code: def _size_of(node: fx.Node) -> int:
      if "val" in node.meta:
          val = node.meta["val"]
          if isinstance(val, py_sym_types):
              if isinstance(val, torch.SymInt):
                  return 1
              else:
                  return 999999
          # NB: The fallback values here are meaningless, maybe we should respect
          # torch._inductor.config.unbacked_symint_fallback (but this is a
          # layering violation)
          elif isinstance(val, (list, tuple)):
              return sum(
                  _tensor_nbytes(
                      hint_int(n.numel(), fallback=4098), n.dtype
                  )
                  for n in val
                  if isinstance(n, torch.Tensor)
              )
          elif isinstance(val, torch.Tensor):
              return _tensor_nbytes(
                  hint_int(val.numel(), fallback=4098), val.dtype
              )
  
          raise RuntimeError(f"Unknown metadata type {type(val)}")
  
      # Only needed since we don't always trace with fake tensors.
      if "tensor_meta" in node.meta:
          metadata = node.meta["tensor_meta"]
          # TODO: What is to_size_hint suppose to be?
          numel = _prod(map(to_size_hint, metadata.shape))  # noqa: F821
          dtype = metadata.dtype
      else:
          return 0
  
      return _tensor_nbytes(numel, dtype)
  
imports: from torch.fx.experimental.proxy_tensor import is_sym_node, py_sym_types
  from torch.fx.experimental.sym_node import magic_methods, method_to_operator
  from torch.fx.experimental.symbolic_shapes import hint_int, free_symbols, is_symbol_binding_fx_node, find_symbol_binding_fx_nodes
  import torch
  import torch.fx
  import operator
  import math
  import torch.utils._pytree
  import copy
  import os
  import itertools
  import sympy
  from collections import defaultdict
  from torch.fx.passes import graph_drawer
  from typing import List, Optional, Set, Tuple, Union
  from .compile_utils import fx_graph_cse, get_aten_target
  from .None import config
  import functools
label_desc: Use image node_id 15 for calling a global function with example usage: _size_of(node) and returns: _tensor_nbytes, int, int, int, sum, _tensor_nbytes