code: def brownian_motion_missing_middle_observations():
      """Synthetic dataset sampled from the BrownianMotion model.
  
      This dataset is a simulation of a 30 timestep Brownian Motion where
      the loc paramters of the middle ten timesteps are unobservable.
  
      Returns:
        dataset: A Dict with the following keys:
          observed_locs: Float `Tensor` of observed loc parameters at each timestep.
          observation_noise: Float `Tensor` of observation noise, must be positive.
          innovation_noise: Float `Tensor` of innovation noise, must be positive.
  
      """
      return dict(
          observed_locs=brownian_motion_lib.OBSERVED_LOC,
          observation_noise_scale=brownian_motion_lib.OBSERVATION_NOISE,
          innovation_noise_scale=brownian_motion_lib.INNOVATION_NOISE,
      )
  
imports: import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
  from inference_gym.internal.datasets import brownian_motion_missing_middle_observations
  from inference_gym.internal.datasets import convection_lorenz_bridge
  from inference_gym.internal.datasets import sp500_closing_prices
  from inference_gym.internal.datasets import synthetic_item_response_theory
  from inference_gym.internal.datasets import synthetic_log_gaussian_cox_process
  from inference_gym.internal.datasets import synthetic_plasma_spectroscopy
  from inference_gym.internal.datasets import synthetic_plasma_spectroscopy_with_bump
label_desc: Use image node_id 4 for calling a global function with example usage: brownian_motion_missing_middle_observations() and returns: dict