9b9a42de05056b418f98e3635f2cffd747123548,art/classifiers/pytorch.py,PyTorchClassifier,loss_gradient,#PyTorchClassifier#Any#Any#,136

Before Change

        :rtype: `np.ndarray`
        
        // Check if loss available
        if not hasattr(self, "_loss_grads") or self._loss_grads is None:
            raise ValueError("Need the loss function to compute the loss gradient.")

        // Compute the gradient and return
        grds = self._sess.run(self._loss_grads, feed_dict={self._input_ph: inputs, self._output_ph: labels})

        return grds

    def _forward_at(self, inputs, layer):

After Change

        // Compute the gradient and return
        loss = self._loss(m_batch, o_batch)
        loss.backward()

        return grds

    def _forward_at(self, inputs, layer):

Instances