code: def forward(self, x):
      x = self.kps_score_lowres(x)
      return torch.nn.functional.interpolate(
          x,
          scale_factor=float(self.up_scale),
          mode="bilinear",
          align_corners=False,
          recompute_scale_factor=False,
      )
  
imports: from typing import Any, Optional
  import torch
  from torch import nn
  from torchvision.ops import MultiScaleRoIAlign
  from ...ops import misc
  from ...transforms._presets import ObjectDetection
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _COCO_PERSON_CATEGORIES, _COCO_PERSON_KEYPOINT_NAMES
  from .._utils import _ovewrite_value_param, handle_legacy_interface
  from ..resnet import resnet50, ResNet50_Weights
  from ._utils import overwrite_eps
  from .backbone_utils import _resnet_fpn_extractor, _validate_trainable_layers
  from .faster_rcnn import FasterRCNN
label_desc: Use image node_id 2 for calling the KeypointRCNNPredictor obj's underlying member method code with example usage: obj.forward(x) and returns: torch