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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_logging_metric_hook(benchmark_log_dir=None, tensors_to_log=None, every_n_secs=600, **kwargs):
 # pylint: disable=unused-argument """Function to get LoggingMetricHook. Args: benchmark_log_dir: `string`, directory path to save the metric log. tensors_to_log: List of tensor names or dictionary mapping labels to tensor names. If not set, log _TENSORS_TO_LOG by default. every_n_secs: `int`, the frequency for logging the metric. Default to every 10 mins. Returns: Returns a ProfilerHook that writes out timelines that can be loaded into profiling tools like chrome://tracing. """

  if benchmark_log_dir is None:
    raise ValueError("metric_log_dir should be provided to use metric logger")
  if tensors_to_log is None:
    tensors_to_log = _TENSORS_TO_LOG
  return metric_hook.LoggingMetricHook(
      tensors=tensors_to_log,
      log_dir=benchmark_log_dir,
      every_n_secs=every_n_secs)