


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

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


lowerCAmelCase__			:      Optional[int]								=logging.get_logger(__name__)  # pylint: disable=invalid-name







class 	__lowercase    (__SCREAMING_SNAKE_CASE  ):





							"""simple docstring"""







							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__=7_6_8       ):





										"""simple docstring"""




										super().__init__(lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Tuple					=					proj_size

										SCREAMING_SNAKE_CASE_		:     int					=					CLIPVisionModel(lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     str					=					PaintByExampleMapper(lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					nn.LayerNorm(config.hidden_size       )
										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					nn.Linear(config.hidden_size			,						self.proj_size       )

										# uncondition for scaling
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					nn.Parameter(torch.randn((1, 1, self.proj_size)       )       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__=False       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     str					=					self.model(pixel_values=lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     List[str]					=					clip_output.pooler_output
										SCREAMING_SNAKE_CASE_		:     Dict					=					self.mapper(latent_states[:, None]       )
										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.final_layer_norm(lowerCAmelCase__       )
										SCREAMING_SNAKE_CASE_		:     Tuple					=					self.proj_out(lowerCAmelCase__       )
										if return_uncond_vector:
													return latent_states, self.uncond_vector

										return latent_states







class 	__lowercase    (nn.Module  ):





							"""simple docstring"""







							def __init__(      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




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






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										for block in self.blocks:
													SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					block(lowerCAmelCase__       )

										return hidden_states












'''simple docstring'''






from ..utils import DummyObject, requires_backends




class 					UpperCAmelCase	(     metaclass=snake_case_  ):
      _lowercase:     List[Any]			=  ['''torch''', '''scipy''']




      def __init__(     self     :					Tuple     ,     *__snake_case     :					Dict     ,     **__snake_case     :					List[str]    )							-> str:
            requires_backends(self     ,     ["""torch""", """scipy"""]    )




      @classmethod
      def 							lowercase__       (     cls     :					str     ,     *__snake_case     :					List[str]     ,     **__snake_case     :					str    )							-> Tuple:
            requires_backends(cls     ,     ["""torch""", """scipy"""]    )




      @classmethod
      def 							lowercase__       (     cls     :					Optional[int]     ,     *__snake_case     :					int     ,     **__snake_case     :					Union[str, Any]    )							-> Optional[int]:
            requires_backends(cls     ,     ["""torch""", """scipy"""]    )






