Easy way to print hex for raw tx hex?

Perhaps, I am mis-using the library. I have to do the following to print tx-hex which is non-intuitive to new users(and even me).
		bitcoin::consensus::encode::serialize_hex(&tx);

We could probably implement LowerHex and UpperHex for everything that implements consensus::Encodable. I don't know that this would be any more discoverable.
What would an intuitive API look like to you?

Not sure if anything but Transaction definitely yes. Hex encoding is very common for transactions.

What would an intuitive API look like to you?

In Fedimint we have consensus_encode_to_vec, and would make sense to have consensus_encode_to_hex.

LowerHex/UpperHex is definitely more idiomatic. We can also probably reuse work in #1254

I had trouble finding serialize_hex at all, @apoelstra had to look it up and encouraged me to ack the related issue. (Hopefully I found the right one)

Thanks @Ademan, improving the hex situation is top of the list atm. (ref: https://github.com/rust-bitcoin/rust-bitcoin/pull/1531#issuecomment-1869004643)

This can potentially be closed by either #2318 or #2039

Closed by #2039

Is this resolved? I still don't find a method of Transaction struct to serialize raw transaction? Are we missing  an implementation of DisplayHex for &Transaction .
Feel free to close this issue if I am missing something

cc @apoelstra @tcharding incase this notification gets lost

Agreed, I dont' think it's resolved. We should implement Display/LowerHex/UpperHex for Transaction and DisplayHex for &Transaction.

I went to do this a month or so ago and decided not to because the code lives in rust-bitcoin (ATM anyway) and I was focusing on the leaf crates.


Running on Mac OSX

Hi, I am trying to get KaHIP running on Mac OSX, but am getting build errors. Does anyone have any suggestions?
I have done the following:
brew install scons
brew install argtable
brew install open-mpi
[check out KaHIP using GitHub desktop]
./compile.sh

I get the error:
clang: error: unknown argument: '-fno-stack-limit'
and
error: unsupported option '-fopenmp'
I have tried using alias g++='gcc-6' but this doesn't make any difference.

COLLECT_GCC=gcc-6
COLLECT_LTO_WRAPPER=/usr/local/Cellar/gcc/6.3.0_1/libexec/gcc/x86_64-apple-darwin15.6.0/6.3.0/lto-wrapper
Target: x86_64-apple-darwin15.6.0
Configured with: ../configure --build=x86_64-apple-darwin15.6.0 --prefix=/usr/local/Cellar/gcc/6.3.0_1 --libdir=/usr/local/Cellar/gcc/6.3.0_1/lib/gcc/6 --enable-languages=c,c++,objc,obj-c++,fortran --program-suffix=-6 --with-gmp=/usr/local/opt/gmp --with-mpfr=/usr/local/opt/mpfr --with-mpc=/usr/local/opt/libmpc --with-isl=/usr/local/opt/isl --with-system-zlib --enable-libstdcxx-time=yes --enable-stage1-checking --enable-checking=release --enable-lto --with-build-config=bootstrap-debug --disable-werror --with-pkgversion='Homebrew GCC 6.3.0_1' --with-bugurl=https://github.com/Homebrew/homebrew-core/issues --enable-plugin --disable-nls --enable-multilib
Thread model: posix
gcc version 6.3.0 (Homebrew GCC 6.3.0_1)

Any suggestions much appreciated!
Thanks

Your output tells you that you use clang. I actually never tried to compile the code with clang. So the easiest for you would be to make sure that gcc is used. If you still want to try clang, you can remove the -fno-stack-limit option and find out how clang supports openmp.
Best,
Christian

Thanks Christian.
For anyone else with this issue, I made some progress by doing the following:
brew reinstall gcc --without-multilib (NB: this took almost 2 hours)
(This installed latest version of gcc, which in my case is gcc-6)
add the following to Sconstruct file in the if SYSTEM == 'Darwin': block (around line 93):
        env['CC'] = 'gcc-6'
        env['CXX'] = 'g++-6'

Thank Peter!

Hi,
First of all, thank you for the detailed explanations. Some progress has been made with the installation thanks to them.
However, the installation continues to fail in the end. I have little experience with C++, so I apologise in advance for any obvious errors on my par.
It Looks as if the installation is still trying to use clang at some point (having seemingly used g++ up until then) even though the environment variables have been altered in the Sconstruct file in the main directory.
@peterwake I cloned the mac installation branch of your repository on my MacBook but it also runs into the same error.
My best guess based on my console output is that mpicxx (see #6 ) seems to be invoking clang for some reason, even though shell mpicxx --showme  returns shell g++ -I/usr/local/include -L/usr/local/lib -lmpi .
Here is my console output:
[…]
scons: done building targets.
scons: Reading SConscript files ...
Checking for C++ header file mpi.h... (cached) yes
scons: done reading SConscript files.
scons: Building targets ...
scons: building associated VariantDir targets: optimized
mpicxx -o optimized/app/kaffpaE.o -c -fopenmp -DNDEBUG -Wall -funroll-loops -fno-stack-limit -O3 -std=c++0x -DMODE_KAFFPAE -O3 -DNDEBUG -funroll-loops -std=c++0x -DMODE_KAFFPAE -DPOINTER64=1 -Iextern/argtable-2.10/include -Ioptimized/extern/argtable-2.10/include -Iextern/argtable-2.10/include -Ioptimized/lib -Ilib -Ioptimized/lib/tools -Ilib/tools -Ioptimized/lib/partition -Ilib/partition -Ioptimized/lib/io -Ilib/io -Ioptimized/lib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib -Ilib/tools -Ilib/partition -Ilib/io -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -I/usr/include/openmpi -I/opt/local/include -Iinclude app/kaffpaE.cpp
mpicxx -o optimized/lib/data_structure/graph_hierarchy.o -c -fopenmp -DNDEBUG -Wall -funroll-loops -fno-stack-limit -O3 -std=c++0x -DMODE_KAFFPAE -O3 -DNDEBUG -funroll-loops -std=c++0x -DMODE_KAFFPAE -DPOINTER64=1 -Iextern/argtable-2.10/include -Ioptimized/extern/argtable-2.10/include -Iextern/argtable-2.10/include -Ioptimized/lib -Ilib -Ioptimized/lib/tools -Ilib/tools -Ioptimized/lib/partition -Ilib/partition -Ioptimized/lib/io -Ilib/io -Ioptimized/lib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib -Ilib/tools -Ilib/partition -Ilib/io -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -I/usr/include/openmpi -I/opt/local/include -Iinclude lib/data_structure/graph_hierarchy.cpp
mpicxx -o optimized/lib/algorithms/strongly_connected_components.o -c -fopenmp -DNDEBUG -Wall -funroll-loops -fno-stack-limit -O3 -std=c++0x -DMODE_KAFFPAE -O3 -DNDEBUG -funroll-loops -std=c++0x -DMODE_KAFFPAE -DPOINTER64=1 -Iextern/argtable-2.10/include -Ioptimized/extern/argtable-2.10/include -Iextern/argtable-2.10/include -Ioptimized/lib -Ilib -Ioptimized/lib/tools -Ilib/tools -Ioptimized/lib/partition -Ilib/partition -Ioptimized/lib/io -Ilib/io -Ioptimized/lib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib -Ilib/tools -Ilib/partition -Ilib/io -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -I/usr/include/openmpi -I/opt/local/include -Iinclude lib/algorithms/strongly_connected_components.cpp
clang: error: unknown argument: '-fno-stack-limit'
clang: error: unknown argument: '-fno-stack-limit'
clang: error: unsupported option '-fopenmp'
clang: error: unsupported option '-fopenmp'
mpicxx -o optimized/lib/algorithms/topological_sort.o -c -fopenmp -DNDEBUG -Wall -funroll-loops -fno-stack-limit -O3 -std=c++0x -DMODE_KAFFPAE -O3 -DNDEBUG -funroll-loops -std=c++0x -DMODE_KAFFPAE -DPOINTER64=1 -Iextern/argtable-2.10/include -Ioptimized/extern/argtable-2.10/include -Iextern/argtable-2.10/include -Ioptimized/lib -Ilib -Ioptimized/lib/tools -Ilib/tools -Ioptimized/lib/partition -Ilib/partition -Ioptimized/lib/io -Ilib/io -Ioptimized/lib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -Ilib -Ilib/tools -Ilib/partition -Ilib/io -Ilib/partition/uncoarsening/refinement/quotient_graph_refinement/flow_refinement -I/usr/include/openmpi -I/opt/local/include -Iinclude lib/algorithms/topological_sort.cpp
scons: *** [optimized/lib/data_structure/graph_hierarchy.o] Error 1
scons: *** [optimized/app/kaffpaE.o] Error 1
clang: error: unknown argument: '-fno-stack-limit'
clang: error: unsupported option '-fopenmp'
scons: *** [optimized/lib/algorithms/strongly_connected_components.o] Error 1
clang: error: unknown argument: '-fno-stack-limit'
clang: error: unsupported option '-fopenmp'
scons: *** [optimized/lib/algorithms/topological_sort.o] Error 1
scons: building terminated because of errors.
compile error in kaffpaE. exiting.

Any suggestions as to what the problem is and/or how it might be fixed would be greatly appreciated.
Regards,
Yani

I added clang support now. The only thing left for you todo is to make sure that your clang installation supports openmp.

@YaniKolev I did get it to work in the end, the problem is looking at my bash history I tried so many things it's difficult to pinpoint what worked. To keep your spirits up, the best news is.. I actually managed to use kaffpae a few days ago to do something! Looking at bash, if you're persuing the gcc option you might try:
mpicxx -v

(does it say clang anywhere)
export OMPI_CC=gcc-6
export OMPI_CXX=g++-6

(does it now NOT say clang anywhere, and mention g++ stuff - in which case try recompiling)

@peterwake @schulzchristian
many thanks for the advice. An OS update coupled with a Peter's advice has seemingly got it to install properly.
However, I wasn't able to make it work with clang (even though my clang 4.0.0 does support openmp).


