Higher VRAM usage with PyTorch2 without xformers under certain situations

[wfng92]

Describe the bug

Edited to reflect the actual issue

In the latest development version, PR #3365 introduced a confusion which makes users believe that PT2 variant of attention processors are fully supported and xformers is no longer needed. This results in higher VRAM usage under certain situations (using LoRA/custom diffusion without xformers)

If the env is installed with both Pytorch2 and xformers, it will

• raise a warning
• default to PyTorch's native efficient flash attention

diffusers currently supports the following PT 2.0 variant of attention processors

• AttnProcessor => AttnProcessor2_0
• AttnAddedKVProcessor => AttnAddedKVProcessor2_0

The following are not supported:

• SlicedAttnProcessor
• SlicedAttnAddedKVProcessor
• LoRAAttnProcessor
• CustomDiffusionAttnProcessor

It would be great if users can still use xformers when calling the pipe.enable_xformers_memory_efficient_attention() function.

Reproduction

from diffusers import (
    DPMSolverMultistepScheduler,
    StableDiffusionPipeline,
)

pipe = StableDiffusionPipeline.from_pretrained(
    "runwayml/stable-diffusion-v1-5",
    torch_dtype=torch.float16
).to("cuda")

pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)

pipe.unet.load_attn_procs("pytorch_lora_weights.bin")
pipe.enable_xformers_memory_efficient_attention()

prompt = "a photo of a dog"
image = pipe(prompt=prompt, cross_attention_kwargs={"scale": 1.0}).images

Logs

"You have specified using flash attention using xFormers but you have PyTorch 2.0 already installed. "
"We will default to PyTorch's native efficient flash attention implementation provided by PyTorch 2.0.

System Info

• diffusers version: 0.17.0.dev0
• Platform: Windows-10-10.0.19045-SP0
• Python version: 3.10.11
• PyTorch version (GPU?): 2.0.0+cu118 (True)
• Huggingface_hub version: 0.13.4
• Transformers version: 4.28.1
• Accelerate version: 0.18.0
• xFormers version: 0.0.19
• Using GPU in script?: Yes
• Using distributed or parallel set-up in script?: No

[patrickvonplaten]

Thanks for the issue @wfng92, agree we should maybe not force disable xformers - @sayakpaul can we maybe revert/change your PR here?

[sayakpaul]

@patrickvonplaten on it. I will drop a follow-up PR to clear this regression.

[sayakpaul]

@wfng92 opened #3457. Let's continue the discussion there :)