class_docstr: Experimental: Ray distributed tqdm implementation.
  
  This class lets you use tqdm from any Ray remote task or actor, and have the
  progress centrally reported from the driver. This avoids issues with overlapping
  / conflicting progress bars, as the driver centrally manages tqdm positions.
  
  Supports a limited subset of tqdm args.
class_docstr_tok: ["Experimental",":","Ray","distributed","tqdm","implementation",".","This","class","lets","you","use","tqdm","from","any","Ray","remote","task","or","actor",",","and","have","the","progress","centrally","reported","from","the","driver",".","This","avoids","issues","with","overlapping","\/","conflicting","progress","bars",",","as","the","driver","centrally","manages","tqdm","positions",".","Supports","a","limited","subset","of","tqdm","args","."]
code: def __init__(
      self,
      iterable: Optional[Iterable] = None,
      desc: Optional[str] = None,
      total: Optional[int] = None,
      position: Optional[int] = None,
      flush_interval_s: Optional[float] = None,
  ):
      import ray._private.services as services
  
      if total is None and iterable is not None:
          try:
              total = len(iterable)
          except (TypeError, AttributeError):
              total = None
  
      self._iterable = iterable
      self._desc = desc or ""
      self._total = total
      self._ip = services.get_node_ip_address()
      self._pid = os.getpid()
      self._pos = position or 0
      self._uuid = uuid.uuid4().hex
      self._x = 0
      self._closed = False
      self._flush_interval_s = (
          flush_interval_s
          if flush_interval_s is not None
          else self.DEFAULT_FLUSH_INTERVAL_SECONDS
      )
      self._last_flush_time = 0.0
  
imports: import builtins
  import copy
  import json
  import logging
  import os
  import sys
  import threading
  import time
  import uuid
  from typing import Any, Dict, Iterable, Optional
  import colorama
  import ray
  from ray._private.ray_constants import env_bool
  from ray.util.debug import log_once
label_desc: Use image node_id 1 to create a new tqdm object  with example: obj = tqdm(iterable, desc, total, position, flush_interval_s)