RuntimeError: Given groups=1, weight of size [5120, 36, 1, 2, 2], expected input[1, 68, 25, 40, 30] to have 36 channels, but got 68 channels instead
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Assessment
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Newbie friendliness
- 48/100
- Issue type
- Bug
- Clarity
- Mostly clear
- Activity status
- Quiet
- Domain
- machine-learning
Research direction
Start with the WanVideoImageToVideoEncode node and trace how its inputs are assembled before the model receives the tensor; inspect the linked workflow2.json for hidden or serialized connections, including UE links. Compare the tensor's 68 channels with the model's expected 36 and identify where the additional 32 enter. Done means explaining the source and giving a reproducible way to remove it; the issue does not name tests to run.
Written by the indexing model from the issue text.
Description
RuntimeError: 68 channels instead of 36 - WanVideoImageToVideoEncode
Error:
RuntimeError: Given groups=1, weight of size [5120, 36, 1, 2, 2], expected input[1, 68, 25, 40, 30] to have 36 channels, but got 68 channels instead
Setup:
- ComfyUI version: 0.19.3
- ComfyUI-WanVideoWrapper: latest (updated)
- Model: Wan2.2-I2V-A14B (fp8_e5m2_scaled_KJ)
- GPU: NVIDIA RTX 3070 Ti Laptop (8GB VRAM)
- OS: Windows 11
Workflow:
- Two WanVideoModelLoader nodes (HIGH + LOW)
- Two WanVideoSampler nodes in cascade
- One WanVideoImageToVideoEncode node
- WanVideoLoraSelectMulti with Lightning LoRA
fun_or_fi2v_model= disabledend_image= not connected (no visible link)extra_latents= not connected (no visible link)
Problem:
The error persists even with fun_or_fi2v_model disabled and no visible connections on end_image or extra_latents. The 68 channels suggest an end_image or extra latent is being injected somewhere, but I cannot find where.
I suspect it may be coming from a cg-use-everywhere (UE) invisible link, but Reject UE Links on the node doesn't fix it.
Question:
What causes exactly 68 channels (36 + 32) in this context, and how can I identify and remove the source of the extra 32 channels?
Thank you!
- Dominant language
- Python
- Stars
- 6.8k
- Forks
- 712
- PR merge metrics
- No merged PRs in 30d
Getting set up
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First steps
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