Created
September 19, 2020 17:39
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Adam Update
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""" | |
Just an example of computing the adam update for a list of parameter gradients. | |
""" | |
def adam_update(l_grad, l_m=None, l_v=None): | |
# l_n = list of running exponential average of first moment of gradient | |
# l_v = list of running exponential average of second moment of gradient | |
# l_grad = list of gradients of current batch | |
β1 = 0.9 | |
β2 = 0.999 | |
ϵ = 1e-7 | |
l_update = [] | |
l_mt1 = [] | |
l_vt1 = [] | |
if l_m is None: | |
l_m = [elem * 0.0 for elem in l_grad] | |
if l_v is None: | |
l_v = [elem * 0.0 for elem in l_grad] | |
for my_grad, m, v in zip(l_grad, l_m, l_v): | |
m = β1 * m + (1-β1) * my_grad | |
v = β2 * v + (1-β2) * my_grad**2 | |
l_update.append((m / (np.sqrt(v) + ϵ))) | |
l_mt1.append(m) | |
l_vt1.append(v) | |
return l_update, l_mt1, l_vt1 |
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