The transparent image is not saved

[DiegoRRR]

Two images are saved : one with a blur background and one with a checker background, none with a transparent background. :( I tried several models, 1.5 and XL. Example:

I also checked in AppData\Local\Temp\gradio\, there is only the version with a checker background.

There is no error in the output. There is a warning about onnxruntime and a warning about transformers but I don't think it's related.

Python 3.10.6 (main, Dec 22 2022, 15:39:53) [MSC v.1934 64 bit (AMD64)]
Version: f2.0.1v1.10.1-previous-526-gc13b26ba
Commit hash: c13b26ba271bac327879d32f01307fc21a012321
Launching Web UI with arguments:
Total VRAM 12288 MB, total RAM 32677 MB
pytorch version: 2.3.1+cu118
Set vram state to: NORMAL_VRAM
Device: cuda:0 NVIDIA GeForce RTX 3060 : native
Hint: your device supports --cuda-malloc for potential speed improvements.
VAE dtype preferences: [torch.bfloat16, torch.float32] -> torch.bfloat16
CUDA Using Stream: False
D:\apps\stable-diffusion\Forge_2024\system\python\lib\site-packages\onnxruntime\
capi\onnxruntime_validation.py:26: UserWarning: Unsupported Windows version (7).
 ONNX Runtime supports Windows 10 and above, only.
  warnings.warn(
D:\apps\stable-diffusion\Forge_2024\system\python\lib\site-packages\transformers
\utils\hub.py:127: FutureWarning: Using `TRANSFORMERS_CACHE` is deprecated and w
ill be removed in v5 of Transformers. Use `HF_HOME` instead.
  warnings.warn(
Using pytorch cross attention
Using pytorch attention for VAE
ControlNet preprocessor location: D:\apps\stable-diffusion\Forge_2024\webui\mode
ls\ControlNetPreprocessor
2024-09-18 20:44:16,947 - ControlNet - INFO - ControlNet UI callback registered.

Model selected: {'checkpoint_info': {'filename': 'D:\\apps\\stable-diffusion\\Fo
rge_2024\\webui\\models\\Stable-diffusion\\1.5\\2.5D artUniverse10 .safetensors'
, 'hash': 'd37a18cd'}, 'additional_modules': [], 'unet_storage_dtype': None}
Using online LoRAs in FP16: False
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 33.2s (prepare environment: 4.8s, import torch: 16.2s, initialize
shared: 0.3s, other imports: 0.6s, load scripts: 5.2s, create ui: 4.3s, gradio l
aunch: 1.6s).
Loading Model: {'checkpoint_info': {'filename': 'D:\\apps\\stable-diffusion\\For
ge_2024\\webui\\models\\Stable-diffusion\\1.5\\2.5D artUniverse10 .safetensors',
 'hash': 'd37a18cd'}, 'additional_modules': [], 'unet_storage_dtype': None}
[Unload] Trying to free all memory for cuda:0 with 0 models keep loaded ... Done
.
StateDict Keys: {'unet': 686, 'vae': 248, 'text_encoder': 197, 'ignore': 0}
D:\apps\stable-diffusion\Forge_2024\system\python\lib\site-packages\transformers
\tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces`
was not set. It will be set to `True` by default. This behavior will be depracte
d in transformers v4.45, and will be then set to `False` by default. For more de
tails check this issue: https://github.com/huggingface/transformers/issues/31884

