My xformers come back without me setting anything :)

[danilomaiaweb]

I updated my Forge again at this moment and mysteriously, without declaring in the argument line on my webui-user.bat, my xformer appeared without me configuring it and it is running perfectly... Go figure, right? These are things from the beyond. :)

Stable Diffusion PATH: F:\ForgeFlux\webui
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: f2.0.1v1.10.1-previous-376-ga616d6e6
Commit hash: a616d6e6214ee3afb0294611b5880e5cf0009b50
CUDA 12.1
Launching Web UI with arguments: --precision full --opt-split-attention --always-batch-cond-uncond --no-half --skip-torch-cuda-test --pin-shared-memory --cuda-malloc --cuda-stream --ckpt-dir 'F:\ModelsForge\Checkpoints' --lora-dir 'F:\ModelsForge\Loras'
Using cudaMallocAsync backend.
Total VRAM 8191 MB, total RAM 32705 MB
pytorch version: 2.3.1+cu121
xformers version: 0.0.27
Set vram state to: NORMAL_VRAM
Always pin shared GPU memory
Device: cuda:0 NVIDIA GeForce RTX 3050 : cudaMallocAsync
VAE dtype preferences: [torch.bfloat16, torch.float32] -> torch.bfloat16
CUDA Using Stream: True
Using xformers cross attention
Using xformers attention for VAE
ControlNet preprocessor location: F:\ForgeFlux\webui\models\ControlNetPreprocessor
[-] ADetailer initialized. version: 24.8.0, num models: 10
sd-webui-prompt-all-in-one background API service started successfully.
23:57:15 - ReActor - STATUS - Running v0.7.1-a1 on Device: CUDA
2024-08-20 23:57:17,471 - ControlNet - INFO - ControlNet UI callback registered.
Model selected: {'checkpoint_info': {'filename': 'F:\ModelsForge\Checkpoints\fluxFusionDSNF4GGUFQ4Q5Q8Fp8Fp16_v0BnbNf4AIO.safetensors', 'hash': '35aa31f8'}, '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().
IIB Database file has been successfully backed up to the backup folder.
Startup time: 34.6s (prepare environment: 12.6s, import torch: 6.7s, initialize shared: 0.1s, other imports: 0.5s, load scripts: 5.6s, create ui: 4.9s, gradio launch: 3.0s, app_started_callback: 1.1s).
Environment vars changed: {'stream': False, 'inference_memory': 1024.0, 'pin_shared_memory': False}
[GPU Setting] You will use 87.50% GPU memory (7167.00 MB) to load weights, and use 12.50% GPU memory (1024.00 MB) to do matrix computation.

This is Amazing !!!

[rubenmejiac]

According to some comments on various posts, and on reddit, xformers are not necessary in Forge, the built-in functionality is faster without them.

[HMRMike]

We did see a slight improvement in some cases:
#1553 (comment)

Not much, but I do welcome every bit of measurable speed.