Tensorflow 2.2 and 2.3 not detecting GPU with CUDA 10.1

System information

OS Platform and Distribution (e.g., Linux Ubuntu 18.04):
TensorFlow installed from (source or binary): binary
TensorFlow version: 2.3 and 2.2
Python version: 3.6
Installed using virtualenv? pip? conda?: venv and pip
GCC/Compiler version (if compiling from source): 7.5
CUDA/cuDNN version: 10.1
GPU model and memory: K80

Describe the problem
After installing tensorflow, GPU is not detected and getting error: 'Cannot open dynamic library libcublas.so.10'.
Provide the exact sequence of commands / steps that you executed before running into the problem

All the steps are followed from the official tensorflow page as it is: https://www.tensorflow.org/install/gpu and https://www.tensorflow.org/install/pip.
Also, i have to install cuda-toolkit separately.
Finally added CUDA-10.1 path in bashrc file.

How I fix the problem:
I started with a clean VM on Azure with nothing installed. Then followed the tensorflow guides (above) to install NVIDIA-Driver, CUDA 10.1, cuDNN, cuda-toolkit and tensorflow.
After all these steps, my local folder had two cuda folders (don't know why):
/usr/local/cuda-10.1/lib64/
/usr/localo/cuda-10.2/lib64/
The error which I was getting was for dynamic library 'libcublas.so.10'. And this file was not present in folder 'cuda-10.1', but instead it was present in 'cuda-10.2' (note, that i have installed everything in venv)
I have to manually copy all the files (including files inside the 'stubs' folder). And then it works.
This site also mention this issue, where they say that with CUDA 10.1, some of the libraries are installed differently - https://forums.developer.nvidia.com/t/cublas-for-10-1-is-missing/71015/4 (the steps here are when you install libraries at system level and not venv).
Expected Behaviour:
Either tensorflow should automatically refer to the missing dynamic libraries or mention how to fix this in Install Set up.
Note: The errors are similar when you install CUDA 10.2, it's just the dynamic library version are different.

@javedsha
TensorFlow v2.3 is compatible with CUDA 10.1 and cuDNN 7.6. For more information regarding this please take a look at the tested build configurations.
And the CUDA version mismatch query has been explained in this StackOverflow comment. Thanks!

@ravikyram
Output of NVIDIA-SMI:
Driver Version: 450.1.06
CUDA Version: 11.0
nvcc --version
10.1
I followed all the steps mentioned in the tensorflow gpu guide, the only thing extra I did was install cuda-toolkit 'sudo apt-get install cuda-toolkit'
What am i doing wrong?

@javedsha The following is a procedure I use for Ubuntu 18.04, confirmed to work with the Ubuntu-shipped python 3.6. Hope it helps to pinpoint your issue.
In your case, the trouble possibly started with the sudo apt-get install cuda-toolkit, as it's not fixed to 10.1. Having 10.1 parallel to 10.2 and 11.0 is not advisable, nor practically feasible due to the env vars. Drivers can be always the latest matching the GPU and are backwards-compatible with CUDA 10.1.
Btw, CUDA version that is reported by the nvidia-smi is not necessarily the CUDA version that Tensorflow picks up (longer story), but with my installation procedure,
# To start fresh, clean up all the nivida-related packages. Be careful when using the same system as a desktop!
sudo apt-get --purge remove 'cuda*'
sudo apt-get --purge remove 'nvidia*'
sudo apt-get --purge remove 'libnvidia*'

# Check if all clean
sudo find /usr/local/cuda/ -name '*blas*'
sudo find /usr/lib/ -name '*blas*'

# CUDA 10.1 instructions for creating a locally available repo and installing from it
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
sudo apt-get update

# Make sure the driver number matches the GPU
sudo apt install nvidia-driver-418
sudo apt install cuda-10.1

# Make sure the libs are now in place
sudo find /usr/local/cuda/ -name '*blas*'
sudo find /usr/lib/ -name '*blas*'

# Run nvidia-smi for sanity check
nvidia-smi

python3 -m venv --no-site-packages ~/.venv-tf2.3-sanity
. ~/.venv-tf2.3-sanity/bin/activate
pip install -U pip
pip install tensorflow==2.3
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([10000, 10000])))"

@ahtik is the local thing same as the stable version? I will give this a try today and will post here. Thank you.

Yes, it's the latest 10.1 cuda, just makes the deployment a bit easier for
my use case.
On September 16, 2020 3:57:53 PM Javed Shaikh<EMAIL_ADDRESS>wrote:

@ahtik is the local thing same as the stable version? I will give this a
try today and will post here. Thank you.
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub, or unsubscribe.

I have the same problem with libcublas.so.10. Same OS, same python version, tf 2.3 etc. The only difference was that I didn't use venv and have different GPU.
I followed Ubutnu 18.04 instructions from official guide: https://www.tensorflow.org/install/gpu
I also found cuda 10.2 folder near cuda 10.1 folder with former having libcublas.so.10 and latter having all other libs.
My solution was to install cuda 10.2 even if it contradicts the guide. GPU is working in tensorflow now. I have taken cuda-10.2 from nvidia website as a deb package.
Also the guide itself (https://www.tensorflow.org/install/gpu) seems to be not perfectly written. It tells you to install CUPTI when there is no way to install it separately. It read as: "Install CUPTI which ships with the CUDA® Toolkit. Append its installation directory to the $LD_LIBRARY_PATH environmental variable:" when it should be IMHO "Install CUDA Toolkit. You will have CUPTI library installed. Append its installation directory to the $LD_LIBRARY_PATH environmental variable:" And I still don't get how section with CUPTI goes before section with cuda installation on Ubuntu. I hope my feedback will be useful.

@Zapunidi The official installation guide is a bit misleading in a sense that CUPTI section can be easily ignored for most users, it's not part of the regular Ubuntu setup and useful only when you need to profile CUDA execution through Tensorflow.
Your issues are potentially resulted from something related lingering in the system before doing the official setup guide. It should work/"works for me", also with an older GTX 1080TI VPS.
If you follow the official installation instruction, the nvidia-smi does output CUDA Version: 11.0, but you can easily ignore that (it can be a different version than was actually installed, longer story...).
It would be helpful if you could try from a cleaned up machine (beware the following if you have gpu used for desktop...):
sudo apt-get --purge remove 'cuda*'
sudo apt-get --purge remove 'nvidia*'
sudo apt-get --purge remove 'libnvidia*'

All cublas-related library files can be shown at any point using
sudo find /usr/local/cuda/ -name '*blas*'
sudo find /usr/lib/ -name '*blas*'

Finally, to perform a basic "sanity check" with the least moving parts:
python3 -m venv ~/.venv-tf2.3-sanity
. ~/.venv-tf2.3-sanity/bin/activate
pip install -U pip
pip install tensorflow==2.3
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([10000, 10000]))); print(tf.sysconfig.get_build_info())"

It would be very helpful if you could report back if this is also resulting in some trouble.

@Zapunidi Indeed, the official guide for Ubuntu doesn't seem to work for me either (all other libs load fine, getting one Warning):
2020-09-17 12:50:29.307000: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
2020-09-17 12:50:29.307313: W tensorflow/stream_executor/platform/default/dso_loader.cc:59] Could not load dynamic library 'libcublas.so.10'; dlerror: libcublas.so.10: cannot open shared object file: No such file or directory
2020-09-17 12:50:29.334711: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcufft.so.10
2020-09-17 12:50:29.340930: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcurand.so.10
2020-09-17 12:50:29.391160: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusolver.so.10
2020-09-17 12:50:29.400149: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcusparse.so.10
2020-09-17 12:50:29.507706: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudnn.so.7

Almost like something in the NVIDIA machine-learning repo still manages to force an upgrade from 10.1..
I do not have this warning when using the local installation method I posted previously. For cudnn and tensorrt/libnvinfer I have a separate tensorrt-cuda10.1 setup.

So the issue is for everyone. It will make sense to upgrade the tensorflow documentation as it is not working.
@Zapunidi did you follow the same steps as mentioned in https://www.tensorflow.org/install/gpu, except that you installed Cuda 10.2 from official package. Did you also installed CUDA toolkit? Could you please post all the steps (detailed) as it can help everyone.

@Zapunidi did you follow the same steps as mentioned in https://www.tensorflow.org/install/gpu, except that you installed Cuda 10.2 from official package. Did you also installed CUDA toolkit? Could you please post all the steps (detailed) as it can help everyone.

I can't see the difference between CUDA and CUDA Toolkit. Even https://www.tensorflow.org/install/gpu joggle these two terms like "The following NVIDIA® software must be installed on your system: ... CUDA® Toolkit —TensorFlow supports CUDA® 10.1 (TensorFlow >= 2.1.0)..." Then for Linux setup the manual just mentions "CUDA" without "Toolkit".
I didn't written down the exact steps, so my report is not reliable, sorry. I remember that I

Installed CUDA Toolkit 10.1 from the link from manual: https://developer.nvidia.com/cuda-toolkit-archive
Installed cuDNN SDK 7.6.5 from nvidia website.
Rebooted
Executed every command from Ubuntu 18.04 console commands block https://www.tensorflow.org/install/gpu I didn't reboot in the middle of the block as it tells me to do because I already had required drivers and kernel module. A violation, yes.

So it was not a clean install. I do not have a spare machine with supported GPU to make clean test for you guys. I also don't think that GPU virtualization is mature to use virtual machine on my primary PC.

@Zapunidi Yes, CUDA and CUDA Toolkit is 100% the same. This reboot in the middle does not matter, as long as you still reboot after the last step.
One thing that might work is to run on top of everything still the "local" installation method like this and see what happens after reboot (taken from my comment above):
# CUDA 10.1 instructions for creating a locally available repo and installing from it
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
sudo apt-get update

# Make sure the driver number matches the GPU. Also -440 would most likely work.
sudo apt install cuda-10.1

# Check which libs are now where, just for your own sanity; env vars should be set after reboot by themselves.
sudo find /usr/local/cuda/ -name '*blas*'
sudo find /usr/lib/ -name '*blas*'

IF this fails and still curious, you can try with my instructions in https://github.com/tensorflow/tensorflow/issues/43236#issuecomment-693244342 using the "local" repo installation method and this way the CUDA version remains 10.1&TF works fine. Just make sure not to reboot before the end and ensure most recent nvidia-driver-418 suitable for your GPU is used (the same that you currently have). This does involve some risk when using on a primary PC, I just don't know a better way to quickly clean up everything cuda-related without removing the nvidia driver at the same time.

The problem is that libcublas seems to be missing when installing cuda-10.1 via apt
Check this thread for more details: https://forums.developer.nvidia.com/t/cublas-for-10-1-is-missing/71015/18

@bnsblue If using the local installer method that I detailed in my comment above [1] then libcublas.so.10 is being installed into /usr/lib/x86_64-linux-gnu/libcublas.so.10 and everything works fine without additional tweaks. This works both for Ubuntu 18.04 and 20.04. Indeed, the TensorFlow official GPU installation method does not work for me as well. Btw, for Ubuntu 20.04 one should still use the 1804 repo in order to get access to cuda-10.1 (2004 apt only seems to have cuda-11).
[1] It has involved a bit for our use and does not include the libcudnn7 and tensorrt bits, but this should still work as well. For nvidia drivers using v455. If you're interested, I can provide the full instruction that I'm using.

