cf5f23996f
- apply_attention_backend now restores the native default when no backend is requested or a
kernel fails. diffusers keeps a process-wide active attention backend that
set_attention_backend updates, and a fresh transformer's processors follow it, so a load
that wanted native could silently inherit a backend (e.g. cuDNN) an earlier speed-profile
load pinned, breaking the bit-identical/off guarantee.
- select_attention_backend drops flash3/flash4 up front when the CUDA capability is below
Hopper/Blackwell. diffusers only checks the kernels package at set time, so an explicit
request on the wrong card set fine then crashed mid-generation; it now falls back to native.
- Add the sdpa alias to the attention_backend Literal so an API request with sdpa (already a
valid alias of native) is accepted instead of 422-rejected by Pydantic.
- Drop the dead replace('-','_') normalization (no alias uses dashes/underscores).
- perf_levers_probe.py output dir is now relative to the script, not a hardcoded path.
|
||
|---|---|---|
| .. | ||
| .gitkeep | ||
| __init__.py | ||
| auth.py | ||
| data_recipe.py | ||
| datasets.py | ||
| export.py | ||
| inference.py | ||
| mcp_servers.py | ||
| models.py | ||
| providers.py | ||
| responses.py | ||
| training.py | ||
| users.py | ||