reduce_lr = ReduceLROnPlateau(monitor="val_loss", patience=10, verbose=1)
reduce_lr.set_model(model)
reduce_lr.on_train_begin()
tensorboard = TensorBoard(log_dir="logs/")
tensorboard.set_model(model)
tensorboard.on_train_begin()
epochs = 3
train_logs_dict = {}
test_logs_dict = {}
for epoch in range(epochs):
training_acc, testing_acc, training_loss, testing_loss = [], [], [], []
print("\nStart of epoch %d" % (epoch + 1, ))
# Iterate over the batches of the dataset.
modelcheckpoint.on_epoch_begin(epoch)
earlystop.on_epoch_begin(epoch)
reduce_lr.on_epoch_begin(epoch)
tensorboard.on_epoch_begin(epoch)
for x_batch_train, y_batch_train in get_batch(batch_size, x_train,
y_train):
train_loss, train_accuracy = model.train_on_batch(
x_batch_train, y_batch_train)
training_acc.append(train_accuracy)
training_loss.append(train_loss)
for x_batch_test, y_batch_test in get_batch(batch_size, x_test, y_test):
test_loss, test_accuracy = model.test_on_batch(x_batch_test,
y_batch_test)
