class_docstr: Represents a get operation on a Pipeline type signature.
  
  If a pipeline instance `my_pipeline` has `output_type`
  {'key_1': Type1, 'key_2': Type2}, then PipelineKey(my_pipeline, 'key_1'),
  represents the output type Type1. And likewise
  PipelineKey(my_pipeline, 'key_2') represents Type2.
  
  Calling __getitem__ on a pipeline will return a PipelineKey instance.
  So my_pipeline['key_1'] returns PipelineKey(my_pipeline, 'key_1'), and so on.
  
  PipelineKey objects are used for assembling a directed acyclic graph of
  Pipeline instances. See dag_pipeline.py.
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code: def __repr__(self):
      return "PipelineKey(%s, %s)" % (self.unit, self.key)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import abc
  import inspect
  import os.path
  from magenta.pipelines import statistics
  import six
  import tensorflow.compat.v1
label_desc: Use image node_id 2 for calling the PipelineKey obj's underlying member method code with example usage: obj.__repr__() and returns: unknown