code: def forward_ad(node, wrt, preserve_result=False, check_dims=True):
    
    if not isinstance(node, gast.FunctionDef):
      raise TypeError
  
    # Activity analysis
    cfg_obj = cfg.CFG.build_cfg(node)
    cfg.Active(range(len(node.args.args))).visit(cfg_obj.entry)
  
    # Build forward mode function
    fad = ForwardAD(wrt, preserve_result, check_dims)
    node = fad.visit(node)
  
    # Annotate stacks
    node = annotate.find_stacks(node)
  
    # Clean up naive forward-mode fcode
    node = gast.Module([node])
    anno.clearanno(node)
  
    return node, fad.required
docs: Perform forward-mode AD on an AST.
  
    This function analyses the AST to determine which variables are active and
    proceeds by taking the naive derivative. Before returning the primal and
    adjoint it annotates push and pop statements as such.
  
    Args:
      node: A `FunctionDef` AST node.
      wrt: A tuple of argument indices with respect to which we take the
          derivative.
      preserve_result: A boolean indicating whether the original
          non-differentiated function value should be returned
      check_dims: A boolean indicating whether the provided derivatives should
          have the same shape as their corresponding arguments.
  
    Returns:
      mod: A `Module` node containing the naive primal and adjoint of the
          function which can be fed to the `split` and `joint` functions.
      required: A list of tuples of functions and argument indices. These
          functions were called by the function but did not have an adjoint.