Not able to install Pytorch

Hi!
I installed Jetpack 4.3 on nvdia jetson nano. While building the project from scratch I skipped Pytorch installation. But now when I tried to train the model using below command.
python3 train.py --model-dir=models/ data/
I got an error saying "Module torch not found". Then I tried to install pytorch explicitly by using command ./install-pytorch.sh
I got only one option

I'm trying to install it but the logs are never ending but multiple things. I'm attaching few logs here.

Please help to resolve the issue.
PS: These are the python versions present currently in system.

Thanks
Mohit

I'm trying to install it but the logs are never ending but multiple things. I'm attaching few logs here.

Hi @mohitg0292, it can take a while for Nano to build torchvision - let it run for a while until it completes.  Or you could run the jetson-inference docker container, which already has PyTorch/ect installed in it for you:  https://github.com/dusty-nv/jetson-inference/blob/master/docs/aux-docker.md

I'm trying to install it but the logs are never ending but multiple things. I'm attaching few logs here.

Hi @mohitg0292, it can take a while for Nano to build torchvision - let it run for a while until it completes. Or you could run the jetson-inference docker container, which already has PyTorch/ect installed in it for you: https://github.com/dusty-nv/jetson-inference/blob/master/docs/aux-docker.md

Ok. I'll try to run the command again and will leave it for while. Just wanted to make sure the attached logs don't have any errors?

No they don't appear to, it's just compiling

You were right. It took 35 minutes to complete installation.
Now when I'm training the model, getting this error.

@mohitg0292 can you try running pip3 install 'pillow<9'

thanks. It worked.
One question. I trained model for 1 epoch and tested the model using.
$ imagenet.py --model=models//resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=data//labels.txt csi://0
On the camera screen, it is showing me "100% Class#0" and not recognizing the object when I put the object in front of camera.
Is there anything I'm missing?

ok. so basically it will not work for one object?
and what does it mean which is displaying on camera screen. "100% Class#0"?

There should be a minimum of two classes, yea

I just trained the model for 6 objects again after deleting .engine file as you suggested. When I tested, it is again showing me class#0 or class #1 or class#4 or class #5, not the name of objects.
also i checked if it is showing the serial number of object but that's also not the case. It is also showing same class for two objects.
Is there anything i'm still missing?
Thanks for your quick response. :)

Do you have a labels.txt file with your class names that you are specifying on the command line when you launch the program?

From: mohitg0292 @.>
Sent: Friday, February 17, 2023 2:12:15 PM
To: dusty-nv/jetson-inference @.>
Cc: Dustin Franklin @.>; Comment @.>
Subject: Re: [dusty-nv/jetson-inference] Not able to install Pytorch (Issue #1563)
I just trained the model for 6 objects again after deleting .engine file as you suggested. When I tested, it is again showing me class#0 or class #1https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdusty-nv%2Fjetson-inference%2Fissues%2F1&data=05|01|dustinf%40nvidia.com|30612de0ab004313766008db111ae26a|43083d15727340c1b7db39efd9ccc17a|0|0|638122579401897445|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=0qKw1gsKLfJIcLPittzdMDCn1nlzQAPR0LeiZGACKs0%3D&reserved=0 or class#4 or class #5https://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdusty-nv%2Fjetson-inference%2Fissues%2F5&data=05|01|dustinf%40nvidia.com|30612de0ab004313766008db111ae26a|43083d15727340c1b7db39efd9ccc17a|0|0|638122579401897445|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=R7hlH6b%2BGJtEXV3FG9CaHa2Rn5xr%2BUaeI0TRBsv6bIA%3D&reserved=0, not the name of objects.
also i checked if it is showing the serial number of object but that's also not the case. It is also showing same class for two objects.
Is there anything i'm still missing?
Thanks for your quick response. :)
—
Reply to this email directly, view it on GitHubhttps://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdusty-nv%2Fjetson-inference%2Fissues%2F1563%23issuecomment-1435118584&data=05|01|dustinf%40nvidia.com|30612de0ab004313766008db111ae26a|43083d15727340c1b7db39efd9ccc17a|0|0|638122579402053694|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=NdpQqoUvuEhXGeVoQy%2BvEU4VBqx5VuG16gEZDJafQmA%3D&reserved=0, or unsubscribehttps://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FADVEGK55SBCLNV4L34SIOCTWX7EQ7ANCNFSM6AAAAAAU6WY42A&data=05|01|dustinf%40nvidia.com|30612de0ab004313766008db111ae26a|43083d15727340c1b7db39efd9ccc17a|0|0|638122579402053694|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=MOh%2FOiOqAAj7JxW%2FMLCdzOk6lMRc1Odnf8nbZ%2BR6vj0%3D&reserved=0.
You are receiving this because you commented.Message ID: @.***>

The lablels.txt file looks like this

This is the output (this one is second item in labels file):

@dusty-nv Can you please look into this issue?
I'm really stuck in this.
Thanks
Mohit

What's the command-line that you are running imagenet program with?    When it starts, it should print out something like "loaded 4 class labels"

Thanks for your quick reply.
I just tested the model again and noticed that it wasn't able to load the labels because of wrong path mentioned in the command. Finally I corrected the path and the labels are loaded. But the accuracy isn't good. and it is not showing the correct object name.
However I've also included "hand" and "background" in labels and retraining the model. I'll again test once the retraining will be finished.
On what the accuracy depends? The number of objects or the background light also (you can see the background light in above pics)?
Also while clicking pictures, I didn't have green background like you showed in the video so I just put green paper in the back for "val". And I put a colored book in the background for "test" pics. Is it fine?
Mohit

hi @dusty-nv !
Ok. I just finished training the model and it was working to identify the object. As the next step I tried to configure the audio and made the changes as suggested on the description page.
I also made changes in imagenet.py but when i tried to run it, it is showing this error.

Then I restarted the JEtson and tried again then it showed this but camera window didn't open.

Also when i undo the changes and tried to run the original imagenet.py it showed me same capturesession error.
Not sure what I did wrong.
Is there something I'm missing? Do we need to do something after making changes in imagenet.py? (like compiling something or exporting onnx file etc?)
I'm not sure why everything stopped working suddenly.
Please help
Mohit

is there something I'm missing? Do we need to do something after making changes in imagenet.py?

I would recommend making your own copy of imagenet.py and putting it somewhere else, or making changes to jetson-inference/python/examples/imagenet.py (and then running cmake ../ && make && sudo make install from the build dir so the updated imagenet.py gets installed)
If you think a problem with your camera has occurred, try running video-viewer.py first to confirm the camera is still working.

Hi @dusty-nv !
As you suggested I followed below steps:

created a separate file in jetson-inference/python/examples/food_container_identifier.py and kept imagenet.py as it is.
Ran "cmake ../ && make && sudo make install"
Trained the model using
python3 train.py --model-dir=models/food_container_identifier data/food_container_identifier
Exported model in Onnx format using
python3 onnx_export.py --model-dir=models/food_container_identifier
Then tested the model using
imagenet.py --model=/home/ttz/jetson-inference/python/training/classification/models/food_container_identifier/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=/home/ttz/jetson-inference/python/training/classification/data/food_container_identifier/labels.txt csi://0

The camera is working at this stage.
-----------------------Next step--------------------------
Then I ran below command to check the audio.
python3 /home/ttz/jetson-inference/python/examples/food_container_identifier.py --model=/home/ttz/jetson-inference/python/training/classification/models/food_container_identifier/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=/home/ttz/jetson-inference/python/training/classification/data/food_container_identifier/labels.txt csi://0
In this case the audio is working and showing this output but the camera screen is not displayed and the system is just repeating one object name and the logs are like this.

After this when I ran imagenet again, I got this error:

To get rid of this error I restarted the Jetson nano and ran imagenet. The camera is working fine. Then I ran food_container_identifier.py to check audio. Again the camera screen didn't work and I was just getting audio. Then when I ran imagenet.pu the camera error is displayed.
So that's a pattern I found out. I hope I was able to explain it.
Thanks
Mohit

@dusty-nv I copied and pasted the whole code from here.
https://github.com/oliver-almaraz/food_container_identifier/blob/main/food_container_identifier.py
I didnt make any changes in existing code.

OK gotcha, thanks - the camera screen isn't displaying because you have commented out the videoOutput stuff.
I may be the audio should run in a different thread - I'm not sure if the audio call to engine.runAndWait() blocks and takes extra time or not.
Other than an ungraceful shutdown, I don't know why the CSI camera doesn't restart.  However you should be able to run sudo systemctl restart nvargus-daemon instead of rebooting your system to get it back.

