Method batched_transform

climart/data_transform/transforms.py:84–86

(self, X: Dict[str, np.ndarray])

        # return np.concatenate([torch.flatten(subX) for subX in X.values()], dim=0)

    def batched_transform(self, X: Dict[str, np.ndarray]) -> np.ndarray:
        return np.concatenate([X[key].reshape((X[key].shape[0], -1)) for key in INPUT_TYPES], axis=1)
        # return torch.cat([torch.flatten(subX, start_dim=1).unsqueeze(1) for subX in X.values()], dim=1)


class RepeatGlobalsTransform(AbstractTransform):