code: def downsample_basic_block(x, planes, stride, no_cuda=False):
      out = F.avg_pool3d(x, kernel_size=1, stride=stride)
      zero_pads = torch.Tensor(
          out.size(0),
          planes - out.size(1),
          out.size(2),
          out.size(3),
          out.size(4),
      ).zero_()
      if not no_cuda:
          if isinstance(out.data, torch.cuda.FloatTensor):
              zero_pads = zero_pads.cuda()
  
      out = Variable(torch.cat([out.data, zero_pads], dim=1))
  
      return out
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from torch.autograd import Variable
  import math
  from functools import partial
label_desc: Use image node_id 2 for calling a global function with example usage: downsample_basic_block(x, planes, stride, no_cuda) and returns: out