d14ad44d0f425c04be5a6cdca13fc513fba53843,test_models_train.py,,,#,11

Before Change

                  loss=deep_speaker_loss,
                  metrics=["accuracy"])

    inputs = list(np.expand_dims(network_inputs, axis=1))
    model.fit(inputs, np.expand_dims([0] * len(inputs), axis=1))

    print(model.summary())

After Change

    output = model.predict(network_inputs)

    // stub_targets = np.expand_dims([0] * BATCH_SIZE * NUM_FRAMES, axis=1)
    stub_targets = np.random.uniform(size=(BATCH_SIZE * NUM_FRAMES, 512))
    print(model.train_on_batch(network_inputs, stub_targets))

    // from triplet_loss import deep_speaker_loss

Instances