I've created a virtual machine with a fresh install of Ubuntu 14.04.5 LTS (Trusty Tahr), then I've installed Qt 5.8. The arch is x64.
I've tried to execute the following example:
http://doc.qt.io/qt-5/qtmultimedia-multimediawidgets-player-example.html, the result is the error:
defaultServiceProvider::requestService(): no service found for -
"org.qt-project.qt.mediaplayer"
I've enabled the QT_DEBUG_PLUGINS=1 variable and seen that:
Got keys from plugin meta data ("gstreamermediaplayer")
QFactoryLoader::QFactoryLoader() checking directory path "/home/user/QtWorkspace/bin/mediaservice" ...
Cannot load library /home/user/Qt/5.8/gcc_64/plugins/mediaservice/libgstmediaplayer.so: (/home/user/Qt/5.8/gcc_64/plugins/mediaservice/../../lib/libqgsttools_p.so.1: undefined symbol: _gst_value_list_type)
QLibraryPrivate::loadPlugin failed on "/home/user/Qt/5.8/gcc_64/plugins/mediaservice/libgstmediaplayer.so" : "Cannot load library /home/user/Qt/5.8/gcc_64/plugins/mediaservice/libgstmediaplayer.so: (/home/user/Qt/5.8/gcc_64/plugins/mediaservice/../../lib/libqgsttools_p.so.1: undefined symbol: _gst_value_list_type)"
defaultServiceProvider::requestService(): no service found for - "org.qt-project.qt.mediaplayer"
What is the cause of the "libqgsttools_p.so.1: undefined symbol: _gst_value_list_type" error? Why this mismatch? Is it possible that QtMultimedia does not support GStreamer 1.0 (Trusty comes with GStreamer 1.2.4 installed)?
Related
I've made a Leanprover installation on Ubuntu 22.04 and used the stable toolchain. The elan toolchain list shows the following default
leanprover/lean4:stable (default)
I've made a test file called test.lean that contains the following
import Leanpkg
#eval Leanpkg.leanVersionString
When I run lean test.lean I get
test.lean:1:0: error: unknown package 'Leanpkg'
test.lean:2:6: error: unknown identifier 'Leanpkg.leanVersionString'
test.lean:2:0: error: unknown constant 'sorryAx'
What should I do to make it work?
I'm playing with a couple of projects that explicitly require pytorch == 1.0.0, but I have an old graphics card that only supports cuda 3.0 so I'm using the cpu, which is very slow, being the graphics card a dual gpu I decided to give a try and build pytorch from the sources with support for 3.0 (I have planned to update the pc but is not gonna happen anytime soon).
I am using docker to do the build, in particular I tried to modify an existing Dockerfile from build-pytorch, on the host system I am using debian/sid and there is cuda 10.2 cudnn 7.6 installed, I'm not sure if I can downgrade cuda, and I don't know if the versions in the container must be exactly the same as the host (like for nvidia drivers).
Gist of the modified Dockerfile
The first thing I noticed when updating the versions is that package cuda-cublas-dev-10-2 was not found, the latest version was 10-0,
CUBLAS packaging changed in CUDA 10.1 to be outside of the toolkit installation path
If I install cublas version 10-0 or if I don't install it obviously no header files are found (error below), if I install the recommended libcublas-dev version the build continues for a while, with some warnings (below) , but then it stops with the error below.
I searched for the error online but I did not find anything specific, if I understand correctly there is a function declared more than once and when it is called the choice is ambiguous, but I have not yet investigated looking at the sources.
I would like to know if anyone has run into this error before and knows how to fix it.
libcublas-dev installed error:
[ 67%] Building NVCC (Device) object caffe2/CMakeFiles/caffe2_gpu.dir/__/aten/src/ATen/native/sparse/cuda/caffe2_gpu_generated_SparseCUDABlas.cu.o
/pytorch/aten/src/ATen/native/sparse/cuda/SparseCUDABlas.cu(58): error: more than one instance of function "at::native::sparse::cuda::cusparseGetErrorString" matches the argument list:
function "cusparseGetErrorString(cusparseStatus_t)"
function "at::native::sparse::cuda::cusparseGetErrorString(cusparseStatus_t)"
argument types are: (cusparseStatus_t)
1 error detected in the compilation of "/tmp/tmpxft_00004ccc_00000000-6_SparseCUDABlas.cpp1.ii".
