class_docstr: Distribution over EKF states.  See :class:`~pyro.contrib.tracking.extended_kalman_filter.EKFState`.
  Currently only supports `log_prob`.
  
  :param x0: PV tensor (mean)
  :type x0: torch.Tensor
  :param P0: covariance
  :type P0: torch.Tensor
  :param dynamic_model: :class:`~pyro.contrib.tracking.dynamic_models.DynamicModel` object
  :param measurement_cov: measurement covariance
  :type measurement_cov: torch.Tensor
  :param time_steps: number time step
  :type time_steps: int
  :param dt: time step
  :type dt: torch.Tensor
code: def rsample(self, sample_shape=torch.Size()):
      raise NotImplementedError(
          "TODO: implement forward filter backward sample"
      )
  
file_path: pyro/pyro/contrib/tracking/distributions.py
imports: import torch
  from torch.distributions import constraints
  import pyro.distributions
  from pyro.contrib.tracking.extended_kalman_filter import EKFState
  from pyro.contrib.tracking.measurements import PositionMeasurement
  from pyro.distributions.torch_distribution import TorchDistribution
label_desc: Use image node_id 2 for calling the EKFDistribution obj's underlying member method code with example usage: obj.rsample(sample_shape) without return types