Keras examples not training

Hello, I am trying to setup Keras on Ubuntu 18.10 with Tensorflow CPU-training. I have installed Keras and Tensorflow with pip3 and copied and pasted the MLP for Binary Classification example from the Keras docs. However when I try to run this example I get the following output:
username@Computer:~/Stock$ python3 Test.py
Using TensorFlow backend.
WARNING:tensorflow:From /home/username/.local/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.
Instructions for updating:
Colocations handled automatically by placer.
WARNING:tensorflow:From /home/username/.local/lib/python3.6/site-packages/keras/backend/tensorflow_backend.py:3680: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.
Instructions for updating:
Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.
WARNING:tensorflow:From /home/username/.local/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.cast instead.
Epoch 1/20
2019-03-07 12:43:21.899003: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2
2019-03-07 12:43:21.906434: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency:<PHONE_NUMBER> Hz
2019-03-07 12:43:21.906786: I tensorflow/compiler/xla/service/service.cc:150] XLA service 0x26df370 executing computations on platform Host. Devices:
2019-03-07 12:43:21.906838: I tensorflow/compiler/xla/service/service.cc:158]   StreamExecutor device (0): <undefined>, <undefined>
1000/1000 [==============================] - 0s 339us/step - loss: 2.4392 - acc: 0.0880
Epoch 2/20
1000/1000 [==============================] - 0s 16us/step - loss: 2.4063 - acc: 0.0890
Epoch 3/20
1000/1000 [==============================] - 0s 16us/step - loss: 2.3452 - acc: 0.1050
Epoch 4/20
1000/1000 [==============================] - 0s 24us/step - loss: 2.3304 - acc: 0.0970
Epoch 5/20
1000/1000 [==============================] - 0s 22us/step - loss: 2.3203 - acc: 0.1200
Epoch 6/20
1000/1000 [==============================] - 0s 20us/step - loss: 2.3172 - acc: 0.1010
Epoch 7/20
1000/1000 [==============================] - 0s 25us/step - loss: 2.3195 - acc: 0.1130
Epoch 8/20
1000/1000 [==============================] - 0s 20us/step - loss: 2.3126 - acc: 0.1110
Epoch 9/20
1000/1000 [==============================] - 0s 26us/step - loss: 2.3158 - acc: 0.0920
Epoch 10/20
1000/1000 [==============================] - 0s 26us/step - loss: 2.3042 - acc: 0.1130
Epoch 11/20
1000/1000 [==============================] - 0s 17us/step - loss: 2.3081 - acc: 0.1020
Epoch 12/20
1000/1000 [==============================] - 0s 17us/step - loss: 2.3064 - acc: 0.1130
Epoch 13/20
1000/1000 [==============================] - 0s 16us/step - loss: 2.3038 - acc: 0.1170
Epoch 14/20
1000/1000 [==============================] - 0s 15us/step - loss: 2.3097 - acc: 0.1070
Epoch 15/20
1000/1000 [==============================] - 0s 13us/step - loss: 2.3162 - acc: 0.0880
Epoch 16/20
1000/1000 [==============================] - 0s 24us/step - loss: 2.3101 - acc: 0.1040
Epoch 17/20
1000/1000 [==============================] - 0s 44us/step - loss: 2.3026 - acc: 0.1020
Epoch 18/20
1000/1000 [==============================] - 0s 41us/step - loss: 2.3051 - acc: 0.0910
Epoch 19/20
1000/1000 [==============================] - 0s 41us/step - loss: 2.3015 - acc: 0.1060
Epoch 20/20
1000/1000 [==============================] - 0s 44us/step - loss: 2.3068 - acc: 0.1100
100/100 [==============================] - 0s 1ms/step

The loss and accuracy seem random and the amount of time per epoch seems suspiciously low. Given that there are no obvious error messages I think the issue is probably a configuration issue. I have tried searching around for similar issues but couldn't find anything related.
Any help would be greatly appreciated.

I looked at the example and noticed this:
# Generate dummy data
x_train = np.random.random((1000, 20))
y_train = np.random.randint(2, size=(1000, 1))
x_test = np.random.random((100, 20))
y_test = np.random.randint(2, size=(100, 1))

As you can see, the model is being trained with random data - there is no relationship between x and y.  Here are some datasets.

Yikes, can't believe I missed that section. I've run some tests with the datasets you linked and they're looking much better. Cheers.


Fix #13671: [Flaky test] BearerTokenAuthenticationPolicy_SucceededFailedSucceeded

Did net - core - ci hang?

I've been cancelling it to rerun tests multiple times

Did you try running it locally in an infinite loop?

Yes. But I can try to run it in parallel


Mobile modal size

The margin is too wide

The solution may be setting a maximmum height for mobile devices and overflow. For example for mobile devices:
  .modal-container {
    overflow-x: auto;
    max-height: 600px;
  }

This is fixed


DSL for Data Modeling

Decomposed to tasks and almost done: https://github.com/metarhia/metaschema


Support alternate kube config file locations

I think this may already be supported via the KUBE_CONFIG env var - but this needs checking and we should still be able to support a --config cli arg


Upgrade of protocol version and governance

From @lucafavatella...
Two things I think we need before the launch - even more than features - are: the process of upgrade of protocol version, and the process of upgrade of governance.

The protocol version is in the block and its header.
I understand the governance tree shall be hashed in the block as all other state trees (e.g. accounts). (Currently the codebase does not include governance in the block.)

Configuration shall be classified:

Items that are in governance since genesis block, hence these items are represented in the genesis block because governance is (TO-BE) hashed in block;

Question: Can oracles only change value of existing governance items, or also introduce new governance items?

Items that are not in governance, and are represented by the protocol version;

I understand these include:

Fields of block header and block;
Serialization of block header and block;
Known transactions and their processing;
Peer-to-peer protocol (?)

Question: Is it possible to link a protocol version to the presence in governance of a certain item?

Anything else?

The result shall be processes established for upgrading the protocol version (e.g. https://github.com/bitcoin/bips/blob/master/bip-0035.mediawiki) and governance. This may enable us to postpone after the launch of the mainnet items that are not urgent.

https://www.pivotaltracker.com/story/show/152479549


0.6.1: build fails with libhwy > 0.15.0

Describe the bug
When building with libhwy > 0.15.0, the build fails with a variety of error messages (.
To Reproduce
Just build with libhwy > 0.15.0. GCC will emit a bunch of error messages related to entities not being found (I suspect they've been moved around).
Expected behavior
libjxl should build fine.
Screenshots
N/A (I have a build log but its insanely huge).
Environment

OS: NixOS 22.05, but this also occurs on Darwin platforms.
Compiler version: GCC 11.3.0 (Apple Clang as well)
CPU type: x86_64
cjxl/djxl version string: JPEG XL encoder v0.6.1 [AVX2,SSE4,SSSE3,Scalar]

Additional context

This can be fixed by building a version of libjxl that is not ancient.

@thebombzen This version is not ancient. According to the releases page, version 0.6.1 is the latest version. And Arch Linux's packages repository also clearly states that version 0.6.1-3 is the latest version. So, if version 0.6.1 is not, in fact, the latest version, where is the latest version, exactly? I would build from master if it weren't for reasons that should be apparent.

0.6.1 was released almost a year ago and predates highway 0.15.0. If you want to build 0.6.1, then build it against highway 0.15.0, which is also the most recent version packaged in the arch repositories.
What are you exactly suggesting be done? 0.7 has a release candidate and it builds against highway 1.0.0. What bug are you suggesting be fixed that isn't already fixed?

I hope this can be closed when 0.7 is released...

I assume this is now working with version 0.7.0


Export Cronjob interprete asterisks by mistake

BUG REPORT INFO
Environment

Cloud provider:  private Cloud

OS details (printf "$(uname -srm)\n$(cat /etc/os-release)\n"):
Linux 5.0.9-200.fc29.x86_64 x86_64
NAME=Fedora
VERSION="29 (Workstation Edition)"
ID=fedora
VERSION_ID=29
VERSION_CODENAME=""
PLATFORM_ID="platform:f29"
PRETTY_NAME="Fedora 29 (Workstation Edition)"
ANSI_COLOR="0;34"
LOGO=fedora-logo-icon
CPE_NAME="cpe:/o:fedoraproject:fedora:29"
HOME_URL="https://fedoraproject.org/"
DOCUMENTATION_URL="https://docs.fedoraproject.org/en-US/fedora/f29/system-administrators-guide/"
SUPPORT_URL="https://fedoraproject.org/wiki/Communicating_and_getting_help"
BUG_REPORT_URL="https://bugzilla.redhat.com/"
REDHAT_BUGZILLA_PRODUCT="Fedora"
REDHAT_BUGZILLA_PRODUCT_VERSION=29
REDHAT_SUPPORT_PRODUCT="Fedora"
REDHAT_SUPPORT_PRODUCT_VERSION=29
PRIVACY_POLICY_URL="https://fedoraproject.org/wiki/Legal:PrivacyPolicy"
VARIANT="Workstation Edition"
VARIANT_ID=workstation

Version of Ansible (ansible --version):
n/a

Version of Jinja (pip freeze | grep -i jinja):
n/a

Version of Shade (pip freeze | grep -i shade):
n/a

The openstack-ansible-contrib version (commit) (git rev-parse --short HEAD):
d16d2f7

Copy of inventory files and custom variables used (please omit your secrets!):
n/a
Command used to invoke ansible:
n/a
Output of ansible run:
n/a
Anything else do we need to know:
This is abou the script reference-architecture/day2ops/scripts/project_export.sh.
Part of the project are cronjob configurations and they include crontab style scheduling configuration (e.g. "1 4 */5 * *"). Unfortunately the asterisks will be interpreted by shell interpreter. This led to unusable cronjob files. Each asterisk is replaced by names of all files in current working directory.
The incorrect line in code is:
if [ "$(echo ${BUFFER} | jq '.items | length > 0')" == "false" ]; then
The BUFFER variable needs to be surrounded by '"'.

Hello, this issue is still present. Does no one use the export_project.sh script to export cronjob configurations?


Add mandatory build before any rush or npm publish

Failed release of 0.1.3-16 because of silent failure of @misk/core build and published package that didn't have a lib directory.

Add following task to all package.json and to package template in @misk/cli
"prepare": "npm run-script ci-build",


Documentation - Can we add an example to Manage Controlled Process(MCP) > Data Importer tool

Required Information

[ ] AEM Version, including Service Packs, Cumulative Fix Packs, etc: AEM 6.3.x, AEM 6.4
[ ] ACS AEM Commons Version: 3.16.0
[ ] Reproducible on Latest? yes

Improve documentation
Can we add an example to the "Data Importer" tool on Manage Controlled Process (MCP) > Data Importer tool
Attached Example
Attaching an example.
data-importer-sample-weretail-activities-added-jcrtitle.xlsx
Notes

I used AEM 6.4's "Metadata Export" option to generate the spreadsheet. Added "jcr:title" additional column.
The first column of the spreadsheet must be "path"
I added jcr:title column. When we run MCP > Data Importer with this file, assets under we-retail/activities will have "jcr:title" applied.

That's a fantastic idea, but we have a separate repository for the docs.  Can you open the issue here? https://github.com/Adobe-Consulting-Services/adobe-consulting-services.github.io
Thanks for your contribution.


The pretrained model is not in accordance with resSFCN

The len of pretrained model's state_dict is 488 and that of resSFCN is 582.
If I want to finetune the model, what the details should I notice? For example, in shanghaiB, how to preprocess images and how to set optimizer?

some layers in resSFCN do not the learnable parameters, such as ReLU, Pooling, etc. so the length of save weights is not same as that of the graph in the code.
you could directly run our code, which will work well.
__C.TRAIN.PRE_GCC_MODEL = './pre/Pretrained_GCC.pth': finetune the model using GCC pretrained model
__C.TRAIN.PRE_GCC_MODEL = '':  finetune the model using ImgNt pretrained model
for shanghai b, we will release the code in C^3 Framework. We will only focus on the implementation on the new framework.
If you want to finetune the model on shanghai B, you should replace the hyper parameters as follows:
__C.DATA.MEAN_STD  and __C.DATA.DATA_PATH.

Other parameters should fixed.


Codabar support

QuaggaJS would be useful for libraries (I mean book-lenders, not code resources!) if it supported the Codabar symbology. There is already web-based software for loaning books to borrowers, and integrating QuaggaJS could make any tablet with a webcam capable of being a checkout computer. Thanks!

