




"""simple docstring"""






import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel

from ...models.attention import BasicTransformerBlock
from ...utils import logging


lowercase__     						=						logging.get_logger(__name__)  # pylint: disable=invalid-name






class lowerCAmelCase__	(     lowercase						):






			'''simple docstring'''



			def __init__(  self  ,      lowercase  ,      lowercase=768  ):
							super().__init__(lowercase  )
							_lowerCamelCase     :			Any    =    proj_size

							_lowerCamelCase     :			Dict    =    CLIPVisionModel(lowercase  )
							_lowerCamelCase     :			List[str]    =    PaintByExampleMapper(lowercase  )
							_lowerCamelCase     :			Optional[Any]    =    nn.LayerNorm(config.hidden_size  )
							_lowerCamelCase     :			int    =    nn.Linear(config.hidden_size  ,      self.proj_size  )

							# uncondition for scaling
							_lowerCamelCase     :			str    =    nn.Parameter(torch.randn((1, 1, self.proj_size)  )  )






			def 					A_    (  self  ,      lowercase  ,      lowercase=False  ):
							_lowerCamelCase     :			Union[str, Any]    =    self.model(pixel_values=lowercase  )
							_lowerCamelCase     :			int    =    clip_output.pooler_output
							_lowerCamelCase     :			str    =    self.mapper(latent_states[:, None]  )
							_lowerCamelCase     :			List[Any]    =    self.final_layer_norm(lowercase  )
							_lowerCamelCase     :			Dict    =    self.proj_out(lowercase  )
							if return_uncond_vector:
											return latent_states, self.uncond_vector

							return latent_states






class lowerCAmelCase__	(     nn.Module						):






			'''simple docstring'''



			def __init__(  self  ,      lowercase  ):
							super().__init__()
							_lowerCamelCase     :			Tuple    =    (config.num_hidden_layers + 1) // 5
							_lowerCamelCase     :			int    =    config.hidden_size
							_lowerCamelCase     :			Optional[Any]    =    1
							_lowerCamelCase     :			str    =    nn.ModuleList(
							    [
							        BasicTransformerBlock(lowercase  ,      lowercase  ,      lowercase  ,      activation_fn='gelu'  ,      attention_bias=lowercase  )
							        for _ in range(lowercase  )
							    ]  )






			def 					A_    (  self  ,      lowercase  ):
							for block in self.blocks:
											_lowerCamelCase     :			Tuple    =    block(lowercase  )

							return hidden_states





"""simple docstring"""






def      _snake_case			(				lowercase__		):
				if not isinstance(lowercase__							,    lowercase__		):
								raise ValueError('Input series is not valid, valid series - [2, 4, 6]'		)
				if len(lowercase__		) == 0:
								raise ValueError('Input list must be a non empty list'		)
				if len(lowercase__		) == 1:
								return True
				_lowerCamelCase     :			List[Any]    =    series[1] - series[0]
				for index in range(len(lowercase__		) - 1		):
								if series[index + 1] - series[index] != common_diff:
												return False
				return True







def      _snake_case			(				lowercase__		):
				if not isinstance(lowercase__							,    lowercase__		):
								raise ValueError('Input series is not valid, valid series - [2, 4, 6]'		)
				if len(lowercase__		) == 0:
								raise ValueError('Input list must be a non empty list'		)
				_lowerCamelCase     :			Optional[int]    =    0
				for val in series:
								answer += val
				return answer / len(lowercase__		)


if __name__ == "__main__":
			import doctest

			doctest.testmod()