DPM ++ karras scheduler.add_noise fails when t = 0

[garychan22]

Describe the bug

When I calling the add_noise function of dpm++ karras when t = 0, it fails

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/xxx/miniconda3/envs/controlnet/lib/python3.8/site-packages/diffusers/schedulers/scheduling_dpmsolver_multistep.py", line 889, in add_noise
    step_indices = [(schedule_timesteps == t).nonzero().item() for t in timesteps]
  File "/home/xxx/miniconda3/envs/controlnet/lib/python3.8/site-packages/diffusers/schedulers/scheduling_dpmsolver_multistep.py", line 889, in <listcomp>
    step_indices = [(schedule_timesteps == t).nonzero().item() for t in timesteps]
RuntimeError: a Tensor with 2 elements cannot be converted to Scalar

Reproduction

import torch
from diffusers import DPMSolverMultistepScheduler
model_path = "models/models--stabilityai--stable-diffusion-2-base"
scheduler = DPMSolverMultistepScheduler.from_pretrained(model_path, subfolder="scheduler", use_karras_sigmas=True)
scheduler.set_timesteps(60)
latents = torch.randn([1, 4, 64, 64])
noise = torch.randn([1, 4, 64, 64])
noisy = scheduler.add_noise(latents, noise, torch.tensor([0]))

Logs

No response

System Info

Copy-and-paste the text below in your GitHub issue and FILL OUT the two last points.

• diffusers version: 0.23.1
• Platform: Linux-5.15.0-86-generic-x86_64-with-glibc2.17
• Python version: 3.8.18
• PyTorch version (GPU?): 2.0.1+cu117 (True)
• Huggingface_hub version: 0.17.1
• Transformers version: 4.33.2
• Accelerate version: 0.23.0
• xFormers version: 0.0.21
• Using GPU in script?:
• Using distributed or parallel set-up in script?:

Who can help?

@yiyixuxu @DN6 @sayakpaul @patrickvonplaten