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 training
For 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().