code: def from_argparse_args(
      cls, args: Union[Namespace, ArgumentParser], **kwargs
  ):
      """Modified version of :func:`pytorch_lightning.utilities.argparse.from_argparse_args` which populates
      ``valid_kwargs`` from :class:`pytorch_lightning.Trainer`."""
      if isinstance(args, ArgumentParser):
          args = cls.parse_argparser(args)
  
      params = vars(args)
  
      # we only want to pass in valid PLTrainer args, the rest may be user specific
      valid_kwargs = inspect.signature(PlTrainer.__init__).parameters
      trainer_kwargs = {
          name: params[name] for name in valid_kwargs if name in params
      }
      trainer_kwargs.update(**kwargs)
  
      return cls(**trainer_kwargs)
  
imports: import inspect
  import warnings
  from argparse import ArgumentParser, Namespace
  from functools import wraps
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  from pytorch_lightning import LightningDataModule, LightningModule
  from pytorch_lightning import Trainer
  from pytorch_lightning.accelerators.tpu import TPUAccelerator
  from pytorch_lightning.callbacks import BaseFinetuning
  from pytorch_lightning.utilities.argparse import add_argparse_args, get_init_arguments_and_types, parse_env_variables
  from torch.utils.data import DataLoader
  import flash
  from flash.core.data.io.output import Output
  from flash.core.data.io.output_transform import OutputTransform
  from flash.core.data.io.transform_predictions import TransformPredictions
  from flash.core.model import Task
  from flash.core.registry import FlashRegistry
label_desc: Use image node_id 1 for calling a global function with example usage: from_argparse_args(cls, args) and returns: cls