code: def cat(tensors: List[torch.Tensor], dim: int = 0):
      """
      Efficient version of torch.cat that avoids a copy if there is only a single element in a list
      """
      assert isinstance(tensors, (list, tuple))
      if len(tensors) == 1:
          return tensors[0]
      return torch.cat(tensors, dim)
  
imports: import logging
  import math
  from typing import List, Dict
  import torch
  from torch import nn
  from torch.nn import functional
  from ...nn.shape_spec import ShapeSpec
  from ...nn.deform_conv import DeformConvWithChangeableStride
  from ...nn.group_norm import NaiveGroupNorm
  from ...data.structures import Instances, Boxes
  from ...nn.focal_loss import sigmoid_focal_loss_jit
  from ...nn.nms import ml_nms
  from ...utils.loss import IOULoss
  from ...utils.comm import get_world_size, reduce_sum, compute_locations
label_desc: Use image node_id 1 for calling a global function with example usage: cat(tensors, dim) and returns: torch, tensors