code: def __init__(self, data):
      for key, value in data.items():
          key = key.lower()
          if isinstance(value, (list, np.ndarray)):
              # TODO: this is hackk way; please fix this later
              if key in ["which_valid_res"]:
                  # to use as index, tensor type has to be long or int
                  value = torch.tensor(value)
              elif key in ["coef_prior_list"]:
                  pass
              else:
                  # loc/scale cannot be in long format
                  # sometimes they may be supplied as int, so dtype conversion is needed
                  value = torch.tensor(value, dtype=torch.double)
          self.__dict__[key] = value
  
imports: import numpy
  import torch
  import pyro
  import pyro.distributions
label_desc: Use image node_id 1 to create a new Model object  with example: obj = Model(data)