From mboxrd@z Thu Jan  1 00:00:00 1970
Return-Path: <girar-builder@altlinux.org>
X-Spam-Checker-Version: SpamAssassin 3.4.1 (2015-04-28) on
 sa.local.altlinux.org
X-Spam-Level: 
X-Spam-Status: No, score=-3.3 required=5.0 tests=BAYES_00,RP_MATCHES_RCVD,
 SPF_FAIL, TO_EQ_FM_DOM_SPF_FAIL autolearn=ham autolearn_force=no version=3.4.1
Date: Fri, 7 Jun 2024 07:01:51 +0000
From: "Girar awaiter (iv)" <girar-builder@altlinux.org>
To: Ivan Melnikov <iv@altlinux.org>
Subject: [#350515] [test-only] FAILED Cardinal.git=24.05-alt2.git77b5becf
Message-ID: <girar.task.350515.1.1@gyle.mskdc.altlinux.org>
Mail-Followup-To: Girar awaiter robot <girar-builder@altlinux.org>
MIME-Version: 1.0
Content-Type: text/plain; charset=us-ascii
Content-Disposition: inline
Content-Transfer-Encoding: quoted-printable
X-girar-task-id: 350515
X-girar-task-owner: iv
X-girar-task-repo: sisyphus
X-girar-task-try: 1
X-girar-task-iter: 1
X-girar-task-status: FAILED
X-girar-task-URL: https://git.altlinux.org/tasks/350515/
X-girar-task-log: logs/events.1.1.log
X-girar-task-summary: [#350515] [test-only] FAILED
 Cardinal.git=24.05-alt2.git77b5becf
User-Agent: Mutt/1.10.1 (2018-07-13)
Cc: sisyphus-incominger@lists.altlinux.org, girar-builder-sisyphus@altlinux.org
X-BeenThere: sisyphus-incominger@lists.altlinux.org
X-Mailman-Version: 2.1.12
Precedence: list
Reply-To: ALT Devel discussion list <devel@lists.altlinux.org>
List-Id: ALT Linux Girar Builder robot reports
 <sisyphus-incominger.lists.altlinux.org>
List-Unsubscribe: <https://lists.altlinux.org/mailman/options/sisyphus-incominger>, 
 <mailto:sisyphus-incominger-request@lists.altlinux.org?subject=unsubscribe>
List-Archive: <http://lists.altlinux.org/pipermail/sisyphus-incominger>
List-Post: <mailto:sisyphus-incominger@lists.altlinux.org>
List-Help: <mailto:sisyphus-incominger-request@lists.altlinux.org?subject=help>
List-Subscribe: <https://lists.altlinux.org/mailman/listinfo/sisyphus-incominger>, 
 <mailto:sisyphus-incominger-request@lists.altlinux.org?subject=subscribe>
X-List-Received-Date: Fri, 07 Jun 2024 07:01:55 -0000
Archived-At: <http://lore.altlinux.org/sisyphus-incominger/girar.task.350515.1.1@gyle.mskdc.altlinux.org/>
List-Archive: <http://lore.altlinux.org/sisyphus-incominger/>

https://git.altlinux.org/tasks/350515/logs/events.1.1.log

subtask  name      aarch64  i586  ppc64le  x86_64
   #100  Cardinal   failed     -        -  failed

2024-Jun-07 06:55:59 :: test-only task #350515 for sisyphus started by iv:
#100 build 24.05-alt2.git77b5becf from /people/iv/packages/Cardinal.git fet=
ched at 2024-Jun-07 06:55:54
2024-Jun-07 06:56:00 :: [ppc64le] #100 Cardinal.git 24.05-alt2.git77b5becf:=
 build start
2024-Jun-07 06:56:00 :: [aarch64] #100 Cardinal.git 24.05-alt2.git77b5becf:=
 build start
2024-Jun-07 06:56:00 :: [x86_64] #100 Cardinal.git 24.05-alt2.git77b5becf: =
build start
2024-Jun-07 06:56:00 :: [i586] #100 Cardinal.git 24.05-alt2.git77b5becf: bu=
ild start
2024-Jun-07 06:56:16 :: [i586] #100 Cardinal.git 24.05-alt2.git77b5becf: bu=
ild SKIPPED
2024-Jun-07 06:56:25 :: [ppc64le] #100 Cardinal.git 24.05-alt2.git77b5becf:=
 build SKIPPED
[x86_64] Cardinal/src/AIDA-X/RTNeural/RTNeural/ModelT.h:345:5:   required f=
rom 'RTNeural::ModelT<T, in_size, out_size, Layers>::ModelT() [with T =3D f=
loat; int in_size =3D 1; int out_size =3D 1; Layers =3D {RTNeural::GRULayer=
T<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 64, 1>}]'
[x86_64] /usr/include/c++/13/variant:282:4:   required from 'constexpr std:=
:__detail::__variant::_Uninitialized<_Type, false>::_Uninitialized(std::in_=
place_index_t<0>, _Args&& ...) [with _Args =3D {}; _Type =3D RTNeural::Mode=
lT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCorre=
ctionMode::None>, RTNeural::DenseT<float, 64, 1> >]'
[x86_64] /usr/include/c++/13/bits/stl_construct.h:119:7:   required from 'v=
oid std::_Construct(_Tp*, _Args&& ...) [with _Tp =3D __detail::__variant::_=
Uninitialized<RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 6=
4, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1=
> >, false>; _Args =3D {const in_place_index_t<0>&}]'
[x86_64] /usr/include/c++/13/variant:567:22:   required from 'void std::__d=
etail::__variant::__emplace(_Variant_storage<_Triv, _Types ...>&, _Args&& .=
=2E.) [with long unsigned int _Np =3D 19; bool _Triv =3D false; _Types =3D =
{NullModel, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 8, =
RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >,=
 RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 8, RTNeural::S=
ampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::=
ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 8, RTNeural::SampleRateCo=
rrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<floa=
t, 1, 1, RTNeural::GRULayerT<float, 1, 12, RTNeural::SampleRateCorrectionMo=
de::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 2, 1, =
RTNeural::GRULayerT<float, 2, 12, RTNeural::SampleRateCorrectionMode::None>=
, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural:=
:GRULayerT<float, 3, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeura=
l::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayer=
T<float, 1, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 16, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, =
2, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 1=
6, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 16, RT=
Neural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, =
RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 20, RTNeural::S=
ampleRateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural:=
:ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 20, RTNeural::SampleRate=
CorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<f=
loat, 3, 1, RTNeural::GRULayerT<float, 3, 20, RTNeural::SampleRateCorrectio=
nMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 1, =
1, RTNeural::GRULayerT<float, 1, 32, RTNeural::SampleRateCorrectionMode::No=
ne>, RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 2, 1, RTNeur=
al::GRULayerT<float, 2, 32, RTNeural::SampleRateCorrectionMode::None>, RTNe=
ural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULa=
yerT<float, 3, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Den=
seT<float, 32, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<floa=
t, 1, 40, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float=
, 40, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 40,=
 RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> =
>, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 40, RTNeural=
::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeur=
al::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleR=
ateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::Model=
T<float, 2, 1, RTNeural::GRULayerT<float, 2, 64, RTNeural::SampleRateCorrec=
tionMode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, =
3, 1, RTNeural::GRULayerT<float, 3, 64, RTNeural::SampleRateCorrectionMode:=
:None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 1, 1, RTN=
eural::LSTMLayerT<float, 1, 8, RTNeural::SampleRateCorrectionMode::None>, R=
TNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LST=
MLayerT<float, 2, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::D=
enseT<float, 8, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<fl=
oat, 3, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<floa=
t, 8, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 12=
, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1>=
 >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 12, RTNeur=
al::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNe=
ural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 12, RTNeural::Samp=
leRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::Mo=
delT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 16, RTNeural::SampleRateCo=
rrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<flo=
at, 2, 1, RTNeural::LSTMLayerT<float, 2, 16, RTNeural::SampleRateCorrection=
Mode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 3, 1=
, RTNeural::LSTMLayerT<float, 3, 16, RTNeural::SampleRateCorrectionMode::No=
ne>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 1, 1, RTNeur=
al::LSTMLayerT<float, 1, 20, RTNeural::SampleRateCorrectionMode::None>, RTN=
eural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTM=
LayerT<float, 2, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::D=
enseT<float, 20, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<f=
loat, 3, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<fl=
oat, 20, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1,=
 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32,=
 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 32, RTN=
eural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, R=
TNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 32, RTNeural::S=
ampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural:=
:ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 40, RTNeural::SampleRat=
eCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<=
float, 2, 1, RTNeural::LSTMLayerT<float, 2, 40, RTNeural::SampleRateCorrect=
ionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 3=
, 1, RTNeural::LSTMLayerT<float, 3, 40, RTNeural::SampleRateCorrectionMode:=
:None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 1, 1, RTN=
eural::LSTMLayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, =
RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::L=
STMLayerT<float, 2, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural=
::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayer=
T<float, 3, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 64, 1> >}; _Args =3D {}]'
[x86_64] /usr/include/c++/13/variant:1570:33:   required from 'std::enable_=
if_t<is_constructible_v<std::variant<_Types>::__to_type<_Np, typename std::=
enable_if<(_Np < sizeof... (_Types)), void>::type>, _Args ...>, std::varian=
t<_Types>::__to_type<_Np>&> std::variant<_Types>::emplace(_Args&& ...) [wit=
h long unsigned int _Np =3D 19; _Args =3D {}; _Types =3D {NullModel, RTNeur=
al::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 8, RTNeural::SampleRa=
teCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<=
float, 2, 1, RTNeural::GRULayerT<float, 2, 8, RTNeural::SampleRateCorrectio=
nMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 3, 1=
, RTNeural::GRULayerT<float, 3, 8, RTNeural::SampleRateCorrectionMode::None=
>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural:=
:GRULayerT<float, 1, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeura=
l::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayer=