@ravikyram why this is waiting for author response? The steps in the documentation doesn't work.

@ahtik Thanks for the response! It would be awesome if you could share the full instructions :)

@ahtik I also tried your "local install" and libcublas.so.10 does not get installed into that location. Any ideas?

Must have gotten something wrong the first time, the libraries show up now. But nvidia-smi fails now.
sudo find /usr/lib/ -name '*blas*'
/usr/lib/x86_64-linux-gnu/libnvblas.so.<IP_ADDRESS>
/usr/lib/x86_64-linux-gnu/libcublas_static.a
/usr/lib/x86_64-linux-gnu/libcublasLt_static.a
/usr/lib/x86_64-linux-gnu/libcublas.so.10
/usr/lib/x86_64-linux-gnu/libnvblas.so.10
/usr/lib/x86_64-linux-gnu/libcublasLt.so.<IP_ADDRESS>
/usr/lib/x86_64-linux-gnu/libcublas.so
/usr/lib/x86_64-linux-gnu/libnvblas.so
/usr/lib/x86_64-linux-gnu/stubs/libcublas.so
/usr/lib/x86_64-linux-gnu/stubs/libcublasLt.so
/usr/lib/x86_64-linux-gnu/libcublasLt.so
/usr/lib/x86_64-linux-gnu/libcublasLt.so.10
/usr/lib/x86_64-linux-gnu/libcublas.so.<IP_ADDRESS>
/usr/lib/pkgconfig/cublas-10.pc

Then nvidia-smi yields: "NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running."
I will continue to try and get this working.

@johntmyers Did you make sure to restart the machine after all the driver and CUDA installation steps? This error is usually from not restarting.

@ahtik Yes, same issue. FWIW I'm using 18.04 on Google Compute Engine, so I'm not sure if something there is not working properly.

@ahtik thanks for your setup above, I would also be grateful if you shared your TensorRT instructions!

@ahtik
I have exactly followed the instruction dated Sep1-16. I am encountering the following error:
ioz@ioz-B250M-DS3H:~$ python3.6 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([10000, 10000])))"
2020-12-25 21:48:47.947244: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.6/dist-packages/tensorflow/init.py", line 41, in
from tensorflow.python.tools import module_util as _module_util
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/init.py", line 45, in
from tensorflow.python import data
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/init.py", line 25, in
from tensorflow.python.data import experimental
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/init.py", line 125, in
from tensorflow.python.data.experimental.ops.parsing_ops import parse_example_dataset
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/ops/parsing_ops.py", line 26, in
from tensorflow.python.ops import parsing_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_ops.py", line 27, in
from tensorflow.python.ops import parsing_config
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_config.py", line 31, in
from tensorflow.python.ops import sparse_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/sparse_ops.py", line 42, in
from tensorflow.python.ops import special_math_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/special_math_ops.py", line 30, in
import opt_einsum
ModuleNotFoundError: No module named 'opt_einsum'
ioz@ioz-B250M-DS3H:~$ python3.6 -c "import tensorflow as tf;

sess = tf.Session(config=tf.ConfigProto(log_device_placement=True))
bash: unexpected EOF while looking for matching `"'
bash: syntax error: unexpected end of file
ioz@ioz-B250M-DS3H:~$ python3.6
Python 3.6.9 (default, Oct  8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as               tf
2020-12-25 21:50:17.792384: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.6/dist-packages/tensorflow/init.py", line 41, in
from tensorflow.python.tools import module_util as _module_util
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/init.py", line 45, in
from tensorflow.python import data
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/init.py", line 25, in
from tensorflow.python.data import experimental
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/init.py", line 125, in
from tensorflow.python.data.experimental.ops.parsing_ops import parse_example_dataset
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/ops/parsing_ops.py", line 26, in
from tensorflow.python.ops import parsing_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_ops.py", line 27, in
from tensorflow.python.ops import parsing_config
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_config.py", line 31, in
from tensorflow.python.ops import sparse_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/sparse_ops.py", line 42, in
from tensorflow.python.ops import special_math_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/special_math_ops.py", line 30, in
import opt_einsum
ModuleNotFoundError: No module named 'opt_einsum'
import tensorflow as tf
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.6/dist-packages/tensorflow/init.py", line 41, in
from tensorflow.python.tools import module_util as _module_util
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/init.py", line 45, in
from tensorflow.python import data
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/init.py", line 25, in
from tensorflow.python.data import experimental
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/init.py", line 125, in
from tensorflow.python.data.experimental.ops.parsing_ops import parse_example_dataset
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/ops/parsing_ops.py", line 26, in
from tensorflow.python.ops import parsing_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_ops.py", line 27, in
from tensorflow.python.ops import parsing_config
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_config.py", line 31, in
from tensorflow.python.ops import sparse_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/sparse_ops.py", line 42, in
from tensorflow.python.ops import special_math_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/special_math_ops.py", line 30, in
import opt_einsum
ModuleNotFoundError: No module named 'opt_einsum'

ioz@ioz-B250M-DS3H:~$ python3.6
Python 3.6.9 (default, Oct  8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.

import tensorflow as tf
2020-12-25 21:50:37.806079: I tensorflow/stream_executor/platform/default/dso_loader.cc:48] Successfully opened dynamic library libcudart.so.10.1
Traceback (most recent call last):
File "", line 1, in
File "/usr/local/lib/python3.6/dist-packages/tensorflow/init.py", line 41, in
from tensorflow.python.tools import module_util as _module_util
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/init.py", line 45, in
from tensorflow.python import data
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/init.py", line 25, in
from tensorflow.python.data import experimental
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/init.py", line 125, in
from tensorflow.python.data.experimental.ops.parsing_ops import parse_example_dataset
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/data/experimental/ops/parsing_ops.py", line 26, in
from tensorflow.python.ops import parsing_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_ops.py", line 27, in
from tensorflow.python.ops import parsing_config
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/parsing_config.py", line 31, in
from tensorflow.python.ops import sparse_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/sparse_ops.py", line 42, in
from tensorflow.python.ops import special_math_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/special_math_ops.py", line 30, in
import opt_einsum
ModuleNotFoundError: No module named 'opt_einsum'

Can you please help me with your thoughts.
Thanks
Guru

@javedsha The following is a procedure I use for Ubuntu 18.04, confirmed to work with the Ubuntu-shipped python 3.6. Hope it helps to pinpoint your issue.
In your case, the trouble possibly started with the sudo apt-get install cuda-toolkit, as it's not fixed to 10.1. Having 10.1 parallel to 10.2 and 11.0 is not advisable, nor practically feasible due to the env vars.
Btw, CUDA version that is reported by the nvidia-smi is not necessarily the CUDA version that Tensorflow picks up (longer story), but with my installation procedure it should report 10.1.
# To start fresh, clean up all the nivida-related packages. Be careful when using the same system as a desktop!
sudo apt-get --purge remove 'cuda*'
sudo apt-get --purge remove 'nvidia*'
sudo apt-get --purge remove 'libnvidia*'

# Check if all clean
sudo find /usr/local/cuda/ -name '*blas*'
sudo find /usr/lib/ -name '*blas*'

# CUDA 10.1 instructions for creating a locally available repo and installing from it
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
sudo apt-get update

# Make sure the driver number matches the GPU. Also -440 would most likely work.
sudo apt install nvidia-driver-418
sudo apt install cuda-10.1

# Make sure the libs are now in place
sudo find /usr/local/cuda/ -name '*blas*'
sudo find /usr/lib/ -name '*blas*'

# Run nvidia-smi for sanity check
nvidia-smi

python3 -m venv ~/.venv-tf2.3-sanity
. ~/.venv-tf2.3-sanity/bin/activate
pip install -U pip
pip install tensorflow==2.3
python -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([10000, 10000])))"

I thank @ahtik for his post. I would like to contibute with my own recipe that I derived from @ahtik 's one. Some comments down below.
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget http://developer.download.nvidia.com/compute/cuda/10.1/Prod/local_installers/cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu1804-10-1-local-10.1.243-418.87.00_1.0-1_amd64.deb
sudo apt-key add /var/cuda-repo-10-1-local-10.1.243-418.87.00/7fa2af80.pub
sudo apt-get update

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/nvidia-driver-440_440.33.01-0ubuntu1_amd64.deb
sudo apt install -y ./nvidia-driver-440_440.33.01-0ubuntu1_amd64.deb

sudo apt-mark hold libnvidia-cfg1-440 libnvidia-compute-440 libnvidia-decode-440 libnvidia-encode-440 libnvidia-fbc1-440 libnvidia-gl-440 libnvidia-ifr1-440 nvidia-compute-utils-440 nvidia-dkms-440 nvidia-driver-440 nvidia-kernel-common-440 nvidia-kernel-source-440 nvidia-utils-440 xserver-xorg-video-nvidia-440

sudo apt install cuda-drivers=440.33.01-1 cuda-runtime-10-1 cuda-demo-suite-10-1 cuda-10.1

wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/libcudnn7_<IP_ADDRESS>-1+cuda10.1_amd64.deb
wget https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/libcudnn7-dev_<IP_ADDRESS>-1+cuda10.1_amd64.deb
sudo dpkg -i libcudnn7_<IP_ADDRESS>-1+cuda10.1_amd64.deb libcudnn7-dev_<IP_ADDRESS>-1+cuda10.1_amd64.deb
sudo dpkg -l | grep cudnn

cat /usr/include/cudnn.h | grep CUDNN_MAJOR -A 2

My server GPU model: GeForce GTX 1070
Driver version: cat /proc/driver/nvidia/version 440.33.01

I had to force cuda-drivers to be 440.33.01-1 to make my nvidia-smi work after the installation.
I had to apt-mark hold some libraries to prevent their automatic upgrade during the installation of cuda 10.1.
I installed only python 3.8 and tensorflow 2.3.0 in my conda environment, to meet tensorflow requirements for cuda 10.1: https://www.tensorflow.org/install/source#gpu.
I realized that in my system I had to use cudnn 7.6.0 instad of 7.6.5 to make E tensorflow/stream_executor/cuda/cuda_driver.cc:314] failed call to cuInit: CUDA_ERROR_NOT_INITIALIZED: initialization error disappear.
I did NOT install cudnn and cudatoolkit in my conda environment.
I exported the following environment variables at login in my .bashrc:

export CUDA_HOME=/usr/local/cuda
export PATH=$CUDA_HOME/bin:$PATH
export LD_LIBRARY_PATH=$CUDA_HOME/lib64:/usr/local/cuda-10.2/lib64 (see https://stackoverflow.com/a/64472380/11644517)
export XLA_FLAGS=--xla_gpu_cuda_data_dir=$CUDA_HOME
export TF_XLA_FLAGS="--tf_xla_enable_xla_devices"

Check if the GPU is working with:
python3 -c "import tensorflow as tf; print(tf.config.list_physical_devices('GPU'))"


Missing .bat file

The build.bat is missing completely, its not in the art folder at all.

i've looked in other places and have found nothing.

build manually. lime test windows -release


Meshes of the fingers include parts of the lever in the simulated model

When moving the fingers in simulation I noticed that there are some part of the mechanism - probably even not required for the scope of the simulation - that move strangely:

https://user-images.githubusercontent.com/6014499/225933133-10316d8a-91a0-4a37-9cca-3e93a7d2c8ed.mp4
I though it was useful to notify that in case it reveals any kind of issue within the urdf generation process.
cc @mfussi66 @Nicogene

Because it is wanted. 😃

Can you elaborate on this @Lawproto?

what do you mean by "strangely"?

