| 15 | |
| 16 | |
| 17 | def basic_static_model(include_top=True): |
| 18 | ni = Input((None, 24, 24, 3)) |
| 19 | nn = Conv2d(16, (5, 5), (1, 1), padding='SAME', act=tf.nn.relu, name="conv1")(ni) |
| 20 | nn = MaxPool2d((3, 3), (2, 2), padding='SAME', name='pool1')(nn) |
| 21 | |
| 22 | nn = Conv2d(16, (5, 5), (1, 1), padding='SAME', act=tf.nn.relu, name="conv2")(nn) |
| 23 | nn = MaxPool2d((3, 3), (2, 2), padding='SAME', name='pool2')(nn) |
| 24 | |
| 25 | nn = Flatten(name='flatten')(nn) |
| 26 | nn = Dense(100, act=None, name="dense1")(nn) |
| 27 | if include_top is True: |
| 28 | nn = Dense(10, act=None, name="dense2")(nn) |
| 29 | M = Model(inputs=ni, outputs=nn) |
| 30 | return M |
| 31 | |
| 32 | |
| 33 | class basic_dynamic_model(Model): |