docstr: A method that records the start event for a metric.
  Args:
      type (str): group id for metric
      key (str): unique id for metric within a group
      name (str): description of the metric
      cuda (bool): indicator to determine if this is a CUDA metric
docstr_tok: ["A","method","that","records","the","start","event","for","a","metric",".","Args",":","type","(","str",")",":","group","id","for","metric","key","(","str",")",":","unique","id","for","metric","within","a","group","name","(","str",")",":","description","of","the","metric","cuda","(","bool",")",":","indicator","to","determine","if","this","is","a","CUDA","metric"]
code: def record_start(self, type, key, name, cuda=True):
      r"""
      A method that records the start event for a metric.
      Args:
          type (str): group id for metric
          key (str): unique id for metric within a group
          name (str): description of the metric
          cuda (bool): indicator to determine if this is a CUDA metric
      """
      self.__metrics_logger.record_start(type, key, name, cuda)
  
imports: import functools
  import time
  from abc import ABC, abstractmethod
  import torch
  from metrics.MetricsLogger import MetricsLogger
label_desc: Use image node_id 3 for calling the TrainerBase obj's underlying member method code with example usage: obj.record_start(type, key, name, cuda) without return types