docstr: Log new value for given name on given step.
  
  Args:
      name (str): name of the variable (it will be converted to a valid
          tensorflow summary name).
      value (float): this is a real number to be logged as a scalar.
      step (int): non-negative integer used for visualization: you can
          log several different variables on one step, but should not log
          different values of the same variable on the same step (this is
          not checked).
docstr_tok: ["Log","new","value","for","given","name","on","given","step",".","Args",":","name","(","str",")",":","name","of","the","variable","(","it","will","be","converted","to","a","valid","tensorflow","summary","name",")",".","value","(","float",")",":","this","is","a","real","number","to","be","logged","as","a","scalar",".","step","(","int",")",":","non-negative","integer","used","for","visualization",":","you","can","log","several","different","variables","on","one","step",",","but","should","not","log","different","values","of","the","same","variable","on","the","same","step","(","this","is","not","checked",")","."]
code: def log_value(self, name, value, step=None):
      """Log new value for given name on given step.
  
      Args:
          name (str): name of the variable (it will be converted to a valid
              tensorflow summary name).
          value (float): this is a real number to be logged as a scalar.
          step (int): non-negative integer used for visualization: you can
              log several different variables on one step, but should not log
              different values of the same variable on the same step (this is
              not checked).
      """
      if isinstance(value, six.string_types):
          raise TypeError(
              '"value" should be a number, got {}'.format(type(value))
          )
      value = float(value)
  
      self._check_step(step)
      tf_name = self._ensure_tf_name(name)
  
      summary = self._scalar_summary(tf_name, value, step)
      self._log_summary(tf_name, summary, value, step=step)
  
imports: from collections import defaultdict
  import os
  import re
  import socket
  import struct
  import time
  import numpy
  import six
  import scipy.misc
  from .crc32c import crc32c
label_desc: Use image node_id 4 for calling the Logger obj's underlying member method code with example usage: obj.log_value(name, value, step) without return types