auto detect available device when exporting

[xin3he]

Type of Change

feature

Description

auto detect available packing device when exporting, priority: ["xpu", "cuda", "cpu"]

Expected Behavior & Potential Risk

When XPU format is required and XPU device is not available, INC will select packing device from ["xpu", "cuda", "cpu"] automatically.

How has this PR been tested?

test on cuda device when using xpu argument.

[github-actions]

⚡ Required checks status: All passing 🟢

Groups summary

🟢 Code Scan Tests workflow

Check ID	Status	Error details
Code-Scan	success		✅
Code-Scan (Bandit Code Scan Bandit)	success		✅
Code-Scan (DocStyle Code Scan DocStyle)	success		✅
Code-Scan (Pylint Code Scan Pylint)	success		✅

These checks are required after the changes to neural_compressor/model/torch_model.py.

🟢 Model Tests workflow

Check ID	Status	Error details
Model-Test	success		✅
Model-Test (Generate Report GenerateReport)	success		✅
Model-Test (Run ONNX Model resnet50-v1-12)	success		✅
Model-Test (Run PyTorch Model resnet18)	success		✅
Model-Test (Run PyTorch Model resnet18_fx)	success		✅
Model-Test (Run TensorFlow Model darknet19)	success		✅
Model-Test (Run TensorFlow Model inception_v1)	success		✅
Model-Test (Run TensorFlow Model resnet-101)	success		✅
Model-Test (Run TensorFlow Model resnet50v1.5)	success		✅
Model-Test (Run TensorFlow Model ssd_mobilenet_v1_ckpt)	success		✅
Model-Test (Run TensorFlow Model ssd_resnet50_v1)	success		✅

These checks are required after the changes to neural_compressor/model/torch_model.py.

🟢 Unit Tests basic workflow

Check ID	Status	Error details
UT-Basic	success		✅
UT-Basic (Coverage Compare CollectDatafiles)	success		✅
UT-Basic (Unit Test FWKs adaptor Test FWKs adaptor)	success		✅
UT-Basic (Unit Test FWKs adaptor baseline Test FWKs adaptor baseline)	success		✅
UT-Basic (Unit Test ITEX Test ITEX)	success		✅
UT-Basic (Unit Test ITEX baseline Test ITEX baseline)	success		✅
UT-Basic (Unit Test Pruning Test PyTorch Pruning)	success		✅
UT-Basic (Unit Test Pruning Test TensorFlow Pruning)	success		✅
UT-Basic (Unit Test Pruning baseline Test PyTorch Pruning baseline)	success		✅
UT-Basic (Unit Test Pruning baseline Test TensorFlow Pruning baseline)	success		✅
UT-Basic (Unit Test TF newAPI Test TF newAPI)	success		✅
UT-Basic (Unit Test TF newAPI baseline Test TF newAPI baseline)	success		✅
UT-Basic (Unit Test User facing API Test User facing API)	success		✅
UT-Basic (Unit Test User facing API baseline Test User facing API baseline)	success		✅
UT-Basic (Unit Test other basic case Test other basic case)	success		✅
UT-Basic (Unit Test other cases baseline Test other cases baseline)	success		✅

UT-Basic coverage report

	Base coverage	PR coverage	Diff
Lines	86.934%	86.985%	0.051%
Branches	76.495%	76.529%	0.034%

These checks are required after the changes to neural_compressor/model/torch_model.py.

🟢 Unit Tests basic no coverage workflow

Check ID	Status	Error details
UT-Basic-No-Coverage	success		✅
UT-Basic-No-Coverage (Unit Test FWKs adaptor Test FWKs adaptor)	success		✅
UT-Basic-No-Coverage (Unit Test Pruning Test PyTorch Pruning)	success		✅
UT-Basic-No-Coverage (Unit Test Pruning Test TensorFlow Pruning)	success		✅
UT-Basic-No-Coverage (Unit Test User facing API Test User facing API)	success		✅
UT-Basic-No-Coverage (Unit Test other basic case Test other basic case)	success		✅

These checks are required after the changes to neural_compressor/model/torch_model.py.

🟢 Unit Tests ITREX workflow

Check ID	Status	Error details
UT-ITREX	success		✅

These checks are required after the changes to neural_compressor/model/torch_model.py.

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Thank you for your contribution! 💜

Note
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[chensuyue]

/azp run Model-Test

[azure-pipelines]

Azure Pipelines successfully started running 1 pipeline(s).

[xin3he]

Keep this branch exist since it is used by IPEX.