class_docstr: TensorFlow variables-based implmentation of computing running mean and std
  Benefit of this implementation is that it can be saved / loaded together with the tensorflow model
class_docstr_tok: ["TensorFlow","variables-based","implmentation","of","computing","running","mean","and","std","Benefit","of","this","implementation","is","that","it","can","be","saved","\/","loaded","together","with","the","tensorflow","model"]
code: def _set_mean_var_count(self):
      self.mean, self.var, self.count = self.sess.run(
          [self._mean, self._var, self._count]
      )
  
file_path: baselines/baselines/common/running_mean_std.py
imports: import tensorflow
  import numpy
  from baselines.common.tf_util import get_session
label_desc: Use image node_id 2 for calling the TfRunningMeanStd obj's underlying member method code with example usage: obj._set_mean_var_count() without return types