


'''simple docstring'''



import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__		: int												=  """src/transformers"""

# Matches is_xxx_available()
A__		: Optional[int]												=  re.compile(R"""is\_([a-z_]*)_available()""")
# Matches from xxx import bla
A__		: int												=  re.compile(R"""\s+from\s+\S*\s+import\s+([^\(\s].*)\n""")
A__		: Optional[Any]												=  re.compile(R"""^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)""")


A__		: List[Any]												=  """\n{0} = None\n"""

A__		: Union[str, Any]												=  """\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n"""


A__		: Any												=  """\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"""



def       UpperCAmelCase__ (     UpperCAmelCase_   :    int							)					->		List[str]:

     if _re_test_backend.search(SCREAMING_SNAKE_CASE_							) is None:
          return None
     __lowerCamelCase       :     str        =		[b[0] for b in _re_backend.findall(SCREAMING_SNAKE_CASE_							)]
     backends.sort()
     return "_and_".join(SCREAMING_SNAKE_CASE_							)



def       UpperCAmelCase__ (     )					->		List[Any]:

     with open(os.path.join(SCREAMING_SNAKE_CASE_				,   '__init__.py'							)				,   'r'				,   encoding='utf-8'				,   newline='\n'							) as f:
          __lowerCamelCase       :     Any        =		f.readlines()

     # Get to the point we do the actual imports for type checking
     __lowerCamelCase       :     List[str]        =		0
     while not lines[line_index].startswith('if TYPE_CHECKING'							):
          line_index += 1

     __lowerCamelCase       :     List[str]        =		{}
     # Go through the end of the file
     while line_index < len(SCREAMING_SNAKE_CASE_							):
          # If the line is an if is_backend_available, we grab all objects associated.
          __lowerCamelCase       :     List[str]        =		find_backend(lines[line_index]							)
          if backend is not None:
               while not lines[line_index].startswith('    else:'							):
                    line_index += 1
               line_index += 1

               __lowerCamelCase       :     List[Any]        =		[]
               # Until we unindent, add backend objects to the list
               while len(lines[line_index]							) <= 1 or lines[line_index].startswith(' ' * 8							):
                    __lowerCamelCase       :     Optional[int]        =		lines[line_index]
                    __lowerCamelCase       :     int        =		_re_single_line_import.search(SCREAMING_SNAKE_CASE_							)
                    if single_line_import_search is not None:
                         objects.extend(single_line_import_search.groups()[0].split(', '							)							)
                    elif line.startswith(' ' * 12							):
                         objects.append(line[12:-2]							)
                    line_index += 1

               __lowerCamelCase       :     List[str]        =		objects
          else:
               line_index += 1

     return backend_specific_objects



def       UpperCAmelCase__ (     UpperCAmelCase_   :    List[str]				,   UpperCAmelCase_   :    str							)					->		str:

     if name.isupper():
          return DUMMY_CONSTANT.format(SCREAMING_SNAKE_CASE_							)
     elif name.islower():
          return DUMMY_FUNCTION.format(SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_							)
     else:
          return DUMMY_CLASS.format(SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_							)



def       UpperCAmelCase__ (     UpperCAmelCase_   :    Union[str, Any]=None							)					->		Any:

     if backend_specific_objects is None:
          __lowerCamelCase       :     Dict        =		read_init()
     # For special correspondence backend to module name as used in the function requires_modulename
     __lowerCamelCase       :     List[str]        =		{}

     for backend, objects in backend_specific_objects.items():
          __lowerCamelCase       :     Union[str, Any]        =		"[" + ", ".join(F'\"{b}\"' for b in backend.split('_and_'							)							) + "]"
          __lowerCamelCase       :     Union[str, Any]        =		"# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
          dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
          dummy_file += "\n".join([create_dummy_object(SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_							) for o in objects]							)
          __lowerCamelCase       :     Optional[int]        =		dummy_file

     return dummy_files



def       UpperCAmelCase__ (     UpperCAmelCase_   :    List[str]=False							)					->		Optional[Any]:
     __lowerCamelCase       :     List[Any]        =		create_dummy_files()
     # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
     __lowerCamelCase       :     Optional[int]        =		{"torch": "pt"}

     # Locate actual dummy modules and read their content.
     __lowerCamelCase       :     Optional[int]        =		os.path.join(SCREAMING_SNAKE_CASE_				,   'utils'							)
     __lowerCamelCase       :     List[str]        =		{
         backend: os.path.join(SCREAMING_SNAKE_CASE_				,   F'dummy_{short_names.get(SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_							)}_objects.py'							)
         for backend in dummy_files.keys()
     }

