code: def __init__(
      self,
      parse_input_fn,
      encoder_fn,
      parse_group_emb_fn,
      logit_fn=CosineLogits(),
      metric_name="auc",
      neg_sample_fn=None,
      loss_fn=sigmoid_loss,
  ):
      self.metric_name = metric_name
      self.metric_class = tf_euler.utils.metrics.get(metric_name)
      self.parse_input_fn = parse_input_fn
      self.parse_group_emb_fn = parse_group_emb_fn
      self.encoder = encoder_fn
      self.neg_sample_fn = neg_sample_fn
      self.logit_fn = logit_fn
      self.loss_fn = loss_fn
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  import tf_euler
  import six
  from tf_euler.python.solution.logits import CosineLogits, PosNegLogits
  from tf_euler.python.solution.losses import sigmoid_loss, xent_loss
  from tf_euler.python.solution.base_unsupervise import UnsuperviseSolution
label_desc: Use image node_id 1 to create a new SuperviseSampleSolution object from inherited base classes: object with example: obj = SuperviseSampleSolution(parse_input_fn, encoder_fn, parse_group_emb_fn, logit_fn, metric_name, neg_sample_fn, loss_fn)