Fix DFPTraining validation set option (#709)

- Fix `validation_size` validation. Allow for `validation_size=0.0` for no validation set.
- Pass `run_validation` to dfencoder `fit()`. This option was recently added to `fit()` and is now required to enable use of a validation set and early stopping. 

Fixes #707
Fixes #708

Authors:
  - Eli Fajardo (https://github.com/efajardo-nv)

Approvers:
  - Michael Demoret (https://github.com/mdemoret-nv)
  - David Gardner (https://github.com/dagardner-nv)

URL: #709

examples/digital_fingerprinting/production/morpheus/dfp/stages/dfp_training.py

@@ -56,7 +56,7 @@ def __init__(self, c: Config, model_kwargs: dict = None, epochs=30, validation_s
 
         self._epochs = epochs
 
-        if (validation_size > 0.0 and validation_size < 1.0):
+        if (validation_size >= 0.0 and validation_size < 1.0):
             self._validation_size = validation_size
         else:
             raise ValueError("validation_size={0} should be a positive float in the "
@@ -85,13 +85,15 @@ def on_data(self, message: MultiDFPMessage):
         # Only train on the feature columns
         train_df = train_df[train_df.columns.intersection(self._config.ae.feature_columns)]
         validation_df = None
+        run_validation = False
 
         # Split into training and validation sets
         if self._validation_size > 0.0:
             train_df, validation_df = train_test_split(train_df, test_size=self._validation_size, shuffle=False)
+            run_validation = True
 
         logger.debug("Training AE model for user: '%s'...", user_id)
-        model.fit(train_df, epochs=self._epochs, val=validation_df)
+        model.fit(train_df, epochs=self._epochs, val=validation_df, run_validation=run_validation)
         logger.debug("Training AE model for user: '%s'... Complete.", user_id)
 
         output_message = MultiAEMessage(message.meta,