code: def _check_tf_pad(
      input_shape, pad_width, mode, constant_values, reflect_type
  ):
      pad_width = _to_tf_padding(pad_width, len(input_shape))
      return isinstance(constant_values, Number) and (
          mode == "constant"
          or (
              reflect_type == "even"
              and (
                  (
                      mode == "reflect"
                      and all(
                          pad_width[i][0] < s and pad_width[i][1] < s
                          for i, s in enumerate(input_shape)
                      )
                  )
                  or (
                      mode == "symmetric"
                      and all(
                          pad_width[i][0] <= s and pad_width[i][1] <= s
                          for i, s in enumerate(input_shape)
                      )
                  )
              )
          )
      )
  
imports: from collections import namedtuple
  from typing import Iterable, Union, Optional, Sequence, Tuple, NamedTuple, List, Literal, Callable, Any
  from numbers import Number
  import tensorflow
  from ivy.func_wrapper import with_unsupported_dtypes
  from ..None import backend_version
  import ivy
  from ivy.functional.ivy.experimental.manipulation import _to_tf_padding
label_desc: Use image node_id 20 for calling a global function with example usage: _check_tf_pad(input_shape, pad_width, mode, constant_values, reflect_type) and returns: unknown