  warnings.warn(
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
K-Model Created: {'storage_dtype': torch.float16, 'computation_dtype': torch.flo
at16}
Model loaded in 17.4s (unload existing model: 0.2s, forge model load: 17.2s).
[Unload] Trying to free 1329.14 MB for cuda:0 with 0 models keep loaded ... Done
.
[Memory Management] Target: JointTextEncoder, Free GPU: 11141.40 MB, Model Requi
re: 234.72 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remain
ing: 9882.68 MB, All loaded to GPU.
Moving model(s) has taken 0.14 seconds
[Unload] Trying to free 1024.00 MB for cuda:0 with 1 models keep loaded ... Curr
ent free memory is 10460.36 MB ... Done.
[LayerDiffuse] LayerMethod.FG_ONLY_ATTN_SD15
[Unload] Trying to free 3155.23 MB for cuda:0 with 0 models keep loaded ... Curr
ent free memory is 10460.06 MB ... Done.
[Memory Management] Target: KModel, Free GPU: 10460.06 MB, Model Require: 1639.4
1 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: 7796
.65 MB, All loaded to GPU.
Moving model(s) has taken 0.69 seconds
100%|██████████████████████████████████████████| 20/20 [00:17<00:00,  1.15it/s]
[Unload] Trying to free 1568.67 MB for cuda:0 with 0 models keep loaded ... Curr
ent free memory is 8347.70 MB ... Done.
[Memory Management] Target: IntegratedAutoencoderKL, Free GPU: 8347.70 MB, Model
 Require: 159.56 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB,
Remaining: 7164.14 MB, All loaded to GPU.
Moving model(s) has taken 0.18 seconds
[Unload] Trying to free 1282.13 MB for cuda:0 with 0 models keep loaded ... Curr
ent free memory is 8186.71 MB ... Done.
[Memory Management] Target: UNet1024, Free GPU: 8186.71 MB, Model Require: 198.5
6 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: 6964
.15 MB, All loaded to GPU.
Moving model(s) has taken 0.14 seconds
100%|████████████████████████████████████████████| 8/8 [00:01<00:00,  6.08it/s]
Total progress: 100%|██████████████████████████| 20/20 [00:17<00:00,  1.18it/s]
Total progress: 100%|██████████████████████████| 20/20 [00:17<00:00,  1.33it/s]

Both LayerDiffuse and Forge are up to date. ( In another folder I keep the old Forge from last year with the old LayerDiffuse from april, with the same settings, these old two work perfectly and I do get a transparent image, except for img2img which was fixed recently, that is why I want the new versions. )

[lllyasviel]

I cannot reproduce your problem, but from the log it seems to be caused by wrong gradio version or some other libs. It is very likely that you are not installing forge in official way.

[DiegoRRR]

(Thanks for replying and for your amazing work on LayerDiffuse and Forge.)

I had problems making it run on my computer, so I kept notes of what I tried. For this installation here are the only things I did: I unzipped webui_forge_cu121_torch21.7z, ran update.bat, then run.bat. It told me to go to: https://pytorch.org to install a PyTorch version that has been compiled with your version of the CUDA driver, so I uninstalled pytorch and installed v2.4.0 cu117 instead of 2.1 cu12. (I did not install torchaudio because in a previous try it annoyed me asking for missing dlls related to mpeg and I guess torchaudio is not necessary here anyway, is it?)

python -m pip uninstall Torch Torchvision Torchaudio
python -m pip install torch==2.4.0 torchvision==0.19.0 --index-url https://download.pytorch.org/whl/cu118

I also had to downgrade Pydantic to 2.7 instead of 2.9, I just changed the number in requirements_versions.txt.

I did not change gradio or any other lib. Is there any way to determine what lib is causing this so I can reinstall it? Maybe that lib was not made for the version of pytorch I installed and I just need to reinstall it.

[lllyasviel]

hi if that is the case then your env is quite complicated. you can try mainly changing opencv/pillow/gradio versions to try

[DiegoRRR]

I've searched for hours with several new installations and I found, two different things were causing the problem:

My copies of the models in models/layer_model/ were either outdated or corrupted. I let it download new copies and it works now. The old version of LayerDiffuse in old Forge worked with these old files though, I tried again earlier today, so I don't think they were corrupted. Were these files updated since march?

I noticed that the problem always still happens anyway if I forgot to update with update.bat after unzipping though.

If I used new layer_models files but forgot to update, or if I updated but used my old layer_models files, the problem always happened. If I update and use the new layer_models files, it always works. So if someone ever has the same problem and reads, check these things.

By the way When LayerDiffuse is enabled, the transparent image should always be saved as png even if "File format for images" in "saving images/grids" is set to jpg.

Thanks again for your great work, lllyasviel.