Support for Codabar was just released with the merge of https://github.com/serratus/quaggaJS/pull/28


Arch linux clang doesn't find standard library headers

Describe the bug
With standard clang version 6.0.1 and gcc version 8.2.1 (delivers std lib on arch) there is an issue of clang complaining that he does not find following headers:

string
map
cmath
functional
limits

When compiling self written programs these issues do not occur. I've tried to edit the CMakeLists.txt by adding the include_directories where these files reside. This works, but then multiple files complain about an undeclared identifier "strlen".
I suppose the issue resides in customizing parameters when executing clang.
The cmake generator line i use is provided in your build guide:
CC=/usr/bin/clang CXX=/usr/bin/clang++ \     cmake -G Ninja -DCMAKE_BUILD_TYPE=Debug -DCMAKE_INSTALL_PREFIX=../debug/filament ../..
This happens on a standard clean install of arch linux with the newest version of clang and gcc.

Thanks for the report. Do you have libc++-dev installed? We require the use of clang and of the clang STL. Based on the error you're describing it sounds like you don't have libc++dev. The README has more information on the prerequisites.

Let me inform you that Arch linux has no such package. Clang in arch uses the gcc standard library by default if i'm not mistaken.

That may be but our code doesn't compile with GCC's standard library.

Ok then it's a personal problem of mine, and i'll try to fix it. Just consider this a headsup than that your project does not compile on arch linux out of the box.

I definitely appreciate the heads up. I'll investigate a bit more and try to find the package name for arch Linux to update our readme.

libc++ might be available under the name libcxx. AUR has a libc++ apparently.

Building it now, i'll get back to you with results. My mistake that i didn't check that out before creating an issue.

No need to apologize, I know it would be a lot easier if it worked with any combination of gcc/clang/libstdc++/libc++ :)

Thank you my friend! It compiles now :) Sorry for wasting your time. I'm excited to explore your engine ;)

Glad you were able to get it to compile, don't hesitate if you run into other issues!

I also can't build it on Arch due to libc++ problem
I installed the libc++ package from AUR so in my /usr/lib/ directory I see files:
-rwxr-xr-x  1 root root       28 Aug 25 12:18 libc++.so
lrwxrwxrwx  1 root root       13 Aug 25 12:18 libc++.so.1 -> libc++.so.1.0
-rwxr-xr-x  1 root root   849936 Aug 25 12:18 libc++.so.1.0

I can run examples from Clion, but when I try to build release(no matter if it's via build.sh file or CMake/Ninja) then I get:
/usr/bin/ld: cannot find -lc++
clang-6.0: error: linker command failed with exit code 1 (use -v to see invocation)

Same as @wefhy, I have both libc++ and libc++abi installed from the AUR (on Manjaro) but ld still can't find -lc++

I have the same problem with Arch and the libc++ from AUR.
Building with ./build release says that ld cannot find -lc++.
But if I try ld -lc++ --verbose then ld finds libc++:
attempt to open /usr/x86_64-pc-linux-gnu/lib64/libc++.so failed
attempt to open /usr/x86_64-pc-linux-gnu/lib64/libc++.a failed
attempt to open /usr/lib/libc++.so succeeded
...

Maybe It's something to do with how ninja finds the libraries, I don't really know how ninja works. I think I'll try to build using a Docker image when I have the time.

Also, I don't think Ninja is a problem here, because the same thing has happened to me when using make (using the -m option).
Right now, the Manjaro repository hosts a libc++ / libc++abi package, but it does not include static libs. To fix this, you need to clone the PKGBUILD from the manjaro package Git repo (https://gitlab.manjaro.org/packages/community/libcxx.git), add the option options=('staticlibs') for the functions package_libc++() and package_libc++abi() in the PKGBUILD, and install it manually using makepkg -si --nocheck.
However, even when the libc++ static libraries are detected, it seems like there are still some problems left. I get a lot of linker errors, such as:
(.text._ZNSt3__17promiseIvE28set_exception_at_thread_exitESt13exception_ptr+0x63): undefined reference to `__cxa_allocate_exception'
/usr/bin/ld: (.text._ZNSt3__17promiseIvE28set_exception_at_thread_exitESt13exception_ptr+0x7d): undefined reference to `__cxa_guard_acquire'
/usr/bin/ld: (.text._ZNSt3__17promiseIvE28set_exception_at_thread_exitESt13exception_ptr+0xc3): undefined reference to `__cxa_guard_release'
/usr/bin/ld: (.text._ZNSt3__17promiseIvE28set_exception_at_thread_exitESt13exception_ptr+0xed): undefined reference to `__cxa_throw'
/usr/bin/ld: (.text._ZNSt3__17promiseIvE28set_exception_at_thread_exitESt13exception_ptr+0xfd): undefined reference to `__cxa_free_exception'

I thought maybe there are some incompatibilities between my current system's clang and libc++. But then I've checked that the two are both version 7.0.1. I am still investigating this error...

Finally solved the problem!
To compile release builds in Arch Linux (or Manjaro), you need to also link libc++abi. You need to use the flag FILAMENT_REQUIRES_CXXABI=ON when running build.sh. (Reading the project's CMakeLists.txt file, this flag was originally intended for CI environments...)

Thanks for the report! Note that this workaround is mentioned in the README.md file.


Error when using quotes

When there is something like: ``blablabla", it is a problem in the markdown render. While this is the correct way to write quotes in LaTeX, markdown interprets it as code (?).
This problem has been seen in: http://arxiv.org/abs/2309.13116v1.

Solved in new alpha.


MAINT: Replace npy_3kcompat.h shims

Reference issue

Continued work to remove all Python2 Code #11584
Follows after #11744
What does this implement/fix?

Removes about half of SciPy's use of npy_3kcompat.h.
What's left is the npy_capsule shims which just clear PyErr
static NPY_INLINE PyObject *
NpyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *))
{
    PyObject *ret = PyCapsule_New(ptr, NULL, dtor);
    if (ret == NULL) {
        PyErr_Clear();
    }
    return ret;
}

I'm hoping I can just change these over and we get better error handling and we no longer depend on numpy py3k.h
Additional information

Updated two comments. Thanks for coming back to review this

All green, so merged. Thanks @sethtroisi!

Updated two comments. Thanks for coming back to review this

you're welcome, sorry it took a while.


Release Google.Cloud.Bigtable.Common.V2 version 1.1.0

Changes since 1.0.0:

Resource name types have Format methods

(Doing Common first will make it easier to do the other ones separately, I think.)


Phi3.5-Vision - Data - training and post training

Hi!
Thank you for your work and for sharing it !
I wanted to know if the post-training data you used to do SFT (33B tokens) and the one you used for DPO were open source
Also, did you share the filtering scripts/methods you are referring to in the paper as well as the pretraining dataset?
Thank you

You can find detailed information about the Phi-3.5 models, including Phi-3.5 Vision, in the following academic papers and resources:
Phi-3 Technical Report on arXiv: This paper provides an in-depth look at the Phi-3.5 series, including the datasets and training methods used. It discusses the advancements in multilingual, multimodal, and long-context capabilities of the Phi-3.5 models.
https://arxiv.org/pdf/2404.14219
Microsoft Tech Community Blog: This blog post highlights the features and capabilities of the Phi-3.5 models, including Phi-3.5 Vision, and provides insights into their performance and applications. https://techcommunity.microsoft.com/blog/azure-ai-services-blog/discover-the-new-multi-lingual-high-quality-phi-3-5-slms/4225280

Thank you @leestott, but can you maybe point me to the data that was used if it was released?
I would like to reproduce Phi-3.5 Vision from the Phi3.5 language model. Is there a training script and data for that?
I could not find it
Best
Estelle


argwhere() needs to respect column major layout

I've been trying to use xt::filter(), and it works in most cases, but I am having the usual problem where my column major object is being traversed in a row major fashion.
I believe the underlying issue is that xt::filter() calls argwhere() on the condition, and I don't think argwhere() respects the column major layout.
// [[Rcpp::depends(xtensor)]]
// [[Rcpp::plugins(cpp14)]]

#include "xtensor-r/rarray.hpp"
#include "xtensor/xindex_view.hpp"

// [[Rcpp::export]]
SEXP filter_traversal(SEXP x_, SEXP condition_) {
  xt::rarray<int> x = x_;
  xt::rarray<rlogical> condition = condition_;
  auto out_view = xt::filter(x, condition);

  xt::rarray<int> out = out_view;

  return out;
}

Rcpp::sourceCpp("~/Desktop/test.cpp")

x <- array(1:8, c(2, 2, 2))
idx <- array(rep(c(TRUE, FALSE), 4), c(2, 2, 2))

x
#> , , 1
#>
#>      [,1] [,2]
#> [1,]    1    3
#> [2,]    2    4
#>
#> , , 2
#>
#>      [,1] [,2]
#> [1,]    5    7
#> [2,]    6    8

idx
#> , , 1
#>
#>       [,1]  [,2]
#> [1,]  TRUE  TRUE
#> [2,] FALSE FALSE
#>
#> , , 2
#>
#>       [,1]  [,2]
#> [1,]  TRUE  TRUE
#> [2,] FALSE FALSE

filter_traversal(x, idx)
#> [1] 1 5 3 7

If traversed in a column major fashion, the correct result is c(1, 3, 5, 7).

Working great thanks!


Documentation generation failing

The doc generation process is failing due to changes moving from the protobuf beta to stable. We use two tools for generating RST documentation from protobuf that need to be updated to support this version, or an alternative solution should be found.
We need to add make docs to the .travis.yml.
Exception occurred:
  File "/home/david/git/schemas/env/local/lib/python2.7/site-packages/docutils/writers/_html_base.py", line 672, in depart_document
    assert not self.context, 'len(context) = %s' % len(self.context)
AssertionError: len(context) = 1
The full traceback has been saved in /tmp/sphinx-err-eTK5l1.log, if you want to report the issue to the developers.
Please also report this if it was a user error, so that a better error message can be provided next time.
A bug report can be filed in the tracker at <https://github.com/sphinx-doc/sphinx/issues>. Thanks!
Makefile:31: recipe for target 'docs' failed
make: *** [docs] Error 1
(env) ➜  schemas git:(maste

Was unrelated to our changes, a bug in docutils https://github.com/sphinx-doc/sphinx/issues/3212 . We can fix our build process, but readthedocs is currently still failing.

RTD is now passing. Closing


pipeline_cellranger.py r1len and r2len parameters being interpreted as False rather than "false"

A couple of bugs found when running cellranger count and speficying r1-length: "false" and r2-length: "false" in pipeline_cellranger.yml.
The issue is that iotools.py from cgat-core is used to process the PARAMS dict. The str2val function converts anything that is for example "false" to False. This resulted in the string "False" being substituted into the commandline status when the lengths were specified as "false" rather than "".
Also the pipeline looks for r1-length and r2-length in the gex: section of the yml rather than the count section so have copied this into the gex: section. Can probably remove from the count: section although haven't tested if it breaks anything downstream yet...

Hi Nick, thanks but the changes submitted seem to relate to the previous pull request?

Hi Nick, thanks but the changes submitted seem to relate to the previous pull request?

Oops, I've done something odd here. I actually made changes on a new branch but this was before I pulled the previous changes. Have opened another pull request for review.

Also we are not seeing the conversion of "false" to "False" that you have described, which may be due to a difference in our environment setup so I think a fix here needs to be able to recognise a set of values e.g.
"false"|"False"|False|""


3.1.7: "paket install --log-file" blows up right away with IndexOutOfRangeException

Documentation shows Filename parameter for --log-file command line switch as optional, but attempt to omit log file name causes Paket to break right away with IndexOutOfRangeException.

