class_docstr: A patched tf.learn Experiment class to handle GPU memory
  sharing issues.
class_docstr_tok: ["A","patched","tf.learn","Experiment","class","to","handle","GPU","memory","sharing","issues","."]
docstr: Determines whether the training has stopped.
docstr_tok: ["Determines","whether","the","training","has","stopped","."]
code: def _has_training_stopped(self, eval_result):
      """Determines whether the training has stopped."""
      if not eval_result:
          return False
  
      global_step = eval_result.get(tf.GraphKeys.GLOBAL_STEP)
      return (
          global_step
          and self._train_steps
          and (global_step >= self._train_steps)
      )
  
imports: import tensorflow
label_desc: Use image node_id 2 for calling the Experiment obj's underlying member method code with example usage: obj._has_training_stopped(eval_result) and returns: unknown, False