    def __init__(self, config):
        """Adding adaptive layer norm, conditional embeddings, and multi-level input embeddings to the decoder layer"""
        super().__init__(config)
        self.layers = nn.ModuleList(
            [LlamaNARDecoderLayer(config) for _ in range(config.num_hidden_layers)]
        )
        self.norm = LlamaAdaptiveRMSNorm(
            config.hidden_size, eps=config.rms_norm_eps, dim_cond=config.hidden_size
        )

        self.embed_cond = nn.Embedding(
            NUM_QUANTIZERS, config.hidden_size
        )  # 7 quantization layers

        for layer in self.layers:
            layer.input_layernorm = LlamaAdaptiveRMSNorm(
                config.hidden_size, eps=config.rms_norm_eps, dim_cond=config.hidden_size
            )
            layer.post_attention_layernorm = LlamaAdaptiveRMSNorm(
                config.hidden_size, eps=config.rms_norm_eps, dim_cond=config.hidden_size
            )

        self.post_init()
Adding adaptive layer norm, conditional embeddings, and multi-level input embeddings to the decoder layer
models/tts/valle_v2/valle_nar.py