code: def register_keras_tensor_specialization(cls, keras_tensor_subclass):
      """Register a specialized KerasTensor subclass for a Tensor type."""
      # We always leave (object, KerasTensor) at the end as a generic fallback
      keras_tensor_classes.insert(-1, (cls, keras_tensor_subclass))
  
imports: from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import type_spec
  from tensorflow.python.keras.utils import object_identity
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops.ragged import ragged_operators
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling a global function with example usage: register_keras_tensor_specialization(cls, keras_tensor_subclass) without return types