code: def __init__(self, inertia, frozen, check_data):
      super().__init__(
          inertia=inertia, frozen=frozen, check_data=check_data
      )
  
imports: import torch
  from .._utils import _cast_as_tensor
  from .._utils import _update_parameter
  from .._utils import _cast_as_parameter
  from .._utils import _check_parameter
  from .._utils import _reshape_weights
label_desc: Use image node_id 1 to create a new ConditionalDistribution object from inherited base classes: Distribution with example: obj = ConditionalDistribution(inertia, frozen, check_data)