You mean if you don't provide a name but still set the switch?

Yes. From the doc it looks perfectly legal, although it does not tell what the default log file name is going to be.

@eiriktsarpalis is this something Argu could handle?

sorry this is not coming from argu. fixing it now


Docker/refact

refactor Docker role to make it easy to maintain

split into different tasks per OS
updates some task to build ansible modules
move logic checks on each task to high level to mitigate DRY

Checklist

[x] commit message has one of the standard prefixes
[x] faq.md updated if appropriate
[ ] other documentation is changed or added (if applicable)
[ ] playbook changes run through VPC or QPC (if you have access)
[ ] for inventory.yml changes, bastillion/nagios/jenkins updated accordingly

@zdtsw will need a rebase.

One spelling mistake. Love splitting it out into individual files! Does this definitely cover all our bases in terms of platforms? I've noticed we don't install docker / podman for RHEL8, either in the new or old version. Is this something we need @sxa ?

Not strictly required since we'd cover that with jenkins machine labels, but ideally we'd include it on there.

Some small changes and also GH Actions sent warnings like:
schema [{'os_img': 'aix/ppc64/jdk'}, {'heap': 'normal'}, {'impl': 'hotspot'}, {'new_baseurl': 'https://api.adoptium.net/v3/binary/latest'}, {'new_vendor': 'eclipse'}, {'baseurl': 'https://api.adoptopenjdk.net/v3/binary/latest'}, {'vendor': 'adoptopenjdk'}, {'project': '{{ heap }}/{{ vendor }}?project=jdk'}] is not of type 'object'
BootJDK

the thing is, I do not think on block level, can set vars.
the change was introduced in this March, could that be something not run yet and never caused issue?

Yes that's fine, let's fix later.


Main docs should have (FCMv1 photos and instructions instead of (FCM/GCM)

Main docs should have (FCMv1 photos and instructions instead of (FCM/GCM)
https://github.com/MicrosoftDocs/azure-docs/blob/416f2ad4185378fe9a42f8aa5c931167e4d82100/articles/notification-hubs/configure-notification-hub-portal-pns-settings.md?plain=1#L51C1-L62C1

Document Details
⚠ Do not edit this section. It is required for learn.microsoft.com ➟ GitHub issue linking.

ID: 2045c90e-edae-77ba-d115-366e72c4326f
Version Independent ID: 172fdb07-e39d-3d8b-ed64-6a88c8cbf8a2
Content: Set up push notifications in Azure Notification Hubs
Content Source: articles/notification-hubs/configure-notification-hub-portal-pns-settings.md
Service: notification-hubs
GitHub Login: @sethmanheim
Microsoft Alias: sethm

@SuhitAgarwal
Thank you for bringing this to our attention.
I've delegated this to content author, who will review it and offer their insightful opinions.


Update how-to-integrate-web-pubsub.md

Remove duplicate row

@mcleanbyron
Can you review the proposed changes?
When the changes are ready for publication, add a #sign-off comment to signal that the PR is ready for the review team to merge.
#label:"aq-pr-triaged"
@MicrosoftDocs/public-repo-pr-review-team

#sign-off


serialize error

message tmp{};
return tmp;
DEBUG mode:
if (!_field)  fill "0xCC"
lead to wrong judgment.
sample code:
proto::message msg;
msg.append_child(proto::message(proto::types::type_binary, 1, "hello"));
auto buffer = msg.serialize();

DEBUG mode:
buffer = ""

Hi, which compiler you using? return a temporary value is not good , so there is a fix #d3cca32, you can try this.
Thank your report! 🍺

It's awesome. :thumbsup:
The new version is also compatible with 64bit. :satisfied:


fix: Wrong return value

What type of PR is this?
/kind bug
What this PR does / why we need it:
Fixed the error in the return value

/approve


enh: support stmt via ws

Codecov Report

Merging #187 (e2eb5c6) into 3.0 (1b52bd5) will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##              3.0     #187   +/-   ##
=======================================
  Coverage   81.19%   81.19%
=======================================
  Files          20       20
  Lines        2568     2568
=======================================
  Hits         2085     2085
  Misses        483      483

:mega: We’re building smart automated test selection to slash your CI/CD build times. Learn more


after forge-extension update: error message with local path (which is not mine) when "background removal" activated

title says it, just updated the ic-light extension in forge and this is the error message i get in the cmd-window:
"
2024-06-08 11:30:02.0788894 [E:onnxruntime:Default, provider_bridge_ort.cc:1534 onnxruntime::TryGetProviderInfo_TensorRT] D:\a_work\1\s\onnxruntime\core\session\provider_bridge_ort.cc:1209 onnxruntime::ProviderLibrary::Get [ONNXRuntimeError] : 1 : FAIL : LoadLibrary failed with error 126 "" when trying to load "E:\ai_gh_repos\webui_forge_cu121_torch21\system\python\lib\site-packages\onnxruntime\capi\onnxruntime_providers_tensorrt.dll"

*************** EP Error ***************
EP Error D:\a_work\1\s\onnxruntime\python\onnxruntime_pybind_state.cc:456 onnxruntime::python::RegisterTensorRTPluginsAsCustomOps Please install TensorRT libraries as mentioned in the GPU requirements page, make sure they're in the PATH or LD_LIBRARY_PATH, and that your GPU is supported.
when using ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider']
Falling back to ['CUDAExecutionProvider', 'CPUExecutionProvider'] and retrying.

"
still, rendering is being done, but unsable if background removal is activated.
if not, everything seems to be working as expected.

not sure, if related to that:
in img2img, i see barely a difference between the the generated image and the init-image, if "Reinforce Foreground" is activated. as though ic-light didn't do any relighting at all.

more of a question:
prior to this update, txt2img in fbc mode had gradients. now there only the option to use a custom image. is there s.th. wrong on my side or have those been removed?

*************** EP Error ***************
EP Error D:\a_work\1\s\onnxruntime\python\onnxruntime_pybind_state.cc:456 onnxruntime::python::RegisterTensorRTPluginsAsCustomOps Please install TensorRT libraries as mentioned in the GPU requirements page, make sure they're in the PATH or LD_LIBRARY_PATH, and that your GPU is supported.
when using ['TensorrtExecutionProvider', 'CUDAExecutionProvider', 'CPUExecutionProvider']
Falling back to ['CUDAExecutionProvider', 'CPUExecutionProvider'] and retrying.

This is a ONNX related issue. @Haoming02 do you know if we need to add any extra dep requirement to the extension?

not sure, if related to that:
in img2img, i see barely a difference between the the generated image and the init-image, if "Reinforce Foreground" is activated. as though ic-light didn't do any relighting at all.

Can you share your generation setup?

more of a question:
prior to this update, txt2img in fbc mode had gradients. now there only the option to use a custom image. is there s.th. wrong on my side or have those been removed?

Yes. They are removed. Previously they are just short-hand for testing purpose.

This is a ONNX related issue. @Haoming02 do you know if we need to add any extra dep requirement to the extension?
so, i guess, i'll just wait and see... or is there sth on my side, that i could do to make it work?

Can you share your generation setup?
sure, here are 2 screenshots, one with and the other without "Reinforce Foreground" activated:

Yes. They are removed. Previously they are just short-hand for testing purpose.
ok. thx.

The Onnx issue should already be fixed by the install.py though.
It should automatically install a onnxruntime package that uses CPU.

The Onnx issue should already be fixed by the install.py though. It should automatically install a onnxruntime package that uses CPU.

looked at the path, that is given in the error message "2024-06-08 18:29:40.9022887 [E:onnxruntime:Default, provider_bridge_ort.cc:1534 onnxruntime::TryGetProviderInfo_TensorRT] D:\a_work\1\s\onnxruntime\core\session\provider_bridge_ort.cc:1209 onnxruntime::ProviderLibrary::Get [ONNXRuntimeError] : 1 : FAIL : LoadLibrary failed with error 126 "" when trying to load "E:\ai_gh_repos\webui_forge_cu121_torch21\system\python\lib\site-packages\onnxruntime\capi\onnxruntime_providers_tensorrt.dll""

so, it is there.

Hmm. By default, it should be using the CPU one. Why is it loading the tensorrt one?
I also had this issue before, but after I manually pip install onnxruntime, the issue went away...

And yeah, I just checked my installation. My onnxruntime does not have those .dll files.
I guess the problem is, the Webui checks that onnxruntime is already installed, so it didn't install it again.
Hence why yours is still using providers other than CPU.

Others also had the same issue: https://github.com/danielgatis/rembg/issues/312
The simplest solution is to uninstall the gpu version and install the cpu version...

yes, i just installed the remb extension and it shows the same behaviour.
not sure, if uninstalling the current gpu-version and installing the cpu-version would have an impact on other installed extensions.
just for the fun of it, i renamed the folder of that runtime and started the server, obviously resulting in a list of error message, starting from "insightface" to whatnot...
i wonder if there'd be a more convenient solution to this.

Others also had the same issue: danielgatis/rembg#312
The simplest solution is to uninstall the gpu version and install the cpu version...

from what I remember the cpu version is pretty slow even on my 14700k and consumes a lot of power. Maybe we should revert to the old rembg implementation that didn't have any issues running on GPU.
The current one doesn't use the embedded python but searches for dependencies system wide for some reason and fails if you don't have cudnn etc installed and added to path.

It's instant on 13700 though?
How large of an image were you processing?

It's instant on 13700 though?
How large of an image were you processing?

strange, it was probably around 5-7 secs last time I checked with a 900px-1024px image

btw, can anyone try
pip uninstall rembg
pip install rembg[gpu]

to see if it can work with non-CPU version of onnxruntime

btw, can anyone try
pip uninstall rembg
pip install rembg[gpu]

to see if it can work with non-CPU version of onnxruntime

No differences for me, even if I completely remove the rembg though venv I get the same error.

pip list

Pain...
So you either get fricked by HuggingFace or by onnxruntime 🤣

Pain...
So you either get fricked by HuggingFace or by onnxruntime 🤣

yup these dependency/package compatibility issues are a huge pain, fortunately I don’t get them so often.
I’ll keep trying, the harder the better. Giving up is the last thing I can do.

@dermesut @huchenlei @Haoming02
lil update from me
A)
I've tried installing cuda, cudnn and tersorrt stuff as suggested here https://github.com/danielgatis/rembg/issues/312#issuecomment-1465316591
I got rid of all the errors and warnings, however the bg extraction speed incresed drastically and took 1 minute for 800px image. :O
B) I've removed the tensorrt libs, replaced the onnxruntime with onnxruntime-gpu in the install.py file. Also removed the rembg and onnxruntime packages from the \system\python\Lib\site-packages folder to make sure Forge does a clean install on startup.
rembg finally started to use cuda instead of tensorrt and the bg extraction speed went down to 1-2 secs.
So to summarize:
tensorrt (onnxruntime): 60 secs
default (unknown): 7 secs
cuda (onnxruntime-gpu): 1-2 secs
N.B. also to mention that I had a newer driver with CUDA 12.5, that onnxruntime didn't support yet. Make sure you have the right cuda and cudnn versions. https://onnxruntime.ai/docs/execution-providers/CUDA-ExecutionProvider.html#requirements or just wait for a newer version (1.18.1) later this month.

