如题：如何设置dask.array的chunksize和shape？
代码如下

>>> x = data.values
>>> x
dask.array<values, shape=(nan, 24), dtype=int64, chunksize=(nan, 24)>

>>> y = data['label'].values
>>> y
dask.array<values, shape=(nan,), dtype=int64, chunksize=(nan,)>
>>> type(y)
dask.array.core.Array

>>> from dask_ml.linear_model import LogisticRegression
>>> lgr = LogisticRegression()
>>> lgr_model = lgr.fit(x, y)
---------------------------------------------------------------------------
NotImplementedError                       Traceback (most recent call last)
<ipython-input-116-f51a6d13cf8c> in <module>()
----> 1 lgr_model = lgr.fit(x, y)

E:\miniconda\envs\course_py35\lib\site-packages\dask_ml\linear_model\glm.py in fit(self, X, y)
    151         self : objectj
    152         """
--> 153         X = self._check_array(X)
    154 
    155         solver_kwargs = self._get_solver_kwargs()

E:\miniconda\envs\course_py35\lib\site-packages\dask_ml\linear_model\glm.py in _check_array(self, X)
    165     def _check_array(self, X):
    166         if self.fit_intercept:
--> 167             X = add_intercept(X)
    168 
    169         return check_array(X)

E:\miniconda\envs\course_py35\lib\site-packages\multipledispatch\dispatcher.py in __call__(self, *args, **kwargs)
    208             self._cache[types] = func
    209         try:
--> 210             return func(*args, **kwargs)
    211 
    212         except MDNotImplementedError:

E:\miniconda\envs\course_py35\lib\site-packages\dask_glm\utils.py in add_intercept(X)
    145 def add_intercept(X):
    146     if np.isnan(np.sum(X.shape)):
--> 147         raise NotImplementedError("Can not add intercept to array with "
    148                                   "unknown chunk shape")
    149     j, k = X.chunks

NotImplementedError: Can not add intercept to array with unknown chunk shape

根据报错提示，x、y数据的chunksize和shape未明确，所以如何设定它们的chunksize