code: def _interpolate(name, dim, interpolate_mode):
      @symbolic_helper.quantized_args(True, False, False)
      @_beartype.beartype
      def symbolic_fn(g, input, output_size, *args):
          (
              scales,
              align_corners,
          ) = symbolic_helper._get_interpolate_attributes(
              g, interpolate_mode, args
          )
          symbolic_helper._interpolate_warning(interpolate_mode)
          align_corners = symbolic_helper._maybe_get_scalar(
              align_corners
          )
          if align_corners:
              return symbolic_helper._unimplemented(
                  name, "align_corners == True", input
              )
          if scales is None:
              scales = symbolic_helper._interpolate_size_to_scales(
                  g, input, output_size, dim
              )
          return g.op("Resize", input, scales, mode_s=interpolate_mode)
  
      return symbolic_fn
  
imports: from __future__ import annotations
  import functools
  import sys
  import warnings
  from typing import List, Optional, Sequence, Tuple, Union
  import torch
  import torch._C._onnx
  import torch.onnx
  from torch import _C
  from torch.onnx import _constants, _type_utils, errors, symbolic_helper, symbolic_opset9
  from torch.onnx._globals import GLOBALS
  from torch.onnx._internal import _beartype, jit_utils, registration
label_desc: Use image node_id 13 for calling a global function with example usage: _interpolate(name, dim, interpolate_mode) and returns: symbolic_fn, g, symbolic_helper