also available in the C++ API. These include:


"torch::Tensor" methods such as "add" / "reshape" / "clone". For the
  full list of methods available, please see:
  https://pytorch.org/cppdocs/api/classat_1_1_tensor.html


C++ tensor indexing API that looks and behaves the same as the
  Python API. For details on its usage, please see:
  https://pytorch.org/cppdocs/notes/tensor_indexing.html


The tensor autograd APIs and the "torch::autograd" package that are
  crucial for building dynamic neural networks in C++ frontend. For
  more details, please see:
  https://pytorch.org/tutorials/advanced/cpp_autograd.html


Authoring Models in C++
The "author in TorchScript, infer in C++" workflow requires model
authoring to be done in TorchScript. However, there might be cases
where the model has to be authored in C++ (e.g. in workflows where a
Python component is undesirable). To serve such use cases, we provide
the full capability of authoring and training a neural net model