Mercurial > pylearn
comparison algorithms/logistic_regression.py @ 473:31acd42b2b0b
__instance_type__ -> InstanceType
author | James Bergstra <bergstrj@iro.umontreal.ca> |
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date | Thu, 23 Oct 2008 18:05:09 -0400 |
parents | 69c800af1370 |
children | 8fcd0f3d9a17 |
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472:69c800af1370 | 473:31acd42b2b0b |
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7 | 7 |
8 import numpy as N | 8 import numpy as N |
9 | 9 |
10 | 10 |
11 class Module_Nclass(module.FancyModule): | 11 class Module_Nclass(module.FancyModule): |
12 class __instance_type__(module.FancyModuleInstance): | 12 class InstanceType(module.FancyModuleInstance): |
13 def initialize(self, n_in, n_out): | 13 def initialize(self, n_in, n_out): |
14 #self.component is the LogisticRegressionTemplate instance that built this guy. | 14 #self.component is the LogisticRegressionTemplate instance that built this guy. |
15 | 15 |
16 self.w = N.zeros((n_in, n_out)) | 16 self.w = N.zeros((n_in, n_out)) |
17 self.b = N.zeros(n_out) | 17 self.b = N.zeros(n_out) |
46 | 46 |
47 self.update = module.Method([self.x, self.targ], sum_xent, | 47 self.update = module.Method([self.x, self.targ], sum_xent, |
48 updates = dict((p, p - self.lr * g) for p, g in zip(self.params, gparams))) | 48 updates = dict((p, p - self.lr * g) for p, g in zip(self.params, gparams))) |
49 | 49 |
50 class Module(module.FancyModule): | 50 class Module(module.FancyModule): |
51 class __instance_type__(module.FancyModuleInstance): | 51 class InstanceType(module.FancyModuleInstance): |
52 def initialize(self, n_in): | 52 def initialize(self, n_in): |
53 #self.component is the LogisticRegressionTemplate instance that built this guy. | 53 #self.component is the LogisticRegressionTemplate instance that built this guy. |
54 | 54 |
55 self.w = N.random.randn(n_in,1) | 55 self.w = N.random.randn(n_in,1) |
56 self.b = N.random.randn(1) | 56 self.b = N.random.randn(1) |