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allow MomentumClip, SineCLR, WaveCLR in config

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Connor Olding 2017-07-21 19:43:57 +00:00
parent e7a6974829
commit 4a108a10ae
1 changed files with 21 additions and 3 deletions
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24
onn.py
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@ -886,9 +886,13 @@ def optim_from_config(config):
optim = RMSprop(mu=mu)
elif config.optim == 'sgd':
d1 = config.optim_decay1 if 'optim_decay1' in config else 0
if d1 > 0:
b1 = np.exp(-1/d1)
optim = Momentum(mu=b1, nesterov=config.nesterov)
clip = config.gradient_clip if 'gradient_clip' in config else 0.0
if d1 > 0 or clip > 0:
b1 = np.exp(-1/d1) if d1 > 0 else 0
if clip > 0:
optim = MomentumClip(mu=b1, nesterov=config.nesterov, clip=clip)
else:
optim = Momentum(mu=b1, nesterov=config.nesterov)
else:
optim = Optimizer()
else:
@ -904,6 +908,20 @@ def learner_from_config(config, optim, rscb):
callback=rscb, expando=expando)
# final learning rate isn't of interest here; it's gonna be close to 0.
log('total epochs', learner.epochs)
elif config.learner in ('sin', 'sine'):
lower_rate = config.learn * 1e-5 # TODO: allow access to this.
epochs = config.epochs * (config.restarts + 1)
frequency = config.epochs
learner = SineCLR(optim, epochs=epochs, frequency=frequency,
upper_rate=config.learn, lower_rate=lower_rate,
callback=rscb)
elif config.learner == 'wave':
lower_rate = config.learn * 1e-5 # TODO: allow access to this.
epochs = config.epochs * (config.restarts + 1)
frequency = config.epochs
learner = WaveCLR(optim, epochs=epochs, frequency=frequency,
upper_rate=config.learn, lower_rate=lower_rate,
callback=rscb)
elif config.learner == 'anneal':
learner = AnnealingLearner(optim, epochs=config.epochs, rate=config.learn,
halve_every=config.learn_halve_every)