
'''simple docstring'''






from dataclasses import dataclass
from typing import Optional, Tuple, Union

import torch
import torch.nn as nn

from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, VectorQuantizer




@dataclass
class     __snake_case		(   __A):
					_lowerCAmelCase			     =	42





class     __snake_case		(   __A    ,   __A):
					@register_to_config
					def __init__(     self,    A = 3,    A = 3,    A = ("DownEncoderBlock2D",),    A = ("UpDecoderBlock2D",),    A = (64,),    A = 1,    A = "silu",    A = 3,    A = 32,    A = 256,    A = 32,    A = None,    A = 0.1_8215,    A = "group",    ):

									"""simple docstring"""


									super().__init__()

									# pass init params to Encoder
									lowerCamelCase					:			Union[str, Any]									= Encoder(
									    in_channels=A,    out_channels=A,    down_block_types=A,    block_out_channels=A,    layers_per_block=A,    act_fn=A,    norm_num_groups=A,    double_z=A,    )

									lowerCamelCase					:			Union[str, Any]									= vq_embed_dim if vq_embed_dim is not None else latent_channels

									lowerCamelCase					:			Any									= nn.Convad(A,    A,    1      )
									lowerCamelCase					:			Optional[Any]									= VectorQuantizer(A,    A,    beta=0.25,    remap=A,    sane_index_shape=A      )
									lowerCamelCase					:			List[Any]									= nn.Convad(A,    A,    1      )

									# pass init params to Decoder
									lowerCamelCase					:			Union[str, Any]									= Decoder(
									    in_channels=A,    out_channels=A,    up_block_types=A,    block_out_channels=A,    layers_per_block=A,    act_fn=A,    norm_num_groups=A,    norm_type=A,    )
					@apply_forward_hook
					def     UpperCAmelCase_							(     self,    A,    A = True      ):

									"""simple docstring"""


									lowerCamelCase					:			Tuple									= self.encoder(A      )
									lowerCamelCase					:			Any									= self.quant_conv(A      )

									if not return_dict:
													return (h,)

									return VQEncoderOutput(latents=A      )
					@apply_forward_hook
					def     UpperCAmelCase_							(     self,    A,    A = False,    A = True      ):

									"""simple docstring"""


									if not force_not_quantize:
													lowerCamelCase					:			Tuple									= self.quantize(A      )
									else:
													lowerCamelCase					:			Dict									= h
									lowerCamelCase					:			Tuple									= self.post_quant_conv(A      )
									lowerCamelCase					:			List[Any]									= self.decoder(A,    quant if self.config.norm_type == 'spatial' else None      )

									if not return_dict:
													return (dec,)

									return DecoderOutput(sample=A      )




					def     UpperCAmelCase_							(     self,    A,    A = True      ):

									"""simple docstring"""


									lowerCamelCase					:			int									= sample
									lowerCamelCase					:			Dict									= self.encode(A      ).latents
									lowerCamelCase					:			Optional[Any]									= self.decode(A      ).sample

									if not return_dict:
													return (dec,)

									return DecoderOutput(sample=A      )


'''simple docstring'''






A			      =      {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
A			      =      ['a', 'b', 'c', 'd', 'e']





def    UpperCAmelCase							(  UpperCAmelCase__							:							Union[str, Any]       ,							UpperCAmelCase__							:							Any       ,							UpperCAmelCase__							:							List[Any]):
				lowerCamelCase					:			List[Any]									= start
				# add current to visited
				visited.append(UpperCAmelCase__)
				lowerCamelCase					:			List[str]									= edges[current]
				for neighbor in neighbors:
								# if neighbor not in visited, visit
								if neighbor not in visited:
												lowerCamelCase					:			Any									= topological_sort(UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__)
    # if all neighbors visited add current to sort
				sort.append(UpperCAmelCase__)
				# if all vertices haven't been visited select a new one to visit
				if len(UpperCAmelCase__) != len(UpperCAmelCase__):
								for vertice in vertices:
												if vertice not in visited:
																lowerCamelCase					:			List[str]									= topological_sort(UpperCAmelCase__       ,							UpperCAmelCase__       ,							UpperCAmelCase__)
    # return sort
				return sort


if __name__ == "__main__":
					A			      =      topological_sort('a', [], [])
					print(sort)
