class_docstr: Callback object that renders a bokeh chart in a jupyter notebook
  that gets updated as the training run proceeds.
  
  Requires a PandasLogger to collect the data it will render.
  
  This is an abstract base-class.  Sub-classes define the specific chart.
class_docstr_tok: ["Callback","object","that","renders","a","bokeh","chart","in","a","jupyter","notebook","that","gets","updated","as","the","training","run","proceeds",".","Requires","a","PandasLogger","to","collect","the","data","it","will","render",".","This","is","an","abstract","base-class",".","Sub-classes","define","the","specific","chart","."]
docstr: returns **kwargs parameters for model.fit()
  to enable all callbacks.  e.g.
  model.fit(X=train, eval_data=test, **pdlogger.callback_args())
code: def callback_args(self):
      """returns **kwargs parameters for model.fit()
      to enable all callbacks.  e.g.
      model.fit(X=train, eval_data=test, **pdlogger.callback_args())
      """
      return {
          "batch_end_callback": self.batch_cb,
          "eval_end_callback": self.eval_cb,
      }
  
imports: import time
label_desc: Use image node_id 9 for calling the LiveBokehChart obj's underlying member method code with example usage: obj.callback_args() and returns: dict