text: from keras.callbacks import TensorBoard
  import tensorflow as tf
  
  # Own Tensorboard class
  class ModifiedTensorBoard(TensorBoard):
  
      # Overriding init to set initial step and writer (we want one log file for all .fit() calls)
      def __init__(self, **kwargs):
          super().__init__(**kwargs)
          self.step = 1
          self.writer = tf.summary.FileWriter(self.log_dir)
  
      # Overriding this method to stop creating default log writer
      def set_model(self, model):
          pass
  
      # Overrided, saves logs with our step number
      # (otherwise every .fit() will start writing from 0th step)
      def on_epoch_end(self, epoch, logs=None):
          self.update_stats(**logs)
  
      # Overrided
      # We train for one batch only, no need to save anything at epoch end
      def on_batch_end(self, batch, logs=None):
          pass
  
      # Overrided, so won't close writer
      def on_train_end(self, _):
          pass
  
      # Custom method for saving own metrics
      # Creates writer, writes custom metrics and closes writer
      def update_stats(self, **stats):
          self._write_logs(stats, self.step)
  
  