cnn-model-1.3.2.py

'''A sample CNN network for classification
'''

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

# keras modules
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Conv2D, Flatten
from tensorflow.keras.optimizers import RMSprop

n_digits = 10
model = Sequential()
model.add(Conv2D(filters=64,
                 kernel_size=3,
                 activation='relu',
                 strides=2,
                 input_shape=(28, 28, 1),
                 padding='same'))
model.add(Conv2D(filters=128,
                 kernel_size=3,
                 activation='relu',
                 strides=2))
model.add(Flatten())
model.add(Dense(n_digits, activation='softmax'))
model.compile(loss='categorical_crossentropy',
              optimizer=RMSprop(),
              metrics=['accuracy'])
model.summary()