code: 
  import argparse
  import itertools
  import operator
  import sys
  from collections import OrderedDict
  
  from run_eval import datetime_now, run_generate
  
  from utils import ROUGE_KEYS
  
  
  # A table of supported tasks and the list of scores in the order of importance to be sorted by.
  # To add a new task, simply list the score names that `run_eval.run_generate()` returns
  __lowerCAmelCase				      =					{
      'translation': ['bleu'],
      'summarization': ROUGE_KEYS,
  }
  
  
  def       a			(   a  )    ->List[Any]:
  
  
  
  
  			'''simple docstring'''
  
  
  			SCREAMING_SNAKE_CASE    	=   search.split()
  			SCREAMING_SNAKE_CASE    	=   dict((g.split('''='''  ) for g in groups)  )
  			SCREAMING_SNAKE_CASE    	=   list(entries.keys()  )
  			SCREAMING_SNAKE_CASE    	=   [[F"""--{k} {v}""" for v in vs.split(''':'''  )] for k, vs in entries.items()]
  			SCREAMING_SNAKE_CASE    	=   [list(_SCREAMING_SNAKE_CASE  ) for x in itertools.product(*_SCREAMING_SNAKE_CASE  )]
  			return matrix, entry_names
  
  
  def       a			(   )    ->int:
  
  
  
  
  			'''simple docstring'''
  
  
  			SCREAMING_SNAKE_CASE    	=   sys.argv[0]
  
  			SCREAMING_SNAKE_CASE    	=   argparse.ArgumentParser(
  			    usage=(
  			        '''\n\nImportant: this script accepts all arguments `run_eval.py` accepts and then a few extra, therefore'''
  			        ''' refer to `run_eval.py -h` for the complete list.'''
  			    )  )
  			parser.add_argument(
  			    '''--search'''		,	type=_SCREAMING_SNAKE_CASE		,	required=_SCREAMING_SNAKE_CASE		,	help='''param space to search, e.g. "num_beams=5:10 length_penalty=0.8:1.0:1.2"'''		,	)
  			parser.add_argument(
  			    '''--bs'''		,	type=_SCREAMING_SNAKE_CASE		,	default=8		,	required=_SCREAMING_SNAKE_CASE		,	help='''initial batch size (may get reduced if it\'s too big)'''  )
  			parser.add_argument('''--task'''		,	type=_SCREAMING_SNAKE_CASE		,	help='''used for task_specific_params + metrics'''  )
  			parser.add_argument(
  			    '''--info'''		,	nargs='''?'''		,	type=_SCREAMING_SNAKE_CASE		,	const=datetime_now()		,	help=(
  			        '''add custom notes to be printed before the results table. If no value is passed, the current datetime'''
  			        ''' string will be used.'''
  			    )		,	)
  			SCREAMING_SNAKE_CASE    	=   parser.parse_known_args()
  			# we share some of the args
  			args_main.extend(['''--task''', args.task]  )
  			SCREAMING_SNAKE_CASE    	=   [prog] + args_main
  
  			# to support variations like translation_en_to_de"
  			SCREAMING_SNAKE_CASE    	=   'translation' if 'translation' in args.task else 'summarization'
  
  			SCREAMING_SNAKE_CASE    	=   parse_search_arg(args.search  )
  			SCREAMING_SNAKE_CASE    	=   task_score_names[task]  # score cols first
  			SCREAMING_SNAKE_CASE    	=   {col: len(str(_SCREAMING_SNAKE_CASE  )  ) for col in col_names}
  			SCREAMING_SNAKE_CASE    	=   []
  			for r in matrix:
  						SCREAMING_SNAKE_CASE    	=   dict((x.replace('''--'''		,	''''''  ).split() for x in r)  )
  						SCREAMING_SNAKE_CASE    	=   ' '.join(_SCREAMING_SNAKE_CASE  ).split()
  						args_exp.extend(['''--bs''', str(args.bs  )]  )  # in case we need to reduce its size due to CUDA OOM
  						SCREAMING_SNAKE_CASE    	=   args_normal + args_exp
  
