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Support the Anima model. (#12012)

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comfyanonymous
2026-01-21 16:44:28 -08:00
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parent bdeac8897e
commit abe2ec26a6
6 changed files with 326 additions and 1 deletions
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22
comfy/model_base.py
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@@ -49,6 +49,7 @@ import comfy.ldm.ace.model
import comfy.ldm.omnigen.omnigen2
import comfy.ldm.qwen_image.model
import comfy.ldm.kandinsky5.model
import comfy.ldm.anima.model
import comfy.model_management
import comfy.patcher_extension
@@ -1147,6 +1148,27 @@ class CosmosPredict2(BaseModel):
sigma = (sigma / (sigma + 1))
return latent_image / (1.0 - sigma)
class Anima(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLOW, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.anima.model.Anima)
def extra_conds(self, **kwargs):
out = super().extra_conds(**kwargs)
cross_attn = kwargs.get("cross_attn", None)
t5xxl_ids = kwargs.get("t5xxl_ids", None)
t5xxl_weights = kwargs.get("t5xxl_weights", None)
device = kwargs["device"]
if cross_attn is not None:
if t5xxl_ids is not None:
cross_attn = self.diffusion_model.preprocess_text_embeds(cross_attn.to(device=device, dtype=self.get_dtype()), t5xxl_ids.unsqueeze(0).to(device=device))
if t5xxl_weights is not None:
cross_attn *= t5xxl_weights.unsqueeze(0).unsqueeze(-1).to(cross_attn)
if cross_attn.shape[1] < 512:
cross_attn = torch.nn.functional.pad(cross_attn, (0, 0, 0, 512 - cross_attn.shape[1]))
out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn)
return out
class Lumina2(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLOW, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.lumina.model.NextDiT)