code: def _patch_tensor_methods():
      torch.matmul = wrapFunc(torch.matmul, _matmul_flops_compute)
      torch.Tensor.matmul = wrapFunc(
          torch.Tensor.matmul, _matmul_flops_compute
      )
      torch.mm = wrapFunc(torch.mm, _matmul_flops_compute)
      torch.Tensor.mm = wrapFunc(torch.Tensor.mm, _matmul_flops_compute)
      torch.bmm = wrapFunc(torch.bmm, _matmul_flops_compute)
      torch.Tensor.bmm = wrapFunc(torch.bmm, _matmul_flops_compute)
  
      torch.addmm = wrapFunc(torch.addmm, _addmm_flops_compute)
      torch.Tensor.addmm = wrapFunc(
          torch.Tensor.addmm, _tensor_addmm_flops_compute
      )
  
      torch.mul = wrapFunc(torch.mul, _mul_flops_compute)
      torch.Tensor.mul = wrapFunc(torch.Tensor.mul, _mul_flops_compute)
  
      torch.add = wrapFunc(torch.add, _add_flops_compute)
      torch.Tensor.add = wrapFunc(torch.Tensor.add, _add_flops_compute)
  
      torch.einsum = wrapFunc(torch.einsum, _einsum_flops_compute)
  
imports: import time
  import torch
  import torch.nn
  import torch.nn.functional
  from functools import partial
  from typing import List, Optional
  from collections import OrderedDict
  import numpy
label_desc: Use image node_id 30 for calling a global function with example usage: _patch_tensor_methods() without return types