0cfe82c6beb9a28a5ff7da81b86fa0e93c388f14,tasks/save_reload_model.py,,,#,10

Before Change

// simple TCN model.
max_len = 100
max_features = 50
i = Input(shape=(max_len,))
x = Embedding(max_features, 16)(i)
x = TCN(nb_filters=12,
        dropout_rate=0.5,  // with dropout here.
        kernel_size=6,
        dilations=[1, 2, 4])(x)
x = Dropout(0.5)(x)  // and dropout here.
x = Dense(1, activation="sigmoid")(x)

model = Model(inputs=[i], outputs=[x])

if os.path.exists("tcn.npz"):
    // Load checkpoint if file exists.
    w = np.load("tcn.npz", allow_pickle=True)["w"]

After Change

// Make inference.
out2 = reloaded_model.predict(inputs)[0, 0]
print("*" * 80)
print("Inference after loading:", out2)

Instances