  						# XXX: need to trap CUDA OOM and lower args.bs if that happens and retry
  
  						SCREAMING_SNAKE_CASE    	=   run_generate(verbose=_SCREAMING_SNAKE_CASE  )
  						# make sure scores are first in the table
  						SCREAMING_SNAKE_CASE    	=   OrderedDict()
  						for score in task_score_names[task]:
  									SCREAMING_SNAKE_CASE    	=   scores[score]
  						result.update(_SCREAMING_SNAKE_CASE  )
  						results.append(_SCREAMING_SNAKE_CASE  )
  
  						# find widest entries
  						for k, v in result.items():
  									SCREAMING_SNAKE_CASE    	=   len(str(_SCREAMING_SNAKE_CASE  )  )
  									if l > col_widths[k]:
  												SCREAMING_SNAKE_CASE    	=   l
  
  			SCREAMING_SNAKE_CASE    	=   sorted(_SCREAMING_SNAKE_CASE		,	key=operator.itemgetter(*task_score_names[task]  )		,	reverse=_SCREAMING_SNAKE_CASE  )
  			print(''' | '''.join([F"""{col:{col_widths[col]}}""" for col in col_names]  )  )
  			print(''' | '''.join([F"""{"-"*col_widths[col]}""" for col in col_names]  )  )
  			for row in results_sorted:
  						print(''' | '''.join([F"""{row[col]:{col_widths[col]}}""" for col in col_names]  )  )
  
  			SCREAMING_SNAKE_CASE    	=   results_sorted[0]
  			for score in task_score_names[task]:
  						del best[score]
  			SCREAMING_SNAKE_CASE    	=   [F"""--{k} {v}""" for k, v in best.items()]
  			SCREAMING_SNAKE_CASE    	=   ['--bs', str(args.bs  )]
  			if args.info:
  						print(F"""\nInfo: {args.info}"""  )
  			print('''\nBest score args:'''  )
  			print(''' '''.join(args_main + best_args + dyn_args  )  )
  
  			return results_sorted
  
  
  if __name__ == "__main__":
  	# Usage:
  	# [normal-run_eval_search.py cmd plus] \
  	# --search="num_beams=1:5:10 length_penalty=0.8:1:1.2 early_stopping=true:false"
  	#
  	# Example:
  	# PYTHONPATH="src:examples/seq2seq" python examples/seq2seq/run_eval_search.py $MODEL_NAME \
  	# $DATA_DIR/val.source $SAVE_DIR/test_translations.txt --reference_path $DATA_DIR/val.target \
  	# --score_path $SAVE_DIR/test_bleu.json --bs $BS --task translation \
  	# --search="num_beams=1:5:10 length_penalty=0.8:1:1.2 early_stopping=true:false"
  	run_search()
style_context: 
  import json
  
  import requests
  
  from .fetch_github_info import AUTHENTICATED_USER_ENDPOINT, fetch_github_info
  
  
  def       a			(   a  )    ->Tuple:
  
  
  
  
  			'''simple docstring'''
  
  
  			class 						lowerCamelCase			:
  
  
  
  
  
  
  
  				def __init__(    self			:int      ,    lowercase			:List[str] )		->			None:
  
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  
  							assert isinstance(lowercase      ,    (bytes, str) )
  							SCREAMING_SNAKE_CASE    	=   content
  
  
  
  
  
  
  
  				def    snake_case__    (    self			:Optional[Any] )		->			Optional[int]:
  
  
  
  
  
  
  
  							"""simple docstring"""
  
  
  
  
  
  
  							return json.loads(self.content )
  
  			def mock_response(*a		,	**a  ):
  						assert args[0] == AUTHENTICATED_USER_ENDPOINT
  						assert "Authorization" in kwargs["headers"]
  						assert kwargs["headers"]["Authorization"].startswith('''token '''  )
  						assert "Accept" in kwargs["headers"]
  						return FakeResponse(B'''{"login":"test","id":1}'''  )
  
  			monkeypatch.setattr(a		,	'''get'''		,	a  )
  			SCREAMING_SNAKE_CASE    	=   fetch_github_info('''token'''  )
  			assert result["login"] == "test"
  			assert result["id"] == 1