code: def get_x_after_pad_or_crop(
      x, shape, axes, perform_padding, input_rank_tensor
  ):
      if perform_padding:
          pad_shape = -tf.ones([input_rank_tensor], dtype=tf.int32)
          pad_shape = tf.tensor_scatter_nd_update(
              pad_shape, tf.expand_dims(axes, -1), shape
          )
          x = _right_pad_or_crop(x, pad_shape)
      return x
  
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 34 for calling a global function with example usage: get_x_after_pad_or_crop(x, shape, axes, perform_padding, input_rank_tensor) and returns: x