class_docstr: Callback for logging the status of training.
docstr: Initializes the callback.
  
  Args:
      epochs: Total number of epochs.
      silent: If 'True' the entire progressbar wrapper is disabled.
docstr_tok: ["Initializes","the","callback",".","Args",":","epochs",":","Total","number","of","epochs",".","silent",":","If","'True","'","the","entire","progressbar","wrapper","is","disabled","."]
code: def __init__(self, epochs: int, silent: bool) -> None:
      """Initializes the callback.
  
      Args:
          epochs: Total number of epochs.
          silent: If 'True' the entire progressbar wrapper is disabled.
      """
      super().__init__()
  
      disable = silent or rasa.shared.utils.io.is_logging_disabled()
      self.progress_bar = tqdm(
          range(epochs), desc="Epochs", disable=disable
      )
  
file_path: rasa/rasa/utils/tensorflow/callback.py
imports: from pathlib import Path
  from typing import Dict, Text, Any, Optional
  import logging
  import tensorflow
  from tqdm import tqdm
  import rasa.shared.utils.io
label_desc: Use image node_id 1 to create a new RasaTrainingLogger object from inherited base classes: tf.keras.callbacks with example: obj = RasaTrainingLogger(epochs, silent)