class_docstr: Log objects to ClearML.
  
  To log all the necessary details for a ParlAI experiment using MLOps. After logging,
  details can be viewed in ClearML Experiment Manager Web UI.
code: def __init__(self, opt: Opt):
      try:
          from clearml import Task, Logger
      except ImportError:
          raise ImportError("Please run `pip install clearml`.")
  
      # Set ClearML Project Name
      project_name = opt.get("clearml_project_name")
      # Set ClearML Task Name
      task_name = opt.get("clearml_task_name")
      # Instantiate CleaML Task
      if Task.current_task():
          self.clearml_task = Task.current_task()
      else:
          self.clearml_task = Task.init(
              project_name=project_name,
              task_name=task_name,
              auto_connect_arg_parser=False,
              auto_connect_frameworks={"tensorboard": False},
              output_uri=True,
          )
  
      # Report Hyperparameter Configurations
      self.clearml_task.connect(opt)
  
      # Initialize ClearML Logger
      self.clearml_logger = Logger.current_logger()
  
imports: import datetime
  import json
  import numbers
  import os
  import pathlib
  import re
  from typing import Optional
  import parlai.utils.logging
  from parlai.core.metrics import Metric, dict_report, get_metric_display_data
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.utils.io import PathManager
label_desc: Use image node_id 2 to create a new ClearMLLogger object from inherited base classes: object with example: obj = ClearMLLogger(opt)