(self, X_shape)
| 1496 | self.is_initialized = False |
| 1497 | |
| 1498 | def _init_params(self, X_shape): |
| 1499 | n_ex, in_rows, in_cols, in_ch = X_shape |
| 1500 | |
| 1501 | scaler = np.random.rand(in_rows, in_cols, in_ch) |
| 1502 | intercept = np.zeros((in_rows, in_cols, in_ch)) |
| 1503 | |
| 1504 | self.parameters = {"scaler": scaler, "intercept": intercept} |
| 1505 | |
| 1506 | self.gradients = { |
| 1507 | "scaler": np.zeros_like(scaler), |
| 1508 | "intercept": np.zeros_like(intercept), |
| 1509 | } |
| 1510 | |
| 1511 | self.is_initialized = True |
| 1512 | |
| 1513 | @property |
| 1514 | def hyperparameters(self): |