class_docstr: Abstract base class for Tensor-like objects that are composed from Tensors.
  
  Each `CompositeTensor` can be decomposed into a structured collection of
  component `tf.Tensor`s, and reconstructed from those components.
  
  The `tensorflow.python.util.nest` module has support for treating composite
  tensors as structure, which makes it easy to flatten and reconstruct
  composite tensors (or larger structures that contain composite tensors).
  E.g.:
  
  ```python
  ct = ...  # Create a composite tensor.
  flat_list_of_tensors = nest.flatten(ct, expand_composites=True)
  transformed_list_of_tensors = ...  # do something with the flat tensors.
  result = nest.pack_sequence_as(ct, transformed_list_of_tensors,
                                 expand_composites=True)
  ```
docstr: Returns a list of `Operation`s that consume this `CompositeTensor`.
  
  Returns:
    A list of `Operation`s.
  
  Raises:
    RuntimeError: If this method is called while executing eagerly.
code: def _consumers(self):
      """Returns a list of `Operation`s that consume this `CompositeTensor`.
  
      Returns:
        A list of `Operation`s.
  
      Raises:
        RuntimeError: If this method is called while executing eagerly.
      """
      consumers = nest.flatten(
          [
              component.consumers()
              for component in nest.flatten(
                  self, expand_composites=True
              )
              if getattr(component, "graph", None) is not None
          ]
      )
      return list(set(consumers))
  
file_path: tensorflow/tensorflow/python/framework/composite_tensor.py
imports: import abc
  from tensorflow.python import pywrap_tensorflow
  from tensorflow.python.util import nest
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 3 for calling the CompositeTensor obj's underlying member method code with example usage: obj._consumers() and returns: list