The transparent image is not saved

Nobody has claimed this yet.

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. )

Start by reproducing the transparent-image save behavior with the current Forge and LayerDiffuse versions using the settings described in the report, then compare the generated and temporary files with the older working versions. The issue is done when the current versions save the transparent result instead of only the blurred or checker-background images.

Written by the indexing model from the issue text.