As I said in the comment, the simulation of that lever is not probably required as the constraint between the two phalanges is enforced software-wise, here  while Gazebo does not use the lever actually.
Nonetheless, I would say that the mesh should not contain that part probably. Not sure if that was wanted.

I just updated the title of the issue to better reflect the actual problem.

Nonetheless, I would say that the mesh should not contain that part probably. Not sure if that was wanted.

This is questionable, I have to integrate the lever in some link to match the mass of the CAD model. It was convenient for me to have it in the last phalanx. Since our CAD-to-URDF is convoluted enough, I would personally live with the aestethic imperfection.

I just updated the title of the issue to better explain the actual problem.
It is not the goal of the URDF to capture exactly how the real-life mechanism operates. As long as the relation between the angles of the links (aka the phalanges) is correct while they rotate, I cannot see any problem.
@xEnVrE I am starting to miss the whole point of this issue, can we please discuss F2F?

It is not the goal of the URDF to capture exactly how the real-life mechanism operates.

That's true outright 👍🏻
However, having a mesh that can somehow interact with the environment during grasping or that does not represent the geometry of the hand could be a headache sometimes.
Perhaps, we can get away with less in the mid-term by removing the mesh and assigning its weight to the phalanx via software.

However, having a mesh that can somehow interact with the environment during grasping or that does not represent the geometry of the hand could be a headache sometimes.

Ok, I can see your point.

Perhaps, we can get away with less in the mid-term by removing the mesh and assigning its weight to the phalanx via software.

Knowing all of this, I could directly integrate the same lever in the medial phalanx for the next URDF generation instead, so it does not lean out.

Me and @Lawproto discussed f2f on it and we agreed that the URDF cannot 100% reproduce the real mechanism and never will as it does not offer the formalism to do it.
We also agreed on the fact that if it was only an aesthetic issue we could probably neglect it. There might be however other connected issues - we did not consider before - such as unwanted collisions or difficulties in using tools like idyntree-model-simplify-shapes which constructs simplified representation of the URDF  and approximates each solid shape of the model with its axis aligned bounding box.

We agreed with @Nicogene and @mfussi66 to adjust manually the meshes of the phalanxes to remove the levers. The weights and the mass matrices will remain unvaried.
@Lawproto, let's remember that we should take this into account whenever in the future we yield the urdf of the hands once again.

Hi @xEnVrE
We will attack this task in our next sprint: Apr 3 – Apr 14.

Below you can find the meshes before and after the manual removal of the levers:
Before

After

Of course the cut is "approximate" as the surfaces of the mesh are not that smooth.
If they are ok I can open a PR with the updated meshes (of course also the right hand will be included!).
cc @pattacini @Nicogene

Of course the cut is "approximate" as the surfaces of the mesh are not that smooth.

@xEnVrE it seems a great job to me!

Let's do it!
Thanks again @xEnVrE!


Add UTType for ASE

I couldn't find a UTType for it online, so the extension is the only think we have.

Thanks so much for the improvement @sindresorhus. Nice clean fix!


Stop using Parallel for SparkFeatureUnion

See https://issues.apache.org/jira/browse/SPARK-12717
The parameter is still here for the converted to_scikit() object
I think it explain the flappy test on my previous PR

Is this issue still present in Spark 2.0.0?

I do not know, the issue appears randomly and I have not reproduced it on my cluster. I have add spark 2.0 to CI in #71 but as it is random, I do not know if it will allow to conclude.
I think this parallelization is not very usefull for a spark computation.

Without threading a pipeline steps will be executed sequentially. I think n_jobs make sense, multiple dags will be submitted and executed in parallel. The overall level of parallelization can be increased via n_jobs.
Shouldn't we drop support for spark versions before 2.0.0?

According to apache jira, it is still an issue in pyspark 2.0.2


websocket_server_async example with strand ws

Beast version 1.71.0
Hello,
I have a simple question about websocket_server_async.cpp example.
In this example session does not use strand. Only listener.
Why we do not need strand for ws ?
If I want to use it how should I use it ?
When construct the ws with boost::asio::make_strand(socket.get_executor()) like this
(as I know there is no need for 1.7 version to bind with strand anymore. )
   session(tcp::socket&& socket)         : ws_(boost::asio::make_strand(socket.get_executor()))
then it compiles but it gives Bad file descriptor error during ws_.async_accept.
accept: Bad file descriptor
Could you please help me about this issue ?  How can I use listener websocket with strand ?
Thank you.

Why we do not need strand for ws ?

The latest version of the example is multithreaded, and uses strands:
https://github.com/boostorg/beast/blob/b15a5ff0e47e72ba3d4711d2514bc65749d036ae/example/websocket/server/async/websocket_server_async.cpp#L222


Merge develop branch into master

Closes #146

The CI has passed, but I will double check that nothing is broken locally tomorrow. (The CI is not very thorough yet)

Thanks for this. It will be interesting to see how we can update the drivers not updated so far.

It will be interesting to see how we can update the drivers not updated so far

Uf, I forgot about this. Branch develop is not working so we can't merge it now...

@tore-espressif I will update the drivers init functions so we can merge develop into master more easily

@tore-espressif @C47D it would appear that master and develop are diverging further and further apart. What's the plan and timeline to merging the two branches together? Right now, from me testing the two for my own needs, both have their set of issues that the other one fixes.

@rashedtalukder Thank you very much for reminding me. I was quite busy lately, but I want to attend to it this week.
Could you please mention the issues you're experiencing, just so we don't forget anything?

Some of the drivers have been updated (passing a pointer to the registered lv_disp_drv_t as parameter to their init function), we will need to update the others.
Apart from that I think there will be no problem with merging develop into master.
I have been busy with day work and other stuff, and will be at least for two weeks, but let me know if you need any help.

@C47D  There are 116 (!) commits that are in develop and not it master.
There are (only) 8 commits that are in master and not in develop (4 out of these 8 are reverts, see here: https://github.com/tore-espressif/lvgl_esp32_drivers/pull/6)
So it seems easier to me to fix develop once and for all and then force merge it into master. Do you agree?


Problem with set content

Here is my storyboard, these two red mark show the view that I used for side menu. And this is my dir

My code looks fine, but I don't know why I can not set ContentView

which I click the sidebar item, nothing happened to second view controller

Well I realize that was I am using both tab layout and navigation controller, which confused me very much, how do I use both tab bar and sidebar?

The tab bar and side bar are really 2 different entities. There is no conflict at all.
Think you need something like this as your last line:
presentViewController(destinationViewController, animated: true, completion: nil)

same problem, did you find a solution?

Same problem, did you find a solution ?
presentViewController(destinationViewController, animated: true, completion: nil)
not  really a good idea i think, we loose self.pushViewController .... so the Navigation Bar
I am blocked to make it worked with a tab bar controller, if somebody has an example !

@PierreBrisorgueil I did find a solution here. Maybe you can contact me via<EMAIL_ADDRESS>

@lostpupil Ok thx, i solved my problem with SWRevealViewController, but i will send you a mail.
I will be happy to understand and offer a sample for this with ENSwiftSideMenu on GitHub if you are agree.

Same problem.. Can anyone please post a solution for this ? @lostpupil ?

no solution for me, just try SWRevealViewController, it will take 15 min max @vimalsaifudin


HuskSync and EcoEnchants in will result in the loss of NBT

My English is poor, please forgive my machine translation
HuskSync 2.1.2
EcoEnchants 8.111.0
Server purpur 1.19.2
MySQL： 8.0.0
Redis：5.0.10
When the player jumps to the server, HuskSync will cause EcoEnchants to lose EnchantsNBT
For example, NBT：
Enchantments(List){"Stat":"ENCHANTS","OGStory":[{"MMOITEMS_ENCHANTS_ñstr":"["bolt 9","plasmic 10","razor 10","criticals 10","thor 10","parry 6","zap_artifact 1"]"}]}
My friend he is HuskSync 2.1 EcoEnchants 8.111.0 and did not have this problem
Hope the author can fix this BUG

HuskSync will sync the persistent data container tags and doesn't sync custom NBT; more likely then not EcoEnchants is using the PDC, however it's possible something broke or the format changed in an update? We don't provide tracking for individual plugin issues or compatibility, so I'm closing this.

HuskSync will sync the persistent data container tags and doesn't sync custom NBT; more likely then not EcoEnchants is using the PDC, however it's possible something broke or the format changed in an update? We don't provide tracking for individual plugin issues or compatibility, so I'm closing this.

Yes, items in Shulker Box will not be a problem, items in the backpack will be lost NBT

HuskSync will sync the persistent data container tags and doesn't sync custom NBT; more likely then not EcoEnchants is using the PDC, however it's possible something broke or the format changed in an update? We don't provide tracking for individual plugin issues or compatibility, so I'm closing this.

Yes, items in Shulker Box will not be a problem, items in the backpack will be lost NBT

Modded items that utilise proprietary item formats aren't currently supported in general in favour of supporting the PDC API


[PX-2975] Updates galleries_institutions to use metaphysics v2

Blocked by: https://github.com/artsy/metaphysics/pull/3259
Jira ticket: https://artsyproduct.atlassian.net/browse/PX-2975
This PR updates the galleries/institutions app to use metaphysics v2 instead of v1. It relies on the schema updates in the ☝ metaphysics PR, hence the [Don't Merge] 😄.
The updates are because the schemas are slightly different, but I clicked around a bit and I think we're all good! 🤞

Alright! Metaphysics has been deployed and hopefully the tests pass now 🤞 . Will keep an eye on it!


Fix #577 | Current view topnav item now being highlighted | Reopen

This is fix for Issue #577
So the problem was, in app/views/topnav.html (line 12-14),

    {{navItem.title}}

And here root.currentView comes from watch function for change of state in app/js/on_run.js where currentView was set as state.title but that title is not same as the nav title so the issue was occurring!
I have created currentView element in required states and set $rootScope.root.currentView = toState.currentView;
Note: As asked by @sudheesh001, I have squashed the changes into single commit. And reopened the Pull Request #578.

