class_docstr: Weights & Biases Logger.
  
  This is a logger class that can be passed into the initialization
  of a KerasModel or TorchModel. It initializes and sets up a wandb logger which
  will log the specified metrics calculated on the specific datasets
  to the user's W&B dashboard.
  
  If a WandbLogger is provided to the wandb_logger flag,
  the metrics are logged to Weights & Biases, along with other information
  such as epoch number, losses, sample counts, and model configuration data.
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docstr: Updates the W&B configuration.
  Parameters
  ----------
  config_data: dict
      additional configuration data to add
docstr_tok: ["Updates","the","W","&","B","configuration",".","Parameters","--","--","--","--","--","config_data",":","dict","additional","configuration","data","to","add"]
code: def update_config(self, config_data):
      """Updates the W&B configuration.
      Parameters
      ----------
      config_data: dict
          additional configuration data to add
      """
      self.wandb_run.config.update(config_data)
  
file_path: deepchem/deepchem/models/wandblogger.py
imports: import logging
  import importlib.util
  from typing import Optional, Union, List, Dict
label_desc: Use image node_id 5 for calling the WandbLogger obj's underlying member method code with example usage: obj.update_config(config_data) without return types