I just checked on my Automatic1111 installation, which has both onnxruntime and onnxruntime-gpu, and there is also onnxruntime_providers_tensorrt.dll inside ~webui\venv\Lib\site-packages\onnxruntime\capi.
But the IC-Light still works fine with no error. Can this somehow be a error caused by Forge?

I just checked on my Automatic1111 installation, which has both onnxruntime and onnxruntime-gpu, and there is also onnxruntime_providers_tensorrt.dll inside ~webui\venv\Lib\site-packages\onnxruntime\capi.
But the IC-Light still works fine with no error.
Tested on Forge as well, still no error.
Also tested by renaming the TensorRT folder (to break the SYSTEM PATH), still no error.
Guess I will test with a clean install later.

Could just be a driver compatibility issue, like in my case.

After updating onnxruntime-gpu to 1.18.1 and installing the latest rembg version the issue went away (bg removal is super fast again)
rembg di per se is not so accurate and good at removing backgrounds, but that's another question.

I happened to encounter that after installing onnxruntime-gpu, an error would be reported. I uninstalled onnxruntime and installed it again, and the error disappeared.


I'm not getting feedback

I'm trying to get it works.
Everything seems to be well configured, but when I'm trying to get some feedback... you can see behavior here.
This is my related .zshrc related configuration:
plugins=(git zsh-syntax-highlighting zsh-autosuggestions history z kubectl kube-aliases docker helm zsh_codex)
zle -N create_completion
bindkey '^X' create_completion

Also, here my ~/.config/open:
[openai]
organization_id = <org_...>
secret_key = <secret_key>

Could you try to install openai using pip install openai? You seem to have installed openapi instead of openai.


Fix: Readmore component needs refining

Readmore component needs refining
This fixes the readmore component's line height to be central with the arrow as well as the padding of the additional text when expanded.

📦 Published PR as canary version: 4.0.0--canary.289.d8f43e6.0

:sparkles: Test out this PR locally via:
npm install<EMAIL_ADDRESS>npm install<EMAIL_ADDRESS>npm install<EMAIL_ADDRESS># or
yarn add<EMAIL_ADDRESS>yarn add<EMAIL_ADDRESS>yarn add<EMAIL_ADDRESS>

Can we switch these to px sizes, nothing else is in rem so would rather everything is static

Done


Module not found: @babel/runtime

Describe the bug
I'm getting an error after updating NextJS version:
error - ./node_modules/next-firebase-auth/build/index.browser.js:1:1496
Module not found: Can't resolve '@babel/runtime/helpers/objectWithoutProperties'

Import trace for requested module:
./services/initAuth.js
./pages/_app.js

Versions
next-firebase-auth version: 1.0.0-canary.4
Firebase JS SDK:

firebase: 9.6.1
firebase-admin: 10.0.1

Next.js: 12.0.8-canary.13 (updated from 12.0.7)
To Reproduce
Steps to reproduce the behavior:

Create a project following your guide
Use next 12.0.8-canary.13
See error

Expected behavior
Should work, but fails.
Additional context
It seems NextJS is pre-compiling its dependencies and now @babel/runtime has been precompiled so it is not available and must be set as dependency in your package.
https://babeljs.io/docs/en/babel-plugin-transform-runtime
Temporary fix
Install the package as a dependency in the webpage project: yarn add @babel/runtime or npm i @babel/runtime (then it works).
Thank you very much for this great package, it is really useful 📈🚀

Fixed in #501.


a disabled mat-expansion-panel cannot be expanded programmatically

Reproduction
https://stackblitz.com/edit/angular-qz4usp?file=src/app/expansion-steps-example.html
Steps to reproduce:

in example, first panel is disabled and the second is not
the first button will call "open" on the first panel, and the second, the second.
notice that the first button doesn't work, but the second does

Expected Behavior
By calling "open" programmatically (via button click), I expect the disabled panel to open, as per the docs

Expansion panels can be disabled using the disabled attribute. A disabled expansion panel can't be toggled by the user, but can still be manipulated programmatically.

Actual Behavior
The disabled (first) panel won't open programmatically
Environment

Angular: 8.2.9
CDK/Material: 8.2.2
Browser(s): chrome 79
Operating System (e.g. Windows, macOS, Ubuntu): windows 10

You can see in this stackblitz example how you can achieve this, it's basically your example but with functionality to open or close expansion panel programatically:
https://stackblitz.com/edit/angular-qz4usp-rkdmag?file=src%2Fapp%2Fexpansion-steps-example.html


BUG: Remember Ping Broken

The option to remember the ping state is no longer working.

Fixed in my fork https://github.com/12944qwerty/better-replies


Added support for #488 - UI Internationalization

Added support for #488 - UI Internationalization:

i18next integration
created translation select dropdown component
to start, implemented footer translation strings for es, en, de, fr, pt

Added dependencies/libraries:

i18next
react-i18next
react-dropdown-select

TODO:

further translations (need help w/ this)

I could work on the french translation!

Feel free to @ me to work on the Brazilian Portuguese translation

Looks good, I'm going to leave this open until we extract more strings

Can help with the Hungarian translation.

Can help with the Hungarian translation.

@KristofKekesi Added Hungarian, ready to be translated!

I can work for Tagalog translation

I can do Spanish (es) and Catalan (ca) 👍🏼

I can work on European Portuguese (pt-pt) translation

If you need a French or Arabic translation I could help.

Can work on Turkish translation.

can help with Arabic (Modern Standard Arabic) (ar)

@Karem34 I wonder if it would be possible to translate to each Arabic dialect. الفصحى could work too thoguh

we need RTL support for that

@nadirabbas RTL?

@DGKSK8LIFE Right-to-left text direction.

@DGKSK8LIFE there are too many dialects to count, most arabs will understand msa

@DGKSK8LIFE there are too many dialects to count, most arabs will understand msa

Yeah agreed. Especially those with internet access. And the functionality is pretty simple/clear so msa should work.

Can work on russian translation.


For variable COLRv1, ensure that bounding box is large enough for all variable positions

Leaving it here so we don't forget. In a conversation with Ben we came to speak more about bounding boxes.
In a variable COLRv1 font, it's important to ensure that the bounding box we place in glyf is large enough. FontTools may want to compute the union or the max rectangle of all variable positions and make a static bounding box, or (possibly harder) to find a way to scale the bounding box variably correctly while the COLRv1 glyph changes with variations.

CC @bungeman

ensure that the bounding box we place in glyf is large enough

but CFF2 glyphs won't have such predefined bounding box. Or maybe you talking about the invisible points that nanoemoji adds to the fallback b/w glyph (be it glyf or CFF) so that it's computed bounding box (ignoring the nominal one which is only stored in glyf and may lie) encompasses all the color glyph layers?
In that case, I don't think the issue is with fonttools, but rather with the authoring tools like nanoemoji that create the variable COLRv1 font.

but CFF2 glyphs won't have such predefined bounding box. Or maybe you talking about the invisible points that nanoemoji adds to the fallback b/w glyph (be it glyf or CFF) so that it's computed bounding box (ignoring the nominal one which is only stored in glyf and may lie) encompasses all the color glyph layers?

Yes.

In that case, I don't think the issue is with fonttools, but rather with the authoring tools like nanoemoji that create the variable COLRv1 font.

Maybe so, yes. It would be an additional benefit if fontTools could check that the bounding box is not too small. Ben and I talke about the case of a narrow, high rectangle for example that has a variable PaintRotate applied, which then widens the bounding box. Someone, maybe nanoemoji, needs to ensure that there's a large enough bounding box in all extremes in the variations space. I leave it up to you if we want to track that here or in nanoemoji.

Computing the bounding box is in general a very hard problem.


Saving 170k+ entries crashes process

Any idea on how to increase performance for bigger scale?

Hello!
I have planned to fix this issue coming 2 weeks. But basically this issue  is about bounding RAM usage. I am working on a video on-demand solution with Peerbit and I am starting to see similiar issues when videos are long.
Two things to fix

Basically (I am assuming you are using the Document store). Is that the index is now in memory, but needs to be on disc when there are many documents. One "easy" solution is the change out the index "engine" to SQLLite with OPFS storage and that problem would be solved.

For the syncing engine, the hashes of all "heads" are kept in memory. This will eventually also create a problem that is similar to (1) and needs to be solved in a similar way as (1). The RAM usage due to this is most likely lower than for the document index.

fire, keep me updated!


executor: use const generics to optimize hash join

Generate hash join code in the compilation time to avoid testing join types during the execution for every row.

It is weird that all planner tests work on my machine .....


Update Dolphin to 4.0-8727

Just updating Dolphin to the latest available version.

Thank you for the contribution. It was merged directly as 85bb642f337609d195e0012c7de8ce278011d2fb to keep commit history cleaner. Your contribution is still credited to you.


forced square format issue after fixing the new access token issue

Hey,
Bit of a newbie here.
I am displaying on my website the last image of my Instagram feed, vertical sized (not square) adjusted in height to fit a box.
Everything worked perfectly until I had to update the access token, which I just did.
My Instagram was perfectly fitting the box, now it seems like it's adding left and right white borders to force a square format.
(I ticked the "non-square format on the Instagram website, is it just not supporting other formats now ?)
Thanks,
Edit : got my new access token via pixelunion - have no idea where to get my own

having the same exact problem, i configured to work with new non-square media. Then it broke today. New access token made images comeback, but back to only square.

@paxnot where did you get your new access token ?

@paxnot found the solution. You need to get the access token by yourself on your instagram developer's page. Here is a simple step by step explaination on how to get it.
You still need to tick the "non-square media" box in your app settings.
Worked perfectly for me !
http://jelled.com/instagram/access-token

@Fanetteg Thanks, this worked for me. Don't forget to set your redirect_url to localhost and untick   Disable implicit OAuth in your client security settings.

@Fanetteg hey thanks a lot for that. I got both my feeds working again.
One of them was from tagged photos, which appears to now be impossible to do...
I needed to get my user ID and every tool for that seams to be broken but this page has a super easy way to do so:
http://www.otzberg.net/iguserid/


Alert does not prompt user for on-going events

Alert does not list events which are currently ongoing. However, when the time frame is extended long enough to include the end time of the event, it will be included in the list of tasks.

Unable to replicate


Fixed docs url

@ntotten you missed a few steps for relasing
https://github.com/auth0/web-header#release

Ah, sorry man. I'll take care of it first thing in the AM.
Sent from Outlook
On Wed, May 20, 2015 at 6:45 PM -0700, "Cristian Douce"<EMAIL_ADDRESS>wrote:
@ntotten you missed a few steps for relasing
https://github.com/auth0/web-header#release
—
Reply to this email directly or view it on GitHub.


