code: def __init__(self, task, experiment_name, metric=None):
      """
  
      Creates an input model for Scan(). Optimized for being used together
      with Params(). For example:
  
      p = talos.AutoParams().params
      model = talos.AutoModel(task='binary').model
  
      talos.Scan(x, y, p, model)
  
      NOTE: the parameter space from Params() is very large, so use limits
      in or reducers in Scan() accordingly.
  
      task : string or None
          If 'continuous' then mae is used for metric, if 'binary',
          'multiclass', or 'multilabel', f1score is used. Accuracy is always
          used.
      experiment_name | str | Must be same as in `Scan()`
      metric : None or list
          You can also input a list with one or more custom metrics or names
          of Keras or Talos metrics.
      """
  
      from talos.callbacks.experiment_log import ExperimentLog
  
      self.task = task
      self.experiment_name = experiment_name
      self.metric = metric
  
      if self.task is not None:
          self.metrics = self._set_metric()
      elif self.metric is not None and isinstance(self.metric, list):
          self.metrics = self.metric + ["acc"]
      else:
          print("Either pick task or provide list as input for metric.")
  
      # create the model
      self.model = self._create_input_model
      self.callback = ExperimentLog
  
label_desc: Use image node_id 1 to create a new AutoModel object  with example: obj = AutoModel(task, experiment_name, metric)