T<float, 2, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 12, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, =
3, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 1=
2, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 16, RT=
Neural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, =
RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 16, RTNeural::S=
ampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural:=
:ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 16, RTNeural::SampleRate=
CorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<f=
loat, 1, 1, RTNeural::GRULayerT<float, 1, 20, RTNeural::SampleRateCorrectio=
nMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 2, =
1, RTNeural::GRULayerT<float, 2, 20, RTNeural::SampleRateCorrectionMode::No=
ne>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 3, 1, RTNeur=
al::GRULayerT<float, 3, 20, RTNeural::SampleRateCorrectionMode::None>, RTNe=
ural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULa=
yerT<float, 1, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Den=
seT<float, 32, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<floa=
t, 2, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float=
, 32, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 32,=
 RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> =
>, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 40, RTNeural=
::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeur=
al::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 40, RTNeural::SampleR=
ateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::Model=
T<float, 3, 1, RTNeural::GRULayerT<float, 3, 40, RTNeural::SampleRateCorrec=
tionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, =
1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode:=
:None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTN=
eural::GRULayerT<float, 2, 64, RTNeural::SampleRateCorrectionMode::None>, R=
TNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GR=
ULayerT<float, 3, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::=
DenseT<float, 64, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<=
float, 1, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<fl=
oat, 8, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, =
8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1>=
 >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 8, RTNeura=
l::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeur=
al::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 12, RTNeural::Sample=
RateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::Mode=
lT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 12, RTNeural::SampleRateCorr=
ectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float=
, 3, 1, RTNeural::LSTMLayerT<float, 3, 12, RTNeural::SampleRateCorrectionMo=
de::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 1, 1, =
RTNeural::LSTMLayerT<float, 1, 16, RTNeural::SampleRateCorrectionMode::None=
>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural=
::LSTMLayerT<float, 2, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeu=
ral::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLa=
yerT<float, 3, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Den=
seT<float, 16, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<flo=
at, 1, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<floa=
t, 20, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 2=
0, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1=
> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 20, RTNeu=
ral::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTN=
eural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 32, RTNeural::Sam=
pleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::M=
odelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 32, RTNeural::SampleRateC=
orrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<fl=
oat, 3, 1, RTNeural::LSTMLayerT<float, 3, 32, RTNeural::SampleRateCorrectio=
nMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 1, =
1, RTNeural::LSTMLayerT<float, 1, 40, RTNeural::SampleRateCorrectionMode::N=
one>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 2, 1, RTNeu=
ral::LSTMLayerT<float, 2, 40, RTNeural::SampleRateCorrectionMode::None>, RT=
Neural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LST=
MLayerT<float, 3, 40, RTNeural::SampleRateCorrectionMode::None>, RTNeural::=
DenseT<float, 40, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<=
float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<f=
loat, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2=
, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64=
, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 64, RT=
Neural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> >};=
 std::enable_if_t<is_constructible_v<__to_type<_Np, typename std::enable_if=
<(_Np < sizeof... (_Types)), void>::type>, _Args ...>, __to_type<_Np>&> =3D=
 RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::=
SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> >&; __to_ty=
pe<_Np> =3D RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64,=
 RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> =
>; typename std::enable_if<(_Np < sizeof... (_Types)), void>::type =3D void=
]'
