code: def _is_padded_shape_compatible_with(
      padded_shape, input_component_shape
  ):
      """Returns `True` if `input_component_shape` can be padded to `padded_shape`.
  
      Args:
        padded_shape: A `tf.TensorShape`.
        input_component_shape: A `tf.TensorShape`.
  
      Returns:
        `True` if `input_component_shape` can be padded to `padded_shape`, otherwise
        `False`.
      """
  
      if (
          padded_shape.dims is None
          or input_component_shape.dims is None
      ):
          return True
      if len(padded_shape.dims) != len(input_component_shape.dims):
          return False
      for padded_dim, input_dim in zip(
          padded_shape.dims, input_component_shape.dims
      ):
          if (
              padded_dim.value is not None
              and input_dim.value is not None
              and padded_dim.value < input_dim.value
          ):
              return False
      return True
  
imports: import numpy
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.util import nest
  from tensorflow.python.data.util import structure
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import smart_cond
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import gen_dataset_ops
label_desc: Use image node_id 2 for calling a global function with example usage: _is_padded_shape_compatible_with(padded_shape, input_component_shape) and returns: True, True, False, False