Support mixed INT8 + FP16 in one model

[yiliu30]

Type of Change

feature
API changed or not

Description

• Support convert unquantized linear into fp16
• Extend the fp16 ops list to align with https://pytorch.org/docs/stable/amp.html#cpu-ops-that-can-autocast-to-bfloat16 in a separate PR

Usage

model = export(model, example_inputs=example_inputs)

quant_config = get_default_static_config()
quant_config.set_local(torch.nn.Linear, StaticQuantConfig(w_dtype="fp16", act_dtype="fp16"))
# prepare
prepare_model = prepare(model, quant_config)
# calibrate
for i in range(2):
    prepare_model(*example_inputs)
# convert
converted_model = convert(prepare_model)

Expected Behavior & Potential Risk

How has this PR been tested?

Pre-CI
Some extension test later.

Dependency Change?

expecttest

[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/torch/algorithms/pt2e_quant/core.py, neural_compressor/torch/algorithms/pt2e_quant/half_precision_rewriter.py, neural_compressor/torch/utils/utility.py.

🟢 Model Tests 3x workflow

Check ID	Status	Error details
Model-Test-3x	success		✅
Model-Test-3x (Generate Report GenerateReport)	success		✅
Model-Test-3x (Run PyTorch Model opt_125m_woq_gptq_int4)	success		✅
Model-Test-3x (Run PyTorch Model opt_125m_woq_gptq_int4_dq_bnb)	success		✅
Model-Test-3x (Run PyTorch Model opt_125m_woq_gptq_int4_dq_ggml)	success		✅

These checks are required after the changes to neural_compressor/torch/algorithms/pt2e_quant/core.py, neural_compressor/torch/algorithms/pt2e_quant/half_precision_rewriter.py, neural_compressor/torch/utils/utility.py.

🟢 Unit Tests 3x-PyTorch workflow

Check ID	Status	Error details
UT-3x-Torch	success		✅
UT-3x-Torch (Coverage Compare CollectDatafiles)	success		✅
UT-3x-Torch (Unit Test 3x Torch Unit Test 3x Torch)	success		✅
UT-3x-Torch (Unit Test 3x Torch baseline Unit Test 3x Torch baseline)	success		✅

These checks are required after the changes to neural_compressor/torch/algorithms/pt2e_quant/core.py, neural_compressor/torch/algorithms/pt2e_quant/half_precision_rewriter.py, neural_compressor/torch/utils/utility.py, test/3x/torch/algorithms/pt2e_quant/test_half_precision_rewriter.py, test/3x/torch/quantization/test_pt2e_quant.py, test/3x/torch/requirements.txt.

---

Thank you for your contribution! 💜

Note
This comment is automatically generated and will be updates every 180 seconds within the next 6 hours. If you have any other questions, contact chensuyue or XuehaoSun for help.

[xin3he]

Shall we add logger.info to teach user that ipex doesn't support fp16?
quant_config.set_local(torch.nn.Linear, StaticQuantConfig(w_dtype="fp16", act_dtype="fp16"))

[yiliu30]

Shall we add logger.info to teach user that ipex doesn't support fp16? quant_config.set_local(torch.nn.Linear, StaticQuantConfig(w_dtype="fp16", act_dtype="fp16"))

Thanks for your suggestions, will refine it by a separate PR.