[x86_64] /usr/include/c++/13/variant:1522:33:   required from 'std::enable_=
if_t<(is_constructible_v<_Tp, _Args ...> && __exactly_once<_Tp>), _Tp&> std=
::variant<_Types>::emplace(_Args&& ...) [with _Tp =3D RTNeural::ModelT<floa=
t, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCorrectionMo=
de::None>, RTNeural::DenseT<float, 64, 1> >; _Args =3D {}; _Types =3D {Null=
Model, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 8, RTNeu=
ral::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNe=
ural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 8, RTNeural::Sample=
RateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::Model=
T<float, 3, 1, RTNeural::GRULayerT<float, 3, 8, RTNeural::SampleRateCorrect=
ionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 1,=
 1, RTNeural::GRULayerT<float, 1, 12, RTNeural::SampleRateCorrectionMode::N=
one>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 2, 1, RTNeu=
ral::GRULayerT<float, 2, 12, RTNeural::SampleRateCorrectionMode::None>, RTN=
eural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRUL=
ayerT<float, 3, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeural::De=
nseT<float, 12, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<flo=
at, 1, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<floa=
t, 16, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 16=
, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1>=
 >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 16, RTNeura=
l::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeu=
ral::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 20, RTNeural::Sample=
RateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::Mode=
lT<float, 2, 1, RTNeural::GRULayerT<float, 2, 20, RTNeural::SampleRateCorre=
ctionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float,=
 3, 1, RTNeural::GRULayerT<float, 3, 20, RTNeural::SampleRateCorrectionMode=
::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 1, 1, RT=
Neural::GRULayerT<float, 1, 32, RTNeural::SampleRateCorrectionMode::None>, =
RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::G=
RULayerT<float, 2, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural:=
:DenseT<float, 32, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<=
float, 3, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<f=
loat, 32, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1,=
 40, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40,=
 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 40, RTNe=
ural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RT=
Neural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 40, RTNeural::Sam=
pleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::M=
odelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCo=
rrectionMode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<flo=
at, 2, 1, RTNeural::GRULayerT<float, 2, 64, RTNeural::SampleRateCorrectionM=
ode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1,=
 RTNeural::GRULayerT<float, 3, 64, RTNeural::SampleRateCorrectionMode::None=
>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural=
::LSTMLayerT<float, 1, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeur=
al::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLaye=
rT<float, 2, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 8, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, =
3, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8,=
 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 12, RTN=
eural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, R=
TNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 12, RTNeural::S=
ampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural:=
:ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 12, RTNeural::SampleRat=
eCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<=
float, 1, 1, RTNeural::LSTMLayerT<float, 1, 16, RTNeural::SampleRateCorrect=
ionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 2=
, 1, RTNeural::LSTMLayerT<float, 2, 16, RTNeural::SampleRateCorrectionMode:=
:None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 3, 1, RTN=
eural::LSTMLayerT<float, 3, 16, RTNeural::SampleRateCorrectionMode::None>, =
RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::L=
STMLayerT<float, 1, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural=
::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayer=
T<float, 2, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 20, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float,=
 3, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, =
20, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 32, =
RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >=
, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 32, RTNeural=
::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeur=
al::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 32, RTNeural::Sample=
RateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::Mode=
lT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 40, RTNeural::SampleRateCorr=
ectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float=
, 2, 1, RTNeural::LSTMLayerT<float, 2, 40, RTNeural::SampleRateCorrectionMo=
de::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 3, 1, =
RTNeural::LSTMLayerT<float, 3, 40, RTNeural::SampleRateCorrectionMode::None=
