


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
lowerCamelCase		   =			'src/diffusers'

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


lowerCamelCase		   =			'\n{0} = None\n'

lowerCamelCase		   =			'\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'


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




def       a_ (       SCREAMING_SNAKE_CASE__   : int	):
       '''simple docstring'''





       _lowerCamelCase			:						int            =_re_backend.findall(SCREAMING_SNAKE_CASE__	)
       if len(SCREAMING_SNAKE_CASE__	) == 0:
              return None

       return "_and_".join(SCREAMING_SNAKE_CASE__	)




def       a_ (       ):
       '''simple docstring'''





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

       # Get to the point we do the actual imports for type checking
       _lowerCamelCase			:						Any            =0
       _lowerCamelCase			:						Optional[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
              _lowerCamelCase			:						Optional[Any]            =find_backend(lines[line_index]	)
              if backend is not None:
                     while not lines[line_index].startswith('else:'	):
                            line_index += 1
                     line_index += 1
                     _lowerCamelCase			:						Optional[Any]            =[]
                     # Until we unindent, add backend objects to the list
                     while line_index < len(SCREAMING_SNAKE_CASE__	) and len(lines[line_index]	) > 1:
                            _lowerCamelCase			:						Tuple            =lines[line_index]
                            _lowerCamelCase			:						List[str]            =_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:
                            _lowerCamelCase			:						Optional[int]            =objects
              else:
                     line_index += 1

       return backend_specific_objects




def       a_ (       SCREAMING_SNAKE_CASE__   : str						,     SCREAMING_SNAKE_CASE__   : Optional[Any]	):
       '''simple docstring'''





       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       a_ (       SCREAMING_SNAKE_CASE__   : int=None	):
       '''simple docstring'''





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

       for backend, objects in backend_specific_objects.items():
              _lowerCamelCase			:						Tuple            ='[' + ', '.join(F'''"{b}"''' for b in backend.split('_and_'	)	) + ']'
              _lowerCamelCase			:						Optional[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			:						Any            =dummy_file

       return dummy_files




def       a_ (       SCREAMING_SNAKE_CASE__   : List[Any]=False	):
       '''simple docstring'''





       _lowerCamelCase			:						int            =create_dummy_files()
       # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
       _lowerCamelCase			:						List[Any]            ={'torch': 'pt'}

       # Locate actual dummy modules and read their content.
       _lowerCamelCase			:						List[str]            =os.path.join(SCREAMING_SNAKE_CASE__						,     'utils'	)
       _lowerCamelCase			:						Union[str, 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()
       }

       _lowerCamelCase			:						List[str]            ={}
       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			:						Union[str, Any]            =f.read()
              else:
                     _lowerCamelCase			:						Dict            =''

       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__":
 lowerCamelCase		   =			argparse.ArgumentParser()
 parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
 lowerCamelCase		   =			parser.parse_args()

 check_dummies(args.fix_and_overwrite)






import time
import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device

from ..test_modeling_common import ids_tensor


if is_torch_available():
 import torch

 from transformers.generation import (
     MaxLengthCriteria,
     MaxNewTokensCriteria,
     MaxTimeCriteria,
     StoppingCriteriaList,
     validate_stopping_criteria,
 )




@require_torch
class A    (  unittest.TestCase	):






      def 			lowerCamelCase			(   self		:	Optional[int]     ,  lowercase_		:	int					)   ->		Optional[int]:
             """simple docstring"""




             _lowerCamelCase			:						List[str]            =3
             _lowerCamelCase			:						Dict            =250

             _lowerCamelCase			:						Tuple            =ids_tensor((batch_size, length)     ,  lowercase_					)
             _lowerCamelCase			:						str            =torch.ones((batch_size, length)     ,  device=lowercase_     ,  dtype=torch.float					) / length
             return input_ids, scores






      def 			lowerCamelCase			(   self		:	Optional[int]					)   ->		Optional[Any]:
             """simple docstring"""




             _lowerCamelCase      ,	_lowerCamelCase			:						Optional[Any]            =self._get_tensors(5					)

             _lowerCamelCase			:						Dict            =StoppingCriteriaList(
                 [
                     MaxLengthCriteria(max_length=10					),
                     MaxTimeCriteria(max_time=0.1					),
                 ]					)

             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase      ,	_lowerCamelCase			:						List[str]            =self._get_tensors(9					)
             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase      ,	_lowerCamelCase			:						Optional[int]            =self._get_tensors(10					)
             self.assertTrue(criteria(lowercase_     ,  lowercase_					)					)






      def 			lowerCamelCase			(   self		:	Optional[int]					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Any            =MaxLengthCriteria(max_length=10					)

             _lowerCamelCase      ,	_lowerCamelCase			:						List[str]            =self._get_tensors(5					)
             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase      ,	_lowerCamelCase			:						Optional[int]            =self._get_tensors(9					)
             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase      ,	_lowerCamelCase			:						Optional[int]            =self._get_tensors(10					)
             self.assertTrue(criteria(lowercase_     ,  lowercase_					)					)






      def 			lowerCamelCase			(   self		:	List[str]					)   ->		Tuple:
             """simple docstring"""




             _lowerCamelCase			:						Union[str, Any]            =MaxNewTokensCriteria(start_length=5     ,  max_new_tokens=5					)

             _lowerCamelCase      ,	_lowerCamelCase			:						str            =self._get_tensors(5					)
             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase      ,	_lowerCamelCase			:						Union[str, Any]            =self._get_tensors(9					)
             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase      ,	_lowerCamelCase			:						Dict            =self._get_tensors(10					)
             self.assertTrue(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase			:						Optional[Any]            =StoppingCriteriaList([criteria]					)
             self.assertEqual(criteria_list.max_length     ,  10					)






      def 			lowerCamelCase			(   self		:	Optional[Any]					)   ->		str:
             """simple docstring"""




             _lowerCamelCase      ,	_lowerCamelCase			:						Optional[Any]            =self._get_tensors(5					)

             _lowerCamelCase			:						Tuple            =MaxTimeCriteria(max_time=0.1					)
             self.assertFalse(criteria(lowercase_     ,  lowercase_					)					)

             _lowerCamelCase			:						int            =MaxTimeCriteria(max_time=0.1     ,  initial_timestamp=time.time() - 0.2					)
             self.assertTrue(criteria(lowercase_     ,  lowercase_					)					)






      def 			lowerCamelCase			(   self		:	Optional[int]					)   ->		Optional[int]:
             """simple docstring"""




             validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10					)]					)     ,  10					)

             with self.assertWarns(lowercase_					):
                    validate_stopping_criteria(StoppingCriteriaList([MaxLengthCriteria(10					)]					)     ,  11					)

             _lowerCamelCase			:						Optional[Any]            =validate_stopping_criteria(StoppingCriteriaList()     ,  11					)

             self.assertEqual(len(lowercase_					)     ,  1					)


