NotImplementedError: の解決法

#最大学習回数
MAX_EPOCH=4

for epoch in range(MAX_EPOCH):
    total_loss=0.0
    for i,data in enumerate(train_data_loader):

      #dataから学習対象データと教師データを取り出す
      train_data,teacher_labels=data

      #入力をtorch.autograd.Variableに変換
      train_data,teacher_labels=Variable(train_data),Variable(teacher_labels)

      #計算された勾配情報を削除
      optimizer.zero_grad()

      #モデルに学習データを与えて予測を計算
      outputs=model(train_data)

      #lossとwによる微分計算
      loss=lossResult(outputs,teacher_labels)
      loss.backward()

      #勾配を更新
      optimizer.step()

      #誤差を累計
      total_loss +=loss.data[0]

      #2000ミニバッチずつ、進捗を表示
      if i % 2000==1999:
        print('学習進捗:[%d,%d] 学習誤差(loss):%.3f'%(epoch+1,i+1,total_loss/2000))
        total_loss=0.0
print('学習終了')
---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
<ipython-input-18-564ed7a502ce> in <module>()
     16 
     17       #モデルに学習データを与えて予測を計算
---> 18       outputs=model(train_data)
     19 
     20       #lossとwによる微分計算

1 frames
/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _call_impl(self, *input, **kwargs)
   1049         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1050                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1051             return forward_call(*input, **kwargs)
   1052         # Do not call functions when jit is used
   1053         full_backward_hooks, non_full_backward_hooks = [], []

/usr/local/lib/python3.7/dist-packages/torch/nn/modules/module.py in _forward_unimplemented(self, *input)
    199         registered hooks while the latter silently ignores them.
    200     """
--> 201     raise NotImplementedError
    202 
    203 

NotImplementedError: