


'''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
__lowercase	:						Tuple       =	'src/diffusers'

# Matches is_xxx_available()
__lowercase	:						Tuple       =	re.compile(R'is\_([a-z_]*)_available\(\)')
# Matches from xxx import bla
__lowercase	:						List[str]       =	re.compile(R'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')


__lowercase	:						Optional[Any]       =	'\n{0} = None\n'

__lowercase	:						Tuple       =	'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, {1})\n'


__lowercase	:						Dict       =	'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Any   ):
					__a			:       Union[str, Any]					    =  _re_backend.findall(_SCREAMING_SNAKE_CASE   )
					if len(_SCREAMING_SNAKE_CASE   ) == 0:
										return None

					return "_and_".join(_SCREAMING_SNAKE_CASE   )






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

					# Get to the point we do the actual imports for type checking
					__a			:       Any					    =  0
					__a			:       Union[str, Any]					    =  {}
					# Go through the end of the file
					while line_index < len(_SCREAMING_SNAKE_CASE   ):
										# If the line contains is_backend_available, we grab all objects associated with the `else` block
										__a			:       Tuple					    =  find_backend(lines[line_index]   )
										if backend is not None:
															while not lines[line_index].startswith('else:'   ):
																				line_index += 1
															line_index += 1
															__a			:       Union[str, Any]					    =  []
															# Until we unindent, add backend objects to the list
															while line_index < len(_SCREAMING_SNAKE_CASE   ) and len(lines[line_index]   ) > 1:
																				__a			:       List[str]					    =  lines[line_index]
																				__a			:       Optional[Any]					    =  _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(' ' * 8   ):
																									objects.append(line[8:-2]   )
																				line_index += 1

															if len(_SCREAMING_SNAKE_CASE   ) > 0:
																				__a			:       List[str]					    =  objects
										else:
															line_index += 1

					return backend_specific_objects






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   int						,      _SCREAMING_SNAKE_CASE      :   Dict   ):
					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   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   Tuple=None   ):
					if backend_specific_objects is None:
										__a			:       List[str]					    =  read_init()
					# For special correspondence backend to module name as used in the function requires_modulename
					__a			:       Optional[int]					    =  {}

					for backend, objects in backend_specific_objects.items():
										__a			:       int					    =  '[' + ', '.join(F"""\"{b}\"""" for b in backend.split('_and_'   )   ) + ']'
										__a			:       str					    =  '# 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]   )
										__a			:       Optional[int]					    =  dummy_file

					return dummy_files






def   lowerCamelCase							(_SCREAMING_SNAKE_CASE      :   List[str]=False   ):
					__a			:       Any					    =  create_dummy_files()
					# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
					__a			:       Any					    =  {'torch': 'pt'}

					# Locate actual dummy modules and read their content.
					__a			:       Optional[Any]					    =  os.path.join(_SCREAMING_SNAKE_CASE						,      'utils'   )
					__a			:       List[Any]					    =  {
					    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()
					}

					__a			:       int					    =  {}
					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:
																				__a			:       str					    =  f.read()
										else:
															__a			:       Any					    =  ''

					for backend in dummy_files.keys():
										if dummy_files[backend] != actual_dummies[backend]:
															if overwrite:
																				print(
																				    F"""Updating diffusers.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"""diffusers.utils.dummy_{short_names.get(_SCREAMING_SNAKE_CASE						,      _SCREAMING_SNAKE_CASE   )}_objects.py. Run `make fix-copies` """
																				    'to fix this.'   )


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

	check_dummies(args.fix_and_overwrite)







'''simple docstring'''



import torch

from transformers import AutoModel





class 							__UpperCamelCase				(		torch.nn.Module					):




	def __init__(   self						,				__a="sayef/fsner-bert-base-uncased"							):

						'''simple docstring'''





						super(__a						,				self							).__init__()

						__a			:       Tuple					    =  AutoModel.from_pretrained(__a						,				return_dict=__a							)
						__a			:       int					    =  torch.nn.CosineSimilarity(3						,				1E-0_8							)
						__a			:       Union[str, Any]					    =  torch.nn.Softmax(dim=1							)




	def       __UpperCAmelCase							(   self						,				**__a							):

						'''simple docstring'''





						return self.bert(**__a							).last_hidden_state




	def       __UpperCAmelCase							(   self						,				__a							):

						'''simple docstring'''





						return token_embeddings.sum(2						,				keepdim=__a							)




	def       __UpperCAmelCase							(   self						,				__a						,				__a						,				__a=1							):

						'''simple docstring'''





						return self.softmax(T * self.cos(__a						,				__a							)							)





	def       __UpperCAmelCase							(   self						,				__a						,				__a							):

						'''simple docstring'''





						__a			:       str					    =  W_supports['sizes'].tolist()
						__a			:       Union[str, Any]					    =  W_supports['start_token_id'].item()
						__a			:       Any					    =  W_supports['end_token_id'].item()

						del W_supports["sizes"]
						del W_supports["start_token_id"]
						del W_supports["end_token_id"]

						__a			:       Tuple					    =  self.BERT(**__a							)
						__a			:       str					    =  self.BERT(**__a							)

						__a			:       Any					    =  None
						__a			:       Dict					    =  None

						__a			:       Dict					    =  W_supports['input_ids'] == start_token_id
						__a			:       Union[str, Any]					    =  W_supports['input_ids'] == end_token_id

						for i, size in enumerate(__a							):
											if i == 0:
																__a			:       Optional[int]					    =  0
											else:
																__a			:       Union[str, Any]					    =  support_sizes[i - 1]

											__a			:       int					    =  S[s : s + size][start_token_masks[s : s + size]]
											__a			:       Union[str, Any]					    =  S[s : s + size][end_token_masks[s : s + size]]

											__a			:       Tuple					    =  torch.matmul(q[i]						,				s_start.T							).sum(1							).softmax(0							)
											__a			:       Dict					    =  torch.matmul(q[i]						,				s_end.T							).sum(1							).softmax(0							)

											if p_starts is not None:
																__a			:       str					    =  torch.vstack((p_starts, p_start)							)
																__a			:       str					    =  torch.vstack((p_ends, p_end)							)
											else:
																__a			:       List[str]					    =  p_start
																__a			:       int					    =  p_end

						return p_starts, p_ends



