Mercurial > pylearn
comparison mlp_factory_approach.py @ 265:ae0a8345869b
commented junk in the default test (main function) of mlp_factory_approach so the test still works
| author | Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca> |
|---|---|
| date | Wed, 04 Jun 2008 17:34:01 -0400 |
| parents | a1793a5e9523 |
| children | eded3cb54930 |
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| 264:a1793a5e9523 | 265:ae0a8345869b |
|---|---|
| 315 self.failUnless(n_match == (numpy.sum(training_set1.fields()['target'] == | 315 self.failUnless(n_match == (numpy.sum(training_set1.fields()['target'] == |
| 316 training_set2.fields()['target'])), omatch) | 316 training_set2.fields()['target'])), omatch) |
| 317 | 317 |
| 318 model1.save('/tmp/model1') | 318 model1.save('/tmp/model1') |
| 319 | 319 |
| 320 denoising_aa = GraphLearner(denoising_g) | 320 #denoising_aa = GraphLearner(denoising_g) |
| 321 model1 = denoising_aa(trainset) | 321 #model1 = denoising_aa(trainset) |
| 322 hidset = model(trainset, fieldnames=['hidden']) | 322 #hidset = model(trainset, fieldnames=['hidden']) |
| 323 model2 = denoising_aa(hidset) | 323 #model2 = denoising_aa(hidset) |
| 324 | 324 |
| 325 f = open('blah', 'w') | 325 #f = open('blah', 'w') |
| 326 for m in model: | 326 #for m in model: |
| 327 m.save(f) | 327 # m.save(f) |
| 328 filetensor.write(f, initial_classification_weights) | 328 #filetensor.write(f, initial_classification_weights) |
| 329 f.flush() | 329 #f.flush() |
| 330 | 330 |
| 331 deep_sigmoid_net = GraphLearner(deepnetwork_g) | 331 #deep_sigmoid_net = GraphLearner(deepnetwork_g) |
| 332 deep_model = deep_sigmoid_net.load('blah') | 332 #deep_model = deep_sigmoid_net.load('blah') |
| 333 deep_model.update(trainset) #do some fine tuning | 333 #deep_model.update(trainset) #do some fine tuning |
| 334 | 334 |
| 335 model1_dup = learn_algo('/tmp/model1') | 335 model1_dup = learn_algo('/tmp/model1') |
| 336 | 336 |
| 337 | 337 |
| 338 def equiv(self, g0, g1): | 338 def equiv(self, g0, g1): |