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Some fixes to previous pr. (#12339)
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comfyanonymous 2026-02-06 17:14:52 -08:00 committed by GitHub
parent 6a26328842
commit 039955c527
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2 changed files with 7 additions and 5 deletions
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2
comfy/ldm/cosmos/predict2.py
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@ -894,6 +894,6 @@ class MiniTrainDIT(nn.Module):
**block_kwargs, **block_kwargs,
) )
x_B_T_H_W_O = self.final_layer(x_B_T_H_W_D, t_embedding_B_T_D, adaln_lora_B_T_3D=adaln_lora_B_T_3D) x_B_T_H_W_O = self.final_layer(x_B_T_H_W_D.to(crossattn_emb.dtype), t_embedding_B_T_D, adaln_lora_B_T_3D=adaln_lora_B_T_3D)
x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)[:, :, :orig_shape[-3], :orig_shape[-2], :orig_shape[-1]] x_B_C_Tt_Hp_Wp = self.unpatchify(x_B_T_H_W_O)[:, :, :orig_shape[-3], :orig_shape[-2], :orig_shape[-1]]
return x_B_C_Tt_Hp_Wp return x_B_C_Tt_Hp_Wp

10
comfy/supported_models.py
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@ -1025,10 +1025,6 @@ class Anima(supported_models_base.BASE):
supported_inference_dtypes = [torch.bfloat16, torch.float16, torch.float32] supported_inference_dtypes = [torch.bfloat16, torch.float16, torch.float32]
def __init__(self, unet_config):
super().__init__(unet_config)
self.memory_usage_factor = (unet_config.get("model_channels", 2048) / 2048) * 0.95
def get_model(self, state_dict, prefix="", device=None): def get_model(self, state_dict, prefix="", device=None):
out = model_base.Anima(self, device=device) out = model_base.Anima(self, device=device)
return out return out
@ -1038,6 +1034,12 @@ class Anima(supported_models_base.BASE):
detect = comfy.text_encoders.hunyuan_video.llama_detect(state_dict, "{}qwen3_06b.transformer.".format(pref)) detect = comfy.text_encoders.hunyuan_video.llama_detect(state_dict, "{}qwen3_06b.transformer.".format(pref))
return supported_models_base.ClipTarget(comfy.text_encoders.anima.AnimaTokenizer, comfy.text_encoders.anima.te(**detect)) return supported_models_base.ClipTarget(comfy.text_encoders.anima.AnimaTokenizer, comfy.text_encoders.anima.te(**detect))
def set_inference_dtype(self, dtype, manual_cast_dtype, **kwargs):
self.memory_usage_factor = (self.unet_config.get("model_channels", 2048) / 2048) * 0.95
if dtype is torch.float16:
self.memory_usage_factor *= 1.4
return super().set_inference_dtype(dtype, manual_cast_dtype, **kwargs)
class CosmosI2VPredict2(CosmosT2IPredict2): class CosmosI2VPredict2(CosmosT2IPredict2):
unet_config = { unet_config = {
"image_model": "cosmos_predict2", "image_model": "cosmos_predict2",