It seems that I wasn't clear. :-(
The `mean_squared_error` is a good example of what I want to achieve.

Let's take a small example
``` python
In [1]: import numpy as np

In [2]: y_true = np.array([1, 2, 3, 4])

In [3]: y_pred = np.array([0, 2, 10, 5])

In [4]: np.mean((y_pred - y_true) ** 2)
Out[4]: 12.75

In [8]: np.mean((np.reshape(y_pred, (-1, 1)) - np.reshape(y_true, (1, -1)) ** 2))
Out[8]: -3.25
```
I wanted a way to convert 1d array of various shape to a common representation and let 2d array untouch (multi-output case).

> Is this intentional not to raise an exception on seemingly invalid input? 
Yes, it is. Do you a suggestion about it?