class_docstr: MemoryProfiler, which is implemented based on memory profiler and Accumulator
class_docstr_tok: ["MemoryProfiler",",","which","is","implemented","based","on","memory","profiler","and","Accumulator"]
docstr: Return the collected memory profiles
docstr_tok: ["Return","the","collected","memory","profiles"]
code: def stats(self) -> CodeMapDict:
      """Return the collected memory profiles"""
      return cast(CodeMapDict, self._accumulator.value)
  
imports: from typing import Any, Callable, Dict, List, Optional, Tuple, Type, TYPE_CHECKING, Union, cast
  import cProfile
  import inspect
  import pstats
  import linecache
  import os
  import atexit
  import sys
  import warnings
  from pyspark.accumulators import AccumulatorParam
  from pyspark.errors import PySparkRuntimeError
label_desc: Use image node_id 3 for calling the MemoryProfiler obj's underlying member method code with example usage: obj.stats() and returns: cast