code: def compute_ConvTranspose2d_madd(module, inp, out):
      assert isinstance(module, nn.ConvTranspose2d)
      assert len(inp.size()) == 4 and len(inp.size()) == len(out.size())
  
      in_c, in_h, in_w = inp.size()[1:]
      k_h, k_w = module.kernel_size
      out_c, out_h, out_w = out.size()[1:]
      groups = module.groups
  
      kernel_mul = k_h * k_w * (in_c // groups)
      kernel_add = kernel_mul - 1 + (0 if module.bias is None else 1)
  
      kernel_mul_group = kernel_mul * in_h * in_w * (out_c // groups)
      kernel_add_group = kernel_add * in_h * in_w * (out_c // groups)
  
      total_mul = kernel_mul_group * groups
      total_add = kernel_add_group * groups
  
      return total_mul + total_add
  
file_path: tensorwatch/tensorwatch/model_graph/torchstat/compute_madd.py
imports: import torch.nn
label_desc: Use image node_id 2 for calling a global function with example usage: compute_ConvTranspose2d_madd(module, inp, out) and returns: unknown