Dummy network with resnet-like architecture.
()
| 55 | |
| 56 | |
| 57 | def model(): |
| 58 | """ |
| 59 | Dummy network with resnet-like architecture. |
| 60 | """ |
| 61 | input_img = tf.keras.layers.Input(shape=(32, 32, 3)) |
| 62 | x = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3))(input_img) |
| 63 | x = tf.keras.layers.ReLU()(x) |
| 64 | x = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3))(x) |
| 65 | x = tf.keras.layers.ReLU()(x) |
| 66 | x = identity_block(x) |
| 67 | x = identity_block_short_conv(x) |
| 68 | x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x) |
| 69 | x = tf.keras.layers.Flatten()(x) |
| 70 | x = tf.keras.layers.Dense(100)(x) |
| 71 | x = tf.keras.layers.ReLU()(x) |
| 72 | x = tf.keras.layers.Dense(10)(x) |
| 73 | return tf.keras.Model(input_img, x, name="Dummy_Model") |
| 74 | |
| 75 | |
| 76 | def optimizer(lr=0.001): |