>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural=
::LSTMLayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeu=
ral::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLa=
yerT<float, 2, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Den=
seT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<flo=
at, 3, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<floa=
t, 64, 1> >}; std::enable_if_t<(is_constructible_v<_Tp, _Args ...> && __exa=
ctly_once<_Tp>), _Tp&> =3D RTNeural::ModelT<float, 1, 1, RTNeural::GRULayer=
T<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT=
<float, 64, 1> >&]'
[x86_64] Cardinal/src/AIDA-X/model_variant.hpp:586:42:   required from here
[x86_64] Cardinal/src/AIDA-X/RTNeural/RTNeural/dense/dense_eigen.h:125:16: =
warning: member 'RTNeural::DenseT<float, 64, 1>::outs_internal' is used uni=
nitialized [-Wuninitialized]
[x86_64] make[1]: Leaving directory '/usr/src/RPM/BUILD/Cardinal-24.05/plug=
ins'
[x86_64] make: *** [Makefile:190: plugins] Error 2
2024-Jun-07 06:59:30 :: [x86_64] Cardinal.git 24.05-alt2.git77b5becf: remot=
e: build failed
2024-Jun-07 06:59:30 :: [x86_64] #100 Cardinal.git 24.05-alt2.git77b5becf: =
build FAILED
2024-Jun-07 06:59:30 :: [x86_64] requesting cancellation of task processing
[aarch64] Cardinal/src/AIDA-X/RTNeural/RTNeural/ModelT.h:345:5:   required =
=66rom 'RTNeural::ModelT<T, in_size, out_size, Layers>::ModelT() [with T =
=3D float; int in_size =3D 1; int out_size =3D 1; Layers =3D {RTNeural::GRU=
LayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::D=
enseT<float, 64, 1>}]'
[aarch64] /usr/include/c++/13/variant:282:4:   required from 'constexpr std=
::__detail::__variant::_Uninitialized<_Type, false>::_Uninitialized(std::in=
_place_index_t<0>, _Args&& ...) [with _Args =3D {}; _Type =3D RTNeural::Mod=
elT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCorr=
ectionMode::None>, RTNeural::DenseT<float, 64, 1> >]'
[aarch64] /usr/include/c++/13/bits/stl_construct.h:119:7:   required from '=
void std::_Construct(_Tp*, _Args&& ...) [with _Tp =3D __detail::__variant::=
_Uninitialized<RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, =
64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, =
1> >, false>; _Args =3D {const in_place_index_t<0>&}]'
[aarch64] /usr/include/c++/13/variant:567:22:   required from 'void std::__=
detail::__variant::__emplace(_Variant_storage<_Triv, _Types ...>&, _Args&& =
=2E..) [with long unsigned int _Np =3D 19; bool _Triv =3D false; _Types =3D=
 {NullModel, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 8,=
 RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >=
, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 8, RTNeural::=
SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural:=
:ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 8, RTNeural::SampleRateC=
orrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<flo=
at, 1, 1, RTNeural::GRULayerT<float, 1, 12, RTNeural::SampleRateCorrectionM=
ode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 2, 1,=
 RTNeural::GRULayerT<float, 2, 12, RTNeural::SampleRateCorrectionMode::None=
>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural=
::GRULayerT<float, 3, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeur=
al::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULaye=
rT<float, 1, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Dense=
T<float, 16, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float,=
 2, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, =
16, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 16, R=
TNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >,=
 RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 20, RTNeural::=
SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural=
::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 20, RTNeural::SampleRat=
eCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<=
float, 3, 1, RTNeural::GRULayerT<float, 3, 20, RTNeural::SampleRateCorrecti=
onMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 1,=
 1, RTNeural::GRULayerT<float, 1, 32, RTNeural::SampleRateCorrectionMode::N=
one>, RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 2, 1, RTNeu=
ral::GRULayerT<float, 2, 32, RTNeural::SampleRateCorrectionMode::None>, RTN=
eural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRUL=
ayerT<float, 3, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::De=
nseT<float, 32, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<flo=
at, 1, 40, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<floa=
t, 40, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 40=
, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1>=
 >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 40, RTNeura=
l::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeu=
ral::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::Sample=
RateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::Mode=
lT<float, 2, 1, RTNeural::GRULayerT<float, 2, 64, RTNeural::SampleRateCorre=
ctionMode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float,=
 3, 1, RTNeural::GRULayerT<float, 3, 64, RTNeural::SampleRateCorrectionMode=
::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 1, 1, RT=
Neural::LSTMLayerT<float, 1, 8, RTNeural::SampleRateCorrectionMode::None>, =
RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LS=
