





"""simple docstring"""
from __future__ import annotations

from math import pi

# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__UpperCamelCase     :						Any						       =  1.054_571_817e-34  # unit of ℏ : J * s

__UpperCamelCase     :						List[Any]						       =  3e8  # unit of c : m * s^-1

def 		_SCREAMING_SNAKE_CASE			(_UpperCAmelCase					:    float  ,     _UpperCAmelCase					:    float  ,     _UpperCAmelCase					:    float			):

 if (force, area, distance).count(0			) != 1:
  raise ValueError('One and only one argument must be 0'			)
 if force < 0:
  raise ValueError('Magnitude of force can not be negative'			)
 if distance < 0:
  raise ValueError('Distance can not be negative'			)
 if area < 0:
  raise ValueError('Area can not be negative'			)
 if force == 0:
  lowerCAmelCase    				= (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (
      240 * (distance) ** 4
  )
  return {"force": force}
 elif area == 0:
  lowerCAmelCase    				= (240 * force * (distance) ** 4) / (
      REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2
  )
  return {"area": area}
 elif distance == 0:
  lowerCAmelCase    				= (
      (REDUCED_PLANCK_CONSTANT * SPEED_OF_LIGHT * pi**2 * area) / (240 * force)
  ) ** (1 / 4)
  return {"distance": distance}
 raise ValueError('One and only one argument must be 0'			)


# Run doctest
if __name__ == "__main__":
       import doctest

       doctest.testmod()












"""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       a							(   a__  ):
 snake_case__             =       42







class       a							(   a__   , a__  ):



 @register_to_config
 def __init__(     self				,       _snake_case = 3				,       _snake_case = 3				,       _snake_case = ("DownEncoderBlock2D",)				,       _snake_case = ("UpDecoderBlock2D",)				,       _snake_case = (64,)				,       _snake_case = 1				,       _snake_case = "silu"				,       _snake_case = 3				,       _snake_case = 32				,       _snake_case = 2_56				,       _snake_case = 32				,       _snake_case = None				,       _snake_case = 0.18_215				,       _snake_case = "group"				,       ):







  """simple docstring"""






  super().__init__()

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

  lowerCAmelCase    				= vq_embed_dim if vq_embed_dim is not None else latent_channels

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

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



 @apply_forward_hook
 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case = True     ):







  """simple docstring"""






  lowerCAmelCase    				= self.encoder(_snake_case     )
  lowerCAmelCase    				= self.quant_conv(_snake_case     )

  if not return_dict:
   return (h,)

  return VQEncoderOutput(latents=_snake_case     )



 @apply_forward_hook
 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case = False				,       _snake_case = True     ):







  """simple docstring"""






  if not force_not_quantize:
   lowerCAmelCase				,lowerCAmelCase				,lowerCAmelCase    				= self.quantize(_snake_case     )
  else:
   lowerCAmelCase    				= h
  lowerCAmelCase    				= self.post_quant_conv(_snake_case     )
  lowerCAmelCase    				= self.decoder(_snake_case				,       quant if self.config.norm_type == 'spatial' else None     )

  if not return_dict:
   return (dec,)

  return DecoderOutput(sample=_snake_case     )



 def    UpperCamelCase__  (     self				,       _snake_case				,       _snake_case = True     ):







  """simple docstring"""






  lowerCAmelCase    				= sample
  lowerCAmelCase    				= self.encode(_snake_case     ).latents
  lowerCAmelCase    				= self.decode(_snake_case     ).sample

  if not return_dict:
   return (dec,)

  return DecoderOutput(sample=_snake_case     )





