t = self.iterations + 1
lr_t = self.lr / (1. - K.pow(self.beta_1, t))
shapes = [x.shape for x in K.batch_get_value(params)]
// zero init of 1st moment
ms = [K.zeros(shape) for shape in shapes]
// zero init of exponentially weighted infinity norm
us = [K.zeros(shape) for shape in shapes]
self.weights = [self.iterations] + ms + us
for p, g, m, u in zip(params, grads, ms, us):
After Change
t = self.iterations + 1
lr_t = self.lr / (1. - K.pow(self.beta_1, t))
shapes = [K.get_variable_shape(p) for p in params]
// zero init of 1st moment
ms = [K.zeros(shape) for shape in shapes]
// zero init of exponentially weighted infinity norm
us = [K.zeros(shape) for shape in shapes]
self.weights = [self.iterations] + ms + us
for p, g, m, u in zip(params, grads, ms, us):
