class_docstr: The base interface Estimator / Transformer / Model / Evaluator needs to inherit
  for supporting saving and loading.
class_docstr_tok: ["The","base","interface","Estimator","\/","Transformer","\/","Model","\/","Evaluator","needs","to","inherit","for","supporting","saving","and","loading","."]
docstr: Load Estimator / Transformer / Model / Evaluator from provided cloud storage path.
  
  .. versionadded:: 3.5.0
docstr_tok: ["Load","Estimator","\/","Transformer","\/","Model","\/","Evaluator","from","provided","cloud","storage","path",".","..","versionadded",":",":","3.5.0"]
code: def load(cls, path: str) -> "Params":
      """
      Load Estimator / Transformer / Model / Evaluator from provided cloud storage path.
  
      .. versionadded:: 3.5.0
      """
      session = SparkSession.active()
  
      tmp_local_dir = tempfile.mkdtemp(prefix="pyspark_ml_model_")
      try:
          file_data_df = session.read.format("binaryFile").load(path)
  
          for row in file_data_df.toLocalIterator():
              file_name = os.path.basename(urlparse(row.path).path)
              file_content = bytes(row.content)
              with open(
                  os.path.join(tmp_local_dir, file_name), "wb"
              ) as f:
                  f.write(file_content)
  
          return cls._load_from_local(tmp_local_dir)
      finally:
          shutil.rmtree(tmp_local_dir, ignore_errors=True)
  
imports: import json
  import shutil
  import os
  import tempfile
  import time
  from urllib.parse import urlparse
  from typing import Any, Dict, List
  from pyspark.ml.base import Params
  from pyspark.sql import SparkSession
  from pyspark.sql.utils import is_remote
  from pyspark import __version__
label_desc: Use image node_id 13 for calling the ParamsReadWrite obj's underlying member method code with example usage: obj.load(cls, path) and returns: cls