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refine Adamlike

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Connor Olding 2020-03-17 07:26:05 -07:00
parent 06bbfc6340
commit 4a5084df48
1 changed files with 8 additions and 6 deletions
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14
onn/optimizer.py
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@ -436,8 +436,8 @@ class Adamlike(Optimizer):
debias=True, runmax=False, yogi=False, eps=1e-8):
self.b1 = _f(b1) # decay term
self.b2 = _f(b2) # decay term
self.b1_t_default = _f(b1) # decay term power t
self.b2_t_default = _f(b2) # decay term power t
self.b1_t_default = _f(np.abs(b1)) # decay term power t
self.b2_t_default = _f(np.abs(b2)) # decay term power t
self.power = _f(power)
self.debias = bool(debias)
self.runmax = bool(runmax)
@ -487,17 +487,19 @@ class Adamlike(Optimizer):
delta = mt
elif self.power == 1:
delta = mt / (vt + self.eps)
elif self.power == 1/2: # TODO: is this actually faster?
elif self.power == 1/2:
delta = mt / (np.sqrt(vt) + self.eps)
elif self.power == 1/3: # TODO: is this actually faster?
elif self.power == 1/3:
delta = mt / (np.cbrt(vt) + self.eps)
elif self.power == 1/4:
delta = mt / (np.sqrt(np.sqrt(vt)) + self.eps)
else:
delta = mt / (vt**self.power + self.eps)
if self.debias:
# decay gain.
self.b1_t *= self.b1
self.b2_t *= self.b2
self.b1_t *= np.abs(self.b1)
self.b2_t *= np.abs(self.b2)
return -self.lr * delta