code: def _from_ivy_array_to_torch_frontend_tensor(
      x, nested=False, include_derived=None, requires_grad=False
  ):
      if nested:
          return ivy.nested_map(
              functools.partial(
                  _from_ivy_array_to_torch_frontend_tensor,
                  requires_grad=requires_grad,
              ),
              x,
              include_derived,
              shallow=False,
          )
      elif isinstance(x, ivy.Array) or ivy.is_native_array(x):
          a = torch_frontend.Tensor(
              x, _init_overload=True, requires_grad=requires_grad
          )
          return a
      return x
  
imports: import functools
  from typing import Callable
  import ivy
  import ivy.functional.frontends.torch
label_desc: Use image node_id 1 for calling a global function with example usage: _from_ivy_array_to_torch_frontend_tensor(x, nested, include_derived, requires_grad) and returns: x, ivy, a