from tensorflow import keras
PARAMS = {'epoch_nr': 100,
mnist = keras.datasets.mnist
(x_train, y_train),(x_test, y_test) = mnist.load_data()
x_train, x_test = x_train / 255.0, x_test / 255.0
model = keras.models.Sequential([
keras.layers.Dense(PARAMS['unit_nr'], activation=keras.activations.relu),
keras.layers.Dropout(PARAMS['dropout']),
keras.layers.Dense(10, activation=keras.activations.softmax)
optimizer = keras.optimizers.SGD(lr=PARAMS['lr'],
momentum=PARAMS['momentum'],
nesterov=PARAMS['use_nesterov'],)
model.compile(optimizer=optimizer,
loss='sparse_categorical_crossentropy',
model.fit(x_train, y_train,
epochs=PARAMS['epoch_nr'],
batch_size=PARAMS['batch_size'])