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raiseValueError("x1 and x2 must have the same size along the given axis")
ifhasattr(xp, 'broadcast_tensors'):
_broadcast=xp.broadcast_tensors
else:
_broadcast=xp.broadcast_arrays
x1_=xp.moveaxis(x1, axis, -1)
x2_=xp.moveaxis(x2, axis, -1)
x1_, x2_=_broadcast(x1_, x2_)
res=x1_[..., None, :] @ x2_[..., None]
returnres[..., 0, 0]
p.s. Found this while implementing a new quantity class that uses the array API to handle any type of array that can be passed in -- array_api_compat has been a great boon!
p.s.2 I found the problem for dask, which actually seems to be able to handle np.vecdot fine (and give the correct answer).
The text was updated successfully, but these errors were encountered:
The implementation for
vecdot
should conjugate its first argument for complex numbers, but unfortunately the present implementation does not:array-api-compat/array_api_compat/common/_aliases.py
Lines 469 to 483 in 8d3f5d5
p.s. Found this while implementing a new quantity class that uses the array API to handle any type of array that can be passed in --
array_api_compat
has been a great boon!p.s.2 I found the problem for
dask
, which actually seems to be able to handlenp.vecdot
fine (and give the correct answer).The text was updated successfully, but these errors were encountered: