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comparison mlp_factory_approach.py @ 212:9b57ea8c767f

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previous commit was supposed to concern only one file, dataset.py, try to undo my other changes with this commit (nothing was broken though, just useless debugging prints)
author Thierry Bertin-Mahieux <bertinmt@iro.umontreal.ca>
date Wed, 21 May 2008 17:42:20 -0400
parents bd728c83faff
children 6fa8fbb0c3f6
comparison
equal deleted inserted replaced
211:bd728c83faff 212:9b57ea8c767f
31 """Update this model from more training data.""" 31 """Update this model from more training data."""
32 params = self.params 32 params = self.params
33 #TODO: why should we have to unpack target like this? 33 #TODO: why should we have to unpack target like this?
34 for input, target in input_target: 34 for input, target in input_target:
35 rval= self.update_fn(input, target[:,0], *params) 35 rval= self.update_fn(input, target[:,0], *params)
36 print rval[0] 36 #print rval[0]
37 37
38 def __call__(self, testset, fieldnames=['output_class']): 38 def __call__(self, testset, fieldnames=['output_class']):
39 """Apply this model (as a function) to new data""" 39 """Apply this model (as a function) to new data"""
40 #TODO: cache fn between calls 40 #TODO: cache fn between calls
41 assert 'input' == testset.fieldNames()[0] 41 assert 'input' == testset.fieldNames()[0]
121 best = rval 121 best = rval
122 for stp in self.early_stopper(): 122 for stp in self.early_stopper():
123 rval.update( 123 rval.update(
124 minset.minibatches([input, target], minibatch_size=min(32, 124 minset.minibatches([input, target], minibatch_size=min(32,
125 len(trainset)))) 125 len(trainset))))
126 print 'mlp.__call__(), we did an update' 126 #print 'mlp.__call__(), we did an update'
127 if stp.set_score: 127 if stp.set_score:
128 stp.score = rval(valset, ['loss_01']) 128 stp.score = rval(valset, ['loss_01'])
129 if (stp.score < stp.best_score): 129 if (stp.score < stp.best_score):
130 best = copy.copy(rval) 130 best = copy.copy(rval)
131 rval = best 131 rval = best