TMLayerT<float, 2, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::=
DenseT<float, 8, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<f=
loat, 3, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<flo=
at, 8, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 1=
2, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1=
> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 12, RTNeu=
ral::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTN=
eural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 12, RTNeural::Sam=
pleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::M=
odelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 16, RTNeural::SampleRateC=
orrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<fl=
oat, 2, 1, RTNeural::LSTMLayerT<float, 2, 16, RTNeural::SampleRateCorrectio=
nMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 3, =
1, RTNeural::LSTMLayerT<float, 3, 16, RTNeural::SampleRateCorrectionMode::N=
one>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 1, 1, RTNeu=
ral::LSTMLayerT<float, 1, 20, RTNeural::SampleRateCorrectionMode::None>, RT=
Neural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LST=
MLayerT<float, 2, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::=
DenseT<float, 20, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<=
float, 3, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<f=
loat, 20, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1=
, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32=
, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 32, RT=
Neural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, =
RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 32, RTNeural::=
SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural=
::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 40, RTNeural::SampleRa=
teCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT=
<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 40, RTNeural::SampleRateCorrec=
tionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, =
3, 1, RTNeural::LSTMLayerT<float, 3, 40, RTNeural::SampleRateCorrectionMode=
::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 1, 1, RT=
Neural::LSTMLayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>,=
 RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::=
LSTMLayerT<float, 2, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeura=
l::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLaye=
rT<float, 3, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Dense=
T<float, 64, 1> >}; _Args =3D {}]'
[aarch64] /usr/include/c++/13/variant:1570:33:   required from 'std::enable=
_if_t<is_constructible_v<std::variant<_Types>::__to_type<_Np, typename std:=
:enable_if<(_Np < sizeof... (_Types)), void>::type>, _Args ...>, std::varia=
nt<_Types>::__to_type<_Np>&> std::variant<_Types>::emplace(_Args&& ...) [wi=
th long unsigned int _Np =3D 19; _Args =3D {}; _Types =3D {NullModel, RTNeu=
ral::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 8, RTNeural::SampleR=
ateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT=
<float, 2, 1, RTNeural::GRULayerT<float, 2, 8, RTNeural::SampleRateCorrecti=
onMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 3, =
1, RTNeural::GRULayerT<float, 3, 8, RTNeural::SampleRateCorrectionMode::Non=
e>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural=
::GRULayerT<float, 1, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeur=
al::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULaye=
rT<float, 2, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Dense=
T<float, 12, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float,=
 3, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, =
12, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 16, R=
TNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >,=
 RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 16, RTNeural::=
SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural=
::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 16, RTNeural::SampleRat=
eCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<=
float, 1, 1, RTNeural::GRULayerT<float, 1, 20, RTNeural::SampleRateCorrecti=
onMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 2,=
 1, RTNeural::GRULayerT<float, 2, 20, RTNeural::SampleRateCorrectionMode::N=
one>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 3, 1, RTNeu=
ral::GRULayerT<float, 3, 20, RTNeural::SampleRateCorrectionMode::None>, RTN=
eural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRUL=
ayerT<float, 1, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::De=
nseT<float, 32, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<flo=
at, 2, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<floa=
t, 32, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 32=
, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1>=
 >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 40, RTNeura=
l::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeu=
ral::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 40, RTNeural::Sample=
RateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::Mode=
lT<float, 3, 1, RTNeural::GRULayerT<float, 3, 40, RTNeural::SampleRateCorre=
ctionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float,=
 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode=