@akigupta131 Following up. Could you answer my previous query

@sudheesh001 Hi, I have just corrected the indentation.

closing for now, as #577 postponed


fix chk resource version make noisy

fix chk resource version make noisy
Important items to consider before making a Pull Request
Please check items PR complies to:

[ ] All commits in the PR are squashed. More info
[ ] The PR is made into dedicated next-release branch, not into master branch1. More info
[ ] The PR is signed. More info

--
1 If you feel your PR does not affect any Go-code or any testable functionality (for example, PR contains docs only or supplementary materials), PR can be made into master branch, but it has to be confirmed by project's maintainer.

0.23.6 already released, you can't add code to already released branch

0.23.6 already released, you can't add code to already released branch

i got it, and looks 0.24.0 has recolved this problem


API endpoint table

See req. 8.3.

I've added the following api end point tables

[x] User endpoint table.
[x] Book endpoint table.
[x] Publisher endpoint table.

We still need to do the following ones when their controllers gets done:

[ ] Authentication endpoint table.
[ ] Statistic endpoint table.

Could we do something like this for the endpoints table?
I think it would be good to have examples of both request and response bodies present. It will enhance the understanding and ease of use of our API.

I agree with Mike, that would be nice 🙂

I thought those would be done for issue #37 or #33

Aaah, Yes. That would make sense.
So what you've made here is just an overview?

Yes, we can also just combine those two but, I thought we agreed to an overview and then a more in-depth table for the sub-requirements in our requirement specification? I am fine with combining them. Req. 8.3 The overview table will then become the entire 8.3.a sub-requirement if we combine them.

Hmm. I don't know. I'm fine with either as well 🤷

I would prefer if we followed the requiments and linked to different sections with the models to keep the API tables short and concise. The link could just be the endpoint name of the 'API endpoint' column.

I will make an issue for the remaining two tables and then move this to done. 😊


Prevent text edits and keyboard commands from reaching the host application

Just tried to use VisBug to modify some text via VisBug in the Google Cloud Platform console, and the keys I pressed did things in the host application, including taking me to some other page. In my opinion, if VisBug handles a keyboard event, it should prevent that event from getting to the host application. Otherwise, both VisBug and the host application handle it, which is never what you want.
When I'm in text edit mode, allow me to type and prevent any of those keypress, input, etc events from getting to the host application. Similarly, if I press a keyboard shortcut that VisBug understands, that also should not reach the host application. My assumption is that event.stopPropagation() would do this, but I'm not deeply familiar with how it works.

VisBug is using capture but if it's captured by the host logic first, then visbug cannot capture that which has already been captured. In order for Visbug to completely take all keyboard commands, it'd need to be a level higher than the page, like devtools is.
aka: i can't steal and keep what's already been stolen. Visbug is a visitor to the page, and sometimes the code there is preventing visbug from getting an effect done or, in this case, keypress management.
thanks for logging this, i'll leave it open, it'd be nice to solve one day!

good point, I hadn't thought about it that way.
In addition to capture, is VisBug also using event.stopPropagation()?

yep! along with all the other friends to try and orchestrate which feature/tool owns which part of the user interaction during which combination of keys. it's all doing it the best it can, but things do leak as you've noticed.


[NEXT]: Trouble getting cockpit to work with nginx

Hi,
I am having trouble to get cockpit to work on nginx. My nginx configuration looks like:
        index index.php;

        location / {
                try_files $uri $uri/ /index.php;
        }

        # Change "cockpit" to the folder name containing cockpit files.
        location /cockpit {
                try_files $uri $uri/ /cockpit/index.php;
        }

        location ~ \.php$ {
            fastcgi_split_path_info ^(.+\.php)(/.+)$;
            fastcgi_pass unix:/var/run/php/php7.0-fpm.sock;
            fastcgi_index index.php;
            include fastcgi_params;
            fastcgi_param SCRIPT_FILENAME $document_root$fastcgi_script_name;
        }

No matter what I try it looks like the only route that is working is:
$app->bind("/", function($params) use($app){
    return "Hello index";
});

// nl route this route does not work!
$app->bind("/nl", function($params) use($app){
    return "Hello NL route";
});

What am I missing here?
BTW, my nginx version is nginx version: nginx/1.10.1 (Ubuntu)

Known issue, Lime/App uses unfortunately PATH_INFO instead of REQUEST_URI.


implement put_u8 for BytesMut

Benching before and after shows that this implementation is about twice as fast as going through put_slice.

You could probably make it even faster by only having one is_inline() check :) You can roughly see what I mean here: https://github.com/carllerche/bytes/pull/82
Do you want to try that out?

Yes, reducing the is_inline to one call makes it a little over 2x faster than this proposed implementation, for a total ~4x faster...

Laziness :). Fixed.


Update node-forge to 0.10.0

Security fix for node-forge dependency — https://github.com/advisories/GHSA-92xj-mqp7-vmcj

Coverage remained the same at 100.0% when pulling 7518c594ca51bba806ddd16e59d718ac9b2b9f52 on rebbix:master into 38a357ed0c153aad09c2857e48a710527e685bfc on node-apn:master.

Hi! is this going to be merged anytime soon?

Please merge to fix Dependabot warnings

Guys this needs to be merged... it's been a high vulnerability for a long time.

If anyone wants to use this in the meantime I forked and updated it: https://github.com/danthegoodman1/node-apn

I recommend using this library: https://www.npmjs.com/package/@parse/node-apn


feat: allow other entrypoints

The change allows the user to run tanka with alternative entrypoints, not limiting to main.jsonnet anymore.
This opens the door to using tk eval for purposes outside of the Tanka/K8s Environments paradigm. For example, one can
write a library with a test.jsonnet and run tk eval test.jsonnet in that library. Caveat: it needs to have a
tkrc.yaml or jsonnetfile.json so Tanka can resolve the JPATH. It also works for tk export and tk show, beware
that it will add default namespace to kubernetes objects, even though a spec.json might not exist.
This change is backwards compatible and still defaults to main.jsonnet if no file is given, tk diff will still want a
spec.json to connect to a cluster.
Feel free to give feedback/pushback on the idea here too.
I've done a grep on main.jsonnet in the codebase to set this up, but there are many other valid references to
main.jsonnet left that don't need replacing.

Adding lifecycle/blocked here because Tanka is currently in feature-freeze (not accepting features not required for the release), so we can get 0.12 out.
Will review once released

rebased

rebased.


Allow to specify the musicbrainz ID when importing without having to wait for beet to search first

From IRC:

16:02:52 < ryanakca> sampsyo: I'm not sure, specifying a music brain ID or URL
on the command line might be messy, but something along the lines of : beet
import -m ID/URL path
16:03:21 < derwin> that'd be sweet.
16:03:33 < derwin> and the code that parses the mbids would totally support
that...
16:04:11 < ryanakca> Alternatively, just cut straight to the "Not found in
musicbrainz db/FAQ link" prompt and allow users to enter the id there (not as
useful for scripting, but I doubt anybody keeps a
                     correspondence between IDs and CD directories)
16:05:03 < ryanakca> This would be particularly useful when importing 10CD
collections and it takes beets ages to look it up in musicbrainz

Original issue reported on code.google.com by<EMAIL_ADDRESS>on 17 Aug 2012 at 1:57

Do not comment here, but on sampsyo/beets#170


Matching against empty body

I have Play application exposing an API, my controller looks like that
class ApiController @Inject()(someClass: SomeClass) extends Controller {
  def addStuff = CorsAction.async(CustomBodyParsers.somePayloadFromJson) { request ⇒
    async {
      await(someClass.someMethod(someParams))
      Ok
    }
  }
}

CorsAction is doing quite nothing except adding headers to allow cross-domain calls, removing it does not make any difference:
object CorsAction extends ActionBuilder[Request] {
  val corsHeaders = Seq(
    "Access-Control-Allow-Origin" -> "*",
    "Access-Control-Allow-Methods" -> "POST, GET, PUT, DELETE, OPTIONS",
    "Access-Control-Allow-Headers" -> "Origin, X-Requested-With, Content-Type, Accept, Referer, User-Agent",
    "Access-Control-Max-Age" -> "1728000"
  )
  def invokeBlock[A](request: Request[A], block: (Request[A]) => Future[Result]) =  Async.async {
    await(block(request)).withHeaders(corsHeaders: _*)
  }
}

This is how I'm matching response in pact file:
{
  "description": "A POST request to add stuff",
  "request": {
    "method": "post",
    "path": "/add",
    "headers": {
      "Content-Type": "application/json"
    },
    "body": {
      "someName": "someValue"
    }
  },
  "response": {
    "status": 200
  }
}

And pact fails with the following output:
BodyMismatch(None,Some(),None,/) (Transformer.scala:20)

So, I guess None and empty body are not 100% correctly matched here: https://github.com/DiUS/pact-jvm/blob/master/pact-jvm-matchers/src/main/scala/au/com/dius/pact/model/Matching.scala#L101-L106
Can you, please, check it?

It is treating a missing body (i.e. no body attribute in the pact file) as different as an empty body. This should not be the case.
Changing the pact file to have an empty body may match. But I'll update the de-serialisation code to return a None for an empty body as well.

You should not get a failure now, as the empty response body should be mapped to None.

Yeah, I tried to put "body": "" in pact file, but it did not helped, mismatch was still there, don't have log output, but it was something like
Some("") vs Some()
Anyway, should be fixed now with your fix, thanks a lot for a quick one :) Do you have plans to release a new version to maven repo?

BTW, after checking the code, I did not really understood how to create a pact for checking only status code without checking body. Like I don't care what's in the body as long as http 200 is coming back after sending post request, guys on provider could put "ok" or "done" or "status": "ok" or whatever else.
The only way I found is leaving pact without body, like in my initial post and checking pacts by creating my own copy of ResponseMatching with DiffConfig(allowUnexpectedKeys = true, structural = true) or am I missing something?

Ok, I now understand what you require. You are correct, leaving the body out means you don't care about it. I'm going to revert the previous commits, because an empty body is different than not validating the body.
I'll review the matching code you hi-lighted and double check the behaviour with the Ruby and .Net versions, but my thoughts are to remove the if statement from line 103. This should fix your problem.

Yes, right, sorry for explaining it wrong way at the beginning.
I'm quite new to Scala, but to me it looks like it would even be possible to replaces lines 102-103 with the following:
case (None, _) => List()

That is probably a better version, but the commit I made should resolve your issue.

Yep, this will also fix the issue. Would it be possible to publish 2.1.10 with last change to maven repo?

Yes, I'm doing the release now. It will take a few hours for the artifacts to be available on maven central.

Cool, thanks! Closing issue now.

Unfortunately I have to annoy you once more and reopen issue, because I found that this issue is not completely fixed during writing more pacts. Situation:

no body and no content-type header defined in pact request, pact-provider code uses "text/plain" as fallback.
provider returns some json or some xml.
bodyMatch function returns on this line: https://github.com/DiUS/pact-jvm/blob/master/pact-jvm-matchers/src/main/scala/au/com/dius/pact/model/Matching.scala#L109 --> boom! test fails.

I've added additional check for that and text files to verify this situation, as well as fixed failing unit test. Pull request is on the way, but I have to say, I did not checked .NET or ruby implementations on how they behaving in situations like that.

