code: def __init__(self, net_outputs, model=None, session=None):
      self.net_outputs = to_list(net_outputs)
      self.graph = net_outputs[0].graph
      self.model = model
  
      with self.graph.as_default():
          self.session = tf.Session()
          if session:
              self.session = session
          self.saver = tf.train.Saver()
          if model:
              self.saver.restore(self.session, model)
  
file_path: tflearn/tflearn/helpers/generator.py
imports: from __future__ import division, print_function, absolute_import
  import tensorflow.compat.v1
  from ..utils import to_list
label_desc: Use image node_id 1 to create a new SequenceGenerator object from inherited base classes: object with example: obj = SequenceGenerator(net_outputs, model, session)