fix bf16 symbolic_trace bug

[xin3he]

Type of Change

bug fix

Description

fix bf16 symbolic_trace bug,

1. cause abnormal recursive calling.
2. missing necessary attributes

By moving BF16 fallback ahead of quantization and removing bf16_symbolic_trace, we fix it.

Expected Behavior

google/vit-base-patch16-224 autotuned with bf16 ops works.

How has this PR been tested?

local test

[github-actions[bot]]

⚡ 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/adaptor/pytorch.py, neural_compressor/adaptor/pytorch_cpu.yaml, neural_compressor/adaptor/torch_utils/bf16_convert.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_fx)	success		✅
Model-Test (Run TensorFlow Model resnet50v1.5)	success		✅
Model-Test (Run TensorFlow Model ssd_resnet50_v1)	success		✅

These checks are required after the changes to neural_compressor/adaptor/pytorch.py, neural_compressor/adaptor/pytorch_cpu.yaml, neural_compressor/adaptor/torch_utils/bf16_convert.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	76.095%	76.101%	0.006%
Branches	65.171%	65.194%	0.023%

These checks are required after the changes to neural_compressor/adaptor/pytorch.py, neural_compressor/adaptor/pytorch_cpu.yaml, neural_compressor/adaptor/torch_utils/bf16_convert.py, test/adaptor/pytorch_adaptor/test_adaptor_pytorch_2x.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/adaptor/pytorch.py, neural_compressor/adaptor/pytorch_cpu.yaml, neural_compressor/adaptor/torch_utils/bf16_convert.py, test/adaptor/pytorch_adaptor/test_adaptor_pytorch_2x.py.

🟢 Unit Tests ITREX workflow

Check ID	Status	Error details
UT-ITREX	success		✅

These checks are required after the changes to neural_compressor/adaptor/pytorch.py, neural_compressor/adaptor/pytorch_cpu.yaml, neural_compressor/adaptor/torch_utils/bf16_convert.py.

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