Doubtful if test Dialogflow model is allowed some time to update its underlying algorithm during training phase

According to Dialogflow, each time intent is updated, training phrase is added, entities are updated, the underlying algorithm gets updated. Even I have experienced that the Dialogflow model taking time to train when I add a training phrase.

I feel the same thing happens in case of testing a Dialogflow bot. When cross validation starts, training of phrases starts. I am thinking if the training for test purpose allows Dialogfolw some time to update its state of algorithm. I am confused, if training the model continuously and letting it to predict an utterance right after finishing training phase would classify that utterance correctly as the model might still be building its knowledge base. The task of classification may leads whereas algorithm building process may lag.
This might produce incorrect results for precision, recall etc.
I am wondering how much might I be correct with such kind of understanding. I hope to be cleared about this confusion.
Thankyou