(minor, ui) argparse stuff - add `add_argparse_args(*, inplace)` option for multiple subparsers?
🐛 Bug

To Reproduce
See script and setup / version stuff.
import argparse

import pytorch_lightning as pl

def main():
    parser = argparse.ArgumentParser()
    parser_main = parser.add_argument_group("main")
    parser_main.add_argument("--my_custom_arg_plz", type=str)
    parser_pl = pl.Trainer.add_argparse_args(
        parser.add_argument_group("pl.Trainer"),
    )
    # Doesn't have pl args.
    print("[ parser ]\n")
    parser.print_help()
    # Has pl.Trainer args, but, uh, didn't actually print any sections :(
    print("\n\n[ parser_pl ]\n")
    parser_pl.print_help()


assert __name__ == "__main__"
main()

"""
Setup: CPython 3.6.9, Ubuntu 18.04

    cd $(mktemp -d)
    python3 -m venv .
    ./bin/pip install -U pip wheel
    ./bin/pip install pytorch-lightning==1.2.0 torch==1.7.1

Output (abbreviated):

    $ ./bin/python ./example.py
    [ parser ]

    usage: example.py [-h] [--my_custom_arg_plz MY_CUSTOM_ARG_PLZ]

    optional arguments:
      -h, --help            show this help message and exit

    main:
      --my_custom_arg_plz MY_CUSTOM_ARG_PLZ

    [ parser_pl ]
    usage: example.py [-h] [--my_custom_arg_plz MY_CUSTOM_ARG_PLZ]
                      [--logger [LOGGER]]
                      [--checkpoint_callback [CHECKPOINT_CALLBACK]]
                      <... soooo many things...>

    optional arguments:
      -h, --help            show this help message and exit
      --my_custom_arg_plz MY_CUSTOM_ARG_PLZ
      --logger [LOGGER]     Logger (or iterable collection of loggers) for
                            experiment tracking.
      --checkpoint_callback [CHECKPOINT_CALLBACK]
      <... soooo many things...>
"""
Expected behavior
Output would ideally look like this:
usage: example.py [-h] [--my_custom_arg_plz MY_CUSTOM_ARG_PLZ]
                  [--logger [LOGGER]]
                  [--checkpoint_callback [CHECKPOINT_CALLBACK]]
                  <... soooo many things...>

optional arguments:
  -h, --help            show this help message and exit

main:
      --my_custom_arg_plz MY_CUSTOM_ARG_PLZ

pl.Trainer:
  --logger [LOGGER]     Logger (or iterable collection of loggers) for
                        experiment tracking.
  --checkpoint_callback [CHECKPOINT_CALLBACK]
  <... soooo many things...>

Environment
You can get the script and run it with:
wget https://raw.githubusercontent.com/PyTorchLightning/pytorch-lightning/master/tests/collect_env_details.py
# For security purposes, please check the contents of collect_env_details.py before running it.
python collect_env_details.py


PyTorch Version (e.g., 1.0): 1.7.1
OS (e.g., Linux): Linux, Ubuntu 18.04
How you installed PyTorch (conda, pip, source): pip
Build command you used (if compiling from source): N/A
Python version: CPython 3.6.9
CUDA/cuDNN version: Doesn't matter.
GPU models and configuration: Doesn't matter.
Any other relevant information: See repro script.

Additional context
I maybe should've done more testing in #5911 😅