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[IPEX] Fix torch.Generator hijack

This commit is contained in:
Nuullll 2024-01-06 19:09:56 +08:00
parent b00b429477
commit 73786c047f
1 changed files with 16 additions and 4 deletions
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16
modules/xpu_specific.py
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@ -94,11 +94,23 @@ def torch_xpu_scaled_dot_product_attention(
return torch.reshape(result, (*N, L, Ev)) return torch.reshape(result, (*N, L, Ev))
def is_xpu_device(device: str | torch.device = None):
if device is None:
return False
if isinstance(device, str):
return device.startswith("xpu")
return device.type == "xpu"
if has_xpu: if has_xpu:
# W/A for https://github.com/intel/intel-extension-for-pytorch/issues/452: torch.Generator API doesn't support XPU device try:
# torch.Generator supports "xpu" device since 2.1
torch.Generator("xpu")
except:
# W/A for https://github.com/intel/intel-extension-for-pytorch/issues/452: torch.Generator API doesn't support XPU device (for IPEX < 2.1)
CondFunc('torch.Generator', CondFunc('torch.Generator',
lambda orig_func, device=None: torch.xpu.Generator(device), lambda orig_func, device=None: torch.xpu.Generator(device),
lambda orig_func, device=None: device is not None and device.type == "xpu") lambda orig_func, device=None: is_xpu_device(device))
# W/A for some OPs that could not handle different input dtypes # W/A for some OPs that could not handle different input dtypes
CondFunc('torch.nn.functional.layer_norm', CondFunc('torch.nn.functional.layer_norm',