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IPEX update to PyTorch 2.1 wheels for Linux

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Disty0
2023-12-13 18:19:08 +03:00
parent 9e9d31f1b7
commit 68206fbc05
4 changed files with 6 additions and 11 deletions
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CHANGELOG.md
+1
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@@ -37,6 +37,7 @@
- **Extra networks** new *settting -> extra networks -> build info on first access*
indexes all networks on first access instead of server startup
- **IPEX**
- Update to **Torch 2.1 - This Update Requires Intel OneApi 2024.0**, thanks @disty0
- Fix IPEX Optimize not applying with Diffusers backend, thanks @disty0
- Disable 32 bit workarounds if the GPU supports 64 bit, thanks @disty0
- More compatibility improvements, thanks @disty0
installer.py
+1 -1
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@@ -424,7 +424,7 @@ def check_torch():
os.environ.setdefault('NEOReadDebugKeys', '1')
os.environ.setdefault('ClDeviceGlobalMemSizeAvailablePercent', '100')
if "linux" in sys.platform:
torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.0.1a0 torchvision==0.15.2a0 intel_extension_for_pytorch==2.0.110+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
torch_command = os.environ.get('TORCH_COMMAND', 'torch==2.1.0a0 torchvision==0.16.0a0 intel-extension-for-pytorch==2.1.10+xpu --extra-index-url https://pytorch-extension.intel.com/release-whl/stable/xpu/us/')
os.environ.setdefault('TENSORFLOW_PACKAGE', 'tensorflow==2.13.0 intel-extension-for-tensorflow[gpu]')
else:
pytorch_pip = 'https://github.com/Nuullll/intel-extension-for-pytorch/releases/download/v2.0.110%2Bxpu-master%2Bdll-bundle/torch-2.0.0a0+gite9ebda2-cp310-cp310-win_amd64.whl'
modules/intel/ipex/__init__.py
-6
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@@ -156,12 +156,6 @@ def ipex_init(): # pylint: disable=too-many-statements
torch.cuda.get_device_properties.minor = 7
torch.cuda.ipc_collect = lambda *args, **kwargs: None
torch.cuda.utilization = lambda *args, **kwargs: 0
if hasattr(torch.xpu, 'getDeviceIdListForCard'):
torch.cuda.getDeviceIdListForCard = torch.xpu.getDeviceIdListForCard
torch.cuda.get_device_id_list_per_card = torch.xpu.getDeviceIdListForCard
else:
torch.cuda.getDeviceIdListForCard = torch.xpu.get_device_id_list_per_card
torch.cuda.get_device_id_list_per_card = torch.xpu.get_device_id_list_per_card
ipex_hijacks()
if not torch.xpu.has_fp64_dtype():
modules/intel/ipex/hijacks.py
+4 -4
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@@ -157,10 +157,10 @@ def ipex_hijacks():
lambda orig_func, f, map_location=None, pickle_module=None, *, weights_only=False, mmap=None, **kwargs:
orig_func(orig_func, f, map_location=return_xpu(map_location), pickle_module=pickle_module, weights_only=weights_only, mmap=mmap, **kwargs),
lambda orig_func, f, map_location=None, pickle_module=None, *, weights_only=False, mmap=None, **kwargs: check_device(map_location))
CondFunc('torch.Generator',
lambda orig_func, device=None: torch.xpu.Generator(return_xpu(device)),
lambda orig_func, device=None: device is not None and device != torch.device("cpu") and device != "cpu")
if hasattr(torch.xpu, "Generator"):
CondFunc('torch.Generator',
lambda orig_func, device=None: torch.xpu.Generator(return_xpu(device)),
lambda orig_func, device=None: device is not None and device != torch.device("cpu") and device != "cpu")
# TiledVAE and ControlNet:
CondFunc('torch.batch_norm',