code: def static_output_shape(input_shape, shape, axes):
      output_shape = input_shape.as_list()
      if shape is not None:
          if axes is None:
              axes = list(range(-len(shape), 0))
          if isinstance(shape, tf.Tensor):
              if isinstance(axes, tf.Tensor):
                  output_shape = [None] * len(output_shape)
              else:
                  for ax in axes:
                      output_shape[ax] = None
          else:
              for idx, ax in enumerate(axes):
                  output_shape[ax] = shape[idx]
      return tf.TensorShape(output_shape)
  
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 38 for calling a global function with example usage: static_output_shape(input_shape, shape, axes) and returns: tf