     __lowerCamelCase       :     List[Any]        =		{}
     for backend, file_path in dummy_file_paths.items():
          if os.path.isfile(SCREAMING_SNAKE_CASE_							):
               with open(SCREAMING_SNAKE_CASE_				,   'r'				,   encoding='utf-8'				,   newline='\n'							) as f:
                    __lowerCamelCase       :     Optional[int]        =		f.read()
          else:
               __lowerCamelCase       :     Union[str, Any]        =		""

     for backend in dummy_files.keys():
          if dummy_files[backend] != actual_dummies[backend]:
               if overwrite:
                    print(
                        F'Updating transformers.utils.dummy_{short_names.get(SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_							)}_objects.py as the main '
                        '__init__ has new objects.'							)
                    with open(dummy_file_paths[backend]				,   'w'				,   encoding='utf-8'				,   newline='\n'							) as f:
                         f.write(dummy_files[backend]							)
               else:
                    raise ValueError(
                        'The main __init__ has objects that are not present in '
                        F'transformers.utils.dummy_{short_names.get(SCREAMING_SNAKE_CASE_				,   SCREAMING_SNAKE_CASE_							)}_objects.py. Run `make fix-copies` '
                        'to fix this.'							)


if __name__ == "__main__":
      A__		: int												=  argparse.ArgumentParser()
      parser.add_argument("""--fix_and_overwrite""", action="""store_true""", help="""Whether to fix inconsistencies.""")
      A__		: Tuple												=  parser.parse_args()

      check_dummies(args.fix_and_overwrite)










'''simple docstring'''



import torch

from transformers import AutoTokenizer





class        UpperCAmelCase_  (_UpperCAmelCase  ):





    """simple docstring"""






    def __init__(							self      ,					SCREAMING_SNAKE_CASE_     )    ->					int:
         __lowerCamelCase       :     Dict        =		AutoTokenizer.from_pretrained(SCREAMING_SNAKE_CASE_     )







    def 				lowercase_    (							self      ,					SCREAMING_SNAKE_CASE_     )    ->					int:

         if isinstance(SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_     ) and all(isinstance(_x      ,					SCREAMING_SNAKE_CASE_     ) for _x in x     ):
              __lowerCamelCase       :     Union[str, Any]        =		None
              for l in x:
                   __lowerCamelCase       :     Tuple        =		self.tokenizer(
                       SCREAMING_SNAKE_CASE_      ,					padding='max_length'      ,					max_length=3_84      ,					truncation=SCREAMING_SNAKE_CASE_      ,					return_tensors='pt'      ,					)
                   __lowerCamelCase       :     str        =		torch.tensor([len(SCREAMING_SNAKE_CASE_     )]     )
                   if d is not None:
                        for k in d.keys():
                             __lowerCamelCase       :     List[Any]        =		torch.cat((d[k], t[k])      ,					0     )
                   else:
                        __lowerCamelCase       :     str        =		t

              __lowerCamelCase       :     List[Any]        =		torch.tensor(self.tokenizer.convert_tokens_to_ids('[E]'     )     )
              __lowerCamelCase       :     Tuple        =		torch.tensor(self.tokenizer.convert_tokens_to_ids('[/E]'     )     )

         elif isinstance(SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_     ) and all(isinstance(_x      ,					SCREAMING_SNAKE_CASE_     ) for _x in x     ):
              __lowerCamelCase       :     Optional[Any]        =		self.tokenizer(
                  SCREAMING_SNAKE_CASE_      ,					padding='max_length'      ,					max_length=3_84      ,					truncation=SCREAMING_SNAKE_CASE_      ,					return_tensors='pt'      ,					)

         else:
              raise Exception(
                  'Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of'
                  ' strings` for supports are supported.'     )

         return d







    def 				lowercase_    (							self      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_      ,					SCREAMING_SNAKE_CASE_=0.7_0     )    ->					str:
         __lowerCamelCase       :     str        =		[]
         for idx in range(len(W_query['input_ids']     )     ):
              __lowerCamelCase       :     Optional[Any]        =		range(p_start.shape[1]     )

              __lowerCamelCase       :     List[Any]        =		[]
              for start_id in start_indexes:
                   for end_id in end_indexes:
                        if start_id < end_id:
                             output.append(
                                 (
                                     start_id,
                                     end_id,
                                     p_start[idx][start_id].item(),
                                     p_end[idx][end_id].item(),
                                 )     )

              output.sort(key=lambda SCREAMING_SNAKE_CASE_     : (tup[2] * tup[3])      ,					reverse=SCREAMING_SNAKE_CASE_     )
              __lowerCamelCase       :     str        =		[]
              for k in range(len(SCREAMING_SNAKE_CASE_     )     ):
                   if output[k][2] * output[k][3] >= thresh:
                        __lowerCamelCase    ,	__lowerCamelCase       :     Union[str, Any]        =		output[k][0], output[k][1]
                        __lowerCamelCase       :     List[str]        =		self.tokenizer.decode(W_query['input_ids'][idx][c_start_pos:c_end_pos]     )
                        temp.append((decoded, output[k][2] * output[k][3])     )

              final_outputs.append(SCREAMING_SNAKE_CASE_     )

         return final_outputs






