class_docstr: Logs train_steps_per_second.
class_docstr_tok: ["Logs","train_steps_per_second","."]
code: def _log_steps_per_sec(self) -> None:
      steps_per_sec = self._step_timer.steps_per_second()
      self._step_timer.restart()
      step = self._train_step.numpy()
      if self._log_to_terminal:
          logging.info("Step: %d, %.3f steps/sec", step, steps_per_sec)
      with tf.compat.v2.summary.record_if(True):
          with tf.name_scope("RunTime/"):
              tf.summary.scalar(
                  name="train_steps_per_sec",
                  data=steps_per_sec,
                  step=step,
              )
  
imports: import os
  from typing import Mapping, Optional, Sequence, Text, Tuple, Union
  from absl import logging
  import tensorflow.compat.v2
  from tf_agents.agents import tf_agent
  from tf_agents.metrics import py_metric
  from tf_agents.policies import async_policy_saver
  from tf_agents.policies import greedy_policy
  from tf_agents.policies import policy_saver
  from tf_agents.policies import tf_policy
  from tf_agents.train import interval_trigger
  from tf_agents.train import learner
  from tf_agents.train import step_per_second_tracker
  from tf_agents.typing import types
label_desc: Use image node_id 2 for calling the StepPerSecondLogTrigger obj's underlying member method code with example usage: obj._log_steps_per_sec() without return types