Ok. But in the practical example we do need the video output, right? Also in your video tutorial on youtube you have also showed the same. Why do we need to comment the video output then?
Ok. I'll try to run the command rather than restarting the system.
But what's the solution I can opt for? Should I send you the complete logs again?

You should be able to leave the videoOutput uncommented, sure.  The videoOutput can save the results to video or a network stream if you prefer over a physical display.

@dusty-nv ok I uncommented videoOutput and other related variables and the video screen is displayed now.
But there are some issues:

Since i'm using separate screen using HDMI port, the videooutput is very slow with audio using food_container_identifier.py.
I did some hit and trial. What I found is after running food_container_identifier.py, I've to run the command systemctl restart nvargus-daemon otherwise I get error failed to create capture session in running imagenet.py
Today I trained the model again and now the objects are not recognized correctly. Not sure what happened differently from yesterday. It was all good in training and running the model using imagenet.py yesterday.

Could you please share which screen you used while making this video?
https://www.youtube.com/watch?v=PH_wht8jTyA
In this sample, the videoOutput it is quite smooth.
Thanks
Mohit

Since i'm using separate screen using HDMI port, the videooutput is very slow with audio using food_container_identifier.py.

I think it may be slowed down by the blocking call to audio engine.runAndWait()
Try commenting that out and seeing if it speeds up
I use a HDMI screen and hauppage device to capture it for youtube videos

Hi @dusty-nv !
I have again trained the program for around 35 objects. The Jetson is not recognizing the objects correctly.
In addition to that I have a query regarding the audio output. Currently I'm using a separate screen using HDMI port and using the audio from the screen.
Now I want to test it without the screen, If I understand it correctly:
I'll connect the jetson with usb using my laptop and run the program through command prompt. I'll probably connect bluetooth speakers via bluetooth device on jetson. Or using the USB to 3.5 mm jack converter and connecting my earphones to 3.5mm jack.
Then I'll run the program through my laptop. The camera and audio output should run right?
Thanks
Mohit

@mohitg0292 yes they should still run without display, but if you want to view the camera from your laptop you'll need to stream it over RTP

Hi @dusty-nv. Thanks, I have configured the bluetooth speaker successfully. But the model is not able to identify any object. The audio is saying only two objects i.e. "Dairy 50g", "tea 200g" and nothing else. I tried to put different objects in front of the camera other than "Dairy 50g", "tea 200g"  but no success. Even the "hand" and "background" are also not identified. The audio also doesn't say "Dove Shampoo 200 ml" and "Butter 350g " which is shown in the output below.
Output on terminal.
class 0005 - 0.403012  (Dairy 50g)
class 0025 - 0.595613  (tea 200g)
class 0005 - 0.450656  (Dairy 50g)
class 0025 - 0.547858  (tea 200g)
class 0005 - 0.313710  (Dairy 50g)
class 0025 - 0.685206  (tea 200g)
class 0005 - 0.410517  (Dairy 50g)
class 0025 - 0.588039  (tea 200g)
class 0005 - 0.473894  (Dairy 50g)
class 0025 - 0.524553  (tea 200g)
class 0005 - 0.406709  (Dairy 50g)
class 0025 - 0.591758  (tea 200g)
class 0005 - 0.425662  (Dairy 50g)
class 0025 - 0.572790  (tea 200g)
class 0005 - 0.393630  (Dairy 50g)
class 0025 - 0.604921  (tea 200g)
class 0005 - 0.353506  (Dairy 50g)
class 0025 - 0.645136  (tea 200g)
class 0025 - 0.999858  (tea 200g)
class 0025 - 0.999902  (tea 200g)
class 0025 - 0.999969  (tea 200g)
class 0025 - 0.998161  (tea 200g)
class 0005 - 0.479680  (Dairy 50g)
class 0025 - 0.518658  (tea 200g)
class 0005 - 0.408632  (Dairy 50g)
class 0025 - 0.589930  (tea 200g)
class 0005 - 0.401045  (Dairy 50g)
class 0025 - 0.597354  (tea 200g)
class 0005 - 0.076208  (Dairy 50g)
class 0025 - 0.921183  (tea 200g)
class 0005 - 0.903241  (Dairy 50g)
class 0025 - 0.095948  (tea 200g)
class 0025 - 0.999941  (tea 200g)
class 0025 - 0.999964  (tea 200g)
class 0025 - 0.999851  (tea 200g)
class 0025 - 0.999095  (tea 200g)
class 0025 - 0.996700  (tea 200g)
class 0025 - 0.995081  (tea 200g)
class 0005 - 0.014279  (Dairy 50g)
class 0025 - 0.985547  (tea 200g)
class 0005 - 0.886126  (Dairy 50g)
class 0008 - 0.034091  (Dove Shampoo 200 ml)
class 0025 - 0.071053  (tea 200g)
class 0005 - 0.987528  (Dairy 50g)
class 0025 - 0.999926  (tea 200g)
class 0005 - 0.278210  (Dairy 50g)
class 0025 - 0.721621  (tea 200g)
class 0005 - 0.189403  (Dairy 50g)
class 0025 - 0.809976  (tea 200g)
class 0005 - 0.999054  (Dairy 50g)
class 0005 - 0.999771  (Dairy 50g)
class 0005 - 0.999645  (Dairy 50g)
class 0005 - 0.997947  (Dairy 50g)
class 0025 - 0.999884  (tea 200g)
class 0005 - 0.980071  (Dairy 50g)
class 0025 - 0.015116  (tea 200g)
class 0025 - 0.999876  (tea 200g)
class 0025 - 0.999899  (tea 200g)
class 0025 - 0.999871  (tea 200g)
class 0025 - 0.999880  (tea 200g)
class 0025 - 0.999848  (tea 200g)
class 0025 - 0.999883  (tea 200g)
class 0025 - 0.996988  (tea 200g)
class 0025 - 0.998979  (tea 200g)
class 0003 - 0.039865  (Butter 350g)
class 0005 - 0.030806  (Dairy 50g)
class 0025 - 0.928849  (tea 200g)
class 0005 - 0.998429  (Dairy 50g)
class 0005 - 0.071530  (Dairy 50g)
class 0025 - 0.927616  (tea 200g)
class 0005 - 0.481068  (Dairy 50g)
class 0025 - 0.516110  (tea 200g)
class 0005 - 0.878848  (Dairy 50g)
class 0025 - 0.118939  (tea 200g)
class 0025 - 0.999926  (tea 200g)
class 0005 - 0.403012  (Dairy 50g)
class 0025 - 0.595613  (tea 200g)
class 0005 - 0.450656  (Dairy 50g)
class 0025 - 0.547858  (tea 200g)
class 0005 - 0.313710  (Dairy 50g)
class 0025 - 0.685206  (tea 200g)
class 0005 - 0.410517  (Dairy 50g)
class 0025 - 0.588039  (tea 200g)
class 0005 - 0.473894  (Dairy 50g)
class 0025 - 0.524553  (tea 200g)
class 0005 - 0.406709  (Dairy 50g)
class 0025 - 0.591758  (tea 200g)
class 0005 - 0.425662  (Dairy 50g)
class 0025 - 0.572790  (tea 200g)
class 0005 - 0.393630  (Dairy 50g)
class 0025 - 0.604921  (tea 200g)
class 0005 - 0.353506  (Dairy 50g)
class 0025 - 0.645136  (tea 200g)
class 0025 - 0.999858  (tea 200g)
class 0025 - 0.999902  (tea 200g)
class 0025 - 0.999969  (tea 200g)
class 0025 - 0.998161  (tea 200g)
class 0005 - 0.479680  (Dairy 50g)
class 0025 - 0.518658  (tea 200g)
class 0005 - 0.408632  (Dairy 50g)
class 0025 - 0.589930  (tea 200g)
class 0005 - 0.401045  (Dairy 50g)
class 0025 - 0.597354  (tea 200g)
class 0005 - 0.076208  (Dairy 50g)
class 0025 - 0.921183  (tea 200g)
class 0005 - 0.903241  (Dairy 50g)
class 0025 - 0.095948  (tea 200g)
class 0025 - 0.999941  (tea 200g)
class 0025 - 0.999964  (tea 200g)
class 0025 - 0.999851  (tea 200g)
class 0025 - 0.999095  (tea 200g)
class 0025 - 0.996700  (tea 200g)
class 0025 - 0.995081  (tea 200g)
class 0005 - 0.014279  (Dairy 50g)
class 0025 - 0.985547  (tea 200g)
class 0005 - 0.886126  (Dairy 50g)
class 0008 - 0.034091  (Dove Shampoo 200 ml)
class 0025 - 0.071053  (tea 200g)
class 0005 - 0.987528  (Dairy 50g)
class 0025 - 0.999926  (tea 200g)
class 0005 - 0.278210  (Dairy 50g)
class 0025 - 0.721621  (tea 200g)
class 0005 - 0.189403  (Dairy 50g)
class 0025 - 0.809976  (tea 200g)
class 0005 - 0.999054  (Dairy 50g)
class 0005 - 0.999771  (Dairy 50g)
class 0005 - 0.999645  (Dairy 50g)
class 0005 - 0.997947  (Dairy 50g)
class 0025 - 0.999884  (tea 200g)
class 0005 - 0.980071  (Dairy 50g)
class 0025 - 0.015116  (tea 200g)
class 0025 - 0.999876  (tea 200g)
class 0025 - 0.999899  (tea 200g)
class 0025 - 0.999871  (tea 200g)
class 0025 - 0.999880  (tea 200g)
class 0025 - 0.999848  (tea 200g)
class 0025 - 0.999883  (tea 200g)
class 0025 - 0.996988  (tea 200g)
class 0025 - 0.998979  (tea 200g)
class 0003 - 0.039865  (Butter 350g)
class 0005 - 0.030806  (Dairy 50g)
class 0025 - 0.928849  (tea 200g)
class 0005 - 0.998429  (Dairy 50g)
class 0005 - 0.071530  (Dairy 50g)
class 0025 - 0.927616  (tea 200g)
class 0005 - 0.481068  (Dairy 50g)
class 0025 - 0.516110  (tea 200g)
class 0005 - 0.878848  (Dairy 50g)
class 0025 - 0.118939  (tea 200g)
class 0025 - 0.999926  (tea 200g)
I have a few more questions. Please answer them.

