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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_unique_variable(name):
 """Gets the variable uniquely identified by that name. Args: name: a name that uniquely identifies the variable. Returns: a tensorflow variable. Raises: ValueError: if no variable uniquely identified by the name exists. """

  candidates = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, name)
  if not candidates:
    raise ValueError('Couldnt find variable %s' % name)

  for candidate in candidates:
    if candidate.op.name == name:
      return candidate
  raise ValueError('Variable %s does not uniquely identify a variable', name)