| 16 | |
| 17 | # define the network |
| 18 | def mlp(): |
| 19 | ni = tl.layers.Input([None, 784], name='input') |
| 20 | net = tl.layers.Dropout(keep=0.8, name='drop1')(ni) |
| 21 | net = tl.layers.Dense(n_units=n_units1, act=tf.nn.relu, name='relu1')(net) |
| 22 | net = tl.layers.Dropout(keep=0.5, name='drop2')(net) |
| 23 | net = tl.layers.Dense(n_units=n_units2, act=tf.nn.relu, name='relu2')(net) |
| 24 | net = tl.layers.Dropout(keep=0.5, name='drop3')(net) |
| 25 | net = tl.layers.Dense(n_units=10, act=None, name='output')(net) |
| 26 | M = tl.models.Model(inputs=ni, outputs=net) |
| 27 | return M |
| 28 | |
| 29 | |
| 30 | network = mlp() |