How to train the model so that it is able to recognize the objects in any environment whether it is supermarket or home or kitchen etc.?
Can we take pictures from mobile for any object and then train the model? Or is it that the pics have to be taken from the camera attached to the jetson (I'm using raspberry Pi v2 camera)?
I have also uploaded the pics on the Google drive which i'm using to train the model. Can you briefly have a look at them and check I'm using the right method? (I tried to upload them on github but getting errors due to the huge size)
I have also noticed that once you train the model and immediately run it then it is able to give different names and even recognize some of them but after a few days something happens and it just says 2-3 names irrespective of any object. I know it doesn't make any sense but I just noticed it.

Thanks a ton
Mohit

3. I have also uploaded the pics on the Google drive which i'm using to train the model. Can you briefly have a look at them and check I'm using the right method? (I tried to upload them on github but getting errors due to the huge size)

Hi @mohitg0292, from browsing through your dataset, I noticed that a bunch of the classes in the train/ folder don't have any images in them.  So the model would be untrained in those classes.   You should make sure that every class has a bunch of images for it (ideally 100 or more).   A lot of times, to save time collecting the dataset, I use all the images I have for train/ and just copy them to test/ and val/  (that's certainly not a best-practice for making a real model, as the test/val sets should be independent, but when you are just in development trying to get the model to work, it can save you time)

How to train the model so that it is able to recognize the objects in any environment whether it is supermarket or home or kitchen etc.?

When in doubt, add more data to your dataset - with a variety of backgrounds, camera angles, lighting conditions, ect.   The number of images for each class should be relatively balanced.

Can we take pictures from mobile for any object and then train the model? Or is it that the pics have to be taken from the camera attached to the jetson (I'm using raspberry Pi v2 camera)?

Yea, you can take pictures with any camera, and then simply upload them or copy/paste them into your appropriate dataset folders later

Hi @dusty-nv ! Thanks for your quick reply.
sorry i forgot to mention. actually i uploaded few pics on drive, not all of them since there were around 4000 images and it was taking too much time.
But all folders (train, text, val) have images with respective objects in the model. But there has to be some logic that the model only identifies these 2 objects (tea, dairy). or not?
I'm not sure but even "hand" or "background" is not identified which is pretty simple.

Do those tea and dairy objects have a lot more images than the others?   What accuracy is your model training to?
You might want to add additional code to train.py to make sure the dataset is loading all the images.  I noticed that your folder names have spaces in them, I don't think that should affect it but I'm not sure.

No every object has same number of images. Like you mentioned in your video. (100 images for training, 20 for val and 5-10 for test). I used blank wall for training images, then put green paper background for val images and colored background for test images. Also sometimes it's different object than tea and dairy. Like "ketchup" repeatedly...
The folders have spaces because as you mentioned in labels.txt file, I have put names in same format. The model is building the folders automatically.
If I'm not wrong, we call train.py to train the model right? ITt doesn't start if I run the "food_container_identifier.py" script/
What accuracy is your model training to? Where can I find this?
I just ran the model again. This time I didn't even put any object in front of camera. Just my hand in different positions. But the audio just said "tea" repeatedly. Only very few times it said, Dermaglos, zucker that's it.
I'm attaching full logs here.
logs.txt

The accuracy is reported when you run train.py as you train it.  I believe you can also run it with the --eval flag to just do the validation and skip training
Have you been deleting the .engine file when you re-export the ONNX?

From: mohitg0292 @.>
Sent: Friday, March 17, 2023 12:17:29 PM
To: dusty-nv/jetson-inference @.>
Cc: Dustin Franklin @.>; Mention @.>
Subject: Re: [dusty-nv/jetson-inference] Not able to install Pytorch (Issue #1563)
No every object has same number of images. Like you mentioned in your video. (100 images for training, 20 for val and 5-10 for test). I used blank wall for training images, then put green paper background for val images and colored background for test images. Also sometimes it's different object than tea and dairy. Like "ketchup" repeatedly...
The folders have spaces because as you mentioned in labels.txt file, I have put names in same format. The model is building the folders automatically.
If I'm not wrong, we call train.py to train the model right? ITt doesn't start if I run the "food_container_identifier.py" script/
What accuracy is your model training to? Where can I find this?
I just ran the model again. This time I didn't even put any object in front of camera. Just my hand in different positions. But the audio just said "tea" repeatedly. Only very few times it said, Dermaglos, zucker that's it.
I'm attaching full logs here.
logs.txthttps://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdusty-nv%2Fjetson-inference%2Ffiles%2F11003436%2Flogs.txt&data=05|01|dustinf%40nvidia.com|e42ba74dabef47acc5cb08db27031b0a|43083d15727340c1b7db39efd9ccc17a|0|0|638146666524946802|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=MI2T1ApvA1pVhmzDXC1mxVsG8RWtRJ3Vck3goH9HCSE%3D&reserved=0
—
Reply to this email directly, view it on GitHubhttps://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fdusty-nv%2Fjetson-inference%2Fissues%2F1563%23issuecomment-1474079067&data=05|01|dustinf%40nvidia.com|e42ba74dabef47acc5cb08db27031b0a|43083d15727340c1b7db39efd9ccc17a|0|0|638146666524946802|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=DAOxtsU5zsvKP%2FLIR210gm6axqhjHHvGZI4aC54X3rs%3D&reserved=0, or unsubscribehttps://nam11.safelinks.protection.outlook.com/?url=https%3A%2F%2Fgithub.com%2Fnotifications%2Funsubscribe-auth%2FADVEGK47M3TKBPEL7TSOKETW4SFBTANCNFSM6AAAAAAU6WY42A&data=05|01|dustinf%40nvidia.com|e42ba74dabef47acc5cb08db27031b0a|43083d15727340c1b7db39efd9ccc17a|0|0|638146666524946802|Unknown|TWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D|3000|||&sdata=3GE4EU2NYSlCTtTt041dlSDETXZb%2FjwQmENpMBaLGHM%3D&reserved=0.
You are receiving this because you were mentioned.Message ID: @.***>

@dusty-nv Thanks for your quick responses.
I just tried to run train.py again with --eval parameter. But the model is running to train the system and didn't skip training.
Yes I always delete .engine file as you recommended.
Can we use AI generated image to train the model? Also would you suggest to add more pictures only in train folder or all the folders? As I didn't really understand the purpose of two other folders i.e. "val" and "test".
Mohit

Hi @dusty-nv !
As you suggested I took more pictures from my mobile camera and put it in train, val and test folders of respective object in ratio 70:20:10.
Then I trained the model after deleting .engine file. It tool around 7 hours to train the model. Here's the training output of training the model.
After that I exported in .onnx format. here's onnx output of onnx.
The labels.txt look like this.