::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RT=
Neural::GRULayerT<float, 2, 64, RTNeural::SampleRateCorrectionMode::None>, =
RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::G=
RULayerT<float, 3, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural:=
:DenseT<float, 64, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT=
<float, 1, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<f=
loat, 8, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2,=
 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1=
> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 8, RTNeur=
al::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeu=
ral::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 12, RTNeural::Sampl=
eRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::Mod=
elT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 12, RTNeural::SampleRateCor=
rectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<floa=
t, 3, 1, RTNeural::LSTMLayerT<float, 3, 12, RTNeural::SampleRateCorrectionM=
ode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 1, 1,=
 RTNeural::LSTMLayerT<float, 1, 16, RTNeural::SampleRateCorrectionMode::Non=
e>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 2, 1, RTNeura=
l::LSTMLayerT<float, 2, 16, RTNeural::SampleRateCorrectionMode::None>, RTNe=
ural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTML=
ayerT<float, 3, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::De=
nseT<float, 16, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<fl=
oat, 1, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<flo=
at, 20, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, =
20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 20, =
1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 20, RTNe=
ural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RT=
Neural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 32, RTNeural::Sa=
mpleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::=
ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 32, RTNeural::SampleRate=
CorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<f=
loat, 3, 1, RTNeural::LSTMLayerT<float, 3, 32, RTNeural::SampleRateCorrecti=
onMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 1,=
 1, RTNeural::LSTMLayerT<float, 1, 40, RTNeural::SampleRateCorrectionMode::=
None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 2, 1, RTNe=
ural::LSTMLayerT<float, 2, 40, RTNeural::SampleRateCorrectionMode::None>, R=
TNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LS=
TMLayerT<float, 3, 40, RTNeural::SampleRateCorrectionMode::None>, RTNeural:=
:DenseT<float, 40, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT=
<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<=
float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, =
2, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 6=
4, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 64, R=
TNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> >}=
; std::enable_if_t<is_constructible_v<__to_type<_Np, typename std::enable_i=
f<(_Np < sizeof... (_Types)), void>::type>, _Args ...>, __to_type<_Np>&> =
=3D RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeura=
l::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, 1> >&; __to=
_type<_Np> =3D RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, =
64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 64, =
1> >; typename std::enable_if<(_Np < sizeof... (_Types)), void>::type =3D v=
oid]'
[aarch64] /usr/include/c++/13/variant:1522:33:   required from 'std::enable=
_if_t<(is_constructible_v<_Tp, _Args ...> && __exactly_once<_Tp>), _Tp&> st=
d::variant<_Types>::emplace(_Args&& ...) [with _Tp =3D RTNeural::ModelT<flo=
at, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateCorrectionM=
ode::None>, RTNeural::DenseT<float, 64, 1> >; _Args =3D {}; _Types =3D {Nul=
lModel, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 8, RTNe=
ural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTN=
eural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 8, RTNeural::Sampl=
eRateCorrectionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::Mode=
lT<float, 3, 1, RTNeural::GRULayerT<float, 3, 8, RTNeural::SampleRateCorrec=
tionMode::None>, RTNeural::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 1=
, 1, RTNeural::GRULayerT<float, 1, 12, RTNeural::SampleRateCorrectionMode::=
None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 2, 1, RTNe=
ural::GRULayerT<float, 2, 12, RTNeural::SampleRateCorrectionMode::None>, RT=
Neural::DenseT<float, 12, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRU=
LayerT<float, 3, 12, RTNeural::SampleRateCorrectionMode::None>, RTNeural::D=
enseT<float, 12, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<fl=
oat, 1, 16, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<flo=
at, 16, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 1=
6, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1=
> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 16, RTNeur=
al::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNe=
ural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 20, RTNeural::Sampl=
eRateCorrectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::Mod=
elT<float, 2, 1, RTNeural::GRULayerT<float, 2, 20, RTNeural::SampleRateCorr=
