code: def extract(a, t, x_shape):
      """extract the appropriate t index for a batch of indices."""
      batch_size = t.shape[0]
      out = a.gather(-1, t)
      return out.reshape(batch_size, *((1,) * (len(x_shape) - 1)))
  
imports: import copy
  import math
  import random
  import warnings
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import build_activation_layer
  from mmcv.ops import batched_nms
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS, TASK_UTILS
  from mmdet.structures import SampleList
  from mmdet.structures.bbox import bbox2roi, bbox_cxcywh_to_xyxy, bbox_xyxy_to_cxcywh, get_box_wh, scale_boxes
  from mmdet.utils import InstanceList
label_desc: Use image node_id 2 for calling a global function with example usage: extract(a, t, x_shape) and returns: out