I ran the model and no success. The model is totally recognizing wrong now. :(
Here are logs for the running the model.
model running logs.txt
Please help and guide me where I'm going wrong. Also in the logs if you'll notice it is printing whole labels in the output.
Mohit

OK, perhaps this because of how you have named your folders and the alphanumeric order in which PyTorch reads them, being different from your labels.txt.   In your training log, this is the order of the classes that the model was trained with:
=> dataset classes:  27 ['Amchur Powder 100g', 'Butter 350g', 'ChainSpray 200ml', 'Dairy 50g', 'Dove Shampoo 200 ml', 'Fastrack ', 'Garam Masala 100g', 'Gefro Box 500g', 'Handwash 500ml', 'Incense 50g', 'Lemon 200ml', 'Mate 500g', 'Pepper 50g', 'Pepper Punt 50g', 'Ponds 90g', 'Salz 500g', 'SpecsBox 100g', 'Thymin 50g', 'Zucker 500g', 'background', 'deo 150ml', 'dermaglos 50g', 'hand', 'ketchup 500ml', 'lechuga crema 55g', 'tea 200g', 'vaseline 100ml']

Try changing your labels.txt to reflect this same order, and see if that helps.

Hi @dusty-nv !!
Thanks for your feedback. You were correct. The model was fetching wrong folders with wrong properties. Actually I didn't create folders manually. The camera-capture tool automatically created folders based on the labels.txt. So for now I manually removed all the spaces from all the folders. But I do have few doubts:

How to disable camera-capture tool creating folders by default? For ex. I added few more objects then again camera-capture tool created folders again repeatedly (since the labels file have spaces and existing folders don't have spaces) and I had to delete the new empty folders.

Can we train the model only for new objects or do we need to train the whole model again?

I have run the --eval command. Can you tell me the performance of the model based on the output? I didn't get it.

While training the model it runs for train (774) and test (176). What are these numbers?

The output of the model is slow. Can you check the code and tell me if it can be improved?
https://drive.google.com/file/d/1ItMTk16HcKsTg3nNDoTbkHZ7H4lsTEKI/view?usp=sharing

Thanks
Mohit Gupta

How to disable camera-capture tool creating folders by default? For ex. I added few more objects then again camera-capture tool created folders again repeatedly (since the labels file have spaces and existing folders don't have spaces) and I had to delete the new empty folders.

camera-capture knows where to put the images based on the labels.txt, so your labels should match the folder names.  Or, after your done training, you can just have a separate labels.txt that has spaces in it.

2. Can we train the model only for new objects or do we need to train the whole model again?

If you keep your new objects in a separate dataset, you should be able to load your previous model from train.py and continue on from there.

3. I have run the --eval command. Can you tell me the performance of the model based on the output?

It says the accuracy (Acc@1) is only 3.915% - this doesn't seem correct.  Maybe you loaded a model that wasn't trained for many epochs.  Regardless, it also outputs the accuracy at the end of each training epoch.

4. While training the model it runs for train (774) and test (176). What are these numbers?

Those are the batch numbers.   If you multiple the batch number by the batch size, that gives you the number of images in the dataset

5. The output of the model is slow. Can you check the code and tell me if it can be improved?
https://drive.google.com/file/d/1ItMTk16HcKsTg3nNDoTbkHZ7H4lsTEKI/view?usp=sharing

I think the calls to pyttsx in your main processing loop are blocking and may be slowing it down:
engine.say(class_desc)
engine.runAndWait()

those should probably be run in a separate thread, so the camera processing loop can continue on


Autodocs

Big updates for package documentation

Looks good. We will see how package and documentation will be published


Use libtest-mimic to make filetests behave like a normal test

While working towards running tests with nextest, I found that the filetests test in cranelift-tools doesn't behave in the way that nextest expects. Wrapping it with libtest-mimic was enough to get nextest working for that test, but as there's more work to do there, this seemed like a reasonably atomic change to break out.

For this particular case could #[test] be used? Using libtest-mimic here is basically the same as a single function with #[test] I think

Great point, that's totally possible!


[AIRFLOW-610] Respect _cmd option in config before defaults

Dear Airflow maintainers,
Please accept this PR. I understand that it will not be reviewed until I have checked off all the steps below!
JIRA

[X] My PR addresses the following:

https://issues.apache.org/jira/browse/AIRFLOW-610

Description

[X] Here are some details about my PR, including screenshots of any UI changes:

This PR is a more or less a rebase of https://github.com/apache/incubator-airflow/pull/1862
The command versions of config parameters were overridden by the
default config. E.g sql_alchemy_conn got the default value even
when sql_alchemy_conn_cmd was specified.

This PR makes the AirflowConfigParser only look at the default values last by having a separate instance of ConfigParser containing the default values.

Tests

[X] My PR adds the following unit tests:
tests/configuration.py:ConfTest.test_command_config
tests/configuration.py:ConfTest.test_remove_option

Commits

[X] My commits all reference JIRA issues in their subject lines, and I have squashed multiple commits if they address the same issue. In addition, my commits follow the guidelines from "How to write a good git commit message":

Subject is separated from body by a blank line
Subject is limited to 50 characters
Subject does not end with a period
Subject uses the imperative mood ("add", not "adding")
Body wraps at 72 characters
Body explains "what" and "why", not "how"

[X] Passes git diff upstream/master -u -- "*.py" | flake8 --diff

I don't really understand why this test fails on Travis, it works locally with sqlite backend.
12) FAIL: test_remove_file_clears_import_error (tests.SchedulerJobTest)
----------------------------------------------------------------------
   Traceback (most recent call last):
    tests/jobs.py line 2889 in test_remove_file_clears_import_error
      self.assertEqual(len(import_errors), 0)
   AssertionError: 1 != 0

(https://travis-ci.org/apache/incubator-airflow/jobs/340156757#L4496)

Oh, can you rename this PR to something like "Correctly respect _cmd option in config files above default values" (if that isn't too long)

Thank you @ashb, I will revise the PR!

Thank you @ashb, I will revise the PR!

Codecov Report

Merging #3029 into master will decrease coverage by <.01%.
The diff coverage is 97.95%.

@@            Coverage Diff             @@
##           master    #3029      +/-   ##
==========================================
- Coverage   73.22%   73.21%   -0.01%
==========================================
  Files         178      178
  Lines       12472    12474       +2
==========================================
+ Hits         9132     9133       +1
- Misses       3340     3341       +1

Impacted Files
Coverage Δ

airflow/configuration.py
83.82% <97.95%> (-1.15%)
:arrow_down:

airflow/jobs.py
80.07% <0%> (+0.17%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 3fe06e9...f43e864. Read the comment docs.

@ashb I addressed most comments now and manage to fix an actual bug with my implementation that the previous failing test catched. Please take a second look!

Thanks! Squashed now.

What's the process for getting this merged? @ashb

@bolkedebruin @jgao54 @Fokko Can we get a merge on this please?

I found an edge case which my patch does not handle that probably should be fixed before merging, if a section is missing in the config but exists in default it gives an error, so lets wait for that. Will fix that during the weekend.

@cjgu Did you get a chance to fix the edge case you found?

Good - Life is important too! Just going through recent PRs that I was involved in now I can merge them directly. No rush.

@ashb Please take a look at the commit I added, will squash it when approved!

Great, squashed it now, so should be ready for merge.

Seems there's some flaky tests, rerunning the tests.

I rebased this onto latest master and fixed the conflicts. It would be nice to get this merged soon as it touches quite a lot of files and easily attracts conflicts. @ashb @Fokko

Sorry for bugging you, but I really would like to get this merged soon as it's been ready for a few weeks now. @ashb @Fokko

Ugh looked like I rebased at a bad point, will redo it.

Looks like the failing tests fail on other branches as well. So this should be ready to be merged.

@cjgu Please rebase on master once more. Master is green now, since so many files are touched, we need to make sure that it is ok.

@Fokko That's due to feedback from the previous PR, https://github.com/apache/incubator-airflow/pull/1862

Any more feedback @Fokko or could we merge this?

Thank you @Fokko!


