model/model.py (2 lines):
	- line 56: #return tf.Variable(tf.constant(0.1, shape=shape, dtype=np.float32), name='biases') #TODO: Should we initialize it from 0
	- line 1290: # TODO: Tmp remove this?


utils/data_utils.py (2 lines):
	- line 122: num_val_img = 0   # you can change the number of validation images here TODO: Pass this as argument
	- line 276: num_val_img = 0   # you can change the number of validation images here TODO: Pass this as argument


conv_split_awa.py (1 line):
	- line 496: model.task_updates(sess, task, task_train_images, task_labels[task]) # TODO: For MAS, should the gradients be for current task or all the previous tasks


conv_split_cub.py (1 line):
	- line 491: model.task_updates(sess, task, task_train_images, task_labels[task]) # TODO: For MAS, should the gradients be for current task or all the previous tasks


conv_split_awa_hybrid.py (1 line):
	- line 509: # TODO: For MAS, should the gradients be for current task or all the previous tasks


conv_split_cub_hybrid.py (1 line):
	- line 515: # TODO: For MAS, should the gradients be for current task or all the previous tasks


conv_split_cifar.py (1 line):
	- line 509: model.task_updates(sess, task, task_train_images, task_labels[task]) # TODO: For MAS, should the gradients be for current task or all the previous tasks