f008a2a43bc4a9eb0760522723c88a70fb9b1f2c,examples/multi_inputs.py,,,#,25

Before Change

    m1.compile(optimizer="adam", loss="mse")
    utils.print_names_and_values(keract.get_activations(m1, [inp_a, inp_b]))
    keract.get_gradients_of_trainable_weights(m1, [inp_a, inp_b], out_c)
    keract.get_gradients_of_activations(m1, [inp_a, inp_b], out_c)

    // Just get the last layer!
    print(keract.get_activations(m1, [inp_a, inp_b], layer_name="last_layer"))
    keract.get_gradients_of_trainable_weights(m1, [inp_a, inp_b], out_c)

After Change

    m1.compile(optimizer="adam", loss="mse")
    utils.print_names_and_values(keract.get_activations(m1, [inp_a, inp_b]))
    utils.print_names_and_values(keract.get_gradients_of_trainable_weights(m1, [inp_a, inp_b], out_c))
    utils.print_names_and_values(keract.get_gradients_of_activations(m1, [inp_a, inp_b], out_c))

    // Just get the last layer!
    print(keract.get_activations(m1, [inp_a, inp_b], layer_name="last_layer"))
    utils.print_names_and_values(keract.get_gradients_of_activations(m1, [inp_a, inp_b], out_c,

Instances