Suggestion: allow direct scenario calls by using reserved tags

The current Karate Way avoids the creation of new steps, but allows for calling scenarios by using a tag reference (example like @name=login).
My suggestion is to allow the use of reserved tags (like the @ignore tag) that allows the call of feature scenarios as part of the steps (as sugar coating for the internal call step).
Use format:
Feature: My Feature file with steps

@Given(I log into the application as "<username>")
Scenario: Some scenario name here
  * def request { user: <username> }
...

@smoke-test
Scenario: My actual smoke test
   Given I log into the application as "my_user"
...

This could both make some (mostly UI) test cases more readable and more maintainable (in case of interface variation).

call read('/some/path/to/X.feature@smoke-test')

This is the current way to call specific scenarios in a feature file. Does this work for your need?

Thanks @stevenspears, as mentioned in the proposal, the idea is for it to be more of a sugar coating from the call step definition for better test readability.
My belief is that Karate is very good and going to the right places where it comes to making use of the Gherkin language, and I understand that adding new implementations to the mix through coding is not part of the Karate way, my suggestion is a sugar coating method (by the use of reserved tags) to do the call read method.

@Gokuroro nope :) we are not going to go down the direction of Given I log into the blah ever. Karate is designed as a programming language (very close to JS). you can read a very detailed discussion on this here: https://github.com/karatelabs/karate/issues/398


Phase and ampliude modulation

Hi Poppy,
I am completely new to poppy (&github btw) but I have choosen to use it for my research rather than my custom IDL tools.
However, there are a few things I have not seen reading the documentation. Is it possible with the current poppy, or expected with next versions, to perform :

phase modulation : define a "diversity", as a list of successive phases (screens, or DM/zernike coefficients), so that their application leads to a list of successive PSFs (ie of dimension 3)?
amplitude modulation/disturbance: I have mainly seen fonctions (in hexdm for example) to alter the phase, is the same easily possible with amplitude ? Unfortunately, complex phase is not supported.
Thanks in advance for your answers, and
best regards from a new popper !

Hi Frederic, I’ll be happy to help with this. But first, we have moved primary development of poppy over to the repo at github.com/spacetelescope/poppy. Could you please repost this question there? That will let the rest of the dev team besides me to also see the discussion. Cheers.

Hi Marshall,
Thank you for your fast answer, I sent the question to the other repo.
Please just tell me if there is anything more I have to do here to close the issue.
Cheers,


Trying to get Atomic Wallet to connect, app just spins, two different browsers show two diff errors

Describe the bug
Wallet doesn't connnect after scanning QR code
To Reproduce
Steps to reproduce the behavior:
Go to market.oceanprotocol.com with either Chrome (Version 91.0.4472.164) (Official Build) (64-bit) or Firefox (89.0.2) (64-bit).
Click on Connect Wallet
Click on Wallet Connect
Scan QR code with iphone (12 ios 14.7)
Expected behavior
market.oceanprotocol.com refreshes to connected wallet.  iphone App shows connection.
Screenshots

Desktop (please complete the following information):

OS: Windows 10 Pro 20H2 x64
Browser:  Chrome (Version 91.0.4472.164) (Official Build) (64-bit) or Firefox (89.0.2) (64-bit)

Smartphone (please complete the following information):

Device: iPhone12
OS: 14.7
Browser: N/A  Atomic Wallet (latest update)

Additional context
Trying to connect wallet and publish some files.

thanks for the report. Not entirely sure what's going on for you, while we know about ongoing issues with WalletConnect (#592) your reported issue seems new.
The error messages suggest there was an issue with portis.io which seemed to make the whole wallet connection fail. This I was not able to reproduce and I can successfully connect multiple mobile wallets like Rainbow or Trust Wallet via WalletConnect with market.
But when trying Atomic Wallet something is indeed different where WalletConnect expects an ETH address but Atomic Wallet exposes a BNB address for whatever reason which seem to make the connection fail in the end. This is on Firefox, and with a freshly installed Atomic Wallet on iPhone, and the market in incognito window:

This would be something out of our hands as we neither control WalletConnect, nor Web3Modal which we use for wallet connection. The issue I'm running into can be reproduced when using Atomic Wallet on https://web3modal.com so this would be an issue for https://github.com/Web3Modal/web3modal/issues
As for your other errors could you try again to be sure it wasn't some portis problem? And maybe try in incognito window to be sure no plugins or anything in your browser's cache is influencing this

Tested a bit in #749 to get our related dependencies in same state as on https://example.walletconnect.org but it does not solve the specific Atomic Wallet issue as then web3modal expects an ETH address to initiate Web3, but only gets a BNB address from Atomic Wallet and there seems to be no way in Atomic Wallet to define which address gets exposed. So this would be then on Atomic Wallet's plate, which is why I would love to see a Dapp example where Atomic Wallet + WalletConnect actually works

Thanks, the demo page shows the QR code and then just stops.  The Wallet app on the phone just hangs showing the ocean market logo and a never ending spinning loading message.  I don't have an exact dapp link, but I did transfer most of my Robinhood holdings, so it's definitely active.


math.dot is not commutative

Docstring for the function dot from creme.utils.math: Returns the dot product of two vectors represented as dicts.
The function actually returns the product of the shorter of the two vectors and the second vector. i.e. if the second vector is shorter, it is multiplied by itself rather than by the first. This make the function not commutative, but a dot product is commutative.
Recreation
a = {'x' + str(i): i for i in range(5)}
b = {'x' + str(i): i + 1 for i in range(3)}
dp1 = dot(x=a, y=b)
dp2 = dot(x=b, y=a)
assert dp1==dp2

I'm writing a fix for this and I'll put in a pull request in the next couple days.

Good catch... I'm ashamed!

Fixed.


[1.16.5] he game crashed whilst rendering overlay Error: java.lang.NoSuchFieldError: children

Provide the crash report


Opt out saving pseudonym profiles

At least in the German translation of https://www.deepl.com/privacy.html it is possible to opt out saving data for pseudonym user profiles (8. [...]  It works by saving a special cookie saying deepl to not save the tranfered texts. Would it be possible to implement an opt-out option for this app?

This options ask to DeepL to not generate your user profile by saving a cookie into your web browser. Since the app only use https requests, and doesn't send or save any cookie, this options it enabled by defaut ;)

That's good :-)
Thank you for the quick info.


On Safari IOS

On IOS Safari, if the modal content requires vertical scrolling, the bottom portion of the modal is covered by the bottom browser bar and cannot be scrolled past.

@gijimmyj It would be helpful if you provide a little more details but if I understand it right.
This can be because of the CSS for the modal & not specifically because of the library as it just handles the scrolling portion.
I'll suggest using bottom: 0 (if fixed positioned) or height: 100% rather than view port height units for ex: 100vh which factors in the additional browser url bar height & make some of your content hide.
Here's more about the same: https://developers.google.com/web/updates/2016/12/url-bar-resizing

@PezCoder 's solution worked for me, changing height: 100vh to height: 100% fixed the odd bottom overflow  👍


Update singer-sdk to 0.4.7

Update singer-sdk to 0.4.7

Oops. I didn't see this when I created #116
ROFL 😆


Padding and Cleanup

Game.js:

Removed all occurences of engine.dimensionProportion
Added timeout updates to every clickable object
Removed unnecessary commented lines of old code
Tweaked the menu button posY a little
Returned all title logos to the Canvas
Padded the letter spaces and input keypad

Testing updates before merge.

Need to fix the width for the leaderboard scene for containerDiv_.


Track 'setClientWl' event trigger

It appears that one resource is still trigger this outdated event and thereby applies a wanted level causing errors in the server logs, I haven't figured out which one it is yet but all resources that does apply wanted level to players who commit crimes are upgraded to the new syntax and works. In game, this issue is known by not getting wanted in a situation you should be getting wanted in. Any ideas are welcome and a patch from anyone who may found it would be even more appreciated.

Did a search in all project files and couldn't find that event anywhere, I have to close this now as it's not a GTW-RPG bug but related to our development server. I'll keep my eyes open tho, maybe I could use the same tool to search in the remaining server files.


Defender for Cloud Agentless Scanning should list the AWS Account IDs used by Microsoft.

