Update pytorch to 1.11 (#4854)
* update setup and action * fix yml * update yml * test yml * update docs * update notebook requirements * test notebooks unit test * reset yml * delete comments * fix yml * fix errors in setup.py * fix setup.py * specify the version of IPEX
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			@ -47,13 +47,6 @@ from bigdl.nano.pytorch import Trainer
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trainer = Trainer(max_epoch=10, use_ipex=True)
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```
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Note: BigDL-Nano does not install IPEX by default. You can install IPEX using the following command:
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```bash
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python -m pip install torch_ipex==1.9.0 -f https://software.intel.com/ipex-whl-stable
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python -m pip install torchvision==0.10.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
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```
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#### Multi-instance Training
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When training on a server with dozens of CPU cores, it is often beneficial to use multiple training instances in a data-parallel fashion to make full use of the CPU cores. However, using PyTorch's DDP API is a little cumbersome and error-prone, and if not configured correctly, it will make the training even slow.
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