[PyTorch Geometric] Allow custom callbacks in graphgym.train

### 🚀 The feature, motivation and pitch The pytorch lightning implementation of torch_geometric.graphgym.train is pretty nice. The only problem now is that I cannot pass my own callbacks as trainer_config. Below is a simple suggested change. Would this be possible to implement? My suggested insertion ``` if 'callbacks' in trainer_config.keys(): callbacks.extend(trainer_config['callbacks']) trainer_config.pop('callbacks') ``` Current train function: ``` def train( model: GraphGymModule, datamodule: GraphGymDataModule, logger: bool = True, trainer_config: Optional[Dict[str, Any]] = None, ): callbacks = [] if logger: callbacks.append(LoggerCallback()) if cfg.train.enable_ckpt: ckpt_cbk = pl.callbacks.ModelCheckpoint(dirpath=get_ckpt_dir()) callbacks.append(ckpt_cbk) #insert suggestion here trainer_config = trainer_config or {} trainer = pl.Trainer( **trainer_config, enable_checkpointing=cfg.train