parameters: (self, session=None)
return_statement: return self._variable.eval(session=session)
docstring: In a session, computes and returns the value of this variable.
  
      This is not a graph construction method, it does not add ops to the graph.
  
      This convenience method requires a session where the graph containing this
      variable has been launched. If no session is passed, the default session is
      used.  See the [Session class](../../api_docs/python/client.md#Session) for
      more information on launching a graph and on sessions.
  
      ```python
      v = tf.Variable([1, 2])
      init = tf.initialize_all_variables()
  
      with tf.Session() as sess:
          sess.run(init)
          # Usage passing the session explicitly.
          print(v.eval(sess))
          # Usage with the default session.  The 'with' block
          # above makes 'sess' the default session.
          print(v.eval())
      ```
  
      Args:
        session: The session to use to evaluate this variable. If
          none, the default session is used.
  
      Returns:
        A numpy `ndarray` with a copy of the value of this variable.
docstring_summary: In a session, computes and returns the value of this variable.
docstring_tokens: In a session computes and returns the value of this variable .
function: def eval(self, session=None):
      """In a session, computes and returns the value of this variable.
  
      This is not a graph construction method, it does not add ops to the graph.
  
      This convenience method requires a session where the graph containing this
      variable has been launched. If no session is passed, the default session is
      used.  See the [Session class](../../api_docs/python/client.md#Session) for
      more information on launching a graph and on sessions.
  
      ```python
      v = tf.Variable([1, 2])
      init = tf.initialize_all_variables()
  
      with tf.Session() as sess:
          sess.run(init)
          # Usage passing the session explicitly.
          print(v.eval(sess))
          # Usage with the default session.  The 'with' block
          # above makes 'sess' the default session.
          print(v.eval())
      ```
  
      Args:
        session: The session to use to evaluate this variable. If
          none, the default session is used.
  
      Returns:
        A numpy `ndarray` with a copy of the value of this variable.
      """
      return self._variable.eval(session=session)
function_tokens: def eval ( self , session = None ) : return self . _variable . eval ( session = session )