code: 
  
  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)
  
  A_		:			Optional[int]										=   logging.getLogger()
  
  
  def       __a       (   )      ->     str:
  
  
  
  
  
  
      '''simple docstring'''
      __UpperCAmelCase									=			argparse.ArgumentParser()
      parser.add_argument('''-f'''      )
      __UpperCAmelCase									=			parser.parse_args()
      return args.f
  class 					A_   (      _a						):
  
  
      '''simple docstring'''
  
  
  
  
  
  
      def      lowerCAmelCase_						(self  )     ->      int:
          __UpperCAmelCase									=			logging.StreamHandler(sys.stdout  )
          logger.addHandler(lowercase__  )
  
          __UpperCAmelCase									=			self.get_auto_remove_tmp_dir()
          __UpperCAmelCase									=			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__  ):
              __UpperCAmelCase									=			run_glue_with_pabee.main()
              for value in result.values():
                  self.assertGreaterEqual(lowercase__     ,      0.75  )
  
  
  
  
  
style_context: 
  
  import numpy as np
  
  
  def       __a       (   SCREAMING_SNAKE_CASE      )      ->     Tuple:
  
  
  
  
  
  
      '''simple docstring'''
      __UpperCAmelCase					,     __UpperCAmelCase									=			a.shape
      __UpperCAmelCase									=			min(SCREAMING_SNAKE_CASE       ,   SCREAMING_SNAKE_CASE      )
      __UpperCAmelCase									=			np.eye(SCREAMING_SNAKE_CASE      )
      __UpperCAmelCase									=			a.copy()
  
      for k in range(t - 1      ):
          # select a column of modified matrix A':
          __UpperCAmelCase									=			r[k:, [k]]
          # construct first basis vector
          __UpperCAmelCase									=			np.zeros_like(SCREAMING_SNAKE_CASE      )
          __UpperCAmelCase									=			1.0
          # determine scaling factor
          __UpperCAmelCase									=			np.linalg.norm(SCREAMING_SNAKE_CASE      )
          # construct vector v for Householder reflection
          __UpperCAmelCase									=			x + np.sign(x[0]      ) * alpha * ea
          v /= np.linalg.norm(SCREAMING_SNAKE_CASE      )
  
          # construct the Householder matrix
          __UpperCAmelCase									=			np.eye(m - k      ) - 2.0 * v @ v.T
          # pad with ones and zeros as necessary
          __UpperCAmelCase									=			np.block([[np.eye(SCREAMING_SNAKE_CASE      ), np.zeros((k, m - k)      )], [np.zeros((m - k, k)      ), q_k]]      )
  
          __UpperCAmelCase									=			q @ q_k.T
          __UpperCAmelCase									=			q_k @ r
  
      return q, r
  
  
  if __name__ == "__main__":
         import doctest
  
         doctest.testmod()
  
  
  
  
  