code: def compute_BatchNorm2d_madd(module, inp, out):
      assert isinstance(module, nn.BatchNorm2d)
      assert len(inp.size()) == 4 and len(inp.size()) == len(out.size())
  
      in_c, in_h, in_w = inp.size()[1:]
  
      # 1. sub mean
      # 2. div standard deviation
      # 3. mul alpha
      # 4. add beta
      return 4 * in_c * in_h * in_w
  
file_path: tensorwatch/tensorwatch/model_graph/torchstat/compute_madd.py
imports: import torch.nn
label_desc: Use image node_id 3 for calling a global function with example usage: compute_BatchNorm2d_madd(module, inp, out) and returns: unknown