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dpctl.tensor.tan returns incorrect result #2893
Description
It seems dpctl.tensor.tan returns result which differs with numpy and Intel MKL:
import dpnp, numpy, dpctl, dpctl.tensor as dpt
a = numpy.array([11], dtype='F')
numpy.tan(a)
# Out: array([-225.95084+0.j], dtype=complex64)
ia = dpnp.array(a, device='cpu')
dpnp.tan(ia)
# array([-225.95085+0.j], dtype=complex64) tan() from Intel MKL is used
na = dpt.asarray(a, device='cpu')
dpt.tan(da)
# Out: usm_ndarray([-225.68439+0.j], dtype=complex64)
na = dpt.asarray(a, device='gpu')
dpt.tan(na)
# Out: usm_ndarray([-225.68439+0.j], dtype=complex64)
# casting to complex128 resolve the issue:
na = dpt.asarray(a, device='cpu', dtype='D')
dpt.tan(na)
# Out: usm_ndarray([-225.95084645+0.j])Is the behavior expected? Or is there something which needs to be fixed in dpctl?
Activity
ndgrigorian commentedon Mar 27, 2025
@antonwolfy
Can you provide more information about the machine that you took this on?
I haven't been able to replicate it locally.
Update: my mistake, I missed that it was complex.
I can replicate it fine.
ndgrigorian commentedon May 5, 2026
Transferred as it is no longer relevant to dpctl