运行示例中的代码，得到错误：reduce() of empty sequence with no initial value

[SniperZhao]

新建了一个python文件，照抄了新手入门的线性回归代码。
运行该python的时候得到错误：

I0622 17:05:55.289027  8472 Util.cpp:166] commandline:  --use_gpu=False 
I0622 17:05:55.294421  8472 GradientMachine.cpp:85] Initing parameters..
I0622 17:05:55.294454  8472 GradientMachine.cpp:92] Init parameters done.
Traceback (most recent call last):
  File "lienerRegression.py", line 61, in <module>
    num_passes=100)
  File "/home/zhaoyuan/002.tools/paddleV2/python27/lib/python2.7/site-packages/paddle/v2/trainer.py", line 153, in train
    in_args = feeder(data_batch)
  File "/home/zhaoyuan/002.tools/paddleV2/python27/lib/python2.7/site-packages/py_paddle/dataprovider_converter.py", line 278, in __call__
    return self.convert(dat, argument)
  File "/home/zhaoyuan/002.tools/paddleV2/python27/lib/python2.7/site-packages/paddle/v2/data_feeder.py", line 134, in convert
    return DataProviderConverter.convert(self, reorder_data(dat), argument)
  File "/home/zhaoyuan/002.tools/paddleV2/python27/lib/python2.7/site-packages/py_paddle/dataprovider_converter.py", line 263, in convert
    scanner.pre_scan(each_step)
  File "/home/zhaoyuan/002.tools/paddleV2/python27/lib/python2.7/site-packages/py_paddle/dataprovider_converter.py", line 112, in pre_scan
    self.__dim__ = reduce(lambda x, y: x * y, self.__shape__)
TypeError: reduce() of empty sequence with no initial value

[chrisxu2016]

Can you paste the code? I'm not sure about this error now? Please make sure that data_reader has no problem

[SniperZhao]

具体代码请见：http://www.paddlepaddle.org/doc_cn/getstarted/concepts/use_concepts_cn.html
拉到最下面的线性回归完整示例部分。

我安装好paddle之后，编辑该代码到【linear.py】文件，然后键入命令【python linear.py】
得到上述报错。

[SniperZhao]

@chrisxu2016 any update?

[juliecbd]

To confirm, I did not have this problem before. I was able to input numpy nd array with multiple samples without problem with the paddle build 1 month ago. I rebuilt it yesterday, and I now have this problem. So I think there have been some commits which break the infer function

[jacquesqiao]

The demo code have some error, the input value is configured as dense_vector

y = paddle.layer.data(name='y', type=paddle.data_type.dense_vector(1))

but the reader yeild a scalar:

def train_reader():
    train_x = np.array([[1, 1], [1, 2], [3, 4], [5, 2]])
    train_y = np.array([-2, -3, -7, -7])

    def reader():
        for i in xrange(train_y.shape[0]):
            yield train_x[i], train_y[i]

    return reader

the reader should be changed to:

def train_reader():
    train_x = np.array([[1, 1], [1, 2], [3, 4], [5, 2]])
    train_y = np.array([[-2], [-3], [-7], [-7]])

    def reader():
        for i in xrange(train_y.shape[0]):
            yield train_x[i], train_y[i]

    return reader

[SniperZhao]

Thank you @jacquesqiao, it works now.