diff options
| -rw-r--r-- | lenet.py | 4 |
1 files changed, 2 insertions, 2 deletions
@@ -118,7 +118,7 @@ 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, metrics=[categorical_accuracy], optimizer = None, keep_training = False): +def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100, metrics=[categorical_accuracy], optimizer = None, keep_training = False, verbose=1): shape = (32, 32, 1) # Pad data to 32x32 (MNIST is 28x28) @@ -133,7 +133,7 @@ def train_classifier(x_train, y_train, x_val, y_val, batch_size=128, epochs=100, model.compile(loss='categorical_crossentropy', metrics=metrics, optimizer=optimizer) if keep_training: model.load_weights('./weights.h5') - history = model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, verbose=1, validation_data = (x_val, y_val)) + history = model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, verbose=verbose, validation_data = (x_val, y_val)) model.save_weights('./model_gan.h5') plot_history(history, 'categorical_accuracy') plot_history(history) |