Fix XPU iGPU regressions (#9322)

* Change bf16 check and switch non-blocking to off default with option to force to regain speed on certain classes of iGPUs and refactor xpu check.

* Turn non_blocking off by default for xpu.

* Update README.md for Intel GPUs.
This commit is contained in:
Simon Lui
2025-08-13 16:13:35 -07:00
committed by GitHub
parent 9df8792d4b
commit c991a5da65
3 changed files with 25 additions and 26 deletions

View File

@@ -78,7 +78,6 @@ try:
torch_version = torch.version.__version__
temp = torch_version.split(".")
torch_version_numeric = (int(temp[0]), int(temp[1]))
xpu_available = (torch_version_numeric[0] < 2 or (torch_version_numeric[0] == 2 and torch_version_numeric[1] <= 4)) and torch.xpu.is_available()
except:
pass
@@ -102,10 +101,14 @@ if args.directml is not None:
try:
import intel_extension_for_pytorch as ipex # noqa: F401
_ = torch.xpu.device_count()
xpu_available = xpu_available or torch.xpu.is_available()
except:
xpu_available = xpu_available or (hasattr(torch, "xpu") and torch.xpu.is_available())
pass
try:
_ = torch.xpu.device_count()
xpu_available = torch.xpu.is_available()
except:
xpu_available = False
try:
if torch.backends.mps.is_available():
@@ -946,10 +949,12 @@ def pick_weight_dtype(dtype, fallback_dtype, device=None):
return dtype
def device_supports_non_blocking(device):
if args.force_non_blocking:
return True
if is_device_mps(device):
return False #pytorch bug? mps doesn't support non blocking
if is_intel_xpu():
return True
if is_intel_xpu(): #xpu does support non blocking but it is slower on iGPUs for some reason so disable by default until situation changes
return False
if args.deterministic: #TODO: figure out why deterministic breaks non blocking from gpu to cpu (previews)
return False
if directml_enabled:
@@ -1282,10 +1287,10 @@ def should_use_bf16(device=None, model_params=0, prioritize_performance=True, ma
return False
if is_intel_xpu():
if torch_version_numeric < (2, 6):
if torch_version_numeric < (2, 3):
return True
else:
return torch.xpu.get_device_capability(device)['has_bfloat16_conversions']
return torch.xpu.is_bf16_supported()
if is_ascend_npu():
return True