code: def process(model, data, device):
      with torch.no_grad():
          model.set_input(data, device)
          model.forward()
  
imports: import os
  import torch
  import hydra
  import logging
  import numpy
  from omegaconf import OmegaConf
  import pickle
  from torch_points3d.datasets.dataset_factory import instantiate_dataset
  from torch_points3d.models.model_factory import instantiate_model
  from torch_points3d.models.base_model import BaseModel
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.metrics.base_tracker import BaseTracker
  from torch_points3d.metrics.colored_tqdm import Coloredtqdm
  from torch_points3d.metrics.model_checkpoint import ModelCheckpoint
  from torch_points3d.utils.colors import COLORS
  from torch_points3d.utils.config import determine_stage
  from torch_points3d.visualization import Visualizer
  from torch_points3d.utils.config import set_debugging_vars_to_global
  from torch_points3d.utils.debugging_vars import extract_histogram
label_desc: Use image node_id 1 for calling a global function with example usage: process(model, data, device) without return types