b12d2e08c429ee2c2d4ffa26dc1fca178a06853e,batchflow/models/torch/base.py,TorchModel,get_gradcam,#TorchModel#,1451

Before Change

        prediction = self.model(inputs)

        if self.classes:
            gradient = torch.zeros((1, self.classes), dtype=prediction.dtype, device=self.device)
            cam_class = cam_class or np.argmax(prediction.detach().cpu().numpy()[0])
            gradient[0][cam_class] = 1
        else:
            gradient = prediction.clone()

After Change

        self.model.eval()
        prediction = self.model(inputs)

        if isinstance(gradient_mode, np.ndarray):
            gradient = self._fill_value(gradient_mode)
        elif "oh" in gradient_mode:
            gradient = torch.zeros_like(prediction)[0:1]
            cam_class = cam_class or np.argmax(prediction.detach().cpu().numpy()[0])
            gradient[0][cam_class] = 1
        else:
            gradient = prediction.clone()

        self.model.zero_grad()
        prediction.backward(gradient=gradient, retain_graph=True)
        self.model.zero_grad()

Instances