The documentation lists the permissions that agentless scanning uses to scan AWS VMs but it does not list the AWS account IDs that are used. This can be concerning from a security perspective in that you need to know what third party AWS accounts have access to your environment.
https://learn.microsoft.com/eN-us/azure/defender-for-cloud/concept-agentless-data-collection

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

ID: ede81000-9e59-b0dc-6bd5-9a94b1999e4f
Version Independent ID: 93f831a1-61dc-c8ec-40bf-bcbe13c38bdc
Content: Agentless scanning of cloud machines using Microsoft Defender for Cloud
Content Source: articles/defender-for-cloud/concept-agentless-data-collection.md
Service: defender-for-cloud
GitHub Login: @bmansheim
Microsoft Alias: benmansheim

@gregjaworski
Thanks for your feedback! We will investigate and update as appropriate.

@gregjaworski
You are correct that the documentation does not list the AWS account IDs that are used for agentless scanning. However, it is important to note that agentless scanning only collects metadata from AWS resources and does not collect any sensitive data. Additionally, the data collected is encrypted in transit and at rest. If you are still concerned about the security implications, you can contact Microsoft support for more information.
Azure support request.


Question: Developing under different preprocessor directives

Overview
How could I develop in VS using a different preprocessor directive such as WINDOWS_UWP? In the past I used the built application and it included a solution that had the changes. Was this just a hack or is there a "supported" way to do this?

Make sure your project settings have the following conditions met:

Build platform is UWP
IL2CPP
API compatibility is .Net 4.x

Thank you!


Empty test manufacture field leads to failing certificate validity check

Avoid duplicates

[X] Bug is not mentioned in the FAQ
[X] Bug is specific for Android only, for general issues / questions that apply to iOS and Android please raise them in the documentation repository
[X] Bug is not already reported in another issue

Technical details

Device name: Xiaomi A1
Android version: 9
App version: 2.6.1

Describe the bug
In some cases the test manufacture field is empty. This then leads to a failing certificate validity check.
Here's a screenshot, which a Twitter user shared with me.
He took a RAT in Germany and then checked if he could travel to German with this test. CWA shows this then:

Also, the certificate which CWA created is shown as invalid in CovPassCheck...
Steps to reproduce the issue

Take a RAT
Request a DCC
Check the DCC with the new validity checker for the country "Germany"
See that CWA says that the certificate is not valid

Expected behaviour
The test manufacture field should be filled.
Additional context

I report this bug based on feedback I got on Twitter.
I assume that the testing site did not transmit this information, that's why this field is empty. IHMO testing site should be forced to have to transfer the name of the testing manufacture.

Can you please find out the rat Anbieter

It was a testing site from https://15minutentest.de/de/de

The issued certificate also does not validate in the CovPassCheckApp.
It was not a one-off error. We issued another one at the test location and that one was also not valid.

The code does validate in the VerificaC19 app by the Italian government.

I'll try another DCC test location (Rotes Kreuz) later today to see if this is an issue with RAT certificates in general or an issue with this specific test location.

I went to another test provider in Berlin and that one did issue a valid certificate!  (https://testaja.de/ts02/)

The issue thus seems to be specific to 15minutentest.de
Will you contact them to fix their certificates?
Also seems like RKI  maybe shouldn't issue certificates where the test brand is not specified in the first place.

Unfortunate turn of events. Even though corona-warn-app does validate the certificate from  https://testaja.de , CovPassCheck does not validate :(

In the case of https://testaja.de the product manufacturer is non-empty but the product name is empty.

@arianvp  Can you please provide me the qr code from testaia.de
<EMAIL_ADDRESS>

Mail has been sent.

This is a complete valid test certficiate. Other check apps and also the iOS CovPass Check App will confirm this.
I can reproduce the issue with Android CovPass Check. But please create a ticket in the Android CovPass Check and I will also forward the issue
https://github.com/Digitaler-Impfnachweis/covpass-android/issues

@thomasaugsten

This is a complete valid test certficiate. Other check apps and also the iOS CovPass Check App will confirm this.
I can reproduce the issue with Android CovPass Check. But please create a ticket in the Android CovPass Check and I will also forward the issue
https://github.com/Digitaler-Impfnachweis/covpass-android/issues

See PS in: https://github.com/Digitaler-Impfnachweis/covpass-android/issues/59#issuecomment-890958483.

Any update on this? Has the test provider been notified and has the issue been corrected? Or will all the EU scanner apps be adjusted to cope with this scenario?
How to make sure test providers don't issue invalid certificates in the future?

The test provider was informed.

TL;DR
Hi @arianvp ,

How to make sure test providers don't issue invalid certificates in the future?

With the change in the Corona-TestVerordnung taking effect since August 01, 2021, providers of RATs would need to connect to Corona-Warn-App to receive a refund for the free-of-charge citizen tests. And there are exactly 2 ways to do this:
Either you are participating in the Schnelltest-Portal of T-Systems International (TSI) which offers a nice web-based solution for the whole work flow, or you connect to TSI's backend via your own software implementation.
For the whole bunch of information see here: https://github.com/corona-warn-app/cwa-quicktest-onboarding/wiki
So, in both cases it's necessary to make a contract with TSI.
In case you want to provide your testees with a EU Digital Covid Certificate (DCC) as a Schnelltest-provider using your own software implementation, you would send testees' data to the TSI backend, which forwards its hash to IBM/Ubirch's backend for signing the DCC. After it had been signed, you may pull the signature for the DCC from TSI, bundle it with testees' data again, and then do what ever you want with it 😉 .
See workflow here: https://github.com/corona-warn-app/cwa-quicktest-onboarding/wiki/Anbindung-an-CWA-mit-Verwendung-von-DCCs#anbindung-an-cwa-mit-verwendung-von-dccs
So, in the case of the empty manufacturer field, there is one and only instance who could check for the validity of the certificates' contents:
TSI.
But as all DCC contents are sent to the CWA Backend (=TSI servers) encrypted, TSI can not do anything, after the test provider went online and is in "production state".
BUT
before the provider gets access to the PROD backend, the provider is required to test its implementation in a WRU environment, and finally needs to pass a "Abnahmetest": https://github.com/corona-warn-app/cwa-quicktest-onboarding/wiki/Checkliste-Abnahmetest
So, the only possibility for TSI to check for such flaws described in this issue would be, to TSI also check contents of produced DCCs extensively. Obviously that didn't happen yet/for all providers.
Probably it would be a good idea, to open an issue in https://github.com/corona-warn-app/cwa-quicktest-onboarding.
But don't expect too much. While I personally perceive the collaboration between SAP and community for CWA as smooth, appreciative and highly constructive, I don't see signs from TSI to value community contributions that much currently.
The reason could be, that they're maybe a bit overwhelmed by workload at the moment - at least I got that impression when looking to issues like
https://github.com/corona-warn-app/cwa-quicktest-onboarding/issues/47 - 3rd party providers can't communicate with TSI because their mailbox is full, or
https://github.com/corona-warn-app/cwa-quicktest-onboarding/issues/31 - 3rd party providers are waiting weeks to get connected to the backend and the issue gets locked when there are too many complaints, even providers try to connect to each other to get some information*, or
https://github.com/corona-warn-app/cwa-documentation/issues/661#issuecomment-891908744 / https://github.com/corona-warn-app/cwa-quicktest-onboarding/issues/24 , where even an issue that users are able to manipulate the period of validity of their DCCs when 3rd party providers have a flawed implementation is apparently considered to be unimportant and it's even not worth to communicate about it.
To be honest, I'm a bit disappointed about TSI's current communication.
But maybe @mlenkeit or @thomasaugsten can add some positive information that could cheer me (or us?) up regarding to this subject?

The initial issue was resolved, test centers have to issue valid certificates, but that's out of the influence of the CWA-Team.  Thus closing this issue.


Speed up pattern matching

Fixes https://github.com/reactjs/react-router/issues/3215

cc @KyleAMathews
I have no clue why we support newlines in paths anyway. Are they even legal characters in URLs? I don't think they are. @mjackson?

Ooo nice! That dropped the matching time for the same route that took ~1.2 seconds down to ~0.2 seconds.
Even faster would be nice given a 100 page site still isn't that big but this is a huge start.

Shoot, this PR is actually wrong.

Fixed.
https://github.com/reactjs/react-router/pull/1166 is no longer needed because we no longer decode URIs or URI components before feeding them into the route matching.
@KyleAMathews Can you run your timing against this updated branch as well now?

I tested the latest version and it takes roughly the same amount of time.

What do you get for the timing against 0.13.x?

I timed things on bricolage.io and got something like 50ms. It's a bit hard to know how apples-to-apples that test is as a) it's against production compiled code vs. dev and b) I don't know if the same route there is last in line like it is currently. But presumably it is.

