class_docstr: RunEnv saves the running environment of the train/dev/predict phase, including program, reader, metrics and so on.
code: def __init__(self):
      self.current_epoch = 0
      self.current_step = 0
      self.main_program = None
      self.start_program = None
      self.main_program_compiled = None
      self.py_reader = None
      self.generator = None
      self.loss = None
      self.labels = None
      self.metrics = None
      self.is_inititalized = False
      self.UNG = paddle.utils.unique_name.generate
  
file_path: PaddleHub/paddlehub/compat/task/task_utils.py
imports: import copy
  import time
  from typing import Any
  import paddle.utils.unique_name
label_desc: Use image node_id 1 to create a new RunEnv object from inherited base classes: object with example: obj = RunEnv()