.NET and ruby has the correct behaviour (I asked on the pact-dev group). I'm going to add the specification tests to the specification project.

Copied the empty body test cases over to the pact spec project


Provide inference of Detic

Thanks for your contribution and we appreciate it a lot. The following instructions would make your pull request more healthy and more easily get feedback. If you do not understand some items, don't worry, just make the pull request and seek help from maintainers.
Motivation
Provide inference of Detic.
Modification
Add Detic1 to projects.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

Hi @ryylcc,
We'd like to express our appreciation for your valuable contributions to the mmdetection. Your efforts have significantly aided in enhancing the project's quality.
It is our pleasure to invite you to join our community thorugh Discord_Special Interest Group (SIG) channel. This is a great place to share your experiences, discuss ideas, and connect with other like-minded people. To become a part of the SIG channel, send a message to the moderator, OpenMMLab, briefly introduce yourself and mention your open-source contributions in the #introductions channel. Our team will gladly facilitate your entry. We eagerly await your presence. Please follow this link to join us: https://discord.gg/UjgXkPWNqA.
If you're on WeChat, we'd also love for you to join our community there. Just add our assistant using the WeChat ID: openmmlabwx. When sending the friend request, remember to include the remark "mmsig + Github ID".
Thanks again for your awesome contribution, and we're excited to have you as part of our community!


buildGoModule might produce different checksum depending on the platform (linux <> darwin)

Describe the bug
Discovered in https://github.com/NixOS/nixpkgs/pull/129649/files#r666294752
To investigate this we would need someone with both Linux and macOS to provide the module derivations for both.

diff -rq /nix/store/9d1rp6pmfaa1sxj5ni40jd5xwwzwdhfc-telegraf-1.19.1-go-modules /nix/store/izq65v2jbqjfb29289hcpkwfkwb8yfqc-telegraf-1.19.1-go-modules
Only in /nix/store/izq65v2jbqjfb29289hcpkwfkwb8yfqc-telegraf-1.19.1-go-modules/github.com/Microsoft: ApplicationInsights-Go
Only in /nix/store/9d1rp6pmfaa1sxj5ni40jd5xwwzwdhfc-telegraf-1.19.1-go-modules/github.com: microsoft~nix~case~hack~1

https://github.com/NixOS/nixpkgs/blob/3f92843767e8e1b83b2401a9ccc44f8debc6919d/pkgs/tools/misc/opentelemetry-collector/default.nix#L18-L20
diff -rq /nix/store/x3mqwlqzrpgbnczsy8ca02ynnc1nsijv-opentelemetry-collector-0.26.0-go-modules /nix/store/naii9fxpfcr2kcj845g3b7hp9ghh6xbm-opentelemetry-collector-0.26.0-go-modules
Only in /nix/store/x3mqwlqzrpgbnczsy8ca02ynnc1nsijv-opentelemetry-collector-0.26.0-go-modules/github.com/Microsoft: ApplicationInsights-Go
Only in /nix/store/naii9fxpfcr2kcj845g3b7hp9ghh6xbm-opentelemetry-collector-0.26.0-go-modules/github.com: microsoft~nix~case~hack~1

diff -rq /nix/store/9d1rp6pmfaa1sxj5ni40jd5xwwzwdhfc-telegraf-1.19.1-go-modules /nix/store/izq65v2jbqjfb29289hcpkwfkwb8yfqc-telegraf-1.19.1-go-modules
Only in /nix/store/izq65v2jbqjfb29289hcpkwfkwb8yfqc-telegraf-1.19.1-go-modules/github.com/Microsoft: ApplicationInsights-Go
Only in /nix/store/9d1rp6pmfaa1sxj5ni40jd5xwwzwdhfc-telegraf-1.19.1-go-modules/github.com: microsoft~nix~case~hack~1

https://github.com/NixOS/nixpkgs/blob/3f92843767e8e1b83b2401a9ccc44f8debc6919d/pkgs/tools/misc/opentelemetry-collector/default.nix#L18-L20
diff -rq /nix/store/x3mqwlqzrpgbnczsy8ca02ynnc1nsijv-opentelemetry-collector-0.26.0-go-modules /nix/store/naii9fxpfcr2kcj845g3b7hp9ghh6xbm-opentelemetry-collector-0.26.0-go-modules
Only in /nix/store/x3mqwlqzrpgbnczsy8ca02ynnc1nsijv-opentelemetry-collector-0.26.0-go-modules/github.com/Microsoft: ApplicationInsights-Go
Only in /nix/store/naii9fxpfcr2kcj845g3b7hp9ghh6xbm-opentelemetry-collector-0.26.0-go-modules/github.com: microsoft~nix~case~hack~1

I don't really understand the diff. Are there different files in both?

Seems to be a case-insensitive conflict with github.com/Microsoft and github.com/microsoft.

Could we normalize this in our code for buildGoModule?

I'd be a bit concerned that any normalization we do ourselves may end up causing more problems with other workarounds or the go 1.17 vendor changes, especially if we end up with 1.17 as default on linux and keeping 1.16 for darwin.
I think I've got a fix that just uses go itself, I'll open a PR in the next couple of days.

Draft fix: https://github.com/NixOS/nixpkgs/pull/131452

Should be resolved by https://github.com/NixOS/nixpkgs/pull/131452


closes issue #46

closes issue #46
fixes some wrong variable names in the help of opt_checkProplist and  opt_setDefaults

Signed-off-by: DanielMiklody<EMAIL_ADDRESS>

sorry for the misunderstanding.... now the doc change is reverted.


Open on GitHub

If I hit some hotkey instead of hitting enter/space, it'd be great if the tool attempt to open whatever I've selected / whatever I'm viewing on GitHub instead of switching views.

Would it make sense to default to origin or upstream?

I don't think it matters, as long as git merge-base --is-ancestor COMMIT REMOTE_NAME/BRANCH_NAME tells us that the commit we're looking at is on the remote.
Maybe iterate over all potential remotes with git for-each-ref --format='%(refname)' refs/**/BRANCH_NAME, and if the only thing that matches is refs/heads/BRANCH_NAME, just show an error message?

So, I have a bash script that does something similar, and perhaps it could be useful:
https://github.com/natecavanaugh/dotfiles/blob/master/bin/git-get-github-url
But the gist is that origin is the default remote, but can be specified by passing -r REMOTE, but it will also try to parse out the output of the git remote -v command and use that info to open the file.
But it also allows you to load a specific file, as well as load a compare view with something like
git get-github-url HEAD^^..HEAD will load up a view like this: https://github.com/natecavanaugh/dotfiles/compare/HEAD^^...HEAD
Anyways, just thought it might be useful depending on what you wanted to look at (and I could see some of these options used by using key modifiers when running the command).
:)

Thanks @natecavanaugh.  I'll check that out (and maybe borrow it with your permission 👍 ).

@drewbrokke If there's anything in there worth taking, help yourself. I just use it whenever I need a link to a file I'm looking at on my system. I think your tool's a lot more useful :)

Closing in favor of the solution for https://github.com/drewbrokke/jack-cli/issues/23.
https://github.com/drewbrokke/jack-cli#custom-key-commands


Fix long names

I open this PR to fix some problems reported by @ozanmert:

All pressure level u winds such as ua300, ua 2000... Have standard and long names "eastward wind" with no other detail... Is this intended?
There are some inconsistencies between variable names and their long names, such as: The long name of ua300m is "eastward wind at 250m"... I guess this should be corrected?

Thank you, Ozan
Standard names must follow those defined by CF, and these represent the physical quantity. Other aspects, such as the level, are represented by other metadata of the variable (such as a scalar coordinate variable representing the pressure level). So standard_names are OK even if repeated for many different variables.
Long names are not critical as these are just free text descriptions. However, you spotted a clear inconsistency between the variable and the corresponding metadata, so this should be fixed. I let the PR open, just in case you found some others.
Long names without much detail are no problem, in principle. For pressure level data we could include the level explicitly, though. E.g. in CMIP6 they do include it:
https://github.com/PCMDI/cmip6-cmor-tables/blob/80d2e4b606555720630a61389cfe3b5cb8f43746/Tables/CMIP6_6hrPlev.json#L312
@larsbuntemeyer @gnikulin what do you think?

I can add this into this PR.

I fix this in #41 after restructuring.


Support styling for the pill component

Detailed description
carbon-components-angular provides a pill component but there is no styling for it. It renders as below. We need to use this component in our product though so we need it to be styled properly.

Is this a feature request (new component, new icon), a bug, or a general issue? Feature request
Is this issue related to a specific component? Yes
What did you expect to happen? What happened instead? What would you like to see changed? New styling available for the Pill component
What browser are you working in? All supported browsers
What version of the Carbon Design System are you using? Latest
What offering/product do you work on? Any pressing ship or release dates we should be aware of? IBM Assess

@markewallace FYI this is the issue we need addressed to get proper styling for the pill component.


Wandering Trader ignores Enchantment restrictions

When enabling the village module the wandering trader ignores most enchantment limitations set in the Enchanting module. I.E. I have set all enchantment limits to vanilla standards, yet the trader offers items with Fortune 7, or Boon of the Earth 4.

This is not a bug. The items sold by the trader have statically-encoded levels (ex: https://github.com/Shadows-of-Fire/Apotheosis/blob/1.20/src/main/resources/data/apotheosis/wanderer_trades/arachnids_fear.json#L22).  They can be changed with a datapack, but otherwise adhere to no limits.


[Feature Request] Add list menu in noweb

Several customers are asking for the WhatsApp list menu to use in place of the buttons that have been discontinued in the unofficial APIs.
I'm using the no-web lib
The list menu I say is the one in print:

+1

+1 😥


Generated functions: Help content

FEATURE: Generated functions should contain a copy of help content
  Help content should include:
      Synopsis
      Parameter specific help
  Inclusion of help content in a stub should be optional (at command level)

Thank you!
On 7 Apr 2017, at 10:52, Chris Dent <notifications<EMAIL_ADDRESS>wrote:
FEATURE: Generated functions should contain a copy of help content
Help content should include:
Synopsis
Parameter specific help
Inclusion of help content in a stub should be optional (at command level)
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHubhttps://github.com/indented-automation/Indented.StubCommand/issues/3, or mute the threadhttps://github.com/notifications/unsubscribe-auth/AAMgZuyz8SZENgAqp1M-WFRluSDpAJyaks5rtgdYgaJpZM4M2sMT.


Patch #337 needed anymore?

Hi, is this message needed or can we create an workaround for newer flutter versions?
binding.runningAsyncTasks does not exist. Follow #337 to patch the code to get it.

Hi, IIRC it is still needed, because Flutter did not merge the proposal (see https://github.com/flutter/flutter/issues/126545). However, feel free to PR to workaround it!

Seems not to be continued on flutter side. What may be a good workaround approach?

On one hand, you can workaround by manually patching as is suggested in #337. On the other hand, https://github.com/flutter/flutter/issues/126545 has some suggestions (e.g. subclass TestWidgetsFlutterBinding).

