You can use dlpack to get from and to TVM with your tensors:
def tensor_to_tvm(t):
    return tvm.nd.from_dlpack(torch.utils.dlpack.to_dlpack(t))
def tensor_from_tvm(a):
    return(torch.utils.dlpack.from_dlpack(a.to_dlpack()))

This allows to feed PyTorch tensors to TVM models and recover the results.
If you want to convert part of your PyTorch to TVM, you can use the JIT and the TVM PyTorch frontend.
I have an in-depth example that does funny tricks to also enable training in the Transformers, PyTorch and TVM blog post 4.
In my courses, we also do converting to TVM and then running from C++ and this kind of stuff.
Best regards
Thomas