"""simple docstring"""




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase      :			Dict							       =		logging.get_logger(__name__)

__lowerCamelCase      :			Optional[Any]							       =		{'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}







class __snake_case    (						lowerCamelCase_		):
   lowerCAmelCase_														=							"ctrl"
   lowerCAmelCase_														=							["past_key_values"]
   lowerCAmelCase_														=							{
       "max_position_embeddings": "n_positions",
       "hidden_size": "n_embd",
       "num_attention_heads": "n_head",
       "num_hidden_layers": "n_layer",
   }




   def __init__(   self      :    Optional[Any]	,     _lowercase      :    Tuple=24_65_34	,     _lowercase      :    Union[str, Any]=2_56	,     _lowercase      :    Any=12_80	,     _lowercase      :    str=81_92	,     _lowercase      :    Optional[Any]=48	,     _lowercase      :    int=16	,     _lowercase      :    int=0.1	,     _lowercase      :    str=0.1	,     _lowercase      :    Any=1E-6	,     _lowercase      :    List[Any]=0.02	,     _lowercase      :    int=True	,     **_lowercase      :    List[Any]	,     ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__      							=				vocab_size
     SCREAMING_SNAKE_CASE__      							=				n_positions
     SCREAMING_SNAKE_CASE__      							=				n_embd
     SCREAMING_SNAKE_CASE__      							=				n_layer
     SCREAMING_SNAKE_CASE__      							=				n_head
     SCREAMING_SNAKE_CASE__      							=				dff
     SCREAMING_SNAKE_CASE__      							=				resid_pdrop
     SCREAMING_SNAKE_CASE__      							=				embd_pdrop
     SCREAMING_SNAKE_CASE__      							=				layer_norm_epsilon
     SCREAMING_SNAKE_CASE__      							=				initializer_range

     SCREAMING_SNAKE_CASE__      							=				use_cache

     super().__init__(**_lowercase				)

import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
   __lowerCamelCase      :			Optional[Any]							       =		{
       '''linear''': PIL.Image.Resampling.BILINEAR,
       '''bilinear''': PIL.Image.Resampling.BILINEAR,
       '''bicubic''': PIL.Image.Resampling.BICUBIC,
       '''lanczos''': PIL.Image.Resampling.LANCZOS,
       '''nearest''': PIL.Image.Resampling.NEAREST,
   }
else:
   __lowerCamelCase      :			int							       =		{
       '''linear''': PIL.Image.LINEAR,
       '''bilinear''': PIL.Image.BILINEAR,
       '''bicubic''': PIL.Image.BICUBIC,
       '''lanczos''': PIL.Image.LANCZOS,
       '''nearest''': PIL.Image.NEAREST,
   }



def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> Optional[Any]:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__      							=				(images / 2 + 0.5).clamp(0			,					1     )
  SCREAMING_SNAKE_CASE__      							=				images.cpu().permute(0			,					2			,					3			,					1     ).float().numpy()
  SCREAMING_SNAKE_CASE__      							=				numpy_to_pil(__UpperCamelCase     )
  return images






def      __SCREAMING_SNAKE_CASE  ( __UpperCamelCase   :	int     )							-> int:







  """simple docstring"""





  if images.ndim == 3:
    SCREAMING_SNAKE_CASE__      							=				images[None, ...]
  SCREAMING_SNAKE_CASE__      							=				(images * 2_55).round().astype("""uint8"""     )
  if images.shape[-1] == 1:
    # special case for grayscale (single channel) images
    SCREAMING_SNAKE_CASE__      							=				[Image.fromarray(image.squeeze()			,					mode="""L"""     ) for image in images]
  else:
    SCREAMING_SNAKE_CASE__      							=				[Image.fromarray(__UpperCamelCase     ) for image in images]

  return pil_images
