docstr: Set summary information during the training process for visualization purposes.
  Saved summary can be viewed via TensorBoard.
  In order to take effect, it needs to be called before fit.
  
  Training summary will be saved to 'log_dir/app_name/train'
  and validation summary (if any) will be saved to 'log_dir/app_name/validation'.
  
  # Arguments
  log_dir: The base directory path to store training and validation logs.
  app_name: The name of the application.
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code: def set_tensorboard(self, log_dir, app_name):
      """
      Set summary information during the training process for visualization purposes.
      Saved summary can be viewed via TensorBoard.
      In order to take effect, it needs to be called before fit.
  
      Training summary will be saved to 'log_dir/app_name/train'
      and validation summary (if any) will be saved to 'log_dir/app_name/validation'.
  
      # Arguments
      log_dir: The base directory path to store training and validation logs.
      app_name: The name of the application.
      """
      callZooFunc(
          self.bigdl_type,
          "zooSetTensorBoard",
          self.value,
          log_dir,
          app_name,
      )
  
imports: import zoo.pipeline.api.autograd
  from zoo.feature.image import ImageSet
  from zoo.feature.text import TextSet
  from zoo.feature.common import FeatureSet
  from zoo.pipeline.api.keras.base import ZooKerasLayer
  from zoo.pipeline.api.keras.utils import *
  from bigdl.nn.layer import Layer
  from zoo.common.utils import callZooFunc
label_desc: Use image node_id 4 for calling the KerasNet obj's underlying member method code with example usage: obj.set_tensorboard(log_dir, app_name) without return types