bimodal_diff_with_val.py 文件源码

def load_dbn(path='models/oulu_ae.mat'):
    """
    load a pretrained dbn from path
    :param path: path to the .mat dbn
    :return: pretrained deep belief network
    """
    # create the network using weights from pretrain_nn.mat
    nn = sio.loadmat(path)
    w1 = nn['w1']
    w2 = nn['w2']
    w3 = nn['w3']
    w4 = nn['w4']
    b1 = nn['b1'][0]
    b2 = nn['b2'][0]
    b3 = nn['b3'][0]
    b4 = nn['b4'][0]
    weights = [w1, w2, w3, w4]
    biases = [b1, b2, b3, b4]
    shapes = [2000, 1000, 500, 50]
    nonlinearities = [rectify, rectify, rectify, linear]
    return weights, biases, shapes, nonlinearities