code: def find_observations(model: "Model") -> Dict[str, Var]:
      """If there are observations available, return them as a dictionary."""
      observations = {}
      for obs in model.observed_RVs:
          aux_obs = model.rvs_to_values.get(obs, None)
          if aux_obs is not None:
              try:
                  obs_data = extract_obs_data(aux_obs)
                  observations[obs.name] = obs_data
              except TypeError:
                  warnings.warn(
                      f"Could not extract data from symbolic observation {obs}"
                  )
          else:
              warnings.warn(f"No data for observation {obs}")
  
      return observations
  
imports: import logging
  import warnings
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Mapping, Optional, Tuple, Union
  import numpy
  from arviz import InferenceData, concat, rcParams
  from arviz.data.base import CoordSpec, DimSpec, dict_to_dataset, requires
  from pytensor.graph.basic import Constant
  from pytensor.tensor.sharedvar import SharedVariable
  import pymc
  from pymc.model import Model, modelcontext
  from pymc.pytensorf import extract_obs_data
  from pymc.util import get_default_varnames
label_desc: Use image node_id 1 for calling a global function with example usage: find_observations(model) and returns: observations