--- a
+++ b/examples/cinc17/entry/evaler.py
@@ -0,0 +1,32 @@
+import json
+import keras
+import numpy as np
+import scipy.io as sio
+import scipy.stats as sst
+
+import load
+import network
+import util
+
+def predict(record):
+    ecg = load.load_ecg(record +".mat")
+    preproc = util.load(".")
+    x = preproc.process_x([ecg])
+
+    params = json.load(open("config.json"))
+    params.update({
+        "compile" : False,
+        "input_shape": [None, 1],
+        "num_categories": len(preproc.classes)
+    })
+
+    model = network.build_network(**params)
+    model.load_weights('model.hdf5')
+
+    probs = model.predict(x)
+    prediction = sst.mode(np.argmax(probs, axis=2).squeeze())[0][0]
+    return preproc.int_to_class[prediction]
+
+if __name__ == '__main__':
+    import sys
+    print predict(sys.argv[1])