simple-generative-model-regressor.py 文件源码

def wavenetBlock(n_atrous_filters, atrous_filter_size, atrous_rate,
                 n_conv_filters, conv_filter_size):
    def f(input_):
        residual = input_
        tanh_out = AtrousConvolution1D(n_atrous_filters, atrous_filter_size,
                                       atrous_rate=atrous_rate,
                                       border_mode='same',
                                       activation='tanh')(input_)
        sigmoid_out = AtrousConvolution1D(n_atrous_filters, atrous_filter_size,
                                          atrous_rate=atrous_rate,
                                          border_mode='same',
                                          activation='sigmoid')(input_)
        merged = merge([tanh_out, sigmoid_out], mode='mul')
        skip_out = Convolution1D(1, 1, activation='relu', border_mode='same')(merged)
        out = merge([skip_out, residual], mode='sum')
        return out, skip_out
    return f