sde_autoencoder.py 文件源码

def build_encoder_layers(input_size, encode_size, sigma=0.5):
    """
    builds an autoencoder with gaussian noise layer
    :param input_size: input size
    :param encode_size: encoded size
    :param sigma: gaussian noise standard deviation
    :return: Weights of encoder layer, denoising autoencoder layer
    """
    W = theano.shared(GlorotUniform().sample(shape=(input_size, encode_size)))

    layers = [
        (InputLayer, {'shape': (None, input_size)}),
        (GaussianNoiseLayer, {'name': 'corrupt', 'sigma': sigma}),
        (DenseLayer, {'name': 'encoder', 'num_units': encode_size, 'nonlinearity': sigmoid, 'W': W}),
        (DenseLayer, {'name': 'decoder', 'num_units': input_size, 'nonlinearity': linear, 'W': W.T}),
    ]
    return W, layers