How to add training = True in tensorflow-java?

The models that I have from Python works only if I provide training = True as well in Python.

for instance in Python;

import tensorflow as tf
my_model = tf.keras.models.load_model("model")
prdct = my_model(input_image, training = True)

Here, if I do not provide training = True, the values in prdct.numpy() are all "nan".

I have the same problem in tensorflow/java as well. I wonder if there is a way to give option training = True in tensorflow/java?
Here is the java code:

        TFloat32 ImagePredicted = (TFloat32) sess
        		.runner()
        		.feed(input_layer, inputTensor)
        		.fetch(outputLayer)
        		.run()
        		.get(0);

Start with the Java Runner code shown in the issue and inspect how the loaded model exposes inputs and options compared with the Python call's training argument. Determine whether the Java API can pass this setting for the exported model, and document or validate the supported behavior with a focused example or test.