code: def rank_initialization(axes):
      rank = tf.size(axes)
      with tf.control_dependencies(
          [
              tf.debugging.assert_less_equal(
                  rank, 3, message="N-D FFT supported only up to 3-D."
              )
          ]
      ):
          rank = tf.identity(rank)
  
      return rank
  
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 32 for calling a global function with example usage: rank_initialization(axes) and returns: rank