code: def _filter_input(
      x: Dict[str, Tensor], featmap_names: List[str]
  ) -> List[Tensor]:
      x_filtered = []
      for k, v in x.items():
          if k in featmap_names:
              x_filtered.append(v)
      return x_filtered
  
imports: from typing import Dict, List, Optional, Tuple, Union
  import torch
  import torch.fx
  import torchvision
  from torch import nn, Tensor
  from torchvision.ops.boxes import box_area
  from ..utils import _log_api_usage_once
  from .roi_align import roi_align
label_desc: Use image node_id 6 for calling a global function with example usage: _filter_input(x, featmap_names) and returns: x_filtered