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it refers to log_sigmas, but they are only set if self.config.use_karras_sigmas, otherwise its UNDEFINED
it refers to self.num_inference_steps, but that param is set AFTER this code segment and here its NONE
actual sigmas at the end are blindly converted from numpy to tensor even if they are already a tensor causing a runtime error
Reproduction
simply use ANY of the above schedulers with either use_exponential_sigmas or use_beta_sigmas
Logs
UnboundLocalError: cannot access local variable 'log_sigmas' where it is not associated with a value
or
TypeError: linspace() received an invalid combination of arguments - got (float, float, NoneType), but expected one of:
or
TypeError: 'NoneType' object cannot be interpreted as an integer
or
TypeError: expected np.ndarray (got Tensor)
System Info
diffusers from main branch as of 11/18/24 commit #345907f
imo, i don't think they ever were? exponential was added via pr #9518 and beta via pr #9538
i did briefly mention the problem in the pr itself, but was told to create an issue.
hlky
linked a pull request
Nov 18, 2024
that will
close
this issue
Describe the bug
following schedulers implement beta and exponential sigma methods:
and in all of them, its pretty much broken.
(ok, i admit i tested only 6, not all)
looking at code segment:
log_sigmas
, but they are only set ifself.config.use_karras_sigmas
, otherwise its UNDEFINEDself.num_inference_steps
, but that param is set AFTER this code segment and here its NONEReproduction
simply use ANY of the above schedulers with either
use_exponential_sigmas
oruse_beta_sigmas
Logs
System Info
diffusers from main branch as of 11/18/24 commit #345907f
Who can help?
@yiyixuxu @sayakpaul @DN6 @asomoza
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