CMake Error at caffe2_gpu_generated_SparseCUDABlas.cu.o.Release.cmake:279 (message):
Error generating file
/pytorch/build/caffe2/CMakeFiles/caffe2_gpu.dir/__/aten/src/ATen/native/sparse/cuda/./caffe2_gpu_generated_SparseCUDABlas.cu.o
caffe2/CMakeFiles/caffe2_gpu.dir/build.make:1260: recipe for target 'caffe2/CMakeFiles/caffe2_gpu.dir/__/aten/src/ATen/native/sparse/cuda/caffe2_gpu_generated_SparseCUDABlas.cu.o' failed
warnings:
ptxas warning : Too big maxrregcount value specified 96, will be ignored
missing header error:
Scanning dependencies of target caffe2_pybind11_state
[ 59%] Building CXX object caffe2/CMakeFiles/caffe2_pybind11_state.dir/python/pybind_state.cc.o
In file included from /pytorch/aten/src/THC/THC.h:4:0,
from /pytorch/torch/lib/THD/../THD/base/TensorDescriptor.h:6,
from /pytorch/torch/lib/THD/../THD/base/TensorDescriptor.hpp:6,
from /pytorch/torch/lib/THD/../THD/THD.h:14,
from /pytorch/torch/lib/THD/base/DataChannelRequest.h:3,
from /pytorch/torch/lib/THD/base/DataChannelRequest.hpp:6,
from /pytorch/torch/lib/THD/base/DataChannelRequest.cpp:1:
/pytorch/build/caffe2/aten/src/THC/THCGeneral.h:17:23: fatal error: cublas_v2.h: No such file or directory
compilation terminated.
make[2]: *** [caffe2/torch/lib/THD/CMakeFiles/THD.dir/base/DataChannelRequest.cpp.o] Error 1
make[2]: *** Waiting for unfinished jobs....
Apparently the problem was that both libcusparse and aten/src/ATen/native/sparse/cuda/SparseCUDABlas.cu implement cusparseGetErrorString() and for version >= 10.2 the one in the library should be used.
--- aten/src/ATen/native/sparse/cuda/SparseCUDABlas.cu.orig 2020-11-16 12:13:17.680023134 +0000
+++ aten/src/ATen/native/sparse/cuda/SparseCUDABlas.cu 2020-11-16 12:13:45.158407583 +0000
## -9,7 +9,7 ##
namespace at { namespace native { namespace sparse { namespace cuda {
-
+#if 0
std::string cusparseGetErrorString(cusparseStatus_t status) {
switch(status)
{
## -51,6 +51,7 ##
}
}
}
+#endif
inline void CUSPARSE_CHECK(cusparseStatus_t status)
{
I haven't tried yet if it works at runtime but the build is successful.
I've followed all the steps in the official guide. Except I built it using:
$ bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=- msse4.1 --copt=-msse4.2 --config=opt -k //tensorflow/tools/pip_package:build_pip_package
And during ./config I've set the right paths and disabled Google Cloud Platform, Hadoop, XLA, VERBS, OpenCL, CUDA, MPI support.
Hardware:
Macbook Pro 13 inch (mid 2014)
CPU: Intel Core i5 (4278U)
RAM: 8GB
Software:
High Sierra (10.13.2)
Clang Version: clang-900.0.39.2
Bazel Version: 0.9.0
Conda Version: 4.4.3
Python: 3.6.3
All the packages are upto date. This worked perfectly fine 2 months ago on this machine. For some strange reasons it doesn't build anymore now. I'm just posting a part of the error list here:
WARNING: Config values are not defined in any .rc file: opt
ERROR: Skipping 'msse4.1': no such target '//:msse4.1': target 'msse4.1' not declared in package '' defined by /Users/rakshithgb/Documents/Tensorflow/tensorflow/BUILD
WARNING: Target pattern parsing failed.