ectionMode::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float=
, 3, 1, RTNeural::GRULayerT<float, 3, 20, RTNeural::SampleRateCorrectionMod=
e::None>, RTNeural::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 1, 1, R=
TNeural::GRULayerT<float, 1, 32, RTNeural::SampleRateCorrectionMode::None>,=
 RTNeural::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::=
GRULayerT<float, 2, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural=
::DenseT<float, 32, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::GRULayerT=
<float, 3, 32, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<=
float, 32, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1=
, 40, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40=
, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::GRULayerT<float, 2, 40, RTN=
eural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, R=
TNeural::ModelT<float, 3, 1, RTNeural::GRULayerT<float, 3, 40, RTNeural::Sa=
mpleRateCorrectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::=
ModelT<float, 1, 1, RTNeural::GRULayerT<float, 1, 64, RTNeural::SampleRateC=
orrectionMode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<fl=
oat, 2, 1, RTNeural::GRULayerT<float, 2, 64, RTNeural::SampleRateCorrection=
Mode::None>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1=
, RTNeural::GRULayerT<float, 3, 64, RTNeural::SampleRateCorrectionMode::Non=
e>, RTNeural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 1, 1, RTNeura=
l::LSTMLayerT<float, 1, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeu=
ral::DenseT<float, 8, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLay=
erT<float, 2, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Dense=
T<float, 8, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float,=
 3, 8, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 8=
, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 12, RT=
Neural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, =
RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 12, RTNeural::=
SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural=
::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 12, RTNeural::SampleRa=
teCorrectionMode::None>, RTNeural::DenseT<float, 12, 1> >, RTNeural::ModelT=
<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 16, RTNeural::SampleRateCorrec=
tionMode::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, =
2, 1, RTNeural::LSTMLayerT<float, 2, 16, RTNeural::SampleRateCorrectionMode=
::None>, RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 3, 1, RT=
Neural::LSTMLayerT<float, 3, 16, RTNeural::SampleRateCorrectionMode::None>,=
 RTNeural::DenseT<float, 16, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::=
LSTMLayerT<float, 1, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeura=
l::DenseT<float, 20, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLaye=
rT<float, 2, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Dense=
T<float, 20, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float=
, 3, 20, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float,=
 20, 1> >, RTNeural::ModelT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 32,=
 RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> =
>, RTNeural::ModelT<float, 2, 1, RTNeural::LSTMLayerT<float, 2, 32, RTNeura=
l::SampleRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeu=
ral::ModelT<float, 3, 1, RTNeural::LSTMLayerT<float, 3, 32, RTNeural::Sampl=
eRateCorrectionMode::None>, RTNeural::DenseT<float, 32, 1> >, RTNeural::Mod=
elT<float, 1, 1, RTNeural::LSTMLayerT<float, 1, 40, RTNeural::SampleRateCor=
rectionMode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<floa=
t, 2, 1, RTNeural::LSTMLayerT<float, 2, 40, RTNeural::SampleRateCorrectionM=
ode::None>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 3, 1,=
 RTNeural::LSTMLayerT<float, 3, 40, RTNeural::SampleRateCorrectionMode::Non=
e>, RTNeural::DenseT<float, 40, 1> >, RTNeural::ModelT<float, 1, 1, RTNeura=
l::LSTMLayerT<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNe=
ural::DenseT<float, 64, 1> >, RTNeural::ModelT<float, 2, 1, RTNeural::LSTML=
ayerT<float, 2, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::De=
nseT<float, 64, 1> >, RTNeural::ModelT<float, 3, 1, RTNeural::LSTMLayerT<fl=
oat, 3, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::DenseT<flo=
at, 64, 1> >}; std::enable_if_t<(is_constructible_v<_Tp, _Args ...> && __ex=
actly_once<_Tp>), _Tp&> =3D RTNeural::ModelT<float, 1, 1, RTNeural::GRULaye=
rT<float, 1, 64, RTNeural::SampleRateCorrectionMode::None>, RTNeural::Dense=
T<float, 64, 1> >&]'
[aarch64] Cardinal/src/AIDA-X/model_variant.hpp:586:42:   required from here
[aarch64] Cardinal/src/AIDA-X/RTNeural/RTNeural/dense/dense_eigen.h:125:16:=
 warning: member 'RTNeural::DenseT<float, 64, 1>::outs_internal' is used un=
initialized [-Wuninitialized]
[aarch64] make[1]: Leaving directory '/usr/src/RPM/BUILD/Cardinal-24.05/plu=
gins'
[aarch64] make: *** [Makefile:190: plugins] Error 2
2024-Jun-07 07:01:50 :: [aarch64] Cardinal.git 24.05-alt2.git77b5becf: remo=
te: build failed
2024-Jun-07 07:01:50 :: [aarch64] #100 Cardinal.git 24.05-alt2.git77b5becf:=
 build FAILED
2024-Jun-07 06:59:30 :: [x86_64] build FAILED
2024-Jun-07 07:01:50 :: [aarch64] build FAILED
2024-Jun-07 07:01:50 :: task #350515 for sisyphus FAILED