class_docstr: Represent and manage a single run of an experiment.
class_docstr_tok: ["Represent","and","manage","a","single","run","of","an","experiment","."]
docstr: Add a new measurement.
  
  The measurement will be processed by the MongoDB observer
  during a heartbeat event.
  Other observers are not yet supported.
  
  :param metric_name: The name of the metric, e.g. training.loss
  :param value: The measured value
  :param step: The step number (integer), e.g. the iteration number
              If not specified, an internal counter for each metric
              is used, incremented by one.
docstr_tok: ["Add","a","new","measurement",".","The","measurement","will","be","processed","by","the","MongoDB","observer","during","a","heartbeat","event",".","Other","observers","are","not","yet","supported",".",":","param","metric_name",":","The","name","of","the","metric",",","e.g",".","training.loss",":","param","value",":","The","measured","value",":","param","step",":","The","step","number","(","integer",")",",","e.g",".","the","iteration","number","If","not","specified",",","an","internal","counter","for","each","metric","is","used",",","incremented","by","one","."]
code: def log_scalar(self, metric_name, value, step=None):
      """
      Add a new measurement.
  
      The measurement will be processed by the MongoDB observer
      during a heartbeat event.
      Other observers are not yet supported.
  
      :param metric_name: The name of the metric, e.g. training.loss
      :param value: The measured value
      :param step: The step number (integer), e.g. the iteration number
                  If not specified, an internal counter for each metric
                  is used, incremented by one.
      """
      # Method added in change https://github.com/chovanecm/sacred/issues/4
      # The same as Experiment.log_scalar (if something changes,
      # update the docstring too!)
  
      self._metrics.log_scalar_metric(metric_name, value, step)
  
imports: import datetime
  import os.path
  import sys
  import traceback
  from sacred import metrics_logger, SETTINGS
  from sacred.metrics_logger import linearize_metrics
  from sacred.randomness import set_global_seed
  from sacred.utils import SacredInterrupt, join_paths, IntervalTimer
  from sacred.stdout_capturing import get_stdcapturer
label_desc: Use image node_id 25 for calling the Run obj's underlying member method code with example usage: obj.log_scalar(metric_name, value, step) without return types