And actually with this PR, the execution time is somewhere between 70 and 120ms (most later runs towards lower end). When I said 200ms earlier, I was including time running some mixin code which runs after the routing is complete.

The first run ought to take longer since pattern compilation is lazy.
I'm going to leave this up for a bit to get a little more review – found a few other simplifications here. It's not a rewrite, just a quick cleanup of what we have right now.
IMO the performance point here (where path-to-regexp is still like 10x faster per https://github.com/reactjs/react-router/issues/3215) is another point in favor of splitting out our path matching into a separate third-party library rather than maintaining our own hand-rolled pattern matching DSL.

Reviewers, removing whitespace makes this easier to read through: https://github.com/reactjs/react-router/pull/3217/files?w=1

I'm curious where the meat of the speedup is. Is it removing the \s\S classes, or the fact that it's not greedily going to the end anchor?

BTW, this LGTM :+1:

It's exactly this change that speeds up @KyleAMathews's use case: https://github.com/reactjs/react-router/pull/3217/commits/6e908b5536a0903546529f69812a0f3fbc97e82f#diff-3740a979a31a412b32b93d9300983835R101
The rest is just taking this opportunity to clean stuff up, since I'm touching this code anyway.

Well, that line is gone in the final diff. I think it's mainly that we don't double-add a (.*?) on there now, unless I'm missing something. That combined with the end of line anchor would seem to be a pretty painfully slow regex, I think.
I'm wondering if we should add some tests for _compilePattern to make sure the regex's being built are coming out as expected.

The 2nd commit is just to clean up the code – the speed improvement comes entirely from the first commit. I guess it was just the ([\s\S]*?) at the end that was slow. Replacing it with a (.*?) is enough to get the full speedup, but really it's unnecessary.
That we have any special-casing there at all is because of our concept of non-greedy splats, which IMO should just be replaced entirely with greedy splats.
I don't think we should assert on the output of _compilePattern per se – I think it makes more sense to assert on the result of route matching, because it's closer to what we actually want.

Nice work, @taion. Thanks! :D

Parts of that code have been bothering me for a while now. I'm happy to have finally had the excuse to get to the root of it. :D

There's a small regression in this PR which affected me when upgrading from 2.0 to 2.1. In 2.0 <Link to="test" /> would work, but in 2.1 it must now be <Link to="/test" /> with the leading slash.

@EvNaverniouk You always had to use the leading slash. We don't yet support relative URLs.

I'm just about done here, but that's actually because https://github.com/reactjs/react-router/pull/3158 was incorrectly released as part of 2.1.0, even though it should not have been.

I'm getting a bunch of these on the client side, whereas things seem to be working fine with SSR.
Warning: [react-router] Location "page" did not match any routes

Are you running 2.1.1 yet? We pushed that to revert #3158.

2.1.1 fixed it. Thanks!


chore: start to remove and deprecate App#getInstance

This pass will include the following changes:

[x] Marked as @ Deprecated
[x] Converted NetworkUtils to class with injected app context
[x] Injected app context into AuthManager
[x] Replace getString() with ResourceHelper
[x] Convert CurrencyUtils and PhoneUtils to injectable singletons
[X] Create PermissionChecker interface for VMs
[X] Create API based Vibrator for VMs and UI
[X] Move local contact fetching out of VM into domain layer

Only thing remaining is the crypto newInstance()'s and factory/converters for Solana. TBD


feat: update to Starlark v0.0.0-20230302034142-4b1e35fe2254

Fix https://github.com/GoogleContainerTools/kpt/issues/3865
Update Starlark to include recent capability such as dictionary concatenation: https://github.com/google/starlark-go/pull/397

Looks great and thanks for the contribution.
cc @mortent.  starlark is built into porch, do we want to bump on the porch side?


Is it still working?

Hi I'm trying to run it on my mac but I'm getting errors whatever command I try to run:
chrome-bandit list --chrome gives ERROR: no records
I am trying to access passwords that were saved before using time machine on my mac, I lost everything and cannot retrieve them. Maybe the encryption key changed when using the new mac?
Thank you for your help and for the library, it's cool

Hi @MilesYM, this is not a recovery tool, it's just a tool to programmatically extract the passwords Chrome has already access to.
The error indicates the program was not able to retrieve the password since it does not accessible/exists.


missing counter.cpp in Archer/rtl

Cmake reports missing counter.cpp in rt/CMakeLists.txt when building ROSE with llvm release_40.
Is there any restriction for that?

@peihunglin I already messaged @jprotze I think we just just forget to add it in the last commit.

@peihunglin forgot to include the file in the last commit. It is commited now


Large (over 6MB) Image Handling

I noticed when serving large files (over 7mb) for the first time, I get an error in the lambda function.

LAMBDA_RUNTIME Failed to post handler success response. Http response code: 413 error

I see discussion online that suggests this may be caused by Lambda having a 6mb payload limit for responses. So I believe what is happening is that when the /original version is created via the lambda task, it is unable to serve the full 6mb+ payload back through CF itself. Subsequent requests, after /original has been created, are served successfully.
I have tested this theory by uploading content to both the storage s3 bucket and creating the /original version in the transformed bucket at the same time. The result was that the image was served successfully on the first request, so my assumption is that this size limit issue is the culprit. However, pre-populating the /original is not really a solution, as there may be transformations that are large as well...
Have I potentially configured something incorrectly on my side, or is this an issue for others?

My bad, I had not implemented the maxImageSize Lambda environment variable so the imageTooBig check was not firing for me.


Convert all discussions into issues, and close the discussions section

Should redirect all questions to StackOverflow, where there is a much bigger audience.

Created #4912 to disable the blank issue-template

The issue-transfer feature is very weak, so decided to just disable the discussions section

Ok!


Sync objc swift demos

updated demo project structure (created new folders)
Added controller with list of samples

LGTM 👍


Removing unnecessary styles + small tweaks to please JSLint

I used JSLint + JSHint to find some unattractive details.
Additionally I found out that some stylings are redundant after removing the .btn-with-count class. This one is needless due to the fact that there's no counter at all 😉

I implemented the majority of the changes from this PR @tomlutzenberger. Thanks man!


Veyoze converts "+" in env keys to " "

I'm storing my ENV variables in a GitHub secret and referencing them via FORGE_ENV_KEYS. I noticed one of my base64 encoded strings has had its + characters replaced with a space  :
Original:
MY_SECRET="base64:B5+B6voa8tXtkUtkvb+VaV8sd2nvu9y80QmTnJ5CveQ="
Results in
MY_SECRET="base64:B5 B6voa8tXtkUtkvb VaV8sd2nvu9y80QmTnJ5CveQ="
Afaik a + character is valid within base64 encoding.

Interesting. Looks like the issue comes from the parse_str method I've used to convert a string variable to array.
It's on my list to check out. Thank you for investing time in Veyoze!

Thanks! I wasn't sure if this was going to be a Veyoze / Forge SDK issue, did have a quick look around but didn't notice that method call.
Spent some time getting it up and running on a client server today, works really well so far!

Found a quick but secure solution ✅. I'll make a PR once I got added some test assertions.

Addressed this issue in this release: https://github.com/mehrancodes/veyoze/releases/tag/v0.1.6
Feel free to drop a comment if you still run into any problems with it.


janstey ceda-cc and cfcheck report for CanESM5 v20190429

The following errors were raised by the ceda-cc quality checks for the control/s20180125-r3i1p2f1/ test sample:

Global attribute: mip_era should be changed to 'SNAPSI' not 'CMIP6'

Variable siconc is not in table 6hrPt, is this meant to be sinconca?

cell_methods attribute erros:
The cell_methods attribute needs to be changed to match the MIP tables for the following variables
mrso, mrsos, snd, snw:
need to change cell_methods attribute to cell_methods="area: mean where land time: point"
e.g. for mrso:
ERROR: Variable [mrso] has incorrect attributes: cell_methods="area: mean where land time: mean" [correct: "area: mean where land time: point"]
rlut, tas,uas, vas:
need to change cell_methods attribute to cell_methods="area: mean time: point"
e.g. for rlut:
ERROR: Variable [rlut] has incorrect attributes: cell_methods="area: mean time: mean" [correct: "area: mean time: point"]
sithick:
need to change cell_methods attribute to cell_methods="area: time: point where sea_ice"
ERROR: Variable [sithick] has incorrect attributes: cell_methods="area: mean where sea_ice time: mean" [correct: "area: time: point where sea_ice"]
tntnd, utendepfd, utendnd, utendogw, utendvtem, utendwtem, vtendogw, xgwdparam, ygwdparam:
need to change cell_methods attribute to cell_methods="longitude: mean time: mean"
e.g. for tntnd:
ERROR: Variable [tntnd] has incorrect attributes: cell_methods="longitude: mean time: point time: mean" [correct: "longitude: mean time: mean"]
tos:
need to change cell_methods attribute to cell_methods= "area: mean where sea time: point"
ERROR:Variable [tos] has incorrect attributes: cell_methods="area: mean where sea time: mean" [correct: "area: mean where sea time: point"]

units:
the units attribute for utendvtem and vtendwtem needs to be changed to units="m s-2"
e.g.
ERROR: Variable [utendvtem] has incorrect attributes: units="m s-1 d-1" [correct: "m s-2"]

