code: def _slice(
      g: jit_utils.GraphContext,
      input: torch._C.Value,
      axes: Union[List, torch.Tensor, torch._C.Value],
      starts: Union[List, torch.Tensor, torch._C.Value],
      ends: Union[List, torch.Tensor, torch._C.Value],
      steps: Optional[Union[List, torch.Tensor, torch._C.Value]] = None,
  ):
      def is_none_value(value):
          if value is None:
              return True
          return (
              isinstance(value, torch._C.Value)
              and value.node().kind() == "prim::Constant"
              and isinstance(value.type(), _C.NoneType)
          )
  
      def to_slice_input(list_or_value, default_value=None):
          # Convert input param into a 1D torch.Value.
          if is_none_value(list_or_value) and default_value is not None:
              list_or_value = [default_value]
  
          if isinstance(list_or_value, (list, torch.Tensor)):
              return g.op(
                  "Constant", value_t=torch.tensor(list_or_value)
              )
  
          rank = symbolic_helper._get_tensor_rank(list_or_value)
          if rank == 0:
              return symbolic_helper._unsqueeze_helper(
                  g, list_or_value, [0]
              )
          if rank == 1:
              return list_or_value
          raise errors.SymbolicValueError(
              f"Rank must be 0 or 1, not {rank}", list_or_value
          )
  
      def get_const_value(list_or_value):
          if isinstance(list_or_value, (list, torch.Tensor)):
              if len(list_or_value) == 1:
                  return list_or_value[0]
              return None
          return symbolic_helper._maybe_get_const(list_or_value, "i")
  
      # Check if slice is a no-op
      if (
          get_const_value(starts) == 0
          and get_const_value(ends) == _constants.INT64_MAX
          and (steps is None or get_const_value(steps) == 1)
      ):
          return input
  
      axes = to_slice_input(axes)
      starts = to_slice_input(starts, default_value=0)
      ends = to_slice_input(ends, default_value=_constants.INT64_MAX)
      if steps is None:
          return g.op("Slice", input, starts, ends, axes)
      steps = to_slice_input(steps, default_value=1)
      return g.op("Slice", input, starts, ends, axes, steps)
  
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 15 for calling a global function with example usage: _slice(g, input, axes, starts, ends, steps) and returns: g, unknown, symbolic_helper, input, g, True, g, symbolic_helper, list_or_value, None, list_or_value