Nano: add Neural Coder example and document (#7167)
* add NC example on nano * update information
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@ -368,3 +368,40 @@ with InferenceOptimizer.get_context(ipex_model, classifer):
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output = classifer(x)
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assert torch.get_num_threads() == 4 # this line just to let you know Nano has provided thread control automatically : )
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```
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## One-click Accleration Without Code Change
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```eval_rst
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.. note::
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Neural Compressor >= 2.0 is needed for this function. You may call ``pip install --upgrade neural-compressor`` before using this functionality.
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```
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We also provides a no-code method for users to accelerate their pytorch inferencing workflow through Neural Coder. Neural Coder is a novel component under Intel® Neural Compressor to further simplify the deployment of deep learning models via one-click. BigDL-Nano is now a backend in Neural Coder. Users could call
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```bash
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python -m neural_coder -o <acceleration_name> example.py
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```
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For `example.py`, it could be a common pytorch inference script without any code changes needed. For `<acceleration_name>`, please check following table.
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| Optimization Set | `<acceleration_name>` |
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| ------------- | ------------- |
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| BF16 + Channels Last | `nano_bf16_channels_last` |
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| BF16 + IPEX + Channels Last | `nano_bf16_ipex_channels_last` |
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| BF16 + IPEX | `nano_bf16_ipex` |
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| BF16 | `nano_bf16` |
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| Channels Last | `nano_fp32_channels_last` |
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| IPEX + Channels Last | `nano_fp32_ipex_channels_last` |
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| IPEX | `nano_fp32_ipex` |
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| INT8 | `nano_int8` |
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| JIT + BF16 + Channels Last | `nano_jit_bf16_channels_last` |
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| JIT + BF16 + IPEX + Channels Last | `nano_jit_bf16_ipex_channels_last` |
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| JIT + BF16 + IPEX | `nano_jit_bf16_ipex` |
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| JIT + BF16 | `nano_jit_bf16` |
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| JIT + Channels Last | `nano_jit_fp32_channels_last` |
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| JIT + IPEX + Channels Last | `nano_jit_fp32_ipex_channels_last` |
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| JIT + IPEX | `nano_jit_fp32_ipex` |
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| JIT | `nano_jit_fp32` |
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| ONNX Runtime | `nano_onnxruntime_fp32` |
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| ONNX Runtime + INT8 | `nano_onnxruntime_int8_qlinear` |
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| OpenVINO | `nano_openvino_fp32` |
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| OpenVINO + INT8 | `nano_openvino_int8` |
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