def METHOD_NAME(model):
    import numpy as np
    x = torch.rand(3, 4, 32000)  # (batch, num_mic, length)
    num_mic = (
        torch.from_numpy(np.array([3, 3, 2]))
        .view(
            -1,
        )
        .type(x.type())
    )  # ad-hoc array
    none_mic = torch.zeros(1).type(x.type())  # fixed-array
    y1 = model(x, num_mic.long())
    y2 = model(x, none_mic.long())
    print(y1.shape, y2.shape)  # (batch, nspk, length)