lllyasviel / lllyasviel/stable-diffusion-webui-forge

[Bug]: Forge UI not generating same images as Stable Diffusion A1111 UI

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Description

### Checklist

- [X] The issue exists after disabling all extensions
- [X] The issue exists on a clean installation of webui
- [ ] The issue is caused by an extension, but I believe it is caused by a bug in the webui
- [X] The issue exists in the current version of the webui
- [X] The issue has not been reported before recently
- [ ] The issue has been reported before but has not been fixed yet

### What happened?

Hello, since I started using the Forge UI, I noticed small changes with the images generated with the Stable Diffusion A1111 UI. Using the same seed, sampler, CFG Scale, Model,... The result have small variations.
Here is an example :

Using Forge :
![test3f](https://github.com/lllyasviel/stable-diffusion-webui-forge/assets/172219676/64b2e669-13cd-414d-a14e-3b52e6b04e3e)

parameters

1girl, looking away, multicolored hair
Steps: 25, Sampler: DPM++ 2M Karras, CFG scale: 7, Seed: 123456789, Size: 750x1000, Model hash: 377c3165ed, Model: ModeleSemiKawai, Clip skip: 2, Version: v1.7.0

Using Stable Diffusion A1111 :
![test3pf](https://github.com/lllyasviel/stable-diffusion-webui-forge/assets/172219676/329c8378-4866-4283-949e-d83c0cdb9da7)

parameters

1girl, looking away, multicolored hair
Steps: 25, Sampler: DPM++ 2M Karras, CFG scale: 7, Seed: 123456789, Size: 750x1000, Model hash: 377c3165ed, Model: ModeleSemiKawai, Clip skip: 2, Version: f0.0.17v1.8.0rc-latest-277-g0af28699

For this example, the changes is the hair near her neck.

### Steps to reproduce the problem

There are no particular steps, the prompt used is quite simple (even with a negative prompt, the issue remains)

### What should have happened?

The images generated should be identical

### What browsers do you use to access the UI ?

Mozilla Firefox

### Sysinfo

[sysinfo-2024-06-09-22-22.json](https://github.com/user-attachments/files/15754383/sysinfo-2024-06-09-22-22.json)

### Console logs

```Shell
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: f0.0.17v1.8.0rc-latest-277-g0af28699
Commit hash: 0af28699c45c1c5bf9cb6818caac6ce881123131
Launching Web UI with arguments:
Total VRAM 4096 MB, total RAM 32472 MB
Trying to enable lowvram mode because your GPU seems to have 4GB or less. If you don't want this use: --always-normal-vram
Set vram state to: LOW_VRAM
Device: cuda:0 NVIDIA GeForce RTX 3050 Laptop GPU : native
Hint: your device supports --pin-shared-memory for potential speed improvements.
Hint: your device supports --cuda-malloc for potential speed improvements.
Hint: your device supports --cuda-stream for potential speed improvements.
VAE dtype: torch.bfloat16
CUDA Stream Activated: False
Using pytorch cross attention
Loading weights [377c3165ed] from D:\Test_AI\webui_forge_cu121_torch21\webui\models\Stable-diffusion\ModeleSemiKawai.safetensors
Running on local URL: http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
model_type EPS
UNet ADM Dimension 0
Startup time: 10.0s (prepare environment: 2.4s, import torch: 3.5s, import gradio: 1.2s, setup paths: 0.7s, initialize shared: 0.2s, other imports: 0.7s, load scripts: 0.6s, create ui: 0.2s, gradio launch: 0.4s).
Using pytorch attention in VAE
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
Using pytorch attention in VAE
extra {'cond_stage_model.clip_l.logit_scale', 'cond_stage_model.clip_l.text_projection'}
To load target model SD1ClipModel
Begin to load 1 model
Moving model(s) has taken 0.00 seconds
Model loaded in 3.9s (load weights from disk: 0.3s, forge load real models: 3.1s, calculate empty prompt: 0.5s).
To load target model BaseModel
Begin to load 1 model
[Memory Management] Current Free GPU Memory (MB) = 3129.2920904159546
[Memory Management] Model Memory (MB) = 1639.4137649536133
[Memory Management] Minimal Inference Memory (MB) = 1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) = 465.8783254623413
Moving model(s) has taken 0.31 seconds
100%|██████████████████████████████████████████████████████████████████████████████████| 25/25 [00:20<00:00, 1.21it/s]
To load target model AutoencoderKL█████████████████████████████████████████████████████| 25/25 [00:19<00:00, 1.22it/s]
Begin to load 1 model
[Memory Management] Current Free GPU Memory (MB) = 3102.9288091659546
[Memory Management] Model Memory (MB) = 159.55708122253418
[Memory Management] Minimal Inference Memory (MB) = 1024.0
[Memory Management] Estimated Remaining GPU Memory (MB) = 1919.3717279434204
Moving model(s) has taken 0.98 seconds
Total progress: 100%|██████████████████████████████████████████████████████████████████| 25/25 [00:21<00:00, 1.14it/s]
Total progress: 100%|██████████████████████████████████████████████████████████████████| 25/25 [00:21<00:00, 1.22it/s]
```

### Additional information

_No response_

Contributor guide

No contributing guide indexed for this repository

Research direction

No source files or tests are identified in the report. Start by reproducing the Forge UI and Stable Diffusion A1111 UI comparison with the listed model, seed, sampler, and settings; done means the generated images are identical or the differing behavior is isolated to a documented setting.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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