code: def backward_and_step(self):
      self.loss.backward()
      self.batch_count += 1
      # accumulate self.grad_accum times then synchronize and update
      if self.batch_count == self.grad_accum:
          self.step()
          self.batch_count = 0
  
imports: import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 7 for calling the SimpleLossCompute obj's underlying member method code with example usage: obj.backward_and_step() without return types