





'''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     lowerCAmelCase__ (				UpperCAmelCase_    ):

       '''simple docstring'''
       _lowerCamelCase								=42






class     lowerCAmelCase__ (				UpperCAmelCase_      , UpperCAmelCase_    ):

       '''simple docstring'''

       @register_to_config
       def __init__( self					:				List[Any]       ,     a__					:				int = 3       ,     a__					:				int = 3       ,     a__					:				Tuple[str] = ("DownEncoderBlock2D",)       ,     a__					:				Tuple[str] = ("UpDecoderBlock2D",)       ,     a__					:				Tuple[int] = (64,)       ,     a__					:				int = 1       ,     a__					:				str = "silu"       ,     a__					:				int = 3       ,     a__					:				int = 32       ,     a__					:				int = 256       ,     a__					:				int = 32       ,     a__					:				Optional[int] = None       ,     a__					:				float = 0.18_215       ,     a__					:				str = "group"       ,     ):
              super().__init__()

              # pass init params to Encoder
              UpperCAmelCase  =						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__       ,     )

              UpperCAmelCase  =						vq_embed_dim if vq_embed_dim is not None else latent_channels

              UpperCAmelCase  =						nn.Convad(a__       ,     a__       ,     1						)
              UpperCAmelCase  =						VectorQuantizer(a__       ,     a__       ,     beta=0.25       ,     remap=a__       ,     sane_index_shape=a__						)
              UpperCAmelCase  =						nn.Convad(a__       ,     a__       ,     1						)

              # pass init params to Decoder
              UpperCAmelCase  =						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 			__snake_case      ( self					:				Tuple       ,     a__					:				torch.FloatTensor       ,     a__					:				bool = True						):
              UpperCAmelCase  =						self.encoder(a__						)
              UpperCAmelCase  =						self.quant_conv(a__						)

              if not return_dict:
                     return (h,)

              return VQEncoderOutput(latents=a__						)

       @apply_forward_hook
       def 			__snake_case      ( self					:				str       ,     a__					:				torch.FloatTensor       ,     a__					:				bool = False       ,     a__					:				bool = True						):
              # also go through quantization layer
              if not force_not_quantize:
                     UpperCAmelCase,					UpperCAmelCase,					UpperCAmelCase  =						self.quantize(a__						)
              else:
                     UpperCAmelCase  =						h
              UpperCAmelCase  =						self.post_quant_conv(a__						)
              UpperCAmelCase  =						self.decoder(a__       ,     quant if self.config.norm_type == '''spatial''' else None						)

              if not return_dict:
                     return (dec,)

              return DecoderOutput(sample=a__						)



       def 			__snake_case      ( self					:				List[Any]       ,     a__					:				torch.FloatTensor       ,     a__					:				bool = True						):
              UpperCAmelCase  =						sample
              UpperCAmelCase  =						self.encode(a__						).latents
              UpperCAmelCase  =						self.decode(a__						).sample

              if not return_dict:
                     return (dec,)

              return DecoderOutput(sample=a__						)



"""simple docstring"""






from math import pow, sqrt


def      UpperCAmelCase__			(							*lowerCAmelCase__	:float						)					->       bool:
      '''simple docstring'''


      lowercase								=      len(lowerCAmelCase__						) > 0 and all(value > 0.0 for value in values						)
      return result


def      UpperCAmelCase__			(							lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float						)					->       float | ValueError:
      '''simple docstring'''


      return (
          round(sqrt(molar_mass_a / molar_mass_a						)   ,						6						)
          if validate(lowerCAmelCase__   ,						lowerCAmelCase__						)
          else ValueError("""Input Error: Molar mass values must greater than 0."""						)
      )


def      UpperCAmelCase__			(							lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float						)					->       float | ValueError:
      '''simple docstring'''


      return (
          round(effusion_rate * sqrt(molar_mass_a / molar_mass_a						)   ,						6						)
          if validate(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__						)
          else ValueError(
              """Input Error: Molar mass and effusion rate values must greater than 0."""						)
      )


def      UpperCAmelCase__			(							lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float						)					->       float | ValueError:
      '''simple docstring'''


      return (
          round(effusion_rate / sqrt(molar_mass_a / molar_mass_a						)   ,						6						)
          if validate(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__						)
          else ValueError(
              """Input Error: Molar mass and effusion rate values must greater than 0."""						)
      )


def      UpperCAmelCase__			(							lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float						)					->       float | ValueError:
      '''simple docstring'''


      return (
          round(molar_mass / pow(effusion_rate_a / effusion_rate_a   ,						2						)   ,						6						)
          if validate(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__						)
          else ValueError(
              """Input Error: Molar mass and effusion rate values must greater than 0."""						)
      )






def      UpperCAmelCase__			(							lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float   ,						lowerCAmelCase__	:float						)					->       float | ValueError:
      '''simple docstring'''


      return (
          round(pow(effusion_rate_a / effusion_rate_a   ,						2						) / molar_mass   ,						6						)
          if validate(lowerCAmelCase__   ,						lowerCAmelCase__   ,						lowerCAmelCase__						)
          else ValueError(
              """Input Error: Molar mass and effusion rate values must greater than 0."""						)
      )



