class_docstr: It is a MongoDB based manager that help you to manage data, network architecture, parameters and logging.
  
  Parameters
  -------------
  ip : str
      Localhost or IP address.
  port : int
      Port number.
  dbname : str
      Database name.
  username : str or None
      User name, set to None if you do not need authentication.
  password : str
      Password.
  project_name : str or None
      Experiment key for this entire project, similar with the repository name of Github.
  
  Attributes
  ------------
  ip, port, dbname and other input parameters : see above
      See above.
  project_name : str
      The given project name, if no given, set to the script name.
  db : mongodb client
      See ``pymongo.MongoClient``.
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docstr: Saves the training log, timestamp will be added automatically.
  
  Parameters
  -----------
  kwargs : logging information
      Events, such as accuracy, loss, step number and etc.
  
  Examples
  ---------
  >>> db.save_training_log(accuracy=0.33, loss=0.98)
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code: def save_training_log(self, **kwargs):
      """Saves the training log, timestamp will be added automatically.
  
      Parameters
      -----------
      kwargs : logging information
          Events, such as accuracy, loss, step number and etc.
  
      Examples
      ---------
      >>> db.save_training_log(accuracy=0.33, loss=0.98)
  
      """
  
      self._fill_project_info(kwargs)
      kwargs.update({"time": datetime.utcnow()})
      _result = self.db.TrainLog.insert_one(kwargs)
      _log = self._print_dict(kwargs)
      logging.info("[Database] train log: " + _log)
  
imports: import os
  import pickle
  import sys
  import time
  from datetime import datetime
  import numpy
  import tensorflow
  import gridfs
  import pymongo
  from tensorlayer import logging
  from tensorlayer.files import assign_weights, del_folder, exists_or_mkdir, load_hdf5_to_weights, save_weights_to_hdf5, static_graph2net
label_desc: Use image node_id 13 for calling the TensorHub obj's underlying member method code with example usage: obj.save_training_log() without return types