How do you patch it, @fzyzcjy?
I've tried creating a duplicate of flutter_test to include this patch and then referenced it in pubspec with the path: ./patched_flutter_test argument, but that causes issues as many other dependencies, including flutter_convenient_test depend on the sdk version.
I'm also curious how difficult would it be to implement a fix in this project so that we don't have to go patching other libraries?

I personally just modify the flutter framework code itself. (I use git patch apply and a small script, but any method works).

I'm also curious how difficult would it be to implement a fix in this project so that we don't have to go patching other libraries?

IIRC I examined it a little bit a long time ago and found some things may not work well, but to be honest I forgot what I tried (it may work indeed and just because I was too tired at that time). I will try to find some time to have a look at it later.

Modifying the flutter code directly is a bit daunting 😬  Is there any way to make use of this library more seamless, such as a small bash script to modify the binding before/after each run or having a custom binding as suggested here? I am happy to help with this, just not sure where to start..

I guess the first approach is possible (just some git-apply-patch things), and the second may also work. To get started on the first approach, maybe firstly play with git patch commands by hand and then create a script; for the second one, maybe firstly have a high-level overview of flutter testing bindings logic.


DropDown touch issue

Taken from https://github.com/kivy/kivy/pull/4014#issue-134670993.
When a selection is made, the dropdown, being a direct child of window, gets the touch_up first, which dismisses the dropdown. Then the dropdown button gets the touch_up, however, the on_release is not triggered because the dropdown is gone so it doesn't collide anymore.
Edit: This one does not appears to be reproducible anymore, below is a different dropdown issue though. :yum:
https://github.com/kivy/kivy/issues/4068#issuecomment-193883143

Did you experience it? Because I couldn't reproduce it anymore.
On Mar 8, 2016 10:50 AM, "dessant"<EMAIL_ADDRESS>wrote:

Taken from #4014 (comment)
https://github.com/kivy/kivy/pull/4014#issue-134670993.
When a selection is made, the dropdown, being a direct child of window,
gets the touch_up first, which dismisses the dropdown. Then the dropdown
button gets the touch_up, however, the on_release is not triggered because
the dropdown is gone so it doesn't collide anymore.
—
Reply to this email directly or view it on GitHub
https://github.com/kivy/kivy/issues/4068.

I did not.

When you run dropdown.py, after the dropdown has been opened, the next click on the dropdown button will dismiss the dropdown, but on_release is not called. It also becomes a visual issue because the second touch does not change the state of the button.
I would expect the touch to not be eaten, and the dropdown button should act as a toggle for opening and closing.

@matham, although this is a different issue, since you're talking about a button from the list not getting the dispatch, which i cannot reproduce, but i don't see a commit either which would have fixed it.
With which commit were you able to reproduce your bug? I've tried with master, your pr commit, and its parent commit.

I was able to reproduce it with master before my pr. But it was in a complex app with many layers of scrollviews and things. But I could not reproduce it after the PR was merged.

Closed by https://github.com/kivy/kivy/pull/4132


 sample()

ISO paper for this feature: P0220R1
First implemented in: VS 2017 15.0
Existing page
Should   mention /std:c++17, MISSING DESCRIPTION

moved to quest


[bluetooth][PTS] Getting Connection failed to be established ocasionally

Trying to connect to PTS, Im getting connection failed to be established occasionally.
Reproducible 2/10
TestCase: GATT/CL/GAD/BV-03-C
IUT: Zephyr, nRF52840PDK
Reproduce with bt shell:

connect 00:1b:dc:08:e6:83 (public)
gatt-discover-include
disconnect

Procedure repeats few times

conn_failed_to_be_estab_filtered.zip

The sniffer trace that has been uploaded does not show a connection that disconnected with that error code, but there is a hole in the sniffer trace , so it might be that the sniffer missed it. Can we get a new sniffer trace?
Also could you provide some more information to help me reproduce the issue?

Which device is central.
which device is peripheral.
a specific commit
Any special configuration

So far I haven't been able to reproduce the frequency of connection failed that you describe. But in a noisy environment this behaviour is expected. A CRC error on the connect request could be the cause.

@MariuszSkamra Are you still seeing this with recent runs of PTS?

we should close this, as there has been no follow up on reproducing it since Sept 21 and I have run conformance tests as part of v1.14.0-rc1 testing that passes all conformance tests.

Closing as non-applicable anymore.


Ethernet/wizchip_conf.c:837:10: error: unused variable 'k' [-Werror=unused-variable]

This file cannot be build with -Werror
Ethernet/wizchip_conf.c: In function 'wizchip_setnetinfo':
Ethernet/wizchip_conf.c:837:10: error: unused variable 'k' [-Werror=unused-variable]
int i,j,k;
^
Ethernet/wizchip_conf.c:837:8: error: unused variable 'j' [-Werror=unused-variable]
int i,j,k;
^
Ethernet/wizchip_conf.c:837:6: error: unused variable 'i' [-Werror=unused-variable]
int i,j,k;
^

What kind of IDE you used?

arm-none-eabi-gcc -mfpu=vfp -march=armv6zk -mtune=arm1176jzf-s -mcpu=arm1176jzf-s -DRPI1 -DBARE_METAL -DNDEBUG -I./include -I./ioLibrary_Driver/Ethernet -I./../lib-bcm2835/include -I./../lib-debug/include -I./../include -Wall -Werror  -O2 -nostartfiles -nostdinc -nostdlib -ffreestanding -mhard-float -mfloat-abi=hard -D_WIZCHIP_=5100 -c ioLibrary_Driver/Ethernet/socket.c -o build/W5100/ioLibrary_Driver/Ethernet/socket.o
ioLibrary_Driver/Ethernet/socket.c: In function ‘_sendto’:
ioLibrary_Driver/Ethernet/socket.c:521:36: error: suggest parentheses around comparison in operand of ‘&’ [-Werror=parentheses]
if((taddr == 0) && (getSn_MR(sn)&Sn_MR_MACRAW != Sn_MR_MACRAW)) return SOCKERR_IPINVALID;
^
ioLibrary_Driver/Ethernet/socket.c:522:36: error: suggest parentheses around comparison in operand of ‘&’ [-Werror=parentheses]
if((port  == 0) && (getSn_MR(sn)&Sn_MR_MACRAW != Sn_MR_MACRAW)) return SOCKERR_PORTZERO;
^
cc1: all warnings being treated as errors
Makefile:108: recipe for target 'build/W5100/ioLibrary_Driver/Ethernet/socket.o' failed
make: *** [build/W5100/ioLibrary_Driver/Ethernet/socket.o] Error 1
pi@nuc-i5:~/workspace/lib-wiznet$ arm-none-eabi-gcc --version
arm-none-eabi-gcc (GCC) 7.3.0
Copyright (C) 2017 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

@khj098765 Please will consider to re-open this issue and fix the bug? Thanks.

@khj098765 Please will consider to re-open this issue and fix the bug? Thanks.

see pull request #53


Metanorma include of asciidoctor-iso produces warning

[metanorma] detecting backends: rfc2 rfc3 iso (eval):44: warning: already initialized constant IsoDoc::WordConvertModule::SW1
(eval):44: warning: previous definition of SW1 was here
(eval):80: warning: already initialized constant IsoDoc::WordConvertModule::WORD_DT_ATTRS
(eval):80: warning: previous definition of WORD_DT_ATTRS was here
(eval):62: warning: already initialized constant IsoDoc::WordConvertModule::COMMENT_IN_COMMENT_LIST1
(eval):62: warning: previous definition of COMMENT_IN_COMMENT_LIST1 was here
(eval):129: warning: already initialized constant IsoDoc::WordConvertModule::COMMENT_TARGET_XREFS1
(eval):129: warning: previous definition of COMMENT_TARGET_XREFS1 was here
(eval):88: warning: already initialized constant IsoDoc::WordConvertModule::WORD_TOC_PREFACE1
(eval):88: warning: previous definition of WORD_TOC_PREFACE1 was here
(eval):96: warning: already initialized constant IsoDoc::WordConvertModule::WORD_TOC_SUFFIX1
(eval):96: warning: previous definition of WORD_TOC_SUFFIX1 was here
gb (eval):44: warning: already initialized constant IsoDoc::WordConvertModule::SW1
(eval):44: warning: previous definition of SW1 was here
(eval):80: warning: already initialized constant IsoDoc::WordConvertModule::WORD_DT_ATTRS
(eval):80: warning: previous definition of WORD_DT_ATTRS was here
(eval):62: warning: already initialized constant IsoDoc::WordConvertModule::COMMENT_IN_COMMENT_LIST1
(eval):62: warning: previous definition of COMMENT_IN_COMMENT_LIST1 was here
(eval):129: warning: already initialized constant IsoDoc::WordConvertModule::COMMENT_TARGET_XREFS1
(eval):129: warning: previous definition of COMMENT_TARGET_XREFS1 was here
(eval):88: warning: already initialized constant IsoDoc::WordConvertModule::WORD_TOC_PREFACE1
(eval):88: warning: previous definition of WORD_TOC_PREFACE1 was here
(eval):96: warning: already initialized constant IsoDoc::WordConvertModule::WORD_TOC_SUFFIX1
(eval):96: warning: previous definition of WORD_TOC_SUFFIX1 was here

Those are long-standing, and result from the way I am trying to do includes of Word conversion methods. They will go away when I refactor the Word conversion code.


Update substring.md

correct a slip of pen.
Proposed changes
Issue Number: nothing
Problem Summary:
Describe the overview of changes.
Checklist(Required)

Does it affect the original behavior: No
Has unit tests been added: No Need
Has document been added or modified: Yes
Does it need to update dependencies: No
Are there any changes that cannot be rolled back: No

Further comments
If this is a relatively large or complex change, kick off the discussion at<EMAIL_ADDRESS>by explaining why you chose the solution you did and what alternatives you considered, etc...

Please update the en doc as well.


Custom argparser extension with Trainer arguments (argument types added)

Before submitting

[x] Was this discussed/approved via a Github issue? (no need for typos and docs improvements)
[x] Did you read the contributor guideline, Pull Request section?
[ ] Did you make sure to update the docs?
[x] Did you write any new necessary tests?
[x] If you made a notable change (that affects users), did you update the CHANGELOG?

What does this PR do?
Fixes #1139
PR review
Anyone in the community is free to review the PR once the tests have passed.
If we didn't discuss your PR in Github issues there's a high chance it will not be merged.
Did you have fun?
Make sure you had fun coding 🙃

Hello @alexeykarnachev! Thanks for opening this PR.

