(self)
return self.response
Return history previously saved while fitting a Keras model.
        The history is avaialble as a DataFrame from the estimator.
        It provides metrics such as loss for each epoch during each run of the fit method.
        Columns will be ['iteration', 'epoch', 'loss'] and any other metrics calculated during training.
Return history previously saved while fitting a Keras model.
        The history is avaialble as a DataFrame from the estimator.
        It provides metrics such as loss for each epoch during each run of the fit method.
        Columns will be ['iteration', 'epoch', 'loss'] and any other metrics calculated during training.
Return history previously saved while fitting a Keras model . The history is avaialble as a DataFrame from the estimator . It provides metrics such as loss for each epoch during each run of the fit method . Columns will be [ iteration epoch loss ] and any other metrics calculated during training .
def get_keras_history(self):
        """
        Return history previously saved while fitting a Keras model.
        The history is avaialble as a DataFrame from the estimator.
        It provides metrics such as loss for each epoch during each run of the fit method.
        Columns will be ['iteration', 'epoch', 'loss'] and any other metrics calculated during training.
        """
        
        # Get the model from cache or disk based on the model_name in request
        self._get_model_by_name()

        assert self.model.using_keras, "Loss history is only available for Keras models"

        # Prepare the response using the histories data frame from the Keras model
        self.response = self.model.pipe.named_steps['estimator'].histories.copy()
        
        # Add the model name to the response
        self.response.insert(0, 'model_name', self.model.name)
        
        self._send_table_description("keras_history")
        
        # Debug information is printed to the terminal and logs if the paramater debug = true
        if self.model.debug:
            self._print_log(4)
        
        # Finally send the response
        return self.response
def get_keras_history ( self ) : # Get the model from cache or disk based on the model_name in request self . _get_model_by_name ( ) assert self . model . using_keras , "Loss history is only available for Keras models" # Prepare the response using the histories data frame from the Keras model self . response = self . model . pipe . named_steps [ 'estimator' ] . histories . copy ( ) # Add the model name to the response self . response . insert ( 0 , 'model_name' , self . model . name ) self . _send_table_description ( "keras_history" ) # Debug information is printed to the terminal and logs if the paramater debug = true if self . model . debug : self . _print_log ( 4 ) # Finally send the response return self . response