      Whether or not to scale the residuals in the conditioner block. Since the top level prior does not have a
            conditioner, the default value is to None and should not be modified.
        num_layers (`int`, *optional*, defaults to 72):
            Number of layers of the transformer architecture.
        emb_dropout (`int`, *optional*, defaults to 0):
            Embedding dropout used in the lyric decoder.
        encoder_config (`JukeboxPriorConfig`, *optional*) :
            Configuration of the encoder which models the prior on the lyrics.
        encoder_loss_fraction (`float`, *optional*, defaults to 0.4):
            Multiplication factor used in front of the lyric encoder loss.
        hidden_size (`int`, *optional*, defaults to 2048):
            Hidden dimension of the attention layers.
        init_scale (`float`, *optional*, defaults to 0.2):
            Initialization scales for the prior modules.
        is_encoder_decoder (`bool`, *optional*, defaults to `True`):
            Whether or not the prior is an encoder-decoder model. In case it is not, and `nb_relevant_lyric_tokens` is
            greater than 0, the `encoder` args should be specified for the lyric encoding.
        mask (`bool`, *optional*, defaults to `False`):
            Whether or not to mask the previous positions in the attention.
        max_duration (`int`, *optional*, defaults to 600):
            Maximum supported duration of the generated song in seconds.
        max_nb_genres (`int`, *optional*, defaults to 1):
            Maximum number of genres that can be used to condition the model.
        merged_decoder (`bool`, *optional*, defaults to `True`):
            Whether or not the decoder and the encoder inputs are merged. This is used for the separated
            encoder-decoder architecture
        metadata_conditioning (`bool`, *optional*, defaults to `True)`:
            Whether or not to condition on the artist and genre metadata.
        metadata_dims (`List[int]`, *optional*, defaults to `[604, 7898]`):
            Number of genres and the number of artists that were used to train the embedding layers of the prior
            models.
        min_duration (`int`, *optional*, defaults to 0):
            Minimum duration of the generated audio on which the model was trained.
        mlp_multiplier (`float`, *optional*, defaults to 1.0):
            Multiplier coefficient used to define the hidden dimension of the MLP layers. 0.25 means that 0.25*width of
            the model will be used.
        music_vocab_size (`int`, *optional*, defaults to 2048):
            Number of different music tokens. Should be similar to the `JukeboxVQVAEConfig.nb_discrete_codes`.
        n_ctx (`int`, *optional*, defaults to 6144):
            Number of context tokens for each prior. The context tokens are the music tokens that are attended to when
            generating music tokens.
        n_heads (`int`, *optional*, defaults to 2):
                Number of attention heads.
        nb_relevant_lyric_tokens (`int`, *optional*, defaults to 384):
            Number of lyric tokens that are used when sampling a single window of length `n_ctx`
        res_conv_depth (`int`, *optional*, defaults to 3):
            Depth of the `JukeboxDecoderConvBock` used to upsample the previously sampled audio in the
            `JukeboxMusicTokenConditioner`.
        res_conv_width (`int`, *optional*, defaults to 128):
            Width of the `JukeboxDecoderConvBock` used to upsample the previously sampled audio in the
            `JukeboxMusicTokenConditioner`.
        res_convolution_multiplier (`int`, *optional*, defaults to 1):
            Multiplier used to scale the `hidden_dim` of the `JukeboxResConv1DBlock`.
        res_dilation_cycle (`int`, *optional*):
            Dilation cycle used to define the `JukeboxMusicTokenConditioner`. Usually similar to the ones used in the
            corresponding level of the VQVAE. The first prior does not use it as it is not conditioned on upper level
            tokens.
        res_dilation_growth_rate (`int`, *optional*, defaults to 1):
            Dilation grow rate used between each convolutionnal block of the `JukeboxMusicTokenConditioner`
        res_downs_t (`List[int]`, *optional*, defaults to `[3, 2, 2]`):
            Downsampling rates used in the audio conditioning network
        res_strides_t (`List[int]`, *optional*, defaults to `[2, 2, 2]`):
            Striding used in the audio conditioning network
        resid_dropout (`int`, *optional*, defaults to 0):
            Residual dropout used in the attention pattern.
        sampling_rate (`int`, *optional*, defaults to 44100):
            Sampling rate used for training.
        spread (`int`, *optional*):
            Spread used in the `summary_spread_attention` pattern
        timing_dims (`int`, *optional*, defaults to 64):
            Dimension of the timing embedding.
        zero_out (`bool`, *optional*, defaults to `False`):
            Whether or not to zero out convolution weights when initializing.
    Z
jukebox_priorZ