code: def _check_torch_pad(
      mode, reflect_type, pad_width, input_shape, constant_values
  ):
      ndim = len(input_shape)
      pad_width = _to_tf_padding(pad_width, ndim)
      if mode != "constant" and (
          ndim > 4 or (ndim > 1 and len(pad_width) > ndim - 1)
      ):
          return False
      return _check_paddle_pad(
          mode,
          reflect_type,
          pad_width,
          input_shape,
          constant_values,
          4,
          extend=False,
      ) and (
          mode != "wrap"
          or all(
              pad_width[i][0] <= s and pad_width[i][1] <= s
              for i, s in enumerate(input_shape)
          )
      )
  
imports: from typing import Iterable, Optional, Union, Sequence, Tuple, NamedTuple, List, Literal, Callable, Any
  from numbers import Number
  from collections import namedtuple
  import torch
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from ..None import backend_version
  import ivy
  from ivy.functional.ivy.experimental.manipulation import _to_tf_padding, _check_paddle_pad, _to_paddle_padding
label_desc: Use image node_id 4 for calling a global function with example usage: _check_torch_pad(mode, reflect_type, pad_width, input_shape, constant_values) and returns: unknown, False