def __init__()

in inference/model.py [0:0]

• 14 lines of code
• 5 McCabe index (conditional complexity)

    def __init__(self, args: ModelArgs):
        """
        Initializes the Transformer model.

        Args:
            args (ModelArgs): Model arguments containing transformer parameters.
        """
        global world_size, rank
        world_size = dist.get_world_size() if dist.is_initialized() else 1
        rank = dist.get_rank() if dist.is_initialized() else 0
        Linear.dtype = torch.float8_e4m3fn if args.dtype == "fp8" else torch.bfloat16
        super().__init__()
        self.max_seq_len = args.max_seq_len
        self.embed = ParallelEmbedding(args.vocab_size, args.dim)
        self.layers = torch.nn.ModuleList()
        for layer_id in range(args.n_layers):
            self.layers.append(Block(layer_id, args))
        self.norm = RMSNorm(args.dim)
        self.head = ColumnParallelLinear(args.dim, args.vocab_size, dtype=torch.get_default_dtype())
        self.register_buffer("freqs_cis", precompute_freqs_cis(args), persistent=False)