Submissions without submission.create audit log entry

On the QA server, we've noticed submissions without a corresponding submission.create audit log entry.
The very first submission on the server was created in 2019-05:
select min("createdAt") from submissions;

From then until 2019-08, all submission.create audit log entries recorded a submissionId (within details). However, from 2019-08 until 2021-02, there were a large number of submission.create audit log entries that did not record a submissionId. Many submissions did still record a submissionId during that time, but many didn't. However, since 2021-02, all submission.create audit log entries once again record a submissionId:
select date_trunc('month', "loggedAt"), details ? 'submissionId', count(*)
from audits
where action = 'submission.create'
group by 1, 2
order by 1 desc, 2 desc;

Looking at the submissions table tells a similar story about the timeline:
select
  date_trunc('month', submissions."createdAt"),
  audits.id is not null,
  count(*)
from submissions
left join audits on
  audits.action = 'submission.create' and
  (audits.details->>'submissionId')::int = submissions.id
where submissions.draft is not true
group by 1, 2
order by 1 desc, 2 desc;

(The query excludes draft submissions, since we know that prior to #458, there was a scenario in which creating a draft submission would not generate a submission.create audit log entry.)
I'm not sure what the cause of this issue was, but it seems to be resolved now. However, I wanted to record my findings. I don't think it's crucial that all submissions have a corresponding submission.create audit log entry. Without one, the submission activity feed in Frontend won't render anything about submission creation, but I think that's fine as long as the issue is resolved now. Given that, I'll go ahead and immediately close this issue.
We also discussed this issue on Slack a couple of times:
https://getodk.slack.com/archives/C01TKJ7TG7J/p1622588812117600
https://getodk.slack.com/archives/C01TKJ7TG7J/p1626894353075400

For posterity, I'll note that one theory we had was that the submitter type played a role in this. However, that didn't end up seeming to be the case: the submissions without an audit log entry were submitted by a mix of app users, web users, and public links. The vast majority by far were submitted by app users, but I think that's probably not too surprising.


Automated cherry pick of #2720: add OnBindIPCompleteFailed and fix aliyun Refresh for snat and dnat

Cherry pick of #2720 on release/2.11.
#2720: add OnBindIPCompleteFailed and fix aliyun Refresh for snat and dnat

/lgtm
/approve

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Add 'closure' function to the optimization function

In order to use optimizer like LBFGS the training procesure needs to provide the closure function that performs a forward, zero_grad and backward on the model.  While this function may be optional for certain optimizers, it is highly recommended to utilize it for every optimizer.
Here is an example without closure:
def training_step(self, batch, batch_idx):
          opt = self.optimizers()
          opt.zero_grad()
          loss = self.compute_loss(batch)
          self.manual_backward(loss)
          opt.step()

And this one with closure:
def training_step(self, batch, batch_idx):
    opt = self.optimizers()

    def closure():
        loss = self.compute_loss(batch)
        opt.zero_grad()
        self.manual_backward(loss)
        return loss

    opt.step(closure=closure)

Hi! Thank you for the hint, and indeed you are right :)  We are already implementing this in #85 , and the feature is going to be available when we release the beta version.

Hey @LoveFrootLoops ! We added the closure possibility in #104 and it will be available in the next release (beta version). If you are curious you can try it out. I have used LBFGS optimiser to correctly train (and faster) a simple Poisson model. Please note that the documentation is not yet ready since it is still a draft pull request, but thanks to your suggestion now everyone will be able to use advanced optimiser.

Hi @LoveFrootLoops! We added some new features and you should be able to use now the new v0.1 version for optimising with LBFGS. Since there are no tutorial yet I give you a snippet of commented code to see how to train a Poisson Problem (we haven't changed the definition of problem classes from current version).
Here is the code:
import torch

from pina.problem import SpatialProblem
from pina.operators import nabla
from pina.geometry import CartesianDomain
from pina import Condition, LabelTensor, PINN
from pina.trainer import Trainer
from pina.model import FeedForward
from pina.equation.equation import Equation
from pina.equation.equation_factory import FixedValue
from pina.plotter import Plotter

# define laplace equation
def laplace_equation(input_, output_):
    force_term = (torch.sin(input_.extract(['x'])*torch.pi) *
                    torch.sin(input_.extract(['y'])*torch.pi))
    nabla_u = nabla(output_.extract(['u']), input_)
    return nabla_u - force_term

class Poisson(SpatialProblem):
    output_variables = ['u']
    spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})

    conditions = {
        'gamma1': Condition(
            location=CartesianDomain({'x': [0, 1], 'y':  1}),
            equation=FixedValue(0.0)),
        'gamma2': Condition(
            location=CartesianDomain({'x': [0, 1], 'y': 0}),
            equation=FixedValue(0.0)),
        'gamma3': Condition(
            location=CartesianDomain({'x':  1, 'y': [0, 1]}),
            equation=FixedValue(0.0)),
        'gamma4': Condition(
            location=CartesianDomain({'x': 0, 'y': [0, 1]}),
            equation=FixedValue(0.0)),
        'D': Condition(
            input_points=LabelTensor(torch.rand(size=(100, 2), requires_grad=True), ['x', 'y']),
            equation=Equation(laplace_equation)),
    }

    def poisson_sol(self, pts):
        return -(
            torch.sin(pts.extract(['x'])*torch.pi) *
            torch.sin(pts.extract(['y'])*torch.pi)
        )/(2*torch.pi**2)

    truth_solution = poisson_sol

# make the problem
poisson_problem = Poisson()
model = FeedForward(len(poisson_problem.input_variables),len(poisson_problem.output_variables))

# make the solver
solver = PINN(problem = poisson_problem, model=model, optimizer=torch.optim.LBFGS)

# sample points
boundaries = ['gamma1', 'gamma2', 'gamma3', 'gamma4']
n = 10
poisson_problem.discretise_domain(n, 'grid', locations=boundaries)

# train the model (ONLY CPU for now, all other devises in the official release)
trainer = Trainer(solver=solver, kwargs={'max_epochs' : 500, 'accelerator':'cpu'})
trainer.train()

# plotter
plotter = Plotter()
plotter.plot(solver)

And here the sample of the output:

Hope you find it helpful! We plan to also start including new models of PINNs and Neural Operators. If you would like to contribute look at #85 and contact us. I hope this helps and solves your problems. Cheers :)

Hi @dario-coscia,
I'm thrilled to see that the latest improvements have yielded such great results. Wow!
I have another request or suggestion that could potentially enhance the training process significantly. I was wondering if it's possible to directly incorporate boundary conditions into the neural network. By doing so, we wouldn't need to train the network on trivial boundary conditions separately, as they would already be satisfied by construction.
The modified approach would look something like this:
def u_mod(input_, output_):
    return input_.extract(['x'])*(1-input_.extract(['x']))*\
        input_.extract(['y'])*(1-input_.extract(['y']))*\
        output_.extract(['u'])

def laplace_equation(input_, output_):
    output_.extract(['u']) = u_mod(input_, output_) ## THIS IS NOT WORKING SO FAR
    force_term = (torch.sin(input_.extract(['x'])*torch.pi) *
                    torch.sin(input_.extract(['y'])*torch.pi))
    nabla_u = nabla(output_.extract(['u']), input_)
    return nabla_u - force_term

class Poisson(SpatialProblem):
    output_variables = ['u']
    spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})

    conditions = {
        'D': Condition(
            input_points=LabelTensor(torch.rand(size=(100, 2), requires_grad=True), ['x', 'y']),
            equation=Equation(laplace_equation)),
    }

As a result, the implementation of "complicated" boundary conditions would be the only requirement, leading to reduced computational effort for the neural network.

Yes! This is sometimes a very nice strategy indeed. You can already do it easily with the new v0.1 version. The idea is to define your own NN model, and impose the constrains in the forward. Here I show you and example:
import torch

from pina.problem import SpatialProblem
from pina.operators import nabla
from pina.geometry import CartesianDomain
from pina import Condition, LabelTensor, PINN
from pina.trainer import Trainer
from pina.model import FeedForward
from pina.equation.equation import Equation
from pina.equation.equation_factory import FixedValue
from pina.plotter import Plotter

# define laplace equation
def laplace_equation(input_, output_):
    force_term = (torch.sin(input_.extract(['x'])*torch.pi) *
                    torch.sin(input_.extract(['y'])*torch.pi))
    nabla_u = nabla(output_.extract(['u']), input_)
    return nabla_u - force_term

# define a costum torch model
class hardMLP(torch.nn.Module):

    def __init__(self, input_dim, output_dim):
        super().__init__()

        self.layers = torch.nn.Sequential(torch.nn.Linear(input_dim, 20),
                                          torch.nn.Tanh(),
                                          torch.nn.Linear(20, 20),
                                          torch.nn.Tanh(),
                                          torch.nn.Linear(20, output_dim))

    # here in the foward we implement the hard constraints
    def forward(self, x):
        return x.extract(['x'])*(1-x.extract(['x']))*x.extract(['y'])*(1-x.extract(['y']))*self.layers(x)

class Poisson(SpatialProblem):
    output_variables = ['u']
    spatial_domain = CartesianDomain({'x': [0, 1], 'y': [0, 1]})

    conditions = {
        'D': Condition(
            input_points=LabelTensor(torch.rand(size=(100, 2), requires_grad=True), ['x', 'y']),
            equation=Equation(laplace_equation)),
    }

    def poisson_sol(self, pts):
        return -(
            torch.sin(pts.extract(['x'])*torch.pi) *
            torch.sin(pts.extract(['y'])*torch.pi)
        )/(2*torch.pi**2)

    truth_solution = poisson_sol

# make the problem
poisson_problem = Poisson()
model = hardMLP(len(poisson_problem.input_variables),len(poisson_problem.output_variables))

# make the solver
solver = PINN(problem = poisson_problem, model=model, optimizer=torch.optim.LBFGS)

# train the model (ONLY CPU for now, all other devises in the official release)
trainer = Trainer(solver=solver, kwargs={'max_epochs' : 250, 'accelerator':'cpu'})
trainer.train()

# plotter
plotter = Plotter()
plotter.plot(solver)

This gives you the following output:

These are just fews of the new capabilities we are including. When releasing the beta version we will make an in depth review and many tutorials, so that everyone can see! Maybe, are you interested in making a tutorial on these hard constrains 😃?
Hope it was helpful for you, and thanks again for the useful feedbacks 🚀

@LoveFrootLoops I close the issue since it was related with the closure function, which we implemented in v0.1 and will release soon. Thanks again for the feedbacks, and hope to hear from you soon for collaboration, if interested!


dependencies requirement false positive?

Describe the bug
Hello, I've encountered with an issue in a specific situation when using the dependencies parameter for a scoped provider.
In the following example, an assert throws because someServiceProvider is not added as a dependency, even though this provider is not overridden.
Is this a false positive error? I thought you should only declare the dependencies of the providers that get overridden.
To Reproduce
import 'package:riverpod/riverpod.dart';
import 'package:test/test.dart';

void main() {
  test('test case', () {
    final parent = ProviderContainer();
    final container = ProviderContainer(
      parent: parent,
      overrides: [
        toOverride.overrideWithValue(4),
      ],
    );

    final notifier = container.read(myNotifierProvider.notifier);
    notifier.someMethod();
  });
}

final someServiceProvider = Provider((ref) => SomeService());
final toOverride = Provider<int>((ref) => throw Exception("not initialized"));

final myNotifierProvider = StateNotifierProvider(
  (ref) {
    final val = ref.watch(toOverride);
    return MyNotifier(ref, val);
  },
  dependencies: [toOverride],
);

class MyNotifier extends StateNotifier<int> {
  MyNotifier(this.ref, int val) : super(val);

  final StateNotifierProviderRef ref;

  void someMethod() {
    final service = ref.read(someServiceProvider);
    // ...
  }
}

class SomeService {}

This is expected. The fact that someServiceProvider is not scoped doesn't matter. It still isn't in "dependencies"
When specifying "dependencies", all dependencies must be listed, whether they are scoped or not.

