diff --git a/mmodel/theano/THEANO.py b/mmodel/theano/THEANO.py
index 26a20d4..a6e66db 100644
--- a/mmodel/theano/THEANO.py
+++ b/mmodel/theano/THEANO.py
@@ -37,16 +37,15 @@ class ModelTHEANO(ModelBase):
         else:
             X_train, X_test, Y_train, Y_test = cross_validation.train_test_split(X, Y, test_size=0.2, random_state=0)
 
-        print type(X), type(X_train), type(X_train[0])
-        return
-
-        X_train, Y_train = np.array(X_train), np.array(Y_train)
-        X_test, Y_test = np.array(X_test), np.array(Y_test)
+        X_train = theano.shared(np.asarray(X_train, dtype=theano.config.floatX), borrow=True)
+        Y_train = theano.shared(np.asarray(Y_train, dtype=theano.config.floatX), borrow=True)
+        X_test = theano.shared(np.asarray(X_test, dtype=theano.config.floatX), borrow=True)
+        Y_test = theano.shared(np.asarray(Y_test, dtype=theano.config.floatX), borrow=True)
 
         n_train_batches = X_train.shape[0] / batch_size
         n_test_batches = X_test.shape[0] / batch_size
 
-        rng = np.random.RandomState("whoami")
+        rng = np.random.RandomState(12306)
         index = T.lscalar()
         x = T.matrix('x')
         y = T.ivector('y')
@@ -89,7 +88,7 @@ class ModelTHEANO(ModelBase):
         layer2 = ConvPoolLayer(
             rng,
             input=layer1.output,
-            image_shape=(batch_size, nkerns[0], 16, 16),
+            image_shape=(batch_size, nkerns[1], 16, 16),
             filter_shape=(nkerns[2], nkerns[1], 5, 5),
             poolsize=(3, 3)
         )
--
libgit2 0.21.2