code: 
  
  
  
  from ..utils import deprecate
  from .attention_processor import (  # noqa: F401
      Attention,
      AttentionProcessor,
      AttnAddedKVProcessor,
      AttnProcessor2_0,
      LoRAAttnProcessor,
      LoRALinearLayer,
      LoRAXFormersAttnProcessor,
      SlicedAttnAddedKVProcessor,
      SlicedAttnProcessor,
      XFormersAttnProcessor,
  )
  from .attention_processor import AttnProcessor as AttnProcessorRename  # noqa: F401
  
  
  deprecate(
      'cross_attention',
      '0.20.0',
      'Importing from cross_attention is deprecated. Please import from diffusers.models.attention_processor instead.',
      standard_warn=False,
  )
  
  
  a__						:			List[Any]										=			AttentionProcessor
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Dict:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Optional[int]:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Optional[Any]:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Dict:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Union[str, Any]:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Dict:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							List[str]:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  class        UpperCAmelCase__  (    A__):
  
  
  
   def __init__(  self		,	*lowercase		,	**lowercase			)  ->							Dict:
    __UpperCamelCase				      =  f"{self.__class__.__name__} is deprecated and will be removed in `0.20.0`. Please use `from diffusers.models.attention_processor import {''.join(self.__class__.__name__.split('Cross'			)			)} instead."
    deprecate("""cross_attention"""		,	"""0.20.0"""		,	_lowerCAmelCase		,	standard_warn=_lowerCAmelCase			)
    super().__init__(*_lowerCAmelCase		,	**_lowerCAmelCase			)
  
  
  
  
  
  
style_context: 
  
  
  
  '''simple docstring'''
  
  
  
  import textwrap
  
  import pyarrow as pa
  import pytest
  
  from datasets import Features, Image
  from datasets.packaged_modules.text.text import Text
  
  from ..utils import require_pil
  
  
  
  
  
  
  
  @pytest.fixture
  def _lowercase   (  __A       ):
  
  
  
   '''simple docstring'''
  
  
  
   __UpperCamelCase				      =  tmp_path / """text.txt"""
   __UpperCamelCase				      =  textwrap.dedent(
       """\
          Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
          Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
          Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
          Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
  
          Second paragraph:
          Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.
          Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.
          Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur.
          Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.
          """       )
   with open(__A							,"""w"""							,encoding="""utf-8"""       ) as f:
    f.write(__A       )
   return str(__A       )
  
  
  
  
  
  
  
  @pytest.fixture
  def _lowercase   (  __A							,__A       ):
  
  
  
   '''simple docstring'''
  
  
  
   __UpperCamelCase				      =  tmp_path / """text_with_image.txt"""
   with open(__A							,"""w"""							,encoding="""utf-8"""       ) as f:
    f.write(__A       )
   return str(__A       )
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""keep_linebreaks"""							,[True, False]       )
  def _lowercase   (  __A							,__A       ):
  
  
  
   '''simple docstring'''
  
  
  
   with open(__A							,encoding="""utf-8"""       ) as f:
    __UpperCamelCase				      =  f.read().splitlines(keepends=__A       )
   __UpperCamelCase				      =  Text(keep_linebreaks=__A							,encoding="""utf-8"""       )
   __UpperCamelCase				      =  text._generate_tables([[text_file]]       )
   __UpperCamelCase				      =  pa.concat_tables([table for _, table in generator]       ).to_pydict()["""text"""]
   assert generated_content == expected_content
  
  
  
  
  
  
  
  @require_pil
  def _lowercase   (  __A       ):
  
  
  
   '''simple docstring'''
  
  
  
   with open(__A							,encoding="""utf-8"""       ) as f:
    __UpperCamelCase				      =  f.read().splitlines()[0]
   __UpperCamelCase				      =  Text(encoding="""utf-8"""							,features=Features({"""image""": Image()}       )       )
   __UpperCamelCase				      =  text._generate_tables([[text_file_with_image]]       )
   __UpperCamelCase				      =  pa.concat_tables([table for _, table in generator]       )
   assert pa_table.schema.field("""image"""       ).type == Image()()
   __UpperCamelCase				      =  pa_table.to_pydict()["""image"""]
   assert generated_content == [{"path": image_file, "bytes": None}]
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""sample_by"""							,["""line""", """paragraph""", """document"""]       )
  def _lowercase   (  __A							,__A       ):
  
  
  
   '''simple docstring'''
  
  
  
   with open(__A							,encoding="""utf-8"""       ) as f:
    __UpperCamelCase				      =  f.read()
   if sample_by == "line":
    __UpperCamelCase				      =  expected_content.splitlines()
   elif sample_by == "paragraph":
    __UpperCamelCase				      =  expected_content.split("""\n\n"""       )
   elif sample_by == "document":
    __UpperCamelCase				      =  [expected_content]
   __UpperCamelCase				      =  Text(sample_by=__A							,encoding="""utf-8"""							,chunksize=100       )
   __UpperCamelCase				      =  text._generate_tables([[text_file]]       )
   __UpperCamelCase				      =  pa.concat_tables([table for _, table in generator]       ).to_pydict()["""text"""]
   assert generated_content == expected_content
  
  
  
  
  
  