code: def generate_run(self, logdir, run_name):
      tf.compat.v1.reset_default_graph()
      sess = tf.compat.v1.Session()
      placeholder = tf.compat.v1.placeholder(tf.float32, shape=[3])
  
      if run_name == self._RUN_WITH_LEGACY_DISTRIBUTION:
          tf.compat.v1.summary.histogram(
              self._LEGACY_DISTRIBUTION_TAG, placeholder
          )
      elif run_name == self._RUN_WITH_DISTRIBUTION:
          summary.op(
              self._DISTRIBUTION_TAG,
              placeholder,
              display_name=self._DISPLAY_NAME,
              description=self._DESCRIPTION,
          )
      elif run_name == self._RUN_WITH_SCALARS:
          tf.compat.v1.summary.scalar(
              self._SCALAR_TAG, tf.reduce_mean(input_tensor=placeholder)
          )
      else:
          assert False, "Invalid run name: %r" % run_name
      summ = tf.compat.v1.summary.merge_all()
  
      subdir = os.path.join(logdir, run_name)
      with test_util.FileWriterCache.get(subdir) as writer:
          writer.add_graph(sess.graph)
          for step in range(self._STEPS):
              feed_dict = {placeholder: [1 + step, 2 + step, 3 + step]}
              s = sess.run(summ, feed_dict=feed_dict)
              writer.add_summary(s, global_step=step)
  
imports: import collections.abc
  import os.path
  import tensorflow
  from tensorboard import errors
  from tensorboard import context
  from tensorboard.backend.event_processing import data_provider
  from tensorboard.backend.event_processing import plugin_event_multiplexer
  from tensorboard.backend.event_processing import tag_types
  from tensorboard.plugins import base_plugin
  from tensorboard.plugins.distribution import compressor
  from tensorboard.plugins.distribution import distributions_plugin
  from tensorboard.plugins.histogram import summary
  from tensorboard.util import test_util
label_desc: Use image node_id 3 for calling the DistributionsPluginTest obj's underlying member method code with example usage: obj.generate_run(logdir, run_name) without return types