TCDScheduler : eta out of range?

[Clement-Lelievre]

Describe the bug

Hi,

I am starting to play with the relatively recent scheduler TCDScheduler and encountered a bug yesterday.

The thing is, I'm embarrassed to say I am unable to provide the exact details of the bug. Right now I am unable to reproduce it again but I'd like to make sure it gets eradicated.

Here is however information from my memory that may help reproduce it:

• diffusers version : it was either 0.27.2 or 0.28.0
• ubuntu 20.04, CUDA 12.2
• where it crashed: here, indicating that I somehow called TCDScheduler.step with a too high eta (it was a float around 7 if I recall well). I did not call .step directly, it was called under the hood when calling my pipeline
• what pipeline used: a standard txt2img sd15 or sdxl pipeline
• doing what: switching schedulers randomly in the below list, to verify that configs work well and that I can infer smoothly while changing scheduler at every inference

_schedulers = [
    DDIMScheduler,
    DDPMScheduler,
    DEISMultistepScheduler,
    DPMSolverMultistepScheduler,
    DPMSolverSinglestepScheduler,
    EulerAncestralDiscreteScheduler,
    EulerDiscreteScheduler,
    HeunDiscreteScheduler,
    KDPM2AncestralDiscreteScheduler,
    KDPM2DiscreteScheduler,
    LCMScheduler,
    LMSDiscreteScheduler,
    PNDMScheduler,
    TCDScheduler,
    UniPCMultistepScheduler,
]

I had a cursory glance at diffusers code and couldn't see how I managed to somehow get an invalid eta value. I saw it defaults to 0.3 in TCDScheduler.step
Do you have a hint? A way to produce the bug when switching schedulers, maybe by being clumsy about the specific config params to use?

This is perhaps best dealt with by either @mhh0318 or @vanakema as they're the main contributors to this scheduler's code. (I am aware that the code originates from an external repo (jabir-zheng)).
cc @yi

Reproduction

as stated above, no MRE unfortunately but some level of detail to help narrow down the problem

Logs

again unfortunately all I know is I ran into the `AssertionError "gamma must be less than or equal to 1.0"`

System Info

• diffusers version: 0.27.2 or 0.28.0
• Platform: Linux-5.15.0-1048-aws-x86_64-with-glibc2.31
• Python version: 3.10.13
• PyTorch version (GPU?): 2.1.0 (True)
• Huggingface_hub version: 0.23.1
• Transformers version: 4.39.3
• Accelerate version: 0.25.0
• xFormers version: not installed
• Using GPU in script?: YES
• Using distributed or parallel set-up in script?: NO

Who can help?

@yiyixuxu @vanakema @mhh

[vanakema]

Oh man haha, I only appear like one of the main contributors because I did a huge refactoring of the Tensor type used across the repo. Someone else would definitely be better equip to answer this

[Clement-Lelievre]

Update: the error came from our implem, not diffusers'.
(FWIW, I had generated a random eta value for DDIMScheduler that was > 1 and then the scheduler was changed to TCDScheduler with the same eta value, triggering the assertionerror I linked above)

I'll close this issue