Describe the bug

After torch.compile wan2.1 vae consume more GPU memory than no compilation, which is unexpected in my opinion.

compiled
Image

no-compile
Image

Reproduction

import sys
import torch
from diffusers import AutoencoderKLWan
def compile_wan_vae(compile):
 model_id = 'Wan-AI/Wan2.1-T2V-14B-Diffusers'
 dtype = torch.float32
 device = 'cuda'
 torch.cuda.memory._record_memory_history()
 vae = AutoencoderKLWan.from_pretrained(
 model_id, subfolder="vae", torch_dtype=dtype
 ).to(device)
 if compile:
 vae.decoder = torch.compile(vae.decoder)
 shape = (1, 16, 13, 120, 120)
 with torch.no_grad():
 latents = torch.randn(shape, device=device, dtype=dtype)
 video = vae.decode(latents, return_dict=False)[0]
 torch.cuda.empty_cache()
 with torch.no_grad():
 for _ in range(3):
 latents = torch.randn(shape, device=device, dtype=dtype)
 video = vae.decode(latents, return_dict=False)[0]
 torch.cuda.memory._dump_snapshot(f"{compile}-compile.pickle")
if __name__ == '__main__':
 compile_wan_vae(sys.argv[1] == 'compile')

Logs

System Info

• 🤗 Diffusers version: 0.34.0
• Platform: Linux-5.10.134-16.1.3.vip.an8.x86_64-x86_64-with-glibc2.39
• Running on Google Colab?: No
• Python version: 3.12.3
• PyTorch version (GPU?): 2.7.1+cu126 (True)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Huggingface_hub version: 0.34.2
• Transformers version: 4.54.0
• Accelerate version: 1.9.0
• PEFT version: 0.16.0
• Bitsandbytes version: not installed
• Safetensors version: 0.5.3
• xFormers version: not installed
• Accelerator: NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
  NVIDIA L20, 46068 MiB
• Using GPU in script?:
• Using distributed or parallel set-up in script?:

Who can help?

No response