keras.py

from keras.models import Sequential  
from keras.layers import Dense, Activation
from sklearn.datasets import load_digits

# Loading digits
x, y = load_digits(n_class=10, return_X_y=True)

# Convert to categorical
yhot = keras.utils.to_categorical(y, num_classes=10)

input_size = 64
hidden_input_size = 32
output_size = 10

model.add(Dense(units=hidden_input_size, input_dim=input_size))
model.add(Activation('relu'))
model.add(Dense(units=output_size, input_dim=hidden_input_size))
model.add(Activation('softmax'))

model.compile(optimizer='rmsprop',
              loss='categorical_crossentropy',
              metrics=['accuracy'])

model.fit(x, y)