Thanks Remi!
Unfortunately, this seems inconvenient and error prone (reading a new non declared service) for Notifiers scoped to a screen.
Maybe it would be better to use a family instead?
There are cases where I don't have an identifier for the family, so it feels weird to use it. Can a random number as a family key be used for this kind of situations?

It's not really inconvenient/error prone. Keep in mind that there is a definitive plan to implement a lint rule for this, which would have an auto-fix
The current situation is only temporary.
But yeah, if you can avoid using scoping, do so.
Maybe consider an enum instead of a random number as family key

Closing since this is expected


Not all labels for border tiles are downloaded

Perhaps it's best to explain my issue with a simple example:

I set the bounding_box in config.json to [0,0, 100,100].
I download labels within the bounding box
I download tiles of size 20*20. One of the downloaded tiles is "Tile X" with coordinates [90,90, 110,110].
In tile X, my model detects an "object O" at coords [105, 105, 106, 106].
This object is however not in labels because it is outside of the bounding box set in config.json. So it seems like a "false positive" when actually the detection is correct.

Is this known/desired?
I imagine a functionality could be added that would check coordinates of tiles and then download all labels within the tiles.

Thanks for the write-up and identification. I think the current behavior is not desired and the ideal functionality would be to use all labels within the downloaded tiles

Sure! Let me know if I can help to fix this, I'd be happy to contribute.

That would be great. I'm prepping a 0.9.0 release now (all of @martham93's recent work) and it will be easiest to branch off that shortly

Hi, sorry I am currently swamped with other work so I am not sure when I find time for this.


💡[FEATURE] Add Hovering effect to the power of code section

Description
hello project admin @Muskansahuincredible, I would like to add a glowing hover effect to the mentioned section as attached in the screenshot so that its more visually appealing. Pls assign this issue to me under Gssoc'24. Thank you
Screenshots

Checklist

[X] I have checked the existing issues.
[X] I have read the Contributing Guidelines
[X] I have read the Code Of Conduct
[X] The changes don't break the code

@mythri1010  please this issue to me as well


Fill frame withzoom (i.e. keep image apect ratio of image fixed)

When an extent is defined to zoom into the aspect ratio of the displayed image changes. I think this should be changed such that the zoomed image always fills the frame. Otherwise the area of display keeps changing and looks hacky.

Should be easy to fix, have a go.

Looking through the code I can't seem to find where a zoom rectangle triggers a response.

https://github.com/MakieOrg/Tyler.jl/blob/346b2c78234374c7493c94c229804570fe65844f/src/Tyler.jl#L138-L142


ICP slow for large DEMs no matter subsample

Something is probably slowing things before the subsampling when manipulating the arrays: almost 2 min on a 5000x5000 DEM with 5e4 subsample size VS 5s for a 1000x1000 with the same subsample.

Now that I've tested this a bit, it was probably the to_points() function!


Try to update coveralls in Github Actions

There was a change in coveralls 3.0.0 that now requires us to add coveralls --service=github.  See: https://github.com/TheKevJames/coveralls-python/issues/252

There was a change in coveralls 3.0.0 that now requires us to add coveralls --service=github.  See: https://github.com/TheKevJames/coveralls-python/issues/252


INTERFACE_INCLUDE_DIRECTORIES is ignored in VS project

Describe the bug
LibA
/LibA/source/main.cpp
/LibA/deps/LibB/LibB.hpp # head only

main.cpp
#include <LiB/LibB.hpp>

For the include above to work, /LibA/deps is added to INTERFACE_INCLUDE_DIRECTORIES of LibA
When using LibA in a cmake project, no problem.
When using LibA in a VS project, /LibA/deps is not in include paths.
Environment

OS: Windows
Compiler: Microsoft (R) C/C++ Optimizing Compiler Version 19.29.30133 for x64

Expected behavior
INTERFACE_INCLUDE_DIRECTORIES should not be ignored in a VS project

Could you add how vcpkg is part of your issue?
You seem to want to use a vendored dependency located in LibA (LibA/deps/LibB), not a dependency LibB managed by vcpkg (installed/<triplet>/include/libB).

LibB is head-only, the it is a private lib just for convenience, so just copied to to LibA/deps.
For LibA to build, /LibA/deps should be in include paths of project LibA.

So this is a VS question, not a vcpkg question.

CMakeLists.txt of LibA has enough include paths in INTERFACE_INCLUDE_DIRECTORIES to use LibA,
but vcpkg doesn't provide all the include paths in INTERFACE_INCLUDE_DIRECTORIES of LibA to VS project

AFAIU you refer to LibB/LibB.hpp is in the source directory of LibA.
vcpkg takes care that you can use the installed (aka binary) output of ports. So the owner of LibA must take care to properly install LibB/LibB.hpp along with LibA files, perhaps with proper exported configuration. If LibA uses CMake, it is actually a CMake question.

Does vcpkg only find include files in vcpkg/installed/include?
And installed packages must meet this rule?
If yes, for #include <LibB/LibB.hpp> in LibA to work, two choices:

port LibB to vcpkg
patch LibA to #include "LibB/LibB.hpp" and make LibA find LibB locally

Does vcpkg only find include files in vcpkg/installed/include?
And installed packages must meet this rule?

Bascially, yes. (The path contains the triplet. For manifest mode, the location is relative to the user project.)

The files in installed are all what is stored to, and restored from, the binary cache.
You cannot assume the existence of the source folder when vcpkg restores a binary artifact, or when working with exported packages.
The include directory is the only one added for includes to VS.

If yes, for #include <LibB/LibB.hpp> in LibA to work, two choices:

port LibB to vcpkg
patch LibA to #include "LibB/LibB.hpp" and make LibA find LibB locally

AFAIU from your initial post, your problem is not "for #include <LibB/LibB.hpp> in LibA to work" when building LibA, but *for #include <LibB/LibB.hpp> in AppXYZ to work when using LibA because

it either doesn't install LibB/LibB.hpp to vcpkg's include directory (already in VS include path)
(to be fixed by adding installation to port LibA, or by creating a port LibB).
or it installs to another path which is not in VS
(to be fixed by manually adding another path).

your problem is not "for #include <LibB/LibB.hpp> in LibA to work" when building LibA, but *for #include <LibB/LibB.hpp> in AppXYZ

Yes, for AppXYZ to work.
Now it's clear that for AppXYZ to use LibA, patches are needed.
Thanks for the clarification.


Update "jei" dependencies

So as stated in my discord server I'm afraid I won't be added jei and rei support. I tried various different methods but in the end I have decided to focus my time on the rewrite. That's not to say that I will never add jei/rei, but this branch is outdated(and will probably be closed soon) and was me basically experimenting with ideas.


Add french translation

Full translation in French from README.md.

Thanks, can you add a link under translations

:clap: Thanks for the contribution, please help to keep this up to date.


Normalize line endings to LF

Approximately every file in this repository is checked in with CRLF. This wreaks havoc if core.autocrlf is set to true, as it is by default by GitHub for Windows. For example, renames aren't recognized. It's my understanding that core.autocrlf=true is a pretty common workflow for Git users on Windows.
This change normalizes all files in the repository to LF line endings. We add a .gitattributes file that tells Git to identify future text files added to the repository and normalize them to LF regardless of the user's setting for core.autocrlf.
Sources differ on whether Visual Studio solutions need to keep CRLF, so .gitattributes includes an entry to retain CRLF in *.sln files.
This diff looks horrific on GitHub, but git diff -w yields only the addition of .gitattributes, plus two unexplained but harmless changes in file mode:
google-api-dotnet-client-samples [crlf]> git diff -w master
diff --git a/.gitattributes b/.gitattributes
new file mode 100644
index 0000000..9b4d81d
--- /dev/null
+++ b/.gitattributes
@@ -0,0 +1,2 @@
+* text=auto
+*.sln text eol=crlf
diff --git a/AdSenseHost.Sample/README.html b/AdSenseHost.Sample/README.html
old mode 100755
new mode 100644
diff --git a/DfaReporting.Sample/GetCompatibleFieldsHelper.cs b/DfaReporting.Sample/GetCompatibleFieldsHelper.cs
old mode 100755
new mode 100644
index 7e88b23..63296c2

/cc @chrsmith


Update the model structure for faster processing

Context: https://github.com/unicode-org/icu/pull/2297
We're updating the model structure to remove unnecessary string concatenations during parsing, which significantly improves latency.
Execution time study:
https://colab.research.google.com/drive/12pK2OV62q_yGSH587johQloAHyMl2srW?usp=sharing

Thanks for reviewing!


Typescript init and Bills, Banks and Beneficiaries working

I have set up typescript and added type to Banks, Bill and Beneficiaries. They are all working with their appropriate types. Please let me know what you think so I should know how to process ASAP. Thanks

Is anyone seeing this or should I just abandon the project

@iamsethsamuel Nice work!
The changes in this PR are much. Very much.
You are requesting to merge your work to a live product. It needs to be tested and reviewed to make sure that it does not break anything (I'm not implying that it does).
Another thing is that a project such as converting a codebase from JS to TS needs to have a plan and follow a step-wise process.
I don't think that there's anything bad about your work. The maintainers are probably very busy.
:+1:

@iamsethsamuel Nice work!
The changes in this PR are much. Very much. You are requesting to merge your work to a live product. It needs to be tested and reviewed to make sure that it does not break anything (I'm not implying that it does). Another thing is that a project such as converting a codebase from JS to TS needs to have a plan and follow a step-wise process. Did you read the contributions guide? +1

Yeah, it's really big. I was thinking that you guys can create a branch for the transition. https://github.com/Flutterwave/Node/issues/69#issuecomment-1261523498 plan is perfect. So if you can create the branch, I will close this PR and recreate it on that branch and we continue from there. And when all is tested, that branch can be merged with the main branch

Hi @iamsethsamuel,
Please raise these changes against the dev branch. Based on the volume of changes made, it would take us some time to review and test for unintended changes, but rest assured, we would work on it.
We appreciate you for making contributions to the library. I'd be in touch.


Reverse mode fixes for multiple occurrences of a code block

Write code block index (for identifying concatenated blocks) to block labels, and also derive from them. This allows to detect "real" multiple occurrences of a block.
Currently, we warn on multiple equal occurrences, and abort with an error on differing occurences.
Should the user be allowed to decide which block to use?
Fixes #72

Should the user be allowed to decide which block to use?

I think an option to force using the first one or maybe the one that differs from the source if it is only one might be practical, but interactive selection sounds a bit too much.

This is me being a bit late to the party: But why is reverse mode a flag instead of a subcommand?

This is me being a bit late to the party: But why is reverse mode a flag instead of a subcommand?

Because all the arguments for the "forward" mode can also be used.

Meanwhole, I am a bit afraid of conflicts with the other MR on top of this one. Although it should probably be rebased after merging this one, maybe I should merge the other one first?

Because all the arguments for the "forward" mode can also be used.

I think since the forward mode is not a subcommand, its arguments are inherited by all subcommands anyway. (E.g. init incorrectly accepts all forward mode flags via
> yarner --some-flag init

as well.)

maybe I should merge the other one first?

As these MR are meant to reduce the context to enable a sufficiently thorough review, I would definitely prefer a rebase to merging just to avoid conflicts.

