class_docstr: Used to incrementally build up a TensorFlow run.
  
  This is particularly useful for batching ops from multiple different
  policies in the multi-agent setting.
class_docstr_tok: ["Used","to","incrementally","build","up","a","TensorFlow","run",".","This","is","particularly","useful","for","batching","ops","from","multiple","different","policies","in","the","multi-agent","setting","."]
code: def __init__(self, session, debug_name):
      self.session = session
      self.debug_name = debug_name
      self.feed_dict = {}
      self.fetches = []
      self._executed = None
  
file_path: ray/python/ray/rllib/utils/tf_run_builder.py
imports: import logging
  import os
  import time
  from ray.util.debug import log_once
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 1 to create a new _TFRunBuilder object  with example: obj = _TFRunBuilder(session, debug_name)