Chainer问题中的自动编码器

Question

我试着用python训练Chainer的自动编码器，并编写了下面的代码。但不起作用。为什么？?

class Autoencoder(Chain):
    def __init__(self):
       super().__init__()
       with self.init_scope():
           self.l1 = L.Linear(3,2)
           self.l2 = L.Linear(2,3)
    def __call__(self,x):
       h1 = self.l1(x)
       h2 = self.l2(h1) 

       return h2

class Dataset(dataset.DatasetMixin):
    def __init__(self,number_of_data, show_initial = False):

       noise_level = 1

       self.data = np.zeros((number_of_data,3),dtype = np.float32)

       OA_vector = np.array([3,2,1])
       OB_vector = np.array([2,-1,1])

       t = np.random.uniform(-0.5,0.5,number_of_data)
       s = np.random.uniform(-0.5,0.5,number_of_data)

       for i in range(0,number_of_data):
           noise = np.random.uniform(-noise_level, noise_level,3)
           self.data[i] = t[i]*OA_vector + s[i]*OB_vector + noise

   def __len__(self):
        return self.data.shape[0]

   def get_example(self,idx):
       return self.data[idx]

if __name__ == "__main__":

    n_epoch = 5
    batch_size = 100

    number_of_data = 1000 #データ数
    train_data = Dataset(number_of_data,False)

    model = Autoencoder()

    optimizer = optimizers.SGD(lr=0.05).setup(model)
    train_iter = iterators.SerialIterator(train_data,batch_size)

    updater = training.StandardUpdater(train_iter,optimizer,device=0)
    trainer = training.Trainer(updater,(n_epoch,"epoch"),out="result")

    trainer.run()

我在用Chainer。数据集生成3个二维矢量。向量的数目是"number_of_data“。

我应该不用教练就这么做吗？我不明白问题出在哪里。

编辑

当我们使用device=0运行上面的代码时，会出现如下错误。

Exception in main training loop: Unsupported type <class 'NoneType'>
Traceback (most recent call last):
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/trainer.py", line 308, in run
    update()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 149, in update
    self.update_core()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 164, in update_core
    optimizer.update(loss_func, in_arrays)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/optimizer.py", line 655, in update
    loss.backward(loss_scale=self._loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 966, in backward
    self._backward_main(retain_grad, loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 1095, in _backward_main
    target_input_indexes, out_grad, in_grad)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 548, in backward_accumulate
    gxs = self.backward(target_input_indexes, grad_outputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 73, in backward
    return ReLUGrad2(y).apply((gy,))
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 258, in apply
    outputs = self.forward(in_data)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 368, in forward
    return self.forward_cpu(inputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 97, in forward_cpu
    y = (self.b > 0) * inputs[0]
  File "cupy/core/core.pyx", line 1310, in cupy.core.core.ndarray.__mul__
  File "cupy/core/elementwise.pxi", line 753, in cupy.core.core.ufunc.__call__
  File "cupy/core/elementwise.pxi", line 68, in cupy.core.core._preprocess_args
Will finalize trainer extensions and updater before reraising the exception.
Traceback (most recent call last):
  File "AC.py", line 70, in <module>
    trainer.run()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/trainer.py", line 322, in run
    six.reraise(*sys.exc_info())
  File "/home/****/.local/lib/python3.5/site-packages/six.py", line 693, in reraise
    raise value
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/trainer.py", line 308, in run
    update()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 149, in update
    self.update_core()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 164, in update_core
    optimizer.update(loss_func, in_arrays)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/optimizer.py", line 655, in update
    loss.backward(loss_scale=self._loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 966, in backward
    self._backward_main(retain_grad, loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 1095, in _backward_main
    target_input_indexes, out_grad, in_grad)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 548, in backward_accumulate
    gxs = self.backward(target_input_indexes, grad_outputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 73, in backward
    return ReLUGrad2(y).apply((gy,))
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 258, in apply
    outputs = self.forward(in_data)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 368, in forward
    return self.forward_cpu(inputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 97, in forward_cpu
    y = (self.b > 0) * inputs[0]
  File "cupy/core/core.pyx", line 1310, in cupy.core.core.ndarray.__mul__
  File "cupy/core/elementwise.pxi", line 753, in cupy.core.core.ufunc.__call__
  File "cupy/core/elementwise.pxi", line 68, in cupy.core.core._preprocess_args
TypeError: Unsupported type <class 'NoneType'>

当我们使用设备=-1运行上面的代码时，会出现如下所示的错误。

Exception in main training loop: unsupported operand type(s) for *: 'bool' and 'NoneType'
Traceback (most recent call last):
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/trainer.py", line 308, in run
    update()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 149, in update
    self.update_core()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 164, in update_core
    optimizer.update(loss_func, in_arrays)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/optimizer.py", line 655, in update
    loss.backward(loss_scale=self._loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 966, in backward
    self._backward_main(retain_grad, loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 1095, in _backward_main
    target_input_indexes, out_grad, in_grad)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 548, in backward_accumulate
    gxs = self.backward(target_input_indexes, grad_outputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 73, in backward
    return ReLUGrad2(y).apply((gy,))
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 258, in apply
    outputs = self.forward(in_data)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 368, in forward
    return self.forward_cpu(inputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 97, in forward_cpu
    y = (self.b > 0) * inputs[0]
Will finalize trainer extensions and updater before reraising the exception.
Traceback (most recent call last):
  File "AC.py", line 70, in <module>
    trainer.run()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/trainer.py", line 322, in run
    six.reraise(*sys.exc_info())
  File "/home/****/.local/lib/python3.5/site-packages/six.py", line 693, in reraise
    raise value
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/trainer.py", line 308, in run
    update()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 149, in update
    self.update_core()
  File "/home/****/.local/lib/python3.5/site-packages/chainer/training/updaters/standard_updater.py", line 164, in update_core
    optimizer.update(loss_func, in_arrays)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/optimizer.py", line 655, in update
    loss.backward(loss_scale=self._loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 966, in backward
    self._backward_main(retain_grad, loss_scale)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/variable.py", line 1095, in _backward_main
    target_input_indexes, out_grad, in_grad)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 548, in backward_accumulate
    gxs = self.backward(target_input_indexes, grad_outputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 73, in backward
    return ReLUGrad2(y).apply((gy,))
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 258, in apply
    outputs = self.forward(in_data)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/function_node.py", line 368, in forward
    return self.forward_cpu(inputs)
  File "/home/****/.local/lib/python3.5/site-packages/chainer/functions/activation/relu.py", line 97, in forward_cpu
    y = (self.b > 0) * inputs[0]
TypeError: unsupported operand type(s) for *: 'bool' and 'NoneType'

Answer 1

我认为model需要在__call__方法中返回损失。

样本修改如下：

class Autoencoder(Chain):
    def __init__(self):
       super().__init__()
       with self.init_scope():
           self.l1 = L.Linear(3,2)
           self.l2 = L.Linear(2,3)

    def forward(self,x):
       h1 = self.l1(x)
       h2 = self.l2(h1) 
       return h2

    def __call__(self,x):
       h = self.forward(x)
       # Instead of h, __call__ should return loss.
       loss = F.mean_squared_error(h, x)
       return loss