




'''simple docstring'''



import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase_							:	List[Any]	     =		logging.getLogger()







def       _UpperCamelCase			(_lowerCamelCase				:  Path ,						_lowerCamelCase				:  list						)-> List[str]:




     '''simple docstring'''





     __snake_case            =	'''\n'''.join(_lowerCamelCase						)
     Path(_lowerCamelCase						).open('''w'''						).writelines(_lowerCamelCase						)


UpperCAmelCase_							:	str	     =		'''patrickvonplaten/t5-tiny-random'''
UpperCAmelCase_							:	int	     =		'''sshleifer/bart-tiny-random'''
UpperCAmelCase_							:	Optional[Any]	     =		'''sshleifer/tiny-mbart'''

UpperCAmelCase_							:	Any	     =		logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks







class      lowerCAmelCase (			__lowerCAmelCase):


       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	List[Any]:



            '''simple docstring'''




            __snake_case            =	Path(self.get_auto_remove_tmp_dir()	) / '''utest_input.source'''
            __snake_case            =	input_file_name.parent / '''utest_output.txt'''
            assert not output_file_name.exists()
            __snake_case            =	[''' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.''']
            _dump_articles(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE	)

            __snake_case            =	str(Path(self.get_auto_remove_tmp_dir()	) / '''scores.json'''	)
            __snake_case            =	'''translation_en_to_de''' if model == T5_TINY else '''summarization'''
            __snake_case            =	F'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

            with patch.object(__SCREAMING_SNAKE_CASE     ,	'''argv'''     ,	__SCREAMING_SNAKE_CASE	):
                 run_generate()
                 assert Path(__SCREAMING_SNAKE_CASE	).exists()
                 # os.remove(Path(output_file_name))


       def    lowerCAmelCase   ( self	)   ->	List[str]:



            '''simple docstring'''




            self.run_eval_tester(__SCREAMING_SNAKE_CASE	)


       @parameterized.expand([BART_TINY, MBART_TINY]	)
       @slow
       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	List[Any]:



            '''simple docstring'''




            self.run_eval_tester(__SCREAMING_SNAKE_CASE	)




       @parameterized.expand([T5_TINY, MBART_TINY]	)
       @slow
       def    lowerCAmelCase   ( self     ,	__SCREAMING_SNAKE_CASE	)   ->	Optional[Any]:



            '''simple docstring'''




            __snake_case            =	Path(self.get_auto_remove_tmp_dir()	) / '''utest_input.source'''
            __snake_case            =	input_file_name.parent / '''utest_output.txt'''
            assert not output_file_name.exists()

            __snake_case            =	{
                '''en''': ['''Machine learning is great, isn\'t it?''', '''I like to eat bananas''', '''Tomorrow is another great day!'''],
                '''de''': [
                    '''Maschinelles Lernen ist großartig, oder?''',
                    '''Ich esse gerne Bananen''',
                    '''Morgen ist wieder ein toller Tag!''',
                ],
            }

            __snake_case            =	Path(self.get_auto_remove_tmp_dir()	)
            __snake_case            =	str(tmp_dir / '''scores.json'''	)
            __snake_case            =	str(tmp_dir / '''val.target'''	)
            _dump_articles(__SCREAMING_SNAKE_CASE     ,	text['''en''']	)
            _dump_articles(__SCREAMING_SNAKE_CASE     ,	text['''de''']	)
            __snake_case            =	'''translation_en_to_de''' if model == T5_TINY else '''summarization'''
            __snake_case            =	F'''
            run_eval_search.py
            {model}
            {str(__SCREAMING_SNAKE_CASE	)}
            {str(__SCREAMING_SNAKE_CASE	)}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
            testargs.extend(['''--search''', '''num_beams=1:2 length_penalty=0.9:1.0''']	)

            with patch.object(__SCREAMING_SNAKE_CASE     ,	'''argv'''     ,	__SCREAMING_SNAKE_CASE	):
                 with CaptureStdout() as cs:
                      run_search()
                 __snake_case            =	[''' num_beams | length_penalty''', model, '''Best score args''']
                 __snake_case            =	['''Info''']
                 if "translation" in task:
                      expected_strings.append('''bleu'''	)
                 else:
                      expected_strings.extend(__SCREAMING_SNAKE_CASE	)
                 for w in expected_strings:
                      assert w in cs.out
                 for w in un_expected_strings:
                      assert w not in cs.out
                 assert Path(__SCREAMING_SNAKE_CASE	).exists()
                 os.remove(Path(__SCREAMING_SNAKE_CASE	)	)












