Early stopping using tensorflow tf.estimator ?
Recently I have come across this function in tensorflow API. 
tf.keras.callbacks.EarlyStopping. tf version is r1.9. 
Arguments:

monitor: quantity to be monitored
min_delta: minimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.
patience: number of epochs with no improvement after which training
will be stopped.
verbose: verbosity mode.
mode: one of {auto, min, max}. In min mode, training will stop when
the quantity monitored has stopped decreasing; in max mode it will
stop when the quantity monitored has stopped increasing; in auto
mode, the direction is automatically inferred from the name of the
monitored quantity.
I am using tensorflow v1.4. I want to use early stopping using the validation set with a patience of 5 epochs. 
I have searched on the web and found out that there used to be a function called ValidationMonitor but it is depreciated now. So is there a way to achieve this  ?