(self, X, GT=None, S=None, compute_loss=True)
return self.sess.run(
            (self.x_reconstr, loss, loss_ae, loss_simplification, loss_projection),
            feed_dict=feed_dict,
        )
Use AE to reconstruct given data.
        GT will be used to measure the loss (e.g., if X is a noisy version of the GT)
Use AE to reconstruct given data.
        GT will be used to measure the loss (e.g., if X is a noisy version of the GT)
Use AE to reconstruct given data . GT will be used to measure the loss ( e . g . if X is a noisy version of the GT )
def reconstruct(self, X, GT=None, S=None, compute_loss=True):
        """Use AE to reconstruct given data.
        GT will be used to measure the loss (e.g., if X is a noisy version of the GT)"""
        if compute_loss:
            loss = self.loss
            loss_ae = self.loss_ae
            loss_simplification = self.loss_simplification
            loss_projection = self.loss_projection
        else:
            loss = self.no_op
            loss_ae = self.no_op
            loss_simplification = self.no_op
            loss_projection = self.no_op

        feed_dict = {self.x: X}
        if GT is not None:
            feed_dict[self.gt] = GT

        if S is not None:
            feed_dict[self.s] = S

        return self.sess.run(
            (self.x_reconstr, loss, loss_ae, loss_simplification, loss_projection),
            feed_dict=feed_dict,
        )
def reconstruct ( self , X , GT = None , S = None , compute_loss = True ) : if compute_loss : loss = self . loss loss_ae = self . loss_ae loss_simplification = self . loss_simplification loss_projection = self . loss_projection else : loss = self . no_op loss_ae = self . no_op loss_simplification = self . no_op loss_projection = self . no_op feed_dict = { self . x : X } if GT is not None : feed_dict [ self . gt ] = GT if S is not None : feed_dict [ self . s ] = S return self . sess . run ( ( self . x_reconstr , loss , loss_ae , loss_simplification , loss_projection ) , feed_dict = feed_dict , )