'''simple docstring'''



import argparse
import os
import re


UpperCAmelCase_							:	List[str]	     =		'''src/transformers/models/auto'''


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase_							:	Tuple	     =		re.compile(R'''[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict''')
# re pattern that matches identifiers in mappings
UpperCAmelCase_							:	Dict	     =		re.compile(R'''\s*\(\s*"(\S[^"]+)"''')







def       _UpperCamelCase			(_lowerCamelCase				:  List[Any] ,						_lowerCamelCase				:  bool = False						)-> str:




     '''simple docstring'''





     with open(_lowerCamelCase ,						'''r''' ,						encoding='''utf-8'''						) as f:
          __snake_case            =	f.read()

     __snake_case            =	content.split('''\n'''						)
     __snake_case            =	[]
     __snake_case            =	0
     while line_idx < len(_lowerCamelCase						):
          if _re_intro_mapping.search(lines[line_idx]						) is not None:
               __snake_case            =	len(re.search(R'''^(\s*)\S''' ,						lines[line_idx]						).groups()[0]						) + 8
               # Start of a new mapping!
               while not lines[line_idx].startswith(''' ''' * indent + '''('''						):
                    new_lines.append(lines[line_idx]						)
                    line_idx += 1

               __snake_case            =	[]
               while lines[line_idx].strip() != "]":
                    # Blocks either fit in one line or not
                    if lines[line_idx].strip() == "(":
                         __snake_case            =	line_idx
                         while not lines[line_idx].startswith(''' ''' * indent + ''')'''						):
                              line_idx += 1
                         blocks.append('''\n'''.join(lines[start_idx : line_idx + 1]						)						)
                    else:
                         blocks.append(lines[line_idx]						)
                    line_idx += 1

               # Sort blocks by their identifiers
               __snake_case            =	sorted(_lowerCamelCase ,						key=lambda _lowerCamelCase						: _re_identifier.search(_lowerCamelCase						).groups()[0]						)
               new_lines += blocks
          else:
               new_lines.append(lines[line_idx]						)
               line_idx += 1

     if overwrite:
          with open(_lowerCamelCase ,						'''w''' ,						encoding='''utf-8'''						) as f:
               f.write('''\n'''.join(_lowerCamelCase						)						)
     elif "\n".join(_lowerCamelCase						) != content:
          return True







def       _UpperCamelCase			(_lowerCamelCase				:  bool = False						)-> Tuple:




     '''simple docstring'''





     __snake_case            =	[os.path.join(_lowerCamelCase ,						_lowerCamelCase						) for f in os.listdir(_lowerCamelCase						) if f.endswith('''.py'''						)]
     __snake_case            =	[sort_auto_mapping(_lowerCamelCase ,						overwrite=_lowerCamelCase						) for fname in fnames]

     if not overwrite and any(_lowerCamelCase						):
          __snake_case            =	[f for f, d in zip(_lowerCamelCase ,						_lowerCamelCase						) if d]
          raise ValueError(
              f'''The following files have auto mappings that need sorting: {", ".join(_lowerCamelCase						)}. Run `make style` to fix'''
              ''' this.'''						)


if __name__ == "__main__":
     UpperCAmelCase_							:	str	     =		argparse.ArgumentParser()
     parser.add_argument('''--check_only''', action='''store_true''', help='''Whether to only check or fix style.''')
     UpperCAmelCase_							:	List[Any]	     =		parser.parse_args()

     sort_all_auto_mappings(not args.check_only)






