class_docstr: Represents a collection of queued / pending MLflow Run operations.
class_docstr_tok: ["Represents","a","collection","of","queued","\/","pending","MLflow","Run","operations","."]
code: def __init__(self, run_id):
      self.run_id = run_id
      self.create_run = None
      self.set_terminated = None
      self.params_queue = []
      self.tags_queue = []
      self.metrics_queue = []
      self.datasets_queue = []
  
imports: import logging
  import os
  from collections import namedtuple
  from concurrent.futures import ThreadPoolExecutor
  from itertools import zip_longest
  from typing import Any, Dict, List, Optional, Union
  from mlflow.entities import Metric, Param, RunTag
  from mlflow.entities.dataset_input import DatasetInput
  from mlflow.exceptions import MlflowException
  from mlflow.tracking.client import MlflowClient
  from mlflow.utils import _truncate_dict, chunk_list
  from mlflow.utils.time import get_current_time_millis
  from mlflow.utils.validation import MAX_DATASETS_PER_BATCH, MAX_ENTITIES_PER_BATCH, MAX_ENTITY_KEY_LENGTH, MAX_METRICS_PER_BATCH, MAX_PARAM_VAL_LENGTH, MAX_PARAMS_TAGS_PER_BATCH, MAX_TAG_VAL_LENGTH
label_desc: Use image node_id 1 to create a new _PendingRunOperations object  with example: obj = _PendingRunOperations(run_id)