


from __future__ import annotations

from typing import Any




class A  :






      def __init__( self						:					Any      ,       lowercase_						:					int      ,       lowercase_						:					int			) ->						None:  # noqa: A002
             """simple docstring"""




             _lowerCamelCase	:		Any          =item
             _lowerCamelCase	:		str          =next




class A  :






      def __init__( self						:					Any			) ->						None:
             """simple docstring"""




             _lowerCamelCase	:		Union[str, Any]          =None
             _lowerCamelCase	:		List[str]          =0






      def 	lowerCamelCase	( self						:					Dict      ,       lowercase_						:					Optional[int]			) ->						None:
             """simple docstring"""




             _lowerCamelCase	:		str          =Node(SCREAMING_SNAKE_CASE_      ,       self.head			)
             self.size += 1






      def 	lowerCamelCase	( self						:					Tuple			) ->						Any:
             """simple docstring"""




             if self.head is None:
                    return None
             else:
                    _lowerCamelCase	:		Optional[Any]          =self.head.item
                    _lowerCamelCase	:		Optional[Any]          =self.head.next
                    self.size -= 1
                    return item






      def 	lowerCamelCase	( self						:					Optional[int]			) ->						bool:
             """simple docstring"""




             return self.head is None






      def __str__( self						:					List[Any]			) ->						str:
             """simple docstring"""




             if self.is_empty():
                    return ""
             else:
                    _lowerCamelCase	:		Optional[Any]          =self.head
                    _lowerCamelCase	:		Tuple          =''
                    _lowerCamelCase	:		List[str]          =[]
                    while iterate:
                           item_list.append(str(iterate.item			)			)
                           _lowerCamelCase	:		Any          =iterate.next

                    _lowerCamelCase	:		str          =' --> '.join(SCREAMING_SNAKE_CASE_			)

                    return item_str






      def __len__( self						:					List[str]			) ->						int:
             """simple docstring"""




             return self.size






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)

lowerCamelCase						 =	logging.getLogger()




def      a_				(   ):
       '''simple docstring'''





       _lowerCamelCase	:		Any          =argparse.ArgumentParser()
       parser.add_argument('-f'					)
       _lowerCamelCase	:		Optional[Any]          =parser.parse_args()
       return args.f




class A  (       UpperCamelCase_					):






      def 	lowerCamelCase	( self						:					List[Any]			) ->						int:
             """simple docstring"""




             _lowerCamelCase	:		Any          =logging.StreamHandler(sys.stdout			)
             logger.addHandler(lowercase_			)

             _lowerCamelCase	:		Dict          =self.get_auto_remove_tmp_dir()
             _lowerCamelCase	:		int          =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(lowercase_      ,       'argv'      ,       lowercase_			):
                    _lowerCamelCase	:		Dict          =run_glue_with_pabee.main()
                    for value in result.values():
                           self.assertGreaterEqual(lowercase_      ,       0.75			)


