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**Note:** Intel® Extension for PyTorch\* has PyTorch version requirement. Please check more detailed information via the URL below.
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More installation methods can be found at [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/1.11.0/tutorials/installation.html)
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More installation methods can be found at [Installation Guide](https://intel.github.io/intel-extension-for-pytorch/1.11.200/tutorials/installation.html)
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## Getting Started
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Minor code changes are required for users to get start with Intel® Extension for PyTorch\*. Both PyTorch imperative mode and TorchScript mode are supported. You just need to import Intel® Extension for PyTorch\* package and apply its optimize function against the model object. If it is a training workload, the optimize function also needs to be applied against the optimizer object.
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The following code snippet shows an inference code with FP32 data type. More examples, including training and C++ examples, are available at [Example page](https://intel.github.io/intel-extension-for-pytorch/1.11.0/tutorials/examples.html).
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The following code snippet shows an inference code with FP32 data type. More examples, including training and C++ examples, are available at [Example page](https://intel.github.io/intel-extension-for-pytorch/1.11.200/tutorials/examples.html).
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