From fe093237ede54aa1a271baeeeb7399b40c133a49 Mon Sep 17 00:00:00 2001 From: Job333 Date: Sun, 22 Jul 2018 12:27:52 +0200 Subject: [PATCH] Declared X_in as dtype='float32' in autoencoder.py train_op ran into trouble as default theano.tensor.matrix is of type float64 while all other variables are of type float32. Declaring X_in as dtype='float32' fixes the problem. --- unsupervised_class2/autoencoder.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/unsupervised_class2/autoencoder.py b/unsupervised_class2/autoencoder.py index 87633fa1..4e9b85eb 100644 --- a/unsupervised_class2/autoencoder.py +++ b/unsupervised_class2/autoencoder.py @@ -60,7 +60,7 @@ def fit(self, X, learning_rate=0.5, mu=0.99, epochs=1, batch_sz=100, show_fig=Fa self.dparams = [self.dW, self.dbh, self.dbo] self.forward_dparams = [self.dW, self.dbh] - X_in = T.matrix('X_%s' % self.id) + X_in = T.matrix('X_%s' % self.id, dtype='float32') X_hat = self.forward_output(X_in) # attach it to the object so it can be used later @@ -177,7 +177,7 @@ def fit(self, X, Y, Xtest, Ytest, for ae in self.hidden_layers: self.params += ae.forward_params - X_in = T.matrix('X_in') + X_in = T.matrix('X_in', dtype='float32') targets = T.ivector('Targets') pY = self.forward(X_in) pFad - Phonifier reborn

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