

"""simple docstring"""



import flax.linen as nn
import jax
import jax.numpy as jnp



class 					a						(       nn.Module				):



    """simple docstring"""



    UpperCAmelCase						 =					42
    UpperCAmelCase						 =					jnp.floataa

    def 				UpperCamelCase	(     self: Any       ):






         """simple docstring"""


         A__										=  nn.Conv(
             self.out_channels    ,						kernel_size=(3, 3)    ,						strides=(1, 1)    ,						padding=((1, 1), (1, 1))    ,						dtype=self.dtype    ,						)





    def __call__(     self: Dict    ,						UpperCamelCase: Tuple       ):






         """simple docstring"""


         A__			,				A__			,				A__			,				A__										=  hidden_states.shape
         A__										=  jax.image.resize(
             UpperCamelCase    ,						shape=(batch, height * 2, width * 2, channels)    ,						method="""nearest"""    ,						)
         A__										=  self.conv(UpperCamelCase       )
         return hidden_states



class 					a						(       nn.Module				):



    """simple docstring"""



    UpperCAmelCase						 =					42
    UpperCAmelCase						 =					jnp.floataa

    def 				UpperCamelCase	(     self: Optional[int]       ):






         """simple docstring"""


         A__										=  nn.Conv(
             self.out_channels    ,						kernel_size=(3, 3)    ,						strides=(2, 2)    ,						padding=((1, 1), (1, 1))    ,						dtype=self.dtype    ,						)





    def __call__(     self: List[Any]    ,						UpperCamelCase: List[str]       ):






         """simple docstring"""


         A__										=  self.conv(UpperCamelCase       )
         return hidden_states



class 					a						(       nn.Module				):



    """simple docstring"""



    UpperCAmelCase						 =					42
    UpperCAmelCase						 =					None
    UpperCAmelCase						 =					0.0
    UpperCAmelCase						 =					None
    UpperCAmelCase						 =					jnp.floataa

    def 				UpperCamelCase	(     self: Dict       ):






         """simple docstring"""


         A__										=  self.in_channels if self.out_channels is None else self.out_channels

         A__										=  nn.GroupNorm(num_groups=32    ,						epsilon=1e-5       )
         A__										=  nn.Conv(
             UpperCamelCase    ,						kernel_size=(3, 3)    ,						strides=(1, 1)    ,						padding=((1, 1), (1, 1))    ,						dtype=self.dtype    ,						)

         A__										=  nn.Dense(UpperCamelCase    ,						dtype=self.dtype       )

         A__										=  nn.GroupNorm(num_groups=32    ,						epsilon=1e-5       )
         A__										=  nn.Dropout(self.dropout_prob       )
         A__										=  nn.Conv(
             UpperCamelCase    ,						kernel_size=(3, 3)    ,						strides=(1, 1)    ,						padding=((1, 1), (1, 1))    ,						dtype=self.dtype    ,						)

         A__										=  self.in_channels != out_channels if self.use_nin_shortcut is None else self.use_nin_shortcut

         A__										=  None
         if use_nin_shortcut:
              A__										=  nn.Conv(
                  UpperCamelCase    ,						kernel_size=(1, 1)    ,						strides=(1, 1)    ,						padding="""VALID"""    ,						dtype=self.dtype    ,						)





    def __call__(     self: str    ,						UpperCamelCase: Optional[int]    ,						UpperCamelCase: List[str]    ,						UpperCamelCase: Union[str, Any]=True       ):






         """simple docstring"""


         A__										=  hidden_states
         A__										=  self.norma(UpperCamelCase       )
         A__										=  nn.swish(UpperCamelCase       )
         A__										=  self.conva(UpperCamelCase       )

         A__										=  self.time_emb_proj(nn.swish(UpperCamelCase       )       )
         A__										=  jnp.expand_dims(jnp.expand_dims(UpperCamelCase    ,						1       )    ,						1       )
         A__										=  hidden_states + temb

         A__										=  self.norma(UpperCamelCase       )
         A__										=  nn.swish(UpperCamelCase       )
         A__										=  self.dropout(UpperCamelCase    ,						UpperCamelCase       )
         A__										=  self.conva(UpperCamelCase       )

         if self.conv_shortcut is not None:
              A__										=  self.conv_shortcut(UpperCamelCase       )

         return hidden_states + residual









"""simple docstring"""



import math
import sys





def  _snake_case     (    UpperCAmelCase_  :					int			):
     if number != int(UpperCAmelCase_			):
          raise ValueError("""the value of input must be a natural number"""			)
     if number < 0:
          raise ValueError("""the value of input must not be a negative number"""			)
     if number == 0:
          return 1
     A__										=  [-1] * (number + 1)
     A__										=  0
     for i in range(1					,   number + 1			):
          A__										=  sys.maxsize
          A__										=  int(math.sqrt(UpperCAmelCase_			)			)
          for j in range(1					,   root + 1			):
               A__										=  1 + answers[i - (j**2)]
               A__										=  min(UpperCAmelCase_					,   UpperCAmelCase_			)
          A__										=  answer
     return answers[number]


if __name__ == "__main__":
 import doctest

 doctest.testmod()






