def train(data, model, num_frontends, resume_epoch, model_dir):
cb = SaveModelsAndTerminateEarly()
cb.set_params(model_dir, resume_epoch)
X_train, y_train = data[0]
X_val, y_val = data[1]
if 1 < num_frontends:
X_train = [X_train] * num_frontends
X_val = [X_val] * num_frontends
try:
model.fit(X_train,
y_train,
validation_data=(X_val, y_val),
nb_epoch=10000,
batch_size=128,
callbacks=[cb],
show_accuracy=True)
except EarlyTermination:
pass
