evaluate_delta_features.py 文件源码

def extract_encoder(network, inputshape, start, end):
    layers = las.layers.get_all_layers(network)
    weights = []
    biases = []
    activations = []
    layersizes = []

    for l in layers[start:end]:
        weights.append(l.W)
        biases.append(l.b)
        activations.append(l.nonlinearity)
        layersizes.append(l.num_units)

    input = T.matrix('input', dtype='float32')
    encoder = InputLayer(inputshape, input, name='input')
    encoder = autoencoder.create_pretrained_encoder(encoder, weights, biases, activations, layersizes)
    return encoder