



'''simple docstring'''




from __future__ import annotations



def       a     (					lowerCamelCase__		, lowerCamelCase__       ):
			'''simple docstring'''





			A_      :		Optional[int]      =	[]
			A_      :		List[Any]      =	[]
			A_      :		str      =	0
			A_      :		Union[str, Any]      =	sum(__lowerCAmelCase       )
			create_state_space_tree(__lowerCAmelCase		, __lowerCAmelCase		, __lowerCAmelCase		, __lowerCAmelCase		, __lowerCAmelCase		, __lowerCAmelCase       )
			return result



def       a     (					lowerCamelCase__		, lowerCamelCase__		, lowerCamelCase__		, lowerCamelCase__		, lowerCamelCase__		, lowerCamelCase__		, ):
			'''simple docstring'''





			if sum(__lowerCAmelCase       ) > max_sum or (remaining_nums_sum + sum(__lowerCAmelCase       )) < max_sum:
						return
			if sum(__lowerCAmelCase       ) == max_sum:
						result.append(__lowerCAmelCase       )
						return
			for index in range(__lowerCAmelCase		, len(__lowerCAmelCase       )       ):
						create_state_space_tree(
						    __lowerCAmelCase		, __lowerCAmelCase		, index + 1		, [*path, nums[index]]		, __lowerCAmelCase		, remaining_nums_sum - nums[index]		, )
lowerCamelCase				:Tuple							       =   [3, 3_4, 4, 1_2, 5, 2]
lowerCamelCase				:Optional[Any]							       =   9
lowerCamelCase				:List[Any]							       =   generate_sum_of_subsets_soln(nums, max_sum)

print(*result)





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

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


__magic_name__  :  List[str]					=       logging.get_logger(__name__)  # pylint: disable=invalid-name





class     SCREAMING_SNAKE_CASE__		(_a			):
     def __init__(						self	:		List[Any]       ,						__lowerCamelCase	:		Tuple       ,						__lowerCamelCase	:		List[Any]=7_68						):



       """simple docstring"""
       super().__init__(__lowerCamelCase						)
       lowerCAmelCase__										=      proj_size

       lowerCAmelCase__										=      CLIPVisionModel(__lowerCamelCase						)
       lowerCAmelCase__										=      PaintByExampleMapper(__lowerCamelCase						)
       lowerCAmelCase__										=      nn.LayerNorm(config.hidden_size						)
       lowerCAmelCase__										=      nn.Linear(config.hidden_size       ,						self.proj_size						)

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



     def        A__      (						self	:		Tuple       ,						__lowerCamelCase	:		int       ,						__lowerCamelCase	:		str=False						):



       """simple docstring"""
       lowerCAmelCase__										=      self.model(pixel_values=__lowerCamelCase						)
       lowerCAmelCase__										=      clip_output.pooler_output
       lowerCAmelCase__										=      self.mapper(latent_states[:, None]						)
       lowerCAmelCase__										=      self.final_layer_norm(__lowerCamelCase						)
       lowerCAmelCase__										=      self.proj_out(__lowerCamelCase						)
       if return_uncond_vector:
         return latent_states, self.uncond_vector

       return latent_states





class     SCREAMING_SNAKE_CASE__		(nn.Module			):
     def __init__(						self	:		Optional[Any]       ,						__lowerCamelCase	:		Tuple						):



       """simple docstring"""
       super().__init__()
       lowerCAmelCase__										=      (config.num_hidden_layers + 1) // 5
       lowerCAmelCase__										=      config.hidden_size
       lowerCAmelCase__										=      1
       lowerCAmelCase__										=      nn.ModuleList(
           [
               BasicTransformerBlock(__lowerCamelCase       ,						__lowerCamelCase       ,						__lowerCamelCase       ,						activation_fn='''gelu'''       ,						attention_bias=__lowerCamelCase						)
               for _ in range(__lowerCamelCase						)
           ]						)



     def        A__      (						self	:		str       ,						__lowerCamelCase	:		Optional[Any]						):



       """simple docstring"""
       for block in self.blocks:
         lowerCAmelCase__										=      block(__lowerCamelCase						)

       return hidden_states

