class_docstr: If you wish to write a custom profiler, you should inherit from this class.
docstr: Logs a profile report after the conclusion of run.
docstr_tok: ["Logs","a","profile","report","after","the","conclusion","of","run","."]
code: def describe(self) -> None:
      """Logs a profile report after the conclusion of run."""
      # users might call `describe` directly as the profilers can be used by themselves.
      # to allow this, we open and close the files within this function by calling `_prepare_streams` and `teardown`
      # manually instead of letting the `Trainer` do it through `setup` and `teardown`
      self._prepare_streams()
      summary = self.summary()
      if summary and self._write_stream is not None:
          self._write_stream(summary)
      if self._output_file is not None:
          self._output_file.flush()
      self.teardown(stage=self._stage)
  
imports: import logging
  import os
  from abc import ABC, abstractmethod
  from contextlib import contextmanager
  from pathlib import Path
  from typing import Any, Callable, Dict, Generator, Optional, TextIO, Union
  from lightning.fabric.utilities.cloud_io import get_filesystem
label_desc: Use image node_id 9 for calling the Profiler obj's underlying member method code with example usage: obj.describe() without return types