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Support loading and using SkyReels-V1-Hunyuan-I2V (#6862)

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* Support SkyReels-V1-Hunyuan-I2V

* VAE scaling

* Fix T2V

oops

* Proper latent scaling
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Jukka Seppänen 2025-02-19 00:06:54 +02:00 committed by GitHub
parent b07258cef2
commit acc152b674
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3 changed files with 11 additions and 2 deletions
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2
comfy/ldm/hunyuan_video/model.py
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@ -310,7 +310,7 @@ class HunyuanVideo(nn.Module):
shape[i] = shape[i] // self.patch_size[i]
img = img.reshape([img.shape[0]] + shape + [self.out_channels] + self.patch_size)
img = img.permute(0, 4, 1, 5, 2, 6, 3, 7)
img = img.reshape(initial_shape)
img = img.reshape(initial_shape[0], self.out_channels, initial_shape[2], initial_shape[3], initial_shape[4])
return img
def forward(self, x, timestep, context, y, guidance=None, attention_mask=None, control=None, transformer_options={}, **kwargs):

9
comfy/model_base.py
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@ -871,6 +871,15 @@ class HunyuanVideo(BaseModel):
if cross_attn is not None:
out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn)
image = kwargs.get("concat_latent_image", None)
noise = kwargs.get("noise", None)
if image is not None:
padding_shape = (noise.shape[0], 16, noise.shape[2] - 1, noise.shape[3], noise.shape[4])
latent_padding = torch.zeros(padding_shape, device=noise.device, dtype=noise.dtype)
image_latents = torch.cat([image.to(noise), latent_padding], dim=2)
out['c_concat'] = comfy.conds.CONDNoiseShape(self.process_latent_in(image_latents))
guidance = kwargs.get("guidance", 6.0)
if guidance is not None:
out['guidance'] = comfy.conds.CONDRegular(torch.FloatTensor([guidance]))

2
comfy/model_detection.py
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@ -136,7 +136,7 @@ def detect_unet_config(state_dict, key_prefix):
if '{}txt_in.individual_token_refiner.blocks.0.norm1.weight'.format(key_prefix) in state_dict_keys: #Hunyuan Video
dit_config = {}
dit_config["image_model"] = "hunyuan_video"
dit_config["in_channels"] = 16
dit_config["in_channels"] = state_dict["img_in.proj.weight"].shape[1] #SkyReels img2video has 32 input channels
dit_config["patch_size"] = [1, 2, 2]
dit_config["out_channels"] = 16
dit_config["vec_in_dim"] = 768