code: def __init__(self, data):
      for key, value in data.items():
          key = key.lower()
          if isinstance(value, (list, np.ndarray)):
              value = torch.tensor(value, dtype=torch.double)
          self.__dict__[key] = value
  
      # transformed data
      self.is_seasonal = self.seasonality > 1
      self.lev_lower_bound = 0
  
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)