCase__						:						str						      ='''post_processor'''
								lowerCamelCase__						:						int						      =getattr(self.backend_tokenizer,    lowerCamelCase,    lowerCamelCase	)
								if tokenizer_component_instance:
											lowerCamelCase__						:						Union[str, Any]						      =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:
														lowerCamelCase__						:						List[str]						      =tuple(state['''sep''']	)
											if "cls" in state:
														lowerCamelCase__						:						List[str]						      =tuple(state['''cls''']	)

											lowerCamelCase__						:						Dict						      =False

											if state.get('''add_prefix_space''',    lowerCamelCase	) != add_prefix_space:
														lowerCamelCase__						:						int						      =add_prefix_space
														lowerCamelCase__						:						int						      =True

											if state.get('''trim_offsets''',    lowerCamelCase	) != trim_offsets:
														lowerCamelCase__						:						Optional[int]						      =trim_offsets
														lowerCamelCase__						:						Union[str, Any]						      =True

											if changes_to_apply:
														lowerCamelCase__						:						Dict						      =getattr(lowerCamelCase,    state.pop('''type'''	)	)
														lowerCamelCase__						:						Dict						      =component_class(**lowerCamelCase	)
														setattr(self.backend_tokenizer,    lowerCamelCase,    lowerCamelCase	)



					@property
					def 						snake_case			(			self				:    str	)->   str:
								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 						snake_case			(			self				:    Tuple,    lowerCamelCase				:    List[Any]	)->   List[str]:
								lowerCamelCase__						:						List[str]						      =AddedToken(lowerCamelCase,    lstrip=lowerCamelCase,    rstrip=lowerCamelCase	) if isinstance(lowerCamelCase,    lowerCamelCase	) else value
								lowerCamelCase__						:						Any						      =value



					def 						snake_case			(			self				:    Optional[Any],    *lowerCamelCase				:    Tuple,    **lowerCamelCase				:    Dict	)->   BatchEncoding:
								lowerCamelCase__						:						Union[str, Any]						      =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 						snake_case			(			self				:    List[str],    *lowerCamelCase				:    Tuple,    **lowerCamelCase				:    List[Any]	)->   BatchEncoding:
								lowerCamelCase__						:						List[Any]						      =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 						snake_case			(			self				:    str,    lowerCamelCase				:    str,    lowerCamelCase				:    Optional[str] = None	)->   Tuple[str]:
								lowerCamelCase__						:						str						      =self._tokenizer.model.save(lowerCamelCase,    name=lowerCamelCase	)
								return tuple(lowerCamelCase	)



					def 						snake_case			(			self				:    Dict,    lowerCamelCase				:    int,    lowerCamelCase				:    int=None	)->   str:
								lowerCamelCase__						:						int						      =[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 						snake_case			(			self				:    Optional[int],    lowerCamelCase				:    List[int],    lowerCamelCase				:    Optional[List[int]] = None	)->   List[int]:
								lowerCamelCase__						:						Tuple						      =[self.sep_token_id]
								lowerCamelCase__						:						str						      =[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]




