xinyun/ComfyUI-CogVideoXWrapper
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pad negative if too short

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kijai 2024-08-30 13:21:09 +03:00
parent 0b19b54916
commit 9208585442
1 changed files with 6 additions and 1 deletions
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7
nodes.py
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@ -283,6 +283,11 @@ class CogVideoSampler:
elif scheduler == "DPM": elif scheduler == "DPM":
pipe.scheduler = CogVideoXDPMScheduler.from_pretrained(base_path, subfolder="scheduler") pipe.scheduler = CogVideoXDPMScheduler.from_pretrained(base_path, subfolder="scheduler")
if negative.shape[1] < positive.shape[1]:
target_length = positive.shape[1]
padding = torch.zeros((negative.shape[0], target_length - negative.shape[1], negative.shape[2]), device=negative.device)
negative = torch.cat((negative, padding), dim=1)
autocastcondition = not pipeline["onediff"] autocastcondition = not pipeline["onediff"]
autocast_context = torch.autocast(mm.get_autocast_device(device)) if autocastcondition else nullcontext() autocast_context = torch.autocast(mm.get_autocast_device(device)) if autocastcondition else nullcontext()
with autocast_context: with autocast_context:
@ -314,7 +319,7 @@ class CogVideoDecode:
return {"required": { return {"required": {
"pipeline": ("COGVIDEOPIPE",), "pipeline": ("COGVIDEOPIPE",),
"samples": ("LATENT", ), "samples": ("LATENT", ),
"enable_vae_tiling": ("BOOLEAN", {"default": False}), "enable_vae_tiling": ("BOOLEAN", {"default": False, "tooltip": "Drastically reduces memory use but may introduce seams"}),
}, },
"optional": { "optional": {
"tile_sample_min_height": ("INT", {"default": 96, "min": 16, "max": 2048, "step": 8}), "tile_sample_min_height": ("INT", {"default": 96, "min": 16, "max": 2048, "step": 8}),