From 9c26f3b6e6b317c910bf3bdafc9b070c151dff4a Mon Sep 17 00:00:00 2001 From: Vasil Zlatanov Date: Wed, 27 Feb 2019 18:32:26 +0000 Subject: Add metric sna optimizer arguments --- lenet.py | 8 +++++--- 1 file 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) -- cgit v1.2.3