nodes/kijai-ComfyUI-WanVideoWrapper
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Author SHA1 Message Date
kijai a3b2f67337 Pad clip vision embeds like in original code 2025-11-08 16:03:00 +02:00
kijai 1e00c8fb28 Update nodes.py 2025-11-08 12:21:11 +02:00
kijai ff16dce5c0 Update nodes_sampler.py 2025-11-07 01:15:13 +02:00
kijai f972b31bf2 Update nodes.py 2025-11-07 01:09:22 +02:00
kijai 3dacd6a719 Update nodes_sampler.py 2025-11-07 00:45:06 +02:00
kijai 7bf99791ad Update nodes.py 2025-11-07 00:44:13 +02:00
kijai 7a5587b5af Let the user resize for QwenVL 
Seems to need smaller resolutions
 2025-11-07 00:39:10 +02:00
kijai d6cf172846 Update nodes.py 2025-11-06 23:41:24 +02:00
kijai cf86f4f0a4 Update model.py 2025-11-06 21:01:03 +02:00
kijai b1f8309a20 Update nodes_model_loading.py 2025-11-06 19:55:54 +02:00
kijai 8992c6af64 Don't include padding for scheduler 2025-11-06 19:22:56 +02:00
kijai e4084a961b Update nodes.py 2025-11-06 18:32:53 +02:00
kijai 3ec1edefbe init 
For testing, no idea if it works yet
 2025-11-06 17:35:48 +02:00
Jukka Seppänen d3f33a9f09 Update readme.md 2025-11-06 16:38:46 +02:00
kijai d0ef3b5601 Update readme.md 2025-11-06 16:37:50 +02:00
kijai 475f96aede Fix accidental positional arg 2025-11-04 20:53:46 +02:00
kijai 1d0516a2a9 Avoid graph break for LongCat 2025-11-04 10:26:37 +02:00
kijai 8002d8a2f9 This still needed for some reason too 2025-11-04 09:58:40 +02:00
kijai 9a588a42ec Fix some precision issues with unmerged lora 2025-11-04 09:47:38 +02:00
kijai 509d6922f5 Update custom_linear.py 2025-11-04 09:44:07 +02:00
kijai 9fa4140159 Make lora torch.compile optional for unmerged lora application 
This change has caused issues especially with LoRAs that have dynamic rank. Will now be disabled by default, to allow full graph with unmerged LoRAs the option to allow compile is available in the Torch Compile Settings -node
 2025-11-04 01:34:51 +02:00
kijai 8ce6916d72 Fix for some cases of using comfy_chunked rope 2025-11-03 10:36:55 +02:00
kijai 0d0d28569a Fix cases where text encoder isn't used (eg. Minimax remover) 2025-11-03 10:29:10 +02:00
kijai 75109fdb79 Fix custom sigmas with euler 2025-11-03 10:12:05 +02:00
kijai 5eae7087fa Fix for S2V 2025-11-02 01:24:50 +02:00
kijai 393fe78ec2 Update model.py 2025-10-31 23:39:55 +02:00
kijai 5f4020b12d Fix a possible issue with Ovi audio model loading 2025-10-31 17:24:24 +02:00
kijai 5da8a6b169 Fix MultiTalk on some models 2025-10-31 16:50:00 +02:00
kijai ce6e7b501d Fix unmerged LoRA application for certain LoRAs 2025-10-30 23:28:38 +02:00
kijai 366f740d28 Update readme.md 2025-10-30 23:10:06 +02:00
Jukka Seppänen d45fe1ee22 Add note about blocking new accounts from posting issues 
Added a note regarding issue posting restrictions due to bot activity.
 2025-10-30 18:19:45 +02:00
kijai da24890d53 Update pyproject.toml 2025-10-30 17:56:20 +02:00
kijai 95391f403d Update nodes_sampler.py 2025-10-30 17:55:55 +02:00
kijai 9e0b3afe4e version checkpoint 2025-10-30 17:53:29 +02:00
kijai ba1beba982 Create LongCat_TI2V_example_01.json 2025-10-30 17:51:52 +02:00
kijai 64c195167b Update nodes.py 2025-10-30 17:33:42 +02:00
kijai cc9bf1e4f5 Store lora diffs in buffers for GGUF as well 2025-10-30 16:44:03 +02:00
kijai a64f115d35 Fix to previous 2025-10-29 11:06:38 +02:00
kijai e45f6f2fc4 Allow WanVideoScheduler -node to work with the looping samplers 
Was broken for Multitalk/WanAnimate/S2V
 2025-10-29 10:41:33 +02:00
kijai 1cd8df5c00 Update custom_linear.py 2025-10-29 02:50:11 +02:00
kijai d2614a9a49 Merge branch 'main' into longcat 2025-10-29 02:33:37 +02:00
kijai 083a8458c4 Register lora diffs as buffers to allow them to work with block swap 
unmerged loras (non GGUF for now) will now be moved with block swap instead of always loaded from cpu to reduce device transfers and allow torch compile full graph
 2025-10-29 02:33:26 +02:00
kijai 1c2f17e8d7 Add utility node to split sampler from settings 
For cleaner previews
 2025-10-29 02:24:24 +02:00
kijai 9d45b9f0de Use comfy core Conv3D workaround for VAE rather than the fp32 cast 2025-10-29 02:23:49 +02:00
Jukka Seppänen 833c6f50c7 Merge pull request #1581 from chengzeyi/fix-ref-conv-dtype-mismatch 
Fix dtype mismatch in ref_conv forward pass
 2025-10-28 14:27:43 +02:00
chengzeyiandClaude d15cf3001f Fix dtype mismatch in ref_conv forward pass 
This commit fixes a RuntimeError that occurs when using Fun-Control
reference images: "Input type (float) and bias type (c10::Half)
should be the same"

Root cause:
- Commit 1ba1a16 changed the dtype handling strategy to convert
  the main latent `x` to `base_dtype` instead of converting
  embeddings to match `x.dtype`
- This caused `fun_ref` input to be in a different dtype than
  the `ref_conv` layer's weights and bias
- Line 2324 already handles this correctly for `attn_cond` by
  converting to `self.attn_conv_in.weight.dtype`

Solution:
- Convert `fun_ref` to match `self.ref_conv.weight.dtype` before
  passing through the convolution layer
- This follows the same pattern used for `attn_cond` on line 2324

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-10-28 12:08:23 +00:00
kijai eebbcd5ee0 Update model.py 2025-10-28 02:04:50 +02:00
kijai 2633119505 Update custom_linear.py 2025-10-28 01:55:25 +02:00
kijai 90908df260 Update model.py 2025-10-28 01:54:42 +02:00
kijai c80a488f70 Use fp32 norms for other models too and other fixes 2025-10-28 01:52:48 +02:00