code: def __init__(
      self,
      metric=None,
      log_dir="/tmp/tflearn_logs/",
      global_step=None,
      session=None,
      graph=None,
      name=None,
  ):
      super(SupervisedEstimator, self).__init__(
          metric=metric,
          log_dir=log_dir,
          global_step=global_step,
          session=session,
          graph=graph,
          name=name,
      )
  
imports: from __future__ import division, print_function, absolute_import
  import os
  import tensorflow.compat.v1
  from tensorflow.python.ops import resources
  from ..utils import validate_func
label_desc: Use image node_id 1 to create a new SupervisedEstimator object from inherited base classes: BaseEstimator with example: obj = SupervisedEstimator(metric, log_dir, global_step, session, graph, name)