In the file tests/trainer/test_trainer.py:

Line 523:12: E127 continuation line over-indented for visual indent
Line 549:12: E127 continuation line over-indented for visual indent
Line 561:12: E127 continuation line over-indented for visual indent

Do see the Hitchhiker's guide to code style

@alexeykarnachev could you pls update from master? we have fixed the failure in #1163

@Borda it seems like something broke. I executed tests in master and get:
tests/loggers/test_trains.py:None (tests/loggers/test_trains.py)
ImportError while importing test module '/home/akarnachev/workspace/projects/pytorch-lightning/tests/loggers/test_trains.py'.
Hint: make sure your test modules/packages have valid Python names.
Traceback:
../../../../anaconda3/envs/pytorch-lightning/lib/python3.7/site-packages/_pytest/python.py:513: in _importtestmodule
    mod = self.fspath.pyimport(ensuresyspath=importmode)
../../../../anaconda3/envs/pytorch-lightning/lib/python3.7/site-packages/py/_path/local.py:701: in pyimport
    __import__(modname)
../../../../anaconda3/envs/pytorch-lightning/lib/python3.7/site-packages/_pytest/assertion/rewrite.py:152: in exec_module
    exec(co, module.__dict__)
loggers/test_trains.py:5: in <module>
    from pytorch_lightning.loggers import TrainsLogger
E   ImportError: cannot import name 'TrainsLogger' from 'pytorch_lightning.loggers' (/home/akarnachev/workspace/projects/pytorch-lightning/pytorch_lightning/loggers/__init__.py)

Is it something on my side?

@Borda sorry, my bad. I forgot to upd conda env

GREAT work! ready to go...

@Borda what is about deprecated arguments? I can scan the entire Trainer code, find the backward compatible comments and skip the arguments which have this comment in one line with itself.
Or, I can do it explicitly through the ignored arguments list. But such the approach imposes responsibility on a developer, who will decide deprecate any argument. He will have to add this argument to the deprecated list.
What do you think?

@alexeykarnachev thx very much for your effort! I would make it easier and just lis the deprecated args in Trainer like
class Trainer(...):
    DEPRECATED_IN_0_8 = ('max_nb_epochs', ..)
    DEPRECATED_IN_0_9 = ...

I believe that the deprecation wont happen much in future :]

This PR works great for me with the exception of boolean casting. I.e. if I run with --checkpoint_callback 0 or false or anything but an empty value, then args.checkpoint_callback -> True, since bool('false') -> True.
This can be resolved with distutils:
bool('false')
# True
bool(distutils.util.strtobool('false'))
# False

Would it be possible to add a line to check for bool types and cast them using the above? Otherwise the behavior is quite counterintuitive.

good point, @joeddav could you do it in review mode as a suggestion (so it is clear and @alexeykarnachev can simply accept it) or follow-up PR?


FEATURE REQUEST - wfuzz

Would you like have a tool or script added? Please include a link
wfuzz
https://github.com/xmendez/wfuzz
Is your feature request related to a problem? Please describe.
Useful for some many things when interacting with a website. Can FUZZ paths, arguments, parameters, headers, cookies, subdomains, etc.
If related to a problem, describe the solution you'd like
Install and get working well on Windows system.
Describe alternatives you've considered
I can install it myself (\python27\python -m pip install wfuzz). It doesn't work great. The output is very laggy, and it runs slow.

added to roadmap

Added to 1.2 release


Refactor redux localstorage

What does this PR do and why?
Fixes https://github.com/jbx-protocol/juice-interface/issues/411
Previously we were updating localStorage in a redux middleware. The problem with this approach is that redux middleware is invoked before the reducer (between the dispatch call and the reducer), so the state in the middleware is a tick behind.
Using a redux subscription appears to be the preferred approach. This is invoked after the reducer, so localStorage is always in sync with the latest state.
This illustrates the difference:
- dispatch(resetState()) --> middleware (with old state) --> localstorage is set (with old state) --> reducer (state updated)
+ dispatch(resetState()) --> middleware (with old state) --> reducer (state updated) --> subscriber (with new state) --> localstorage is set (with new state)

This approach is described here: https://stackoverflow.com/questions/35305661/where-to-write-to-localstorage-in-a-redux-app.
https://user-images.githubusercontent.com/94939382/151093697-87347857-5a2f-481c-9f81-81be0127d783.mp4
Acceptance checklist

[x] I have evaluated the Approval Guidelines for this PR.
[x] I have tested this PR in all supported browsers.

@aeolianeth I'm fine with this solution. I'd prefer it kept within the middleware but I don't feel strongly about that.

awesome thank you!
@peripheralist over to you 🏀


Compiling if FILEs in DAT section needs attention - is slow... compared to rest of compile

Issue being Addressed
Time for assembling a simple PASM-only program is over an order of magnitude worse than flexspin. 540ms vs 25ms, or rather "noticable delay" vs "instant".
It seems the slow compile time is mostly correlated with including large FILEs in a DAT section. So I guess there's some horrible per-byte loop that runs on either the FILE includes or the whole output binary.
Initially reported by  Ada, 2024-09-13.
Enhancement
Rewrite the byte loops in the DATA file handling to improve compile performance.
Alternatives
N/A
Additional information
N/A

The program that I noticed this on:
crapvga-2024-09-17.zip
(Simple VGA driver that I livecoded in like 10 minutes to prove a point - there's a big image file)


Tests pass in phantom, fail in chrome

Has to do with parsing parsing numbers as a currency
Expected:
"$40,000.00"
Result:
"$40,000"
Diff:
"$40,000.00" "$40,000"

Working on this tonight


Revert "apt-repos: Downgrade PostgreSQL to dodge PGroonga regression."

This reverts commit 9c8d2b7be39314b41f04a1e1356942afe21ab223 (#21115).
The PostgreSQL fix was released 2022-05-12.

This takes back out the --allow-downgrades flags in addition to removing the pin file -- just thinking it through aloud, I think that's probably safest, because we don't expect these versions to do any downgrading, and it's better to have to explicitly add those back in if we end up in a similar situation again.
Out of curiosity, can you link to the Pg fix?

It’s the same fix that was made back in February. They just refused to make an exception to their 3 month release cycle for it.

https://chat.zulip.org/#narrow/stream/43-automated-testing/topic/main.20failing/near/1326361
#21104
pgroonga/pgroonga#203
https://www.postgresql.org/message-id/flat/4c347490-d734-5fdd-d613-1327601b4e7e%40mit.edu
postgres/postgres@e5691cc9170bcd6c684715c2755d919c5a16fea2

Merged, thanks @andersk!

Should we backport this to 5.x as well?


Remove resource type from attribute keys

Fixes #47  .
Changes proposed in this pull request:

Remove resource type from attribute keys that has been prepended to each key name.
Reformat meta.py using the black formatter

@onyame This pull request will fix #47. Note that as the attribute names of nearly all attributes are going to change as a result of this PR, CYHPER queries that have been crafted using previous versions of GitLab2PROV will possibly no longer work.
If that does not pose an issue for you, i would go on to merge and therefore complete the milestone for v0.5 . I'll wait for your feedback.


Phaser Project Won't Load in Pages

Version

Phaser v3.50.1
OS: Windows 10
Browser: Chrome

Description
I am trying to create my project into a Github page but for some reason it cannot load my scripts. I checked the console and it keeps reporting that it cannot find my app.bundle.js file. Does anyone know if it has to do with Phaser or the localhost setup? Thank you!
https://mariofan235.github.io/Odyssey_Maker/

I was able to solve it here; just needed to add a page direct since Pages goes to the default index.html: https://stackoverflow.com/a/25327759/12449136


Mlflow duplicate logging

Please check that this issue hasn't been reported before.

[X] I searched previous Bug Reports didn't find any similar reports.

Expected Behavior
one log in one step
Current behaviour
duplicated log in one step

Steps to reproduce

pull docker image : winglian/axolotl:main-20241030-py3.11-cu124-2.4.1
setup mlflow (ghcr.io/mlflow/mlflow:v2.17.2)
run axolotl docker
prepare dataset, base model, train config file.
run accelerate launch -m axolotl.cli.train my_config.yml
go to mlflow logging dir
check the log file

Config yaml
base_model: meta-llama/Llama-3.2-3B
plugins:
  - axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: false

strict: false
chat_template:
output_dir: /workspace/axolotl/3_model/pretraining
skip_prepare_dataset: true
datasets:
  - path: /workspace/axolotl/2_data/dataset-tokenized-8k/train
    split: train
    type:

sequence_len: 8192
sample_packing: false
pad_to_sequence_len: false

# mlflow configuration if you're using it
mlflow_tracking_uri: http://mlflow-server:5000
mlflow_experiment_name: llama-3B
mlflow_run_name: llama-3B

gradient_accumulation_steps: 1
micro_batch_size: 2
  # num_epochs: 1
# max_steps: 200000
optimizer: adamw_torch
lr_scheduler: cosine
lr_scheduler_kwargs:
cosine_min_lr_ratio: 1e-3

learning_rate: 1e-5

train_on_inputs: false
group_by_length: false
bf16: true
fp16:
tf32: false

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
logging_steps: 1
xformers_attention:
#flash_attention: true

warmup_steps: 20000
  #evals_per_epoch: 2
eval_table_size:

save_steps: 40000
debug:
deepspeed:
weight_decay: 0.0
fsdp:
#   - full_shard
#   - auto_wrap
# fsdp_config:
#   fsdp_limit_all_gathers: true
#   fsdp_sync_module_states: true
#   fsdp_offload_params: false
#   fsdp_use_orig_params: false
#   fsdp_cpu_ram_efficient_loading: true
#   fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP
#   fsdp_transformer_layer_cls_to_wrap: LlamaDecoderLayer
#   fsdp_state_dict_type: FULL_STATE_DICT
#   fsdp_sharding_strategy: FULL_SHARD
#   fsdp_backward_prefetch: BACKWARD_PRE
special_tokens:
  pad_token: <|end_of_text|>

Possible solution
No response
Which Operating Systems are you using?

[X] Linux
[ ] macOS
[ ] Windows

Python Version
3.11
axolotl branch-commit
main/8c3a727f9d60ffd3af385f90bcc3fa3a56398fe1
Acknowledgements

[X] My issue title is concise, descriptive, and in title casing.
[X] I have searched the existing issues to make sure this bug has not been reported yet.
[X] I am using the latest version of axolotl.
[X] I have provided enough information for the maintainers to reproduce and diagnose the issue.

cc @awhazell , do you perhaps see any duplicate logging recently to mlflow?

The MLFlowCallback may be being duplicated- it's added explicitly here but also by the reports_to argument to the trainer I think. The fix may just be to delete the addition of that callback in the linked code.
I can't see any duplicate logs in my version though- I'm using postgres as a backend store which might deal with duplicates somehow

@awhazell , thanks for catching that.
@jsh2581 , would you be able to try out the linked PR to see if it solves it for you?


