86aca57545cfe312151cc35528035cd9c0aafe2d,art/classifiers/pytorch.py,PyTorchClassifier,predict,#PyTorchClassifier#Any#Any#,48

Before Change

        self._model.train(False)

        // Run prediction
        preds = self._forward_at(torch.from_numpy(inputs), self._logit_layer).detach().numpy()
        if not logits:
            exp = np.exp(preds - np.max(preds, axis=1, keepdims=True))
            preds = exp / np.sum(exp, axis=1, keepdims=True)

After Change

        // if not logits:
        //     exp = np.exp(preds - np.max(preds, axis=1, keepdims=True))
        //     preds = exp / np.sum(exp, axis=1, keepdims=True)
        (logit_output, output) = self._model(torch.from_numpy(inputs))

        if logits:
            preds = logit_output.detach().numpy()
        else:
            preds = output.detach().numpy()

        return preds

Instances