code: def axes_initialization(shape, axes, input_shape, input_rank_tensor):
      if axes is None:
          axes = (
              tf.range(-tf.size(input_shape), 0)
              if shape is None
              else tf.range(-tf.size(shape), 0)
          )
      axes = tf.where(
          tf.math.less(axes, 0), axes + input_rank_tensor, axes
      )
      return axes
  
imports: import math
  from typing import Union, Optional, Tuple, List, Literal, Sequence, Callable
  import tensorflow
  from ivy.func_wrapper import inputs_to_ivy_arrays, output_to_native_arrays, with_unsupported_dtypes, with_supported_dtypes, with_supported_device_and_dtypes
  from ..None import backend_version
  import ivy
  from ivy.functional.ivy.layers import _handle_padding, _get_num_padded_values, _validate_max_pool_params, _depth_max_pooling_helper
  from ivy.functional.ivy.experimental.layers import _padding_ceil_mode, _get_size
label_desc: Use image node_id 29 for calling a global function with example usage: axes_initialization(shape, axes, input_shape, input_rank_tensor) and returns: axes