class_docstr: A specialized KerasTensor representation for `tf.RaggedTensor`s.
  
  Specifically, it:
  
  1. Specializes the conversion to a placeholder in order
  to maintain shape information for non-ragged dimensions.
  2. Overloads the KerasTensor's operators with the RaggedTensor versions
  when they don't match the `tf.Tensor` versions
  3. Exposes some of the instance method/attribute that are unique to
  the RaggedTensor API (such as ragged_rank).
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code: def ragged_rank(self):
      return self.type_spec.ragged_rank
  
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 2 for calling the RaggedKerasTensor obj's underlying member method code with example usage: obj.ragged_rank() and returns: self