22                 beta, eps, decay, running_mean, running_var):  argument
32                 beta, eps, decay, running_mean, running_var):  argument
55                 running_mean, running_var)
58                 running_mean, running_var = backend.from_chx(
59                     (running_mean, running_var))
64                 running_var *= decay
65                 running_var += (1 - decay) * adjust * var
77                                        running_mean, running_var)
81                 running_var = backend.to_chx(running_var)
84         return y, y_layout, running_mean, running_var, mean, var, inv_std, None
140                 beta, eps, decay, running_mean, running_var):  argument
174             if isinstance(running_var, intel64.ideep.mdarray):
175                 running_var.inplace_axpby(
178                 running_var *= decay
179                 running_var += var * adjust * (1 - decay)
180         return y, None, running_mean, running_var, mean, var, inv_std, None
216                 beta, eps, decay, running_mean, running_var):  argument
219             var = running_var
238             y, y_layout, running_mean, running_var, mean, var, inv_std,
303         self.running_var = var
361         if self.running_mean is None or self.running_var is None:
369                 and self.running_var.is_contiguous):
378             x, gamma, beta, self.running_mean, self.running_var,
436             y, y_layout, self.running_mean, self.running_var,
444                     running_var=self.running_var))
948     eps, running_mean, running_var, decay, axis = argument.parse_kwargs(
954     return BatchNormalization(eps, running_mean, running_var, decay,