code: def get_perm(input_rank_tensor, axes):
      all_dims = tf.range(input_rank_tensor, dtype=tf.dtypes.int32)
      perm = tf.concat(
          [
              tf.boolean_mask(
                  all_dims,
                  tf.foldl(
                      lambda acc, elem: tf.math.logical_and(
                          acc, tf.math.not_equal(all_dims, elem)
                      ),
                      axes,
                      initializer=tf.fill(all_dims.shape, True),
                  ),
              ),
              axes,
          ],
          0,
      )
      return perm
  
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 35 for calling a global function with example usage: get_perm(input_rank_tensor, axes) and returns: perm