import tensorflow as tf


        '''

        total_loss = self.loss
        # add regularizers in case there are any
        if len(self.regularizers)>0:
            total_loss += tf.add_n(self.regularizers, name="regularization")

        # 1st part of minimize: compute_gradient
        self.grads_and_vars = self._optimizer.compute_gradients(total_loss)

        # clip gradients
