| 1049 | self.is_initialized = False |
| 1050 | |
| 1051 | def _init_params(self): |
| 1052 | scaler = np.random.rand(self.in_ch) |
| 1053 | intercept = np.zeros(self.in_ch) |
| 1054 | |
| 1055 | # init running mean and std at 0 and 1, respectively |
| 1056 | running_mean = np.zeros(self.in_ch) |
| 1057 | running_var = np.ones(self.in_ch) |
| 1058 | |
| 1059 | self.parameters = { |
| 1060 | "scaler": scaler, |
| 1061 | "intercept": intercept, |
| 1062 | "running_var": running_var, |
| 1063 | "running_mean": running_mean, |
| 1064 | } |
| 1065 | |
| 1066 | self.gradients = { |
| 1067 | "scaler": np.zeros_like(scaler), |
| 1068 | "intercept": np.zeros_like(intercept), |
| 1069 | } |
| 1070 | |
| 1071 | self.is_initialized = True |
| 1072 | |
| 1073 | @property |
| 1074 | def hyperparameters(self): |