title: Tensorflow and class intantiations. Do I need a separate graph for each instantiation?
body: <p>I have a quick question.  Consider, as an example, that I am writing a tensorflow program to model a single-layer perceptron that will perform boolean functions.  If I'm writing a class to contain that perceptron, will I need to create a separate graph using tf.graph for each instantiation of the class?</p>
  
  <p>I.e. if I an modeling the boolean functions AND, OR and NAND, and I write a class Perceptron: 
           ...</p>
  
  <p>Will I need to run tf.graph() in the <strong>init</strong> method for each class instantion  so that they're not using the same namespace? Or can I get away with defining scopes for each type of operation and only instantiate one class to perform all three types of operations?</p>
  
  <p>Thanks</p>