I think I am convinced now to remove meta variables. Thus, the other MR is mostly obsolete. I will fix this one now, and then go for removing meta vars.

Made reverse mode a subcommand


Public cloud emails

In this PR I did the following:

Split the email templates into two folders: private-cloud and public-cloud and simply used the exact same private cloud templates for public cloud without changing much content
Created constants for public cloud and split constants into public-cloud and private-cloud
Created Public cloud emails in the root of the email folder alongside the existing private cloud emails
Some changing of the content of the emails but not thoroughly
Added the calls to the appropriate send email functions from our API endpoints

This is a PR for the general structure and logic for public cloud and private cloud emails. At this stage someone else can work on the content.

Tests fail. I have converted this to a draft and am looking into it


Timelapse illumination correction method [MICCAI 2020]

Hi @tying84 and @Mirkazemi - Thanks for making BASIC available for python.
In your 2020 paper "Background and Illumination Correction for Time-Lapse Microscopy Data with Correlated Foreground" you introduce an improved method for illumination correction in timelapse imaging.
Is code for this updated method available in python? The paper states:

We will also develop our method into a user-friendly software tool that a large biological community can benefit from.

Can you point me to this resource? @roshankern and I are very interested in applying your method! Thank you in advance

Hi, thank you @gwaygenomics for your interest!
We, @Nicholas-Schaub, @tdmorello, @tying84, and I, are now trying to develop a brand-new version in the dev branch. That method and some improved implementation will also be provided there.
Please wait for one or two months until it gets completed!

Thanks @yfukai - we look forward to applying your implementation.

The BaSiC code is already in Python. The one with the segmentation mask
will also be added in a few weeks.
Tingying
Gregory Way @.***> schrieb am Fr. 27. Mai 2022 um 18:50:

Hi @tying84 https://github.com/tying84 and @Mirkazemi
https://github.com/Mirkazemi - Thanks for making this code available on
python.
In your 2020 paper "Background and Illumination Correction for Time-Lapse
Microscopy Data with Correlated Foreground"
https://link.springer.com/chapter/10.1007/978-3-030-59722-1_17 you
introduce an improved method for illumination correction in timelapse
imaging.
Is this code available in python? The paper states:
We will also develop our method into a user-friendly software tool that a
large biological community can benefit from.
Can you point me to this resource? @roshankern
https://github.com/roshankern and I are very interested in applying
your method! Thank you in advance
—
Reply to this email directly, view it on GitHub
https://github.com/peng-lab/BaSiCPy/issues/65, or unsubscribe
https://github.com/notifications/unsubscribe-auth/ACXOKOZY7KQEB73SGLQDPH3VMD4OJANCNFSM5XEXYB2Q
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You are receiving this because you were mentioned.Message ID:
@.***>

Implemented for the beta release! Please check out the fitting_weight parameter. @gwaybio
https://basicpy.readthedocs.io/en/latest/api.html#basicpy.basicpy.BaSiC.fit

perfect! Thanks @yfukai - @jenna-tomkinson, @roshankern, and I are looking forward to testing this out!


ksampler

[AnimateDiffEvo] - INFO - Using motion module mm_sd15_v3.safetensors:v3.
[AnimateDiffEvo] - ERROR - Encountered AttributeError while attempting to restore functions - likely, an error occured while trying to save original functions before injection, and a more specific error was thrown by ComfyUI.
!!! Exception during processing !!!
Traceback (most recent call last):
File "E:\mycomfyui\ComfyUI\execution.py", line 151, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "E:\mycomfyui\ComfyUI\execution.py", line 81, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "E:\mycomfyui\ComfyUI\execution.py", line 74, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "E:\mycomfyui\ComfyUI\nodes.py", line 1369, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "E:\mycomfyui\ComfyUI\nodes.py", line 1339, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "E:\mycomfyui\ComfyUI\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 9, in informative_sample
return original_sample(*args, **kwargs)  # This code helps interpret error messages that occur within exceptions but does not have any impact on other operations.
File "E:\mycomfyui\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 264, in motion_sample
function_injections.inject_functions(model, params)
File "E:\mycomfyui\ComfyUI\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 198, in inject_functions
self.orig_prepare_mask = comfy.sample.prepare_mask
AttributeError: module 'comfy.sample' has no attribute 'prepare_mask'. Did you mean: 'prepare_noise'?

Update AnimateDiff-Evolved to fix the issue


@instana/collector at ^1.106.2 depends on optional dependencies unsafely

If you install your node modules with:
yarn install --production --ignore-optional --frozen-lockfile

Then the resulting installation will not run, as @instana/collector fails to require the event-loop-lagmodule, which is marked as optional, but in the code, it is required just asconst lag = require('event-loop-lag')(1000);`
This means our production build cannot start if we use the @instana/collector package.

Furthermore, you currently depend on node-gyp for installs, which results in errors if python is not available on the host system, as is the case in both the node:lts-slim and node:lts-alpine official docker images.

Thanks again for the fix around the faulty event-loop-lag module dependency declaration.
Regarding the other aspect you mention: Where exactly did you encounter a hard dependency on node-gyp? All dependencies that are native add-ons and might use node-gyp (@instana/autoprofile, event-loop-stats, gcstats.js,  and netlinkwrapper) are declared as optional dependencies precisely for the reason that Python or other build tools are not available on the target system. I think the code that loads those dependencies should always handles the case that they are not installed correctly (in contrast to the code loading event-loop-lag, which was wrongly classified as optional).
So an npm install or yarn install on a slim or alpine image will indeed log errors when trying to install those native add-ons, but it will ultimately succeed. What am I missing?

The event-loop-lag issue has been fixed in version 1.106.3.

Closing this as the reported error around --ignore-optional  has been fixed and I didn't hear back from you about the hard dependency on node-gyp (I still think there is none).


Command.Group is causing an error

TypeError: undefined is not iterable (cannot read property Symbol(Symbol.iterator))

Using the example from the Readme: https://github.com/pacocoursey/cmdk?tab=readme-ov-file#use-inside-popover
Replace List with Group
Let me know if you need version information or any more details!
Super cool component btw!

On an aside, I cannot click items under Command.List, is this expected?

I'm experiencing the same issue

Same problem here.

https://github.com/pacocoursey/cmdk/issues/244 This worked for me guys.

@pacocoursey
Why did you close this as complete? I have this error without the use of shadcn, with the example from the README, with s/List/Group/. The linked issue does not resolve


Add support for generating MethodImpl metadata in metadata transform

implementation only for ECMA metadata as we don't have TypeSystem api surface that is general purpose enough to avoid using the ECMA metadata reader directly
metadata transform tests for generic and non-generic scenarios

👍


cannot import name 'cached_download' from 'huggingface_hub'

it seems like hugging face changed something, using pip install huggingface_hub==0.25.2 to downgrade

maybe you can try: pip install --upgrade diffusers

thanks! this worked for me for the same error

I am getting a JSON error when I try and type anything and click on Generate. Did you face any issues like that?

I am getting a JSON error when I try and type anything and click on Generate. Did you face any issues like that?

I did. I changed my gradio version to 4.43.0. That fixed the error.


Fix caddy_version label in php/Dockerfile

caddy_version label wasn't pulled from the version build arg, so the
label was mismatched when using a value other than the default.

Same as #95, but for the PHP variant. (Hadn't noticed that it had the same pattern.)

Thanks once again. :)


SWSH promo update + Machamp fix + formats.yaml update

Missing Lapras (SWSH052) due to no information that I can find on my own accord. Also a small break between 57-63 due to info I also couldn't find.
Machamp fix was merely a markup edit
formats.yaml update adds Champion's Path / Darkness Ablaze to Standard 2020-21, adds Champion's Path to Expanded (forgot to add Darkness Ablaze to it when the update was done, woops)

SWSH051 Lapras is a reprint https://bulbapedia.bulbagarden.net/wiki/Lapras_(Sword_%26_Shield_48)

Just found that in the scans while I was checking through them. I'll go ahead and add it to this PR


Store contract info before vm.Instantiate

Currently contract information is stored after the instantiate method of the VM has been invoked.
Currently the issue with this is that if  contract A during instantiation is also instantiating contract B and B wants to know about its caller by querying contract info (to know  the code id and for potential whitelist check ) it will fail because the information is only stored after the vm.Instantiate() method has been executed.
Here is a diagram of the execution flow

I don't see any dependency that prevents from  moving  the logic above the vm instantiation call
https://github.com/CosmWasm/wasmd/blob/14688c09855ee928a12bcb7cd102a53b78e3cbfb/x/wasm/keeper/keeper.go#L317-L321

The contract response is handled in L329 after the metadata for contract A is stored. Therefore Contract B should be able to query Contract A's metadata. Contract A can not query it's own contract info though.

to know the code id and for potential whitelist check

I have not heard about code id for authz, yet. Can you elaborate a bit more on this, please?
Btw we have examples for forwarding an address or pre-authz that give strong guarantees and work nicely with code migration.
You can find examples for this in https://github.com/confio/tfi or https://github.com/confio/poe-contracts .

Confirmed is working


[WIP] user_info_card: Redesign user card popover.

This PR stays draft until #25459 gets merged.
The first 8 commits are the same as #25459 and the last commit is the redesign commit. After #25459 gets merged I will make the code in the last commit clearer and split the last commit and make the commit history clear.
Fixes part of #22802
Fixes:

Screenshots and screen captures:

Self-review checklist

[x] Self-reviewed the changes for clarity and maintainability
(variable names, code reuse, readability, etc.).

Communicate decisions, questions, and potential concerns.

[x] Explains differences from previous plans (e.g., issue description).
[x] Highlights technical choices and bugs encountered.
[x] Calls out remaining decisions and concerns.
[x] Automated tests verify logic where appropriate.

Individual commits are ready for review (see commit discipline).

[x] Each commit is a coherent idea.
[x] Commit message(s) explain reasoning and motivation for changes.

Completed manual review and testing of the following:

[x] Visual appearance of the changes.
[x] Responsiveness and internationalization.
[x] Strings and tooltips.
[x] End-to-end functionality of buttons, interactions and flows.
[x] Corner cases, error conditions, and easily imagined bugs.

@zulipbot add "QA needed"


How to allow multiple input formats?

With the locale set to us-en the user has to enter the date formatted like 01/01/2016 (MM/DD/YYYY) if they type it in manually (otherwise the date is not considered valid).
Is there a way to allow the user to also type in the date without having to pad the the month and day with zeros and not have to put in the full year (like 1/1/16)?
Of course we'd like to have this same sort of behavior (not forcing the padded numbers but allowing it) with date formats for all locales.

The dateFormat prop can accept an array of formats where they will all be used for reading but the first one is used for displaying.

The problem with using the dateFormat prop is that it overrides the format based on locale.  So if I set dateFormat={['MM/DD/YYYY', 'M/D/YY', ...]} it would be fine for en-US but wrong for en-GB since it uses the first format in the dateFormat array to display the date.

I'm searching for this answer as well!

I have the same issue today. And I wonder, theoretically. If we pass a function as first date format that will change it depends on locales could it display date in local format? I know this doable in some languages (a property, not a function that is dynamically calculated when needed)

This issue was fixed for me with this. I just added different formats for slashes and dashes
dateFormat={["dd/MM/yyyy", "dd-MM-yyyy"]}

The dateFormat prop can accept an array of formats where they will all be used for reading but the first one is used for displaying.