import tensorflow as tf

						correct = tf.equal(
							tf.cast(tf.ones_like(label_ids, dtype=tf.int32), tf.int32),
							tf.cast(pred_label, tf.int32)
						)
						st_accuracy = tf.reduce_mean(tf.cast(correct, tf.float32))

						pred_label = tf.argmax(distillation_loss["te_logits"], axis=-1, output_type=tf.int32)
						correct = tf.equal(
							tf.cast(tf.zeros_like(label_ids, dtype=tf.int32), tf.int32),
							tf.cast(pred_label, tf.int32)
						)
						te_accuracy = tf.reduce_mean(tf.cast(correct, tf.float32))
					except:
						te_accuracy = tf.constant(0.0)
						st_accuracy = tf.constant(0.0)

					try:
						st_accuracy = tf.reduce_mean(distillation_loss["src_f1_prob"])						
						te_accuracy = tf.reduce_mean(distillation_loss["tgt_f1_prob"])
					except:
						te_accuracy = tf.constant(0.0)
						st_accuracy = tf.constant(0.0)
