docstr: Log new images for given name on given step.
  
  Args:
      name (str): name of the variable (it will be converted to a valid
          tensorflow summary name).
      images (list): list of images to visualize
      step (int): non-negative integer used for visualization
docstr_tok: ["Log","new","images","for","given","name","on","given","step",".","Args",":","name","(","str",")",":","name","of","the","variable","(","it","will","be","converted","to","a","valid","tensorflow","summary","name",")",".","images","(","list",")",":","list","of","images","to","visualize","step","(","int",")",":","non-negative","integer","used","for","visualization"]
code: def log_images(self, name, images, step=None):
      """Log new images for given name on given step.
  
      Args:
          name (str): name of the variable (it will be converted to a valid
              tensorflow summary name).
          images (list): list of images to visualize
          step (int): non-negative integer used for visualization
      """
      if isinstance(images, six.string_types):
          raise TypeError(
              '"images" should be a list of ndarrays, got {}'.format(
                  type(images)
              )
          )
  
      self._check_step(step)
      tf_name = self._ensure_tf_name(name)
  
      summary = self._image_summary(tf_name, images, step=step)
      self._log_summary(tf_name, summary, images, 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 6 for calling the Logger obj's underlying member method code with example usage: obj.log_images(name, images, step) without return types