Siimplied Keras for Users

easy_keras.py

from keras import layers, models

Nin = 784
Nh = 100
number_of_class = 10
Nout = number_of_class

class ANN(models.Model):
    def __init__(self, Nin, Nh, Nout):
        # Prepare network layers and activate functions
        hidden = layers.Dense(Nh)
        output = layers.Dense(Nout)
        relu = layers.Activation('relu')
        softmax = layers.Activation('softmax')      
        
        # Connect network elements
        x = layers.Input(shape=(Nin,))
        h = relu(hidden(x))
        y = softmax(output(h))
        
        super().__init__(x, y)

        self.compile(loss='categorical_crossentropy', 
                     optimizer='adam', 
                     metrics=['accuracy'])
        
model = ANN(Nin, Nh, Nout)