





"""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 		lowercase					(					_UpperCAmelCase					):
      _SCREAMING_SNAKE_CASE					=      42







class 		lowercase					(					_UpperCAmelCase     ,  _UpperCAmelCase					):





      @register_to_config
      def __init__(       self      ,						lowercase = 3      ,						lowercase = 3      ,						lowercase = ("DownEncoderBlock2D",)      ,						lowercase = ("UpDecoderBlock2D",)      ,						lowercase = (64,)      ,						lowercase = 1      ,						lowercase = "silu"      ,						lowercase = 3      ,						lowercase = 32      ,						lowercase = 256      ,						lowercase = 32      ,						lowercase = None      ,						lowercase = 0.18_215      ,						lowercase = "group"      ,						)		->     Union[str, Any]:
            super().__init__()

            # pass init params to Encoder
            lowerCAmelCase  						=       Encoder(
                in_channels=lowercase      ,						out_channels=lowercase      ,						down_block_types=lowercase      ,						block_out_channels=lowercase      ,						layers_per_block=lowercase      ,						act_fn=lowercase      ,						norm_num_groups=lowercase      ,						double_z=lowercase      ,						)

            lowerCAmelCase  						=       vq_embed_dim if vq_embed_dim is not None else latent_channels

            lowerCAmelCase  						=       nn.Convad(lowercase      ,						lowercase      ,						1 )
            lowerCAmelCase  						=       VectorQuantizer(lowercase      ,						lowercase      ,						beta=0.25      ,						remap=lowercase      ,						sane_index_shape=lowercase )
            lowerCAmelCase  						=       nn.Convad(lowercase      ,						lowercase      ,						1 )

            # pass init params to Decoder
            lowerCAmelCase  						=       Decoder(
                in_channels=lowercase      ,						out_channels=lowercase      ,						up_block_types=lowercase      ,						block_out_channels=lowercase      ,						layers_per_block=lowercase      ,						act_fn=lowercase      ,						norm_num_groups=lowercase      ,						norm_type=lowercase      ,						)





      @apply_forward_hook
      def     _snake_case			(       self      ,						lowercase      ,						lowercase = True )		->     VQEncoderOutput:
            lowerCAmelCase  						=       self.encoder(lowercase )
            lowerCAmelCase  						=       self.quant_conv(lowercase )

            if not return_dict:
                  return (h,)

            return VQEncoderOutput(latents=lowercase )





      @apply_forward_hook
      def     _snake_case			(       self      ,						lowercase      ,						lowercase = False      ,						lowercase = True )		->     Union[DecoderOutput, torch.FloatTensor]:
            # also go through quantization layer
            if not force_not_quantize:
                  lowerCAmelCase						,		lowerCAmelCase						,		lowerCAmelCase  						=       self.quantize(lowercase )
            else:
                  lowerCAmelCase  						=       h
            lowerCAmelCase  						=       self.post_quant_conv(lowercase )
            lowerCAmelCase  						=       self.decoder(lowercase      ,						quant if self.config.norm_type == """spatial""" else None )

            if not return_dict:
                  return (dec,)

            return DecoderOutput(sample=lowercase )





      def     _snake_case			(       self      ,						lowercase      ,						lowercase = True )		->     Union[DecoderOutput, torch.FloatTensor]:
            lowerCAmelCase  						=       sample
            lowerCAmelCase  						=       self.encode(lowercase ).latents
            lowerCAmelCase  						=       self.decode(lowercase ).sample

            if not return_dict:
                  return (dec,)

            return DecoderOutput(sample=lowercase )













"""simple docstring"""





def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						int							,						SCREAMING_SNAKE_CASE     :						int			):







      '''simple docstring'''




      while b:
            lowerCAmelCase						,		lowerCAmelCase  						=       b, a % b
      return a


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						int							,						SCREAMING_SNAKE_CASE     :						int			):







      '''simple docstring'''




      return a if b == 0 else euclidean_gcd_recursive(SCREAMING_SNAKE_CASE							,						a % b			)


def 			UpperCAmelCase__							(  ):







      '''simple docstring'''




      print(F'euclidean_gcd(3, 5) = {euclidean_gcd(3							,						5			)}'			)
      print(F'euclidean_gcd(5, 3) = {euclidean_gcd(5							,						3			)}'			)
      print(F'euclidean_gcd(1, 3) = {euclidean_gcd(1							,						3			)}'			)
      print(F'euclidean_gcd(3, 6) = {euclidean_gcd(3							,						6			)}'			)
      print(F'euclidean_gcd(6, 3) = {euclidean_gcd(6							,						3			)}'			)

      print(F'euclidean_gcd_recursive(3, 5) = {euclidean_gcd_recursive(3							,						5			)}'			)
      print(F'euclidean_gcd_recursive(5, 3) = {euclidean_gcd_recursive(5							,						3			)}'			)
      print(F'euclidean_gcd_recursive(1, 3) = {euclidean_gcd_recursive(1							,						3			)}'			)
      print(F'euclidean_gcd_recursive(3, 6) = {euclidean_gcd_recursive(3							,						6			)}'			)
      print(F'euclidean_gcd_recursive(6, 3) = {euclidean_gcd_recursive(6							,						3			)}'			)


if __name__ == "__main__":
       main()