ERROR: /private/var/tmp/_bazel_rakshithgb/fde7bc60972656b0c2db4fd0b79e24fb/external/com_googlesource_code_re2/BUILD:96:1: First argument of 'load' must be a label and start with either '//', ':', or '#'. Use --incompatible_load_argument_is_label=false to temporarily disable this check.
ERROR: /private/var/tmp/_bazel_rakshithgb/fde7bc60972656b0c2db4fd0b79e24fb/external/com_googlesource_code_re2/BUILD:98:1: name 're2_test' is not defined (did you mean 'ios_test'?)
ERROR: /private/var/tmp/_bazel_rakshithgb/fde7bc60972656b0c2db4fd0b79e24fb/external/com_googlesource_code_re2/BUILD:100:1: name 're2_test' is not defined (did you mean 'ios_test'?)
And it ends like this:
ERROR: /Users/rakshithgb/Documents/Tensorflow/tensorflow/tensorflow/core/kernels/BUILD:550:1: Target '#local_config_sycl//sycl:using_sycl' contains an error and its package is in error and referenced by '//tensorflow/core/kernels:debug_ops'
WARNING: errors encountered while analyzing target '//tensorflow/tools/pip_package:build_pip_package': it will not be built
INFO: Analysed target //tensorflow/tools/pip_package:build_pip_package (203 packages loaded).
INFO: Found 0 targets...
ERROR: command succeeded, but there were errors parsing the target pattern
INFO: Elapsed time: 12.763s, Critical Path: 0.02s
FAILED: Build did NOT complete successfully
Has anyone else had this issue? How do I fix it? I've uploaded the entire error log on GitHub Tensorflow issue page. #15622
Ok it looks like the new bazel version isn't compatible with the current Tensorflow release. It looks like the fix will be issued in the next release. According to this thread on GitHub - #15492
The temporary fix that worked for me was to build it using --incompatible_load_argument_is_label=false in the bazel command. So my build command now looks like this:
$ bazel build --config=opt --incompatible_load_argument_is_label=false //tensorflow/tools/pip_package:build_pip_package
I'm having the following error when trying to load rjags. I recently upgraded to OSX El Capitain and also installed the latest version of JAGS 4.0.1. Does any one know how to fix it?
library(rjags)
Error : .onLoad failed in loadNamespace() for 'rjags', details:
call: dyn.load(file)
error: unable to load shared object '/usr/local/lib/JAGS/modules-3/bugs.so':
dlopen(/usr/local/lib/JAGS/modules-3/bugs.so, 6): Symbol not found: _R_finite
Referenced from: /usr/local/lib/JAGS/modules-3/bugs.so
Expected in: /usr/local/lib/libjrmath.0.dylib
in /usr/local/lib/JAGS/modules-3/bugs.so
Error: package or namespace load failed for ‘rjags’
I found a solution by installing the development version of the rjags package.
http://sourceforge.net/projects/mcmc-jags/files/rjags/4/
I need to develop a gstreamer source element, so after running a script to generate plug-in sources and adding some basic boilerplate code, I got my plug-in to build, however when trying to load it from gst-inspect tool, I get:
(gst-plugin-scanner:10260): GStreamer-WARNING **: Failed to load plugin '/usr/lib64/gstreamer-0.10/libgstbcmdec.so': /usr/lib64/gstreamer-0.10/libgstbcmdec.so: undefined symbol: gst_video_format_new_caps
I found that this symbol should be in gstreamer-plugins-base so I double-checked that its already installed. Also added -lgstvideo-0.10 to the Makefile.am (so added to GST_LIBS) however this doesnt help. Any ideas what I am doing wrong?
I am working on Fedora core 14, 64 bit, and have the latest gstreamer-* packages (used yum).
What is your exact Makefile.am? Is it looking like this?
libgstbcmdec_la_LIBADD = \
$(GST_PLUGINS_BASE_LIBS) -lgstvideo-$(GST_MAJORMINOR) \
...