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Add SeedVR2 support (CORE-6) (#14110)

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This commit is contained in:
John Pollock
2026-06-08 18:15:05 +08:00
committed by GitHub
parent 739061dd4c
commit 7863cf0e53
26 changed files with 7383 additions and 40 deletions
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comfy/ldm/modules/diffusionmodules/model.py
+6 -2
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@@ -13,6 +13,7 @@ if model_management.xformers_enabled_vae():
import xformers
import xformers.ops
def torch_cat_if_needed(xl, dim):
xl = [x for x in xl if x is not None and x.shape[dim] > 0]
if len(xl) > 1:
@@ -22,7 +23,8 @@ def torch_cat_if_needed(xl, dim):
else:
return None
def get_timestep_embedding(timesteps, embedding_dim):
def get_timestep_embedding(timesteps, embedding_dim, flip_sin_to_cos=False, downscale_freq_shift=1):
"""
This matches the implementation in Denoising Diffusion Probabilistic Models:
From Fairseq.
@@ -33,11 +35,13 @@ def get_timestep_embedding(timesteps, embedding_dim):
assert len(timesteps.shape) == 1
half_dim = embedding_dim // 2
emb = math.log(10000) / (half_dim - 1)
emb = math.log(10000) / (half_dim - downscale_freq_shift)
emb = torch.exp(torch.arange(half_dim, dtype=torch.float32) * -emb)
emb = emb.to(device=timesteps.device)
emb = timesteps.float()[:, None] * emb[None, :]
emb = torch.cat([torch.sin(emb), torch.cos(emb)], dim=1)
if flip_sin_to_cos:
emb = torch.cat([emb[:, half_dim:], emb[:, :half_dim]], dim=-1)
if embedding_dim % 2 == 1: # zero pad
emb = torch.nn.functional.pad(emb, (0,1,0,0))
return emb