class Transformer(nn.Module):
def __init__(self, config: ModelArgs) -> None:
super().__init__()
self.config = config
self.tok_embeddings = nn.Embedding(config.vocab_size, config.dim)
self.layers = nn.ModuleList(TransformerBlock(config) for _ in range(config.n_layer))
self.norm = RMSNorm(config.dim, eps=config.norm_eps)
self.output = nn.Linear(config.dim, config.vocab_size, bias=False)
self.freqs_cis: Optional[Tensor] = None
self.mask_cache: Optional[Tensor] = None
self.max_batch_size = -1
self.max_seq_length = -1
- Embedding: vocab_size, dim