




from __future__ import annotations

from collections import deque
from queue import Queue
from timeit import timeit

__SCREAMING_SNAKE_CASE    :   int       ={
    """A""": ["""B""", """C"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E"""],
}

def 			lowerCAmelCase_			(  lowerCamelCase:       dict     ,				lowerCamelCase:       str						)					->			list[str]:


      '''simple docstring'''




      lowerCamelCase__        =				{start}
      lowerCamelCase__        =				[start]
      lowerCamelCase__        =				Queue()
      queue.put(lowerCamelCase						)
      while not queue.empty():
            lowerCamelCase__        =				queue.get()
            for w in graph[v]:
                  if w not in explored:
                        explored.add(lowerCamelCase						)
                        result.append(lowerCamelCase						)
                        queue.put(lowerCamelCase						)
      return result

def 			lowerCAmelCase_			(  lowerCamelCase:       dict     ,				lowerCamelCase:       str						)					->			list[str]:


      '''simple docstring'''




      lowerCamelCase__        =				{start}
      lowerCamelCase__        =				[start]
      lowerCamelCase__        =				deque([start]						)
      while queue:
            lowerCamelCase__        =				queue.popleft()
            for child in graph[v]:
                  if child not in visited:
                        visited.add(lowerCamelCase						)
                        result.append(lowerCamelCase						)
                        queue.append(lowerCamelCase						)
      return result

def 			lowerCAmelCase_			(  lowerCamelCase:       str						)					->			None:


      '''simple docstring'''




      lowerCamelCase__        =				f"""from __main__ import G, {name}"""
      lowerCamelCase__        =				1_00_00
      lowerCamelCase__        =				timeit(f"""{name}(G, 'A')"""     ,				setup=lowerCamelCase     ,				number=lowerCamelCase						)
      print(f"""{name:<35} finished {number} runs in {res:.5f} seconds"""						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()

      benchmark_function("""breadth_first_search""")
      benchmark_function("""breadth_first_search_with_deque""")
      # breadth_first_search                finished 10000 runs in 0.20999 seconds
      # breadth_first_search_with_deque     finished 10000 runs in 0.01421 seconds





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)

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

def 			lowerCAmelCase_			(  )					->			Any:


      '''simple docstring'''




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






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     def  __snake_case   (    self  :   Optional[Any]			)				->       Optional[Any]:
           lowerCamelCase__        =				logging.StreamHandler(sys.stdout			)
           logger.addHandler(A__			)

           lowerCamelCase__        =				self.get_auto_remove_tmp_dir()
           lowerCamelCase__        =				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(A__	,  'argv'	,  A__			):
                 lowerCamelCase__        =				run_glue_with_pabee.main()
                 for value in result.values():
                       self.assertGreaterEqual(A__	,  0.75			)