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llama: use a more efficient rope implementation #12434

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Merged
comfyanonymous merged 1 commit into from
Feb 13, 2026
Merged

llama: use a more efficient rope implementation #12434

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25 changes: 14 additions & 11 deletions comfy/text_encoders/llama.py
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Original file line number Diff line number Diff line change
Expand Up @@ -355,13 +355,6 @@ def forward(self, x: torch.Tensor):



def rotate_half(x):
"""Rotates half the hidden dims of the input."""
x1 = x[..., : x.shape[-1] // 2]
x2 = x[..., x.shape[-1] // 2 :]
return torch.cat((-x2, x1), dim=-1)


def precompute_freqs_cis(head_dim, position_ids, theta, rope_scale=None, rope_dims=None, device=None):
if not isinstance(theta, list):
theta = [theta]
Expand Down Expand Up @@ -390,20 +383,30 @@ def precompute_freqs_cis(head_dim, position_ids, theta, rope_scale=None, rope_di
else:
cos = cos.unsqueeze(1)
sin = sin.unsqueeze(1)
out.append((cos, sin))
sin_split = sin.shape[-1] // 2
out.append((cos, sin[..., : sin_split], -sin[..., sin_split :]))

if len(out) == 1:
return out[0]

return out


def apply_rope(xq, xk, freqs_cis):
org_dtype = xq.dtype
cos = freqs_cis[0]
sin = freqs_cis[1]
q_embed = (xq * cos) + (rotate_half(xq) * sin)
k_embed = (xk * cos) + (rotate_half(xk) * sin)
nsin = freqs_cis[2]

q_embed = (xq * cos)
q_split = q_embed.shape[-1] // 2
q_embed[..., : q_split].addcmul_(xq[..., q_split :], nsin)
q_embed[..., q_split :].addcmul_(xq[..., : q_split], sin)

k_embed = (xk * cos)
k_split = k_embed.shape[-1] // 2
k_embed[..., : k_split].addcmul_(xk[..., k_split :], nsin)
k_embed[..., k_split :].addcmul_(xk[..., : k_split], sin)

return q_embed.to(org_dtype), k_embed.to(org_dtype)


Expand Down