code: def __init__(self, label_idx, label_dim, metric_name="f1"):
      self.label_idx = label_idx
      self.label_dim = label_dim
      self.metric_name = metric_name
      self.metric_class = tf_euler.utils.metrics.get(metric_name)
      self.out_fc = tf.layers.Dense(label_dim, use_bias=False)
  
file_path: euler/tf_euler/python/mp_utils/base.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
label_desc: Use image node_id 1 to create a new SuperviseModel object from inherited base classes: object with example: obj = SuperviseModel(label_idx, label_dim, metric_name)