(self, X: Dict[str, np.ndarray])
| 78 | self._out_dim = sum(self.input_dim.values()) |
| 79 | |
| 80 | def transform(self, X: Dict[str, np.ndarray]) -> np.ndarray: |
| 81 | return np.concatenate([X[key].flatten() for key in INPUT_TYPES], axis=0) |
| 82 | # return np.concatenate([torch.flatten(subX) for subX in X.values()], dim=0) |
| 83 | |
| 84 | def batched_transform(self, X: Dict[str, np.ndarray]) -> np.ndarray: |
| 85 | return np.concatenate([X[key].reshape((X[key].shape[0], -1)) for key in INPUT_TYPES], axis=1) |
nothing calls this directly
no outgoing calls
no test coverage detected