import flax.linen as nn
import jax
import jax.numpy as jnp
class  A_			(							nn.Module			):
  _SCREAMING_SNAKE_CASE     					=      42
  _SCREAMING_SNAKE_CASE     					=      jnp.floataa

  def 		_UpperCAmelCase (		self			:   str							):
   __a							=	nn.Conv(
       self.out_channels  ,				kernel_size=(3, 3)  ,				strides=(1, 1)  ,				padding=((1, 1), (1, 1))  ,				dtype=self.dtype  ,				)

  def __call__(		self			:   Union[str, Any]  ,				__SCREAMING_SNAKE_CASE			:   List[Any]							):
   __a							=	hidden_states.shape
   __a							=	jax.image.resize(
       A_  ,				shape=(batch, height * 2, width * 2, channels)  ,				method="nearest"  ,				)
   __a							=	self.conv(A_							)
   return hidden_states
class  A_			(							nn.Module			):
  _SCREAMING_SNAKE_CASE     					=      42
  _SCREAMING_SNAKE_CASE     					=      jnp.floataa

  def 		_UpperCAmelCase (		self			:   str							):
   __a							=	nn.Conv(
       self.out_channels  ,				kernel_size=(3, 3)  ,				strides=(2, 2)  ,				padding=((1, 1), (1, 1))  ,				dtype=self.dtype  ,				)

  def __call__(		self			:   Optional[Any]  ,				__SCREAMING_SNAKE_CASE			:   int							):
   __a							=	self.conv(A_							)
   return hidden_states
class  A_			(							nn.Module			):
  _SCREAMING_SNAKE_CASE     					=      42
  _SCREAMING_SNAKE_CASE     					=      None
  _SCREAMING_SNAKE_CASE     					=      0.0
  _SCREAMING_SNAKE_CASE     					=      None
  _SCREAMING_SNAKE_CASE     					=      jnp.floataa

  def 		_UpperCAmelCase (		self			:   Union[str, Any]							):
   __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(
       A_  ,				kernel_size=(3, 3)  ,				strides=(1, 1)  ,				padding=((1, 1), (1, 1))  ,				dtype=self.dtype  ,				)

   __a							=	nn.Dense(A_  ,				dtype=self.dtype							)

   __a							=	nn.GroupNorm(num_groups=32  ,				epsilon=1E-5							)
   __a							=	nn.Dropout(self.dropout_prob							)
   __a							=	nn.Conv(
       A_  ,				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(
        A_  ,				kernel_size=(1, 1)  ,				strides=(1, 1)  ,				padding="VALID"  ,				dtype=self.dtype  ,				)

  def __call__(		self			:   Optional[int]  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]  ,				__SCREAMING_SNAKE_CASE			:   List[Any]  ,				__SCREAMING_SNAKE_CASE			:   Tuple=True							):
   __a							=	hidden_states
   __a							=	self.norma(A_							)
   __a							=	nn.swish(A_							)
   __a							=	self.conva(A_							)

   __a							=	self.time_emb_proj(nn.swish(A_							)							)
   __a							=	jnp.expand_dims(jnp.expand_dims(A_  ,				1							)  ,				1							)
   __a							=	hidden_states + temb

   __a							=	self.norma(A_							)
   __a							=	nn.swish(A_							)
   __a							=	self.dropout(A_  ,				A_							)
   __a							=	self.conva(A_							)

   if self.conv_shortcut is not None:
    __a							=	self.conv_shortcut(A_							)

   return hidden_states + residual









# Author: OMKAR PATHAK, Nwachukwu Chidiebere

# Use a Python dictionary to construct the graph.
from __future__ import annotations

from pprint import pformat
from typing import Generic, TypeVar

__lowerCamelCase			:	str					    =	TypeVar("""T""")



class    A__  (			Generic[T]     ):





      def __init__(					self			,				A_ = True  ):
       '''simple docstring'''




       UpperCamelCase      :   dict[T, list[T]]			      =  {}  # dictionary of lists
       UpperCamelCase      :   Union[str, Any]			      =  directed





      def 			__UpperCamelCase(					self			,				A_			,				A_  ):
       '''simple docstring'''




       if not self.directed:  # For undirected graphs
        # if both source vertex and destination vertex are both present in the
        # adjacency list, add destination vertex to source vertex list of adjacent
        # vertices and add source vertex to destination vertex list of adjacent
        # vertices.
        if source_vertex in self.adj_list and destination_vertex in self.adj_list:
         self.adj_list[source_vertex].append(A_  )
         self.adj_list[destination_vertex].append(A_  )
        # if only source vertex is present in adjacency list, add destination vertex
        # to source vertex list of adjacent vertices, then create a new vertex with
        # destination vertex as key and assign a list containing the source vertex
        # as it's first adjacent vertex.
        elif source_vertex in self.adj_list:
         self.adj_list[source_vertex].append(A_  )
         UpperCamelCase      :   Any			      =  [source_vertex]
        # if only destination vertex is present in adjacency list, add source vertex
        # to destination vertex list of adjacent vertices, then create a new vertex
        # with source vertex as key and assign a list containing the source vertex
        # as it's first adjacent vertex.
        elif destination_vertex in self.adj_list:
         self.adj_list[destination_vertex].append(A_  )
         UpperCamelCase      :   Any			      =  [destination_vertex]
        # if both source vertex and destination vertex are not present in adjacency
        # list, create a new vertex with source vertex as key and assign a list
        # containing the destination vertex as it's first adjacent vertex also
        # create a new vertex with destination vertex as key and assign a list
        # containing the source vertex as it's first adjacent vertex.
        else:
         UpperCamelCase      :   Union[str, Any]			      =  [destination_vertex]
         UpperCamelCase      :   List[str]			      =  [source_vertex]
       else:  # For directed graphs
        # if both source vertex and destination vertex are present in adjacency
        # list, add destination vertex to source vertex list of adjacent vertices.
        if source_vertex in self.adj_list and destination_vertex in self.adj_list:
         self.adj_list[source_vertex].append(A_  )
        # if only source vertex is present in adjacency list, add destination
        # vertex to source vertex list of adjacent vertices and create a new vertex
        # with destination vertex as key, which has no adjacent vertex
        elif source_vertex in self.adj_list:
         self.adj_list[source_vertex].append(A_  )
         UpperCamelCase      :   List[str]			      =  []
        # if only destination vertex is present in adjacency list, create a new
        # vertex with source vertex as key and assign a list containing destination
        # vertex as first adjacent vertex
        elif destination_vertex in self.adj_list:
         UpperCamelCase      :   Union[str, Any]			      =  [destination_vertex]
        # if both source vertex and destination vertex are not present in adjacency
        # list, create a new vertex with source vertex as key and a list containing
        # destination vertex as it's first adjacent vertex. Then create a new vertex
        # with destination vertex as key, which has no adjacent vertex
        else:
         UpperCamelCase      :   Union[str, Any]			      =  [destination_vertex]
         UpperCamelCase      :   Dict			      =  []

       return self





      def __repr__(					self  ):
       '''simple docstring'''




       return pformat(self.adj_list  )
