Understanding inference

[Nishant-DN]

Currently I am trying to understand the inference part of the Faceboxes. I actually tried visualizing it using Tensorboard as well as the frozen graph. But I was only able to get the overall picture, but not the entire scenario. So I am trying to understand this with some print statements that output the tensor values. I am feeding images from the wider face dataset as prescribed while training. For the inference to happen, I have changed def get_input_fn(is_training=True): to def get_input_fn(is_training=False): . But in both the cases all the nodes are getting executed. I am not able to differentiate between the training and evaluation nodes. How to do that?

Any help would be appreciated!!!!