Hide default pl flags with -h?
Is there a way to hide the pl flags? As it become super unreadable when using -h (pl has a lot of unused flags)
e.g. given this snippet :
if __name__ == '__main__':
    parser = ArgumentParser(add_help=False)
    parser = Trainer.add_argparse_args(parser)

    # figure out which model to use
    parser.add_argument('--model_name', type=str, default='gan', help='gan or mnist')
    temp_args = parser.parse_known_args()[0]

    parser.add_argument('--something_important_and_unique', type=str, default='123', help='123 or 456')

    # let the model add what it wants
    if temp_args.model_name == 'gan':
        parser = GoodGAN.add_model_specific_args(parser)
    elif temp_args.model_name == 'mnist':
        parser = LitMNIST.add_model_specific_args(parser)

    args = parser.parse_args()

    # train
    main(args)

and running
 python train.py -h
This is the output:
(general)~\laplace_pool_final>python test_something.py -h
usage: test_something.py [-h] [--logger LOGGER]
                         [--checkpoint_callback CHECKPOINT_CALLBACK]
                         [--early_stop_callback EARLY_STOP_CALLBACK]
                         [--default_save_path DEFAULT_SAVE_PATH]
                         [--gradient_clip_val GRADIENT_CLIP_VAL]
                         [--process_position PROCESS_POSITION]
                         [--num_nodes NUM_NODES] [--gpus GPUS]
                         [--num_tpu_cores NUM_TPU_CORES]
                         [--log_gpu_memory LOG_GPU_MEMORY]
                         [--progress_bar_refresh_rate PROGRESS_BAR_REFRESH_RATE]
                         [--overfit_pct OVERFIT_PCT]
                         [--track_grad_norm TRACK_GRAD_NORM]
                         [--check_val_every_n_epoch CHECK_VAL_EVERY_N_EPOCH]
                         [--fast_dev_run FAST_DEV_RUN]
                         [--accumulate_grad_batches ACCUMULATE_GRAD_BATCHES]
                         [--max_epochs MAX_EPOCHS] [--min_epochs MIN_EPOCHS]
                         [--max_steps MAX_STEPS] [--min_steps MIN_STEPS]
                         [--train_percent_check TRAIN_PERCENT_CHECK]
                         [--val_percent_check VAL_PERCENT_CHECK]
                         [--test_percent_check TEST_PERCENT_CHECK]
                         [--val_check_interval VAL_CHECK_INTERVAL]
                         [--log_save_interval LOG_SAVE_INTERVAL]
                         [--row_log_interval ROW_LOG_INTERVAL]
                         [--distributed_backend DISTRIBUTED_BACKEND]
                         [--precision PRECISION]
                         [--print_nan_grads PRINT_NAN_GRADS]
                         [--weights_summary WEIGHTS_SUMMARY]
                         [--weights_save_path WEIGHTS_SAVE_PATH]
                         [--amp_level AMP_LEVEL]
                         [--num_sanity_val_steps NUM_SANITY_VAL_STEPS]
                         [--truncated_bptt_steps TRUNCATED_BPTT_STEPS]
                         [--resume_from_checkpoint RESUME_FROM_CHECKPOINT]
                         [--benchmark BENCHMARK]
                         [--reload_dataloaders_every_epoch RELOAD_DATALOADERS_EVERY_EPOCH]
                         [--model_name MODEL_NAME]
                         [--something_important_and_unique SOMETHING_IMPORTANT_AND_UNIQUE]
                         [--encoder_layers ENCODER_LAYERS]

optional arguments:
  -h, --help            show this help message and exit
  --logger LOGGER       autogenerated by pl.Trainer
  --checkpoint_callback CHECKPOINT_CALLBACK
                        autogenerated by pl.Trainer
  --early_stop_callback EARLY_STOP_CALLBACK
                        autogenerated by pl.Trainer
  --default_save_path DEFAULT_SAVE_PATH
                        autogenerated by pl.Trainer
  --gradient_clip_val GRADIENT_CLIP_VAL
                        autogenerated by pl.Trainer
  --process_position PROCESS_POSITION
                        autogenerated by pl.Trainer
  --num_nodes NUM_NODES
                        autogenerated by pl.Trainer
  --gpus GPUS           autogenerated by pl.Trainer
  --num_tpu_cores NUM_TPU_CORES
                        autogenerated by pl.Trainer
  --log_gpu_memory LOG_GPU_MEMORY
                        autogenerated by pl.Trainer
  --progress_bar_refresh_rate PROGRESS_BAR_REFRESH_RATE
                        autogenerated by pl.Trainer
  --overfit_pct OVERFIT_PCT
                        autogenerated by pl.Trainer
  --track_grad_norm TRACK_GRAD_NORM
                        autogenerated by pl.Trainer
  --check_val_every_n_epoch CHECK_VAL_EVERY_N_EPOCH
                        autogenerated by pl.Trainer
  --fast_dev_run FAST_DEV_RUN
                        autogenerated by pl.Trainer
  --accumulate_grad_batches ACCUMULATE_GRAD_BATCHES
                        autogenerated by pl.Trainer
  --max_epochs MAX_EPOCHS
                        autogenerated by pl.Trainer
  --min_epochs MIN_EPOCHS
                        autogenerated by pl.Trainer
  --max_steps MAX_STEPS
                        autogenerated by pl.Trainer
  --min_steps MIN_STEPS
                        autogenerated by pl.Trainer
  --train_percent_check TRAIN_PERCENT_CHECK
                        autogenerated by pl.Trainer
  --val_percent_check VAL_PERCENT_CHECK
                        autogenerated by pl.Trainer
  --test_percent_check TEST_PERCENT_CHECK
                        autogenerated by pl.Trainer
  --val_check_interval VAL_CHECK_INTERVAL
                        autogenerated by pl.Trainer
  --log_save_interval LOG_SAVE_INTERVAL
                        autogenerated by pl.Trainer
  --row_log_interval ROW_LOG_INTERVAL
                        autogenerated by pl.Trainer
  --distributed_backend DISTRIBUTED_BACKEND
                        autogenerated by pl.Trainer
  --precision PRECISION
                        autogenerated by pl.Trainer
  --print_nan_grads PRINT_NAN_GRADS
                        autogenerated by pl.Trainer
  --weights_summary WEIGHTS_SUMMARY
                        autogenerated by pl.Trainer
  --weights_save_path WEIGHTS_SAVE_PATH
                        autogenerated by pl.Trainer
  --amp_level AMP_LEVEL
                        autogenerated by pl.Trainer
  --num_sanity_val_steps NUM_SANITY_VAL_STEPS
                        autogenerated by pl.Trainer
  --truncated_bptt_steps TRUNCATED_BPTT_STEPS
                        autogenerated by pl.Trainer
  --resume_from_checkpoint RESUME_FROM_CHECKPOINT
                        autogenerated by pl.Trainer
  --benchmark BENCHMARK
                        autogenerated by pl.Trainer
  --reload_dataloaders_every_epoch RELOAD_DATALOADERS_EVERY_EPOCH
                        autogenerated by pl.Trainer
  --model_name MODEL_NAME
                        gan or mnist
  --something_important_and_unique SOMETHING_IMPORTANT_AND_UNIQUE
                        123 or 456
  --encoder_layers ENCODER_LAYERS

Where I would've preferred only to see the flags I've really created (model and something_important_and_unique )