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In [2]: from scipy._lib.array_api_compat.dask.array import clip
In [3]: import dask.array as da
In [4]: clip(da.asarray(0), max=7)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[4], line 1
----> 1 clip(da.asarray(0), max=7)
File ~/dev/pixi-dev-scipystack/scipy/scipy/build-install/lib/python3.12/site-packages/scipy/_lib/array_api_compat/_internal.py:28, in get_xp.<locals>.inner.<locals>.wrapped_f(*args, **kwargs)
26 @wraps(f)
27 def wrapped_f(*args, **kwargs):
---> 28 return f(*args, xp=xp, **kwargs)
File ~/dev/pixi-dev-scipystack/scipy/scipy/build-install/lib/python3.12/site-packages/scipy/_lib/array_api_compat/common/_aliases.py:284, in clip(x, min, max, xp, out)
282 min_shape = () if _isscalar(min) else min.shape
283 max_shape = () if _isscalar(max) else max.shape
--> 284 result_shape = xp.broadcast_shapes(x.shape, min_shape, max_shape)
286 wrapped_xp = array_namespace(x)
288 # np.clip does type promotion but the array API clip requires that the
289 # output have the same dtype as x. We do this instead of just downcasting
290 # the result of xp.clip() to handle some corner cases better (e.g.,
(...)
306 # At least handle the case of Python integers correctly (see
307 # https://github.com/numpy/numpy/pull/26892).
AttributeError: module 'dask.array' has no attribute 'broadcast_shapes'
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