class_docstr: Metrics logger
docstr: Log metrics. Each metric's log will be stored in the corresponding list.
  
  Args:
      metric (str): Metric name.
      value (float): Value.
docstr_tok: ["Log","metrics",".","Each","metric","'s","log","will","be","stored","in","the","corresponding","list",".","Args",":","metric","(","str",")",":","Metric","name",".","value","(","float",")",":","Value","."]
code: def log(self, metric, value):
      """Log metrics. Each metric's log will be stored in the corresponding list.
  
      Args:
          metric (str): Metric name.
          value (float): Value.
      """
      if metric not in self._log:
          self._log[metric] = []
      self._log[metric].append(value)
  
imports: import itertools
  import numpy
  import tensorflow
  from tensorflow_estimator.python.estimator.export.export import build_supervised_input_receiver_fn_from_input_fn
label_desc: Use image node_id 2 for calling the MetricsLogger obj's underlying member method code with example usage: obj.log(metric, value) without return types