I'm working with Tensorflow 1.13 and have created a custom loss function. I need kind of like iteration number in my loss function and can't figure out how to do it with Tensorflow. Is there any way to make it?
You will need to create a variable for storing that value. Tensorflow minimizer function has an argument called global_step, which provides the iterations number during training process (it's not necessary to be the epoch).
global_step: Optional Variable to increment by one after the variables have been updated.
So here is how you can do that
# ...
global_step = tf.Variable(0, name='global_step', trainable=False)
loss = custom_loss(global_step)
optimizer = tf.train.RMSPropOptimizer(learning_rate=1e-4)
minimizer = optimizer.minimize(loss, global_step=global_step)
# global_step will contain number of iterations during trainingFor more details, you can take a look at the optimizer.minimize() function. Also, there is a global function for it as well tf.train.global_step().