Chart domains should update as training progresses

TensorBoard version: https://pypi.org/project/tb-nightly/1.14.0a20190301/

Repro steps:

1. Train with Keras.fit() using the TensorBoard callback for 5 epochs
2. Open TensorBoard and look at the Scalars dashboard. See the loss and accuracy charts for epochs 1-5.
3. Continue training with Keras.fit() using the TensorBoard callback for another 5 epochs

Expected: As long as I didn't manually change the zoom of the charts, the chart should rescale to show me the new data (of the new epochs).

Actual: The data from the continued training gets added to the chart but I can see that it goes off the chart.

Relevant code (assuming notebook environment):

model.fit(x=x_train, 
          y=y_train, 
          epochs=5, 
          validation_data=(x_test, y_test), 
          callbacks=[tensorboard_callback])

%tensorboard --logdir logs

model.fit(x=x_train, 
          y=y_train, 
          epochs=10,
          initial_epoch=5,
          validation_data=(x_test, y_test), 
          callbacks=[tensorboard_callback])

Image of current behavior:

Note: this is not specific to Keras.fit().

Reproduce the issue through the Scalars dashboard using the Keras.fit() and TensorBoard callback sequence described in the report. Start by tracing how chart domains respond when continued-training data arrives without a manual zoom change. Done means new epochs remain visible through automatic rescaling while preserving manually adjusted zoom.