Kernel updates for 2023-10-06

Description of changes
Previous: #256915
Was upstreamed in 6.1 and 6.5 (still present in 6.4): https://github.com/NixOS/nixpkgs/pull/255824
Things done

Built on platform(s)

[ ] x86_64-linux
[ ] aarch64-linux
[ ] x86_64-darwin
[ ] aarch64-darwin

[ ] For non-Linux: Is sandbox = true set in nix.conf? (See Nix manual)
[ ] Tested, as applicable:

NixOS test(s) (look inside nixos/tests)
and/or package tests
or, for functions and "core" functionality, tests in lib/tests or pkgs/test
made sure NixOS tests are linked to the relevant packages

[ ] Tested compilation of all packages that depend on this change using nix-shell -p nixpkgs-review --run "nixpkgs-review rev HEAD". Note: all changes have to be committed, also see nixpkgs-review usage
[ ] Tested basic functionality of all binary files (usually in ./result/bin/)
23.11 Release Notes (or backporting 23.05 Release notes)

[ ] (Package updates) Added a release notes entry if the change is major or breaking
[ ] (Module updates) Added a release notes entry if the change is significant
[ ] (Module addition) Added a release notes entry if adding a new NixOS module

[ ] Fits CONTRIBUTING.md.

Building 6.5.6

https://github.com/NixOS/nixpkgs/pull/254723 should be merged together with this PR to combine rebuilds.

Built 6.5.6, rebooting in a bit

For the record I'm the upstream tester of the final regression patch on 6.1 and it does work on my machine. I can build these and test them soon as well but I don't expect issues.

6.4 probably should be removed, there is also a pending RT update for 6.1 and those two would be the only two remaining places were the patch is being applied.

For the record I'm the upstream tester of the final regression patch on 6.1 and it does work on my machine. I can build these and test them soon as well but I don't expect issues.
I believe the patch was not applied to 6.4 due to EOL. Should we remove 6.4?

Drop being worked on in https://github.com/NixOS/nixpkgs/pull/258569.

Only reference on the patch should be 6.1-rt now

Rebooted int 6.5.6, working good. Attempting to get an nvme crash from https://github.com/NixOS/nixpkgs/issues/257159

Please merge https://github.com/NixOS/nixpkgs/pull/254723 at the same time.

Are we good to go here?

Sure, though I was waiting for a review. UnU

Also, haven't gotten an nvme crash so far, so seems the issue I had been experiencing on 6.5 series is fixed. :3

Haven't had the time to do a review today, let alone from the other PRs that are rquested to be merged here. Unless someone's faster, I'll probably be able to do this tomorrow.

fixed the hardened update script, pushing hardened updates to this branch as well.

Haven't had the time to do a review today, let alone from the other PRs that are rquested to be merged here.

When I ask for another PR to be merged, the only reason I haven't just merged it by myself is that I want to group the rebuilds.  I'm happy to take the blame for any consequences.

Built and booted into 6.5.6-hardened1
Regarding https://github.com/NixOS/nixpkgs/pull/254723, sure can merge though I don't want to self merge this PR, specially without a review/approve. :C
On the other hand 6.5.6 does seem to fix nvme issues (other that those addressed by the rptx revert / patch in NixOS) so if there isn't any opposition I could merge both by end of day in Americas/Mexico_City timezone.

Merged both this and 254723


docs: fix "the the" -> "the"

Description:
Replace typos "the the" with "the".

Thank you @benlesh for the approval! I think you also have to merge this PR because I don't have rights to do it.


fix: make LogRecord accept the "any" type as Body

Fixes #34, makes log record accept a body of the type any.

Thank you for your contribution @mralves! will release soon


Develop timeseries course.

[x] Decide date/time
[x] Book room
[x] Update course webpage
[x] Advertise to SWC/GCNU
[ ] Develop materials
[ ] Deliver
[ ] Edit to fit into one week course based on pilot

Moved to https://github.com/neuroinformatics-unit/software-skills


CSS Styling is retained on file open

The default styling of the 'Choose File` remains in effect after file is selected.
This results in unwanted styling of the rendered markdown html. The intended behavior should be this styling only is in place when the 'Choose File' prompt is shown.

Hm, it seems like there's a typo on line 33 in main.js
(Once fixed,) This also resets the styling before any file is selected. The changed styling should only be in place once after a file has been selected.
Your current background color makes it just slightly hard to read the text it's over. You're welcome to use the same background color from the normal css file, #2f2f2f.
I appreciate the pull requests to try to fix this issue!


OCPBUGS-4070: enable metrics in OCP by default

What type of PR is this?

What this PR does / why we need it:
Which issue(s) this PR fixes:

Does this PR have test?

Special notes for your reviewer:
Does this PR introduce a user-facing change?

docs have been notified about the original upstream PR
QE has tested the original upstream PR
no PX impact

/test e2e-operator


Update provisioning job secrets via PowerShell/API?

We have this solution configured and working well for AWS Console access. For security, we'd like to be able to rotate the access key used by the IAM user created for provisioning (AzureADRoleManager in the tutorial).
I have been trouble finding documentation on a way to update the secrets for the provisioning job programmatically. I found a reference to a Microsoft Graph API in this doc (https://docs.microsoft.com/en-us/azure/active-directory/app-provisioning/application-provisioning-configure-api). However, I was not able to locate an API reference for the  /beta/servicePrincipals/{id}/synchronization/secrets endpoint used in the example.
I played around with it in Graph Explorer but I wasn't able to tell how to retrieve the values for the current secret. I got something like the following:
{
<EMAIL_ADDRESS>"https://graph.microsoft.com/beta/$metadata#servicePrincipals('b9a2fcdb-fe85-4d17-979e-04e8a2c93652')/synchronization/secrets",
    "value": [
        {
            "key": "ClientSecret",
            "value": "*"
        },
        {
            "key": "SecretToken",
            "value": "*"
        },
        {
            "key": "SyncNotificationSettings",
            "value": "{\"Enabled\":true,\"Recipients\":\"[email address removed]"}"
        },
        {
            "key": "SyncAll",
            "value": "false"
        }
    ]
}

Without being able to retrieve the existing secret, that leaves us needing to store the current credentials elsewhere in order to use them to generate a new access key in AWS.
It would be really nice if automatic key rotation was integrated into the portal configuration. The provisioning user should be able to request a new key, update the secrets, then delete the old key after validation if given the appropriate IAM permissions.

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

ID: 8fa5814d-91e2-2f75-77e7-62a8597f340c
Version Independent ID: 458e93d7-a180-4c2f-5077-9b9d124d726a
Content: Tutorial: Azure Active Directory single sign-on (SSO) integration with Amazon Web Services (AWS)
Content Source: articles/active-directory/saas-apps/amazon-web-service-tutorial.md
Service: active-directory
Sub-service: saas-app-tutorial
GitHub Login: @jeevansd
Microsoft Alias: jeedes

@learley Thanks for the feedback !  I have assigned this issue to content author to investigate and update the document as appropriate.

@learley This is the article which talks about USer Provisioning APIs https://docs.microsoft.com/en-us/azure/active-directory/app-provisioning/application-provisioning-configure-api

#please-close


[BUG] Only support subm mode?

Is there an existing issue for this?

[x] I have searched the existing issues

Current Behavior
In rule_book generation process, only has subm mode's rule_book. so, it doesn't have normal mode?
And in spconv process, only subm rule_book can be used? or, normal rule_book also works?
Expected Behavior
No response
Environment
- GCC:
- NVCC:
- PyTorch:
- PyTorch CUDA:
- TorchSparse:

Anything else?
No response

@ys-2020, could you please take a look at this issue when you have time? Thanks!

Hi @matri123 , a normal convolution mode is supported in our framework. Could you further clarify which part makes you confused? Maybe with a link to the doc or a sample code. Thanks

https://github.com/mit-han-lab/torchsparse/blob/master/torchsparse/nn/functional/build_kmap.py#L32
only has subm and downsample, does

Hi. In subm mode, the input feature map will not be downsampled. (The output resolution and point coordinates will be kept the same as input.) I guess this might be the normal mode you want?

Close this issue as complete. If you have further questions, feel free to reopen it.


chore: bump ratatui to 0.29.0

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 0.00%. Comparing base (7be6cd3) to head (139036c).

Additional details and impacted files
@@          Coverage Diff          @@
##            main     #42   +/-   ##
=====================================
  Coverage   0.00%   0.00%
=====================================
  Files          2       2
  Lines        150     150
=====================================
  Misses       150     150

:umbrella: View full report in Codecov by Sentry.
:loudspeaker: Have feedback on the report? Share it here.

closing in favor of #43 (which came after, but also fixed a few other things). Thank you for the PR :)


Profile name validation does not allow @ character

Bug Report
Version
v0.0.22-alpha
Description
Profile names are validated using validate_identifier.
I am using profile names of the pattern <role>@<account>, e.g.: admin@prod. Those profile names are not an issue in other places, such as the aws cli. This is an established pattern that is not easy to change for me.
Due to this validation I can not use such profiles.  Is this something that can be fixed by adding @ to the list of acceptable characters or are there other limitations that prevent this?

thanks for the report! We'll work on a fix for this. We're planning on expanding the scope of allowed characters to be a bit more lenient. It won't behave exactly like the CLI (which actually uses shlex.split(..)), but it behave identically for most use cases.

Yeah, shout-out for this feature as well 👍 role@account is quite common pattern for naming profiles when you're working in the enterprise with multitudes of AWS accounts.

fixed in 0.0.26-alpha


add google() to build.gradle in CLI template

Motivation
Fixes android build issue

closing this PR because the same change is introduced in https://github.com/facebook/react-native/commit/6e356895e79fb92640295a14483af1a430732247


Add support for live playlists in SegmentedFileOutput

This hardcodes the live playlist window to 5 segments. We could expose this in the protocol, but I'm not sure there is any reason to overload the request until we get a use case.


Add font scaling

Should the font scale change the size of the "category" font? Also, should we consider changing the sizes of icons too? Just some considerations I had when testing, I don't have a strict opinion on these.

For "category" font, are you referring to the text in the navigation header? If so, I believe it would make sense to scale this since it is important for users to see this detail. Same thing goes for the navigation icons.

I agree 100%. From my testing, it didn't seem to scale either, but it shouldn't be too difficult a fix. If you'd like to make the change, feel free to move ahead with it, otherwise, I can merge to a new branch and make another PR. Either way, once the fix is made I'll merge it with main!

Apologies for not getting to this sooner. I noticed a couple of things with the icons when scaled larger.

The icons seem to be slightly more pixelated. I'm not sure if this is just my device or a broader issue with the SVG icons.
The icons also seem to clip into the edges of the menu bar, I'm guessing because the height of the menu bar is static (and maybe should be dynamic?).

My suggestions would be to either cut out some of the larger scaling options or to make the menu itself scale properly. The first method would definitely be an easier fix, but what do you think is best?

I think scaling the header would be best, but I cannot find a way to change the header height on iOS (aside from building a custom header from scratch). I'll remove the larger scaling options for now and revisit this again later if we decide that the larger options are needed.

Sounds good, other than that minor issue, the PR is ready to be merged!


Updete toc.yml (Typo "Cognitive services"→"Cognitive Services")

https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/cognitive-services
#PingMSFTDocs
related: #2816

Looks good/correct; merging now. Thanks.

It's not clear that the Azure service is being referred to (implied by the revision in the PR) and not generically cognitive services.

Correct, I don't believe the intent of this TOC entry is to specifically refer to the service, and as such shouldn't be a proper noun.