The removed `finished()` call was responsible for enforcing that the
initializer was provided the correct number of values. Putting it back in
to restore previous behavior.
The error generated by the compiler was:
no matching function for call to 'maxi'
RealScalar threshold = numext::maxi(tol*tol*rhsNorm2,considerAsZero);
The important part in the following notes was:
candidate template ignored: deduced conflicting
types for parameter 'T'"
('codi::Multiply11<...>' vs. 'codi::ActiveReal<...>')
EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y)
I am using CoDiPack to provide the RealScalar type.
This bug was introduced in bc000deaa Fix conjugate-gradient for very small rhs
- access violation when initializing 0x0 matrices
- exception can be thrown during stack unwind while comma-initializing a matrix if eigen_assert if configured to throw
See
<https://stackoverflow.com/questions/59709148/ensuring-that-eigen-uses-avx-vectorization-for-a-certain-operation>
for an explanation of the problem this solves.
In short, for some reason, before this commit the half-packet is
selected when the array / matrix size is not a multiple of
`unpacket_traits<PacketType>::size`, where `PacketType` starts out
being the full Packet.
For example, for some data of 100 `float`s, `Packet4f` will be
selected rather than `Packet8f`, because 100 is not a multiple of 8,
the size of `Packet8f`.
This commit switches to selecting the half-packet if the size is
less than the packet size, which seems to make more sense.
As I stated in the SO post I'm not sure that I'm understanding the
issue correctly, but this fix resolves the issue in my program. Moreover,
`make check` passes, with the exception of line 614 and 616 in
`test/packetmath.cpp`, which however also fail on master on my machine:
CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i0, internal::pbessel_i0);
...
CHECK_CWISE1_IF(PacketTraits::HasBessel, numext::bessel_i1, internal::pbessel_i1);
This provides a new op that matches std::rint and previous behavior of
pround. Also adds corresponding unsupported/../Tensor op.
Performance is the same as e. g. floor (tested SSE/AVX).
* Adding Missing operations for vector comparison in SYCL. This caused compiler error for vector comparison when compiling SYCL
* Fixing the compiler error for placement new in TensorForcedEval.h This caused compiler error when compiling SYCL backend
* Reducing the SYCL warning by removing the abort function inside the kernel
* Adding Strong inline to functions inside SYCL interop.
This fixes deprecated-copy warnings when compiling with GCC>=9
Also protect some additional Base-constructors from getting called by user code code (#1587)
