mirror of
https://github.com/huggingface/diffusers.git
synced 2026-10-27 21:33:02 +03:00
d5baa4fb54
* tests: fix cuda model tests. * up * up * up * add to docstrings. * restore previous beehaviour. --------- Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
45 lines
1.7 KiB
Python
45 lines
1.7 KiB
Python
import torch
|
|
|
|
from diffusers.models.attention_dispatch import AttentionBackendName
|
|
|
|
|
|
_BF16_REQUIRED_BACKENDS = {
|
|
AttentionBackendName._NATIVE_CUDNN,
|
|
AttentionBackendName.FLASH_HUB,
|
|
AttentionBackendName.FLASH_VARLEN_HUB,
|
|
AttentionBackendName._FLASH_3_HUB,
|
|
AttentionBackendName._FLASH_3_VARLEN_HUB,
|
|
}
|
|
|
|
|
|
def _maybe_cast_to_bf16(backend, model, inputs_dict):
|
|
"""Cast model and floating-point inputs to bfloat16 when the backend requires it."""
|
|
if not backend or backend not in _BF16_REQUIRED_BACKENDS:
|
|
return model, inputs_dict
|
|
if getattr(model, "_keep_in_fp32_modules", None):
|
|
raise NotImplementedError("Do not know how to define casting for models with `_keep_in_fp32_modules`.")
|
|
model = model.to(dtype=torch.bfloat16)
|
|
inputs_dict = {
|
|
k: v.to(dtype=torch.bfloat16) if isinstance(v, torch.Tensor) and v.is_floating_point() else v
|
|
for k, v in inputs_dict.items()
|
|
}
|
|
return model, inputs_dict
|
|
|
|
|
|
def run_nondeterministic(fn):
|
|
"""
|
|
Run `fn` with `enable_full_determinism`'s deterministic-algorithm requirement lifted, restoring the previous
|
|
setting afterwards.
|
|
|
|
Several models reach a backward kernel that has no deterministic CUDA implementation (reflection/replication
|
|
padding, average pooling), which makes every test doing a backward pass raise under
|
|
`torch.use_deterministic_algorithms(True)`. Wrap those tests instead of relaxing determinism for the whole module,
|
|
and name the offending op at the call site.
|
|
"""
|
|
was_enabled = torch.are_deterministic_algorithms_enabled()
|
|
torch.use_deterministic_algorithms(False)
|
|
try:
|
|
fn()
|
|
finally:
|
|
torch.use_deterministic_algorithms(was_enabled)
|