class_docstr: Wraps function bodies around autograph-specific boilerplate.
class_docstr_tok: ["Wraps","function","bodies","around","autograph-specific","boilerplate","."]
docstr: Returns the options with which to create function scopes.
docstr_tok: ["Returns","the","options","with","which","to","create","function","scopes","."]
code: def _function_scope_options(self, fn_scope):
      """Returns the options with which to create function scopes."""
      # Top-level function receive the options that were directly requested.
      # All others receive the options corresponding to a recursive conversion.
      # Note: this mainly controls the user_requested flag, which is important
      # primarily because the FunctionScope context also creates a
      # ControlStatusCtx(autograph=ENABLED) when user_requested is True. See
      # function_wrappers.py.
      if fn_scope.level == 2:
          return self.ctx.user.options
      return self.ctx.user.options.call_options()
  
file_path: tensorflow-upstream/tensorflow/python/autograph/converters/functions.py
imports: import gast
  from tensorflow.python.autograph.core import converter
  from tensorflow.python.autograph.pyct import anno
  from tensorflow.python.autograph.pyct import parser
  from tensorflow.python.autograph.pyct import qual_names
  from tensorflow.python.autograph.pyct import templates
  from tensorflow.python.autograph.pyct.static_analysis import activity
  from tensorflow.python.autograph.pyct.static_analysis import annos
label_desc: Use image node_id 1 for calling the FunctionTransformer obj's underlying member method code with example usage: obj._function_scope_options(fn_scope) and returns: self, self