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comparison pylearn/gd/sgd.py @ 1462:7c72948e1d53

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Catch only exception to don't catch ctrl-C.
author Frederic Bastien <nouiz@nouiz.org>
date Fri, 08 Apr 2011 14:03:09 -0400
parents 86bf03990aad
children cac29ca79a74
comparison
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1461:2aa80f5b5bbc 1462:7c72948e1d53
14 :param stepsizes: step by this amount times the negative gradient on each iteration 14 :param stepsizes: step by this amount times the negative gradient on each iteration
15 :type stepsizes: [symbolic] scalar or list of one [symbolic] scalar per param 15 :type stepsizes: [symbolic] scalar or list of one [symbolic] scalar per param
16 """ 16 """
17 try: 17 try:
18 iter(stepsizes) 18 iter(stepsizes)
19 except: 19 except Exception:
20 stepsizes = [stepsizes for p in params] 20 stepsizes = [stepsizes for p in params]
21 if len(params) != len(grads): 21 if len(params) != len(grads):
22 raise ValueError('params and grads have different lens') 22 raise ValueError('params and grads have different lens')
23 updates = [(p, p - step * gp) for (step, p, gp) in zip(stepsizes, params, grads)] 23 updates = [(p, p - step * gp) for (step, p, gp) in zip(stepsizes, params, grads)]
24 return updates 24 return updates
25 25
26 def sgd_momentum_updates(params, grads, stepsizes, momentum=0.9): 26 def sgd_momentum_updates(params, grads, stepsizes, momentum=0.9):
27 # if stepsizes is just a scalar, expand it to match params 27 # if stepsizes is just a scalar, expand it to match params
28 try: 28 try:
29 iter(stepsizes) 29 iter(stepsizes)
30 except: 30 except Exception:
31 stepsizes = [stepsizes for p in params] 31 stepsizes = [stepsizes for p in params]
32 try: 32 try:
33 iter(momentum) 33 iter(momentum)
34 except: 34 except Exception:
35 momentum = [momentum for p in params] 35 momentum = [momentum for p in params]
36 if len(params) != len(grads): 36 if len(params) != len(grads):
37 raise ValueError('params and grads have different lens') 37 raise ValueError('params and grads have different lens')
38 headings = [theano.shared(p.get_value(borrow=False)*0) for p in params] 38 headings = [theano.shared(p.get_value(borrow=False)*0) for p in params]
39 updates = [] 39 updates = []