

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

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


lowerCAmelCase     :   Dict						     =  logging.get_logger(__name__)  # pylint: disable=invalid-name
class  _A		(  __magic_name__):

  def __init__(				self ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE=768					):





        """simple docstring"""







        super().__init__(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  List[str]           =     proj_size

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

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



  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE=False					):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_				:  Any           =     self.model(pixel_values=_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  List[str]           =     clip_output.pooler_output
        SCREAMING_SNAKE_CASE_				:  List[str]           =     self.mapper(latent_states[:, None]					)
        SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     self.final_layer_norm(_SCREAMING_SNAKE_CASE					)
        SCREAMING_SNAKE_CASE_				:  int           =     self.proj_out(_SCREAMING_SNAKE_CASE					)
        if return_uncond_vector:
              return latent_states, self.uncond_vector

        return latent_states

class  _A		(  nn.Module):

  def __init__(				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        super().__init__()
        SCREAMING_SNAKE_CASE_				:  Dict           =     (config.num_hidden_layers + 1) // 5
        SCREAMING_SNAKE_CASE_				:  str           =     config.hidden_size
        SCREAMING_SNAKE_CASE_				:  Dict           =     1
        SCREAMING_SNAKE_CASE_				:  List[Any]           =     nn.ModuleList(
            [
                BasicTransformerBlock(_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE ,					_SCREAMING_SNAKE_CASE ,					activation_fn='gelu' ,					attention_bias=_SCREAMING_SNAKE_CASE					)
                for _ in range(_SCREAMING_SNAKE_CASE					)
            ]					)



  def  UpperCAmelCase    (				self ,					_SCREAMING_SNAKE_CASE					):





        """simple docstring"""







        for block in self.blocks:
              SCREAMING_SNAKE_CASE_				:  Any           =     block(_SCREAMING_SNAKE_CASE					)

        return hidden_states









def    A_  (							a  ):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  List[Any]           =     0
      while num > 0:
            digit_sum += num % 1_0
            num //= 1_0
      return digit_sum

def    A_  (							a = 1_0_0  ):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_				:  List[str]           =     1
      SCREAMING_SNAKE_CASE_				:  Union[str, Any]           =     2

      for i in range(2					,   max_n + 1  ):
            SCREAMING_SNAKE_CASE_				:  List[str]           =     pre_numerator
            SCREAMING_SNAKE_CASE_				:  str           =     2 * i // 3 if i % 3 == 0 else 1
            SCREAMING_SNAKE_CASE_				:  Tuple           =     cur_numerator
            SCREAMING_SNAKE_CASE_				:  Tuple           =     e_cont * pre_numerator + temp

      return sum_digits(a  )


if __name__ == "__main__":
    print(F'{solution() = }')






