Move regularization parameters to train().

lmjohns3 · Mar 24, 2015 · d9960f7 · d9960f7
1 parent 99edbb9
commit d9960f7
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Showing 2 changed files with 5 additions and 5 deletions.
diff --git a/examples/cifar-autoencoder.py b/examples/cifar-autoencoder.py
@@ -46,10 +46,9 @@ def main(args):
     e = theanets.Experiment(
         theanets.Autoencoder,
         layers=(K, feat ** 2, K),
-        input_noise=1,
     )
 
-    e.train(whiten(train), whiten(valid))
+    e.train(whiten(train), whiten(valid), input_noise=1)
 
     plot_layers([
         color(e.network.find(1, 0).get_value().T).T,

diff --git a/examples/lstm_chime.py b/examples/lstm_chime.py
@@ -57,8 +57,9 @@ def layer(n):
     theanets.recurrent.Classifier,
     layers=(39, layer(156), layer(300), layer(102), 51),
     recurrent_error_start=0,
-    input_noise=0.6,
-    max_gradient_norm=10,
 )
 e.train(batches(scipy.io.netcdf_file(TRAIN_NC)),
-        batches(scipy.io.netcdf_file(VALID_NC)))
+        batches(scipy.io.netcdf_file(VALID_NC)),
+        input_noise=0.6,
+        max_gradient_norm=10,
+)