def __init__(self,
var_list,
*,
beta1=0.9,
beta2=0.999,
epsilon=1e-08,
scale_grad_by_procs=True,
comm=None):
self.var_list = var_list
self.beta1 = beta1
self.beta2 = beta2
self.epsilon = epsilon
self.scale_grad_by_procs = scale_grad_by_procs
size = sum(U.numel(v) for v in var_list)
self.m = np.zeros(size, 'float32')
self.v = np.zeros(size, 'float32')
self.t = 0
self.setfromflat = U.SetFromFlat(var_list)
self.getflat = U.GetFlat(var_list)
self.comm = MPI.COMM_WORLD if comm is None else comm
def nograd(self, var_list):
return tf.concat(axis=0,
values=[
tf.reshape(tf.zeros_like(v), [U.numel(v)])
for v in var_list
])