Update llama.py

This commit is contained in:
Daniel Han 2024-07-23 10:35:03 -07:00
commit 9a18fee63f

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@ -1054,7 +1054,7 @@ pass
# See https://github.com/vllm-project/vllm/blob/main/vllm/model_executor/layers/rotary_embedding.py#L736
# For Llama 3.1
class LlamaExtendedRotaryEmbedding(LlamaRotaryEmbedding):
class LlamaExtendedRotaryEmbedding(torch.nn.Module):
def __init__(self, dim, max_position_embeddings=2048, base=10000, device=None):
super().__init__()
self.dim = dim
@ -1113,6 +1113,24 @@ class LlamaExtendedRotaryEmbedding(LlamaRotaryEmbedding):
new_freqs.append((1 - smooth) * freq / scale_factor + smooth * freq)
return torch.tensor(new_freqs, dtype=freqs.dtype, device=freqs.device)
pass
def forward(self, x, position_ids=None, seq_len=None):
# x: [bs, num_attention_heads, seq_len, head_size]
if seq_len > self.current_rope_size:
self._set_cos_sin_cache(seq_len=seq_len, device=x.device, dtype=x.dtype)
return (
self.cos_cached[:seq_len].to(dtype = x.dtype),
self.sin_cached[:seq_len].to(dtype = x.dtype),
)
pass
def extend_rope_embedding(self, x, seq_len):
if seq_len <= self.current_rope_size: return
# Iteratively grow by increments of 8192
self.current_rope_size = int(round(seq_len / 8192)) * 8192
self._set_cos_sin_cache(self.current_rope_size, device = "cuda:0", dtype = x.dtype)
pass
pass