Add metric sna optimizer arguments

1 files changed, 5 insertions, 3 deletions

diff --git a/lenet.py b/lenet.py
index 8595eb8..d09f3cc 100644
--- a/lenet.py
+++ b/lenet.py
@@ -106,12 +106,14 @@ def plot_history(history, metric = None):
     plt.ylabel('Loss')
     plt.xlabel('Epoch')
 
-def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100):
+def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100, metrics=['categorical_accuracy'], optimizer = None):
   shape = (32, 32, 1)
   model = get_lenet(shape)
 
-  sgd = optimizers.SGD(lr=0.001, decay=1e-6, momentum=0.9, nesterov=True)
-  model.compile(loss='categorical_crossentropy', optimizer=sgd)
+  if optimizer = None:
+      optimizer = optimizers.SGD(lr=0.001, decay=1e-6, momentum=0.9, nesterov=True)
+
+  model.compile(loss='categorical_crossentropy', metrics=metrics, optimizer=optimizer)
   
   history = model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, verbose=1, validation_data = (x_val, y_val))
   plot_history(history)