Merge pull request #118 from dansbecker/master
Add predict() for Sequential models
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commit
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@ -3,6 +3,7 @@ from __future__ import print_function
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import theano
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import theano
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import theano.tensor as T
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import theano.tensor as T
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import numpy as np
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import numpy as np
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import warnings
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from . import optimizers
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from . import optimizers
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from . import objectives
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from . import objectives
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@ -222,8 +223,7 @@ class Sequential(object):
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history['val_acc'].append(float(val_acc))
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history['val_acc'].append(float(val_acc))
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return history
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return history
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def predict(self, X, batch_size=128, verbose=1):
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def predict_proba(self, X, batch_size=128, verbose=1):
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batches = make_batches(len(X), batch_size)
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batches = make_batches(len(X), batch_size)
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if verbose==1:
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if verbose==1:
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progbar = Progbar(target=len(X))
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progbar = Progbar(target=len(X))
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@ -241,6 +241,12 @@ class Sequential(object):
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return preds
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return preds
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def predict_proba(self, X, batch_size=128, verbose=1):
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preds = self.predict(X, batch_size, verbose)
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if preds.min()<0 or preds.max()>1:
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warnings.warn("Network returning invalid probability values.")
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return preds
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def predict_classes(self, X, batch_size=128, verbose=1):
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def predict_classes(self, X, batch_size=128, verbose=1):
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proba = self.predict_proba(X, batch_size=batch_size, verbose=verbose)
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proba = self.predict_proba(X, batch_size=batch_size, verbose=verbose)
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