model.py 文件源码

def __init__(self, frame_sizes, n_rnn, dim, learn_h0, q_levels,
                 weight_norm):
        super().__init__()

        self.dim = dim
        self.q_levels = q_levels

        ns_frame_samples = map(int, np.cumprod(frame_sizes))
        self.frame_level_rnns = torch.nn.ModuleList([
            FrameLevelRNN(
                frame_size, n_frame_samples, n_rnn, dim, learn_h0, weight_norm
            )
            for (frame_size, n_frame_samples) in zip(
                frame_sizes, ns_frame_samples
            )
        ])

        self.sample_level_mlp = SampleLevelMLP(
            frame_sizes[0], dim, q_levels, weight_norm
        )