Variable siconc is not in table 6hrPt, is this meant to be sinconca?

cell_methods attribute erros:
The cell_methods attribute needs to be changed to match the MIP tables for the following variables

As discussed in the CEDA meeting on Oct 19, SNAPSI is happy to accept siconc in lieu of sinconca, and the cell methods should describe what was done/output.

units: the units attribute for utendvtem and vtendwtem needs to be changed to units="m s-2" e.g. ERROR: Variable [utendvtem] has incorrect attributes: units="m s-1 d-1" [correct: "m s-2"]

The units attribute has been changed to m s-2 for these. I plotted the data to confirm that the units of these fields are in fact m s-2, i.e. the units of the actual data are correct and it was the metadata that was wrong.
Just to add, the m s-1 d-1 units I had in an older version of the SNAPSI tables probably propagated from the CMIP6 cmor tables, which still have the incorrect units for utendwtem and utendvtem. The DynVarMIP data request in Gerber and Manzini 2016, Table 2 requested m s-2 for these fields.

Global attribute: mip_era should be changed to 'SNAPSI' not 'CMIP6'

I've set mip_era = "SNAPSI" in all files

Variable siconc is not in table 6hrPt, is this meant to be sinconca?

cell_methods attribute erros:
The cell_methods attribute needs to be changed to match the MIP tables for the following variables

As discussed in the CEDA meeting on Oct 19, SNAPSI is happy to accept siconc in lieu of sinconca, and the cell methods should describe what was done/output.

If it becomes possible to provide siconca I'll let you know, but thanks for accepting siconc.
cell_methods in the files reflects what the data actually are, and here's the list of variables for which cell_methods differs from the specification in the SNAPSI tables (version 0.9.4):
6hrPt: mrso, mrsos, rlut, sithick, snd, snw, tas, tos, uas, vas
6hrZ: tntnd, utendepfd, utendogw, utendnd, utendvtem, utendwtem, vtendogw, xgwdparam, ygwdparam


Logged in component

fixes #148
also fixed a small type error i was getting in Profile component

a finley tear!


Add ptr and struct type output + async support (close #40)

This is my first contrib in rust, please have a deep look.

Amazing work! Thanks @zifeo


[Small Enhancement] Make scalar field separator overwritable

I would like to have a custom Hydrator extending ScalarHydrator just to change field separator ('_'), but I dont want to overwrite all method.
It's not very risky to make it extensible.

This is internal API, not supposed to be extensible in first place.

@Ocramius Ok, protected accessors put me doubt

Well, it's indeed a bit of a messy re-use abstract class in the ORM, but you shouldn't really rely on it. What is the use-case?

@Ocramius Handle a backward compatibility with a bundle which create his own scalar array with a custom normalizer behind a $query->getArrayResult().
Dots are used to separate fields in previous versions.
Of course I could re-implement a full custom scalar hydrator, feel free to dismiss

That indeed sounds like a weird misuse :-\
Dismissing then, as per discussion. Thanks for your understanding :)


XMLTV parser fails on broken date

telly release with the issue:

telly-<IP_ADDRESS>.darwin-amd64
Last working telly release (if known):
Operating environment (Docker/Windows/Linux/QNAP, etc.):

OS X
Description of problem:
XML contains:
<programme channel="BTSport2.uk" start="20180904033000 +0000" stop="20180904040000 +0000">
    <title lang="en">Arsenal Classics</title>
    <desc lang="en">Classic Arsenal matches from the football archives, featuring a memorable league clash with Aston Villa (1991) and a League Cup third round win over Manchester United . 3/8</desc>
    <date>1991|2001</date>
    <category lang="en">Sport</category>
    <icon src="https://images.metadata.sky.com/pd-image/b24bc05c-92cd-42b6-be67-45f90c60b521/16-9" />
    <episode-num system="xmltv_ns">.24.</episode-num>
    </programme>

Telly fails with:
INFO[2018-08-30T15:58:01-05:00] telly is preparing to go live (version=<IP_ADDRESS>, branch=dev, revision=f1de7f04430f9f6d35ad7caf55d4d5360a1d681c)
INFO[2018-08-30T15:58:01-05:00] Loading M3U from http://api.vaders.tv/vget?username=REDACTED&password=REDACTED&vod=false&format=ts
INFO[2018-08-30T15:58:04-05:00] Loading XMLTV from http://vaders.tv/p2.xml.gz
INFO[2018-08-30T15:58:05-05:00] File (http://vaders.tv/p2.xml.gz) is gzipp'ed, ungzipping now, this might take a while
ERRO[2018-08-30T15:58:13-05:00] Could not decode xmltv programme              error="the type Date field of date is not a time, value is: 1991|2001"
ERRO[2018-08-30T15:58:13-05:00] error when parsing EPG                        error="the type Date field of date is not a time, value is: 1991|2001"
ERRO[2018-08-30T15:58:13-05:00] error when preparing provider                 error="the type Date field of date is not a time, value is: 1991|2001"
ERRO[2018-08-30T15:58:13-05:00] error when processing provider                error="the type Date field of date is not a time, value is: 1991|2001"
INFO[2018-08-30T15:58:13-05:00] telly is live and on the air!
INFO[2018-08-30T15:58:13-05:00] Broadcasting from http://<IP_ADDRESS>:6077/
INFO[2018-08-30T15:58:13-05:00] EPG URL: http://<IP_ADDRESS>:6077/epg.xml

Contents of telly.config.toml [if you're using a version above 1.1]:

REMEMBER TO DELETE ANY CREDENTIALS IN CONFIG FILES OR COMMAND LINES

Command line used to run telly [if applicable]:

REMEMBER TO DELETE ANY CREDENTIALS IN CONFIG FILES OR COMMAND LINES

Docker run command used to run telly [if applicable]:

REMEMBER TO DELETE ANY CREDENTIALS IN CONFIG FILES OR COMMAND LINES

telly or docker log:

Additional information:

I tried to talk to the support guys at Vader's, it was pointless... They kept telling me to read the pinned post on the app they support... And will not fix the XML file.
I love this feature of auto downloading/ungz.. Any plans in the work to fix this?

Yep


docs:--20200222 modify the spelling mistake of 'electronic'

Related Issue
Follow:#102
Propose changes
modify the spelling mistake of 'electronic' at /docs/faculty/soa/README.md
modify the spelling mistake of 'electronic' at /docs/faculty/soa.
Additional information
NULL.
Checklist
NULL.
Screenshoot
NULL.

There is no need to add reviewers manually.


Implement Copy-Paste and Drag'n'Drop from File Explorer

VSCode Version: Code 1.19.3 (7c4205b5c6e52a53b81c69d2b2dc8a627abaa0ba, 2018-01-25T10:36:34.867Z)
OS Version: Windows_NT x64 10.0.16299

There's already existing #6566, which was closed by the author for some reason.

@Deilan you can drop from the file explorer into the VS Code explorer unless you run as administrator, are you?

@bpasero Oh, that's right. But Copy-Paste doesn't work even without administrator privileges

/duplicate https://github.com/Microsoft/vscode/issues/6566


Exception while invoking method 'tabular_getInfo' Error: Did not check() all arguments during call to 'tabular_getInfo'

I20150116-16:32:36.177(0)? Exception while invoking method 'tabular_getInfo' Error: Did not check() all arguments during call to 'tabular_getInfo'
I20150116-16:32:36.179(0)?     at [object Object]..extend.throwUnlessAllArgumentsHaveBeenChecked (packages/check/match.js:357:1)
I20150116-16:32:36.179(0)?     at Object.Match.failIfArgumentsAreNotAllChecked (packages/check/match.js:112:1)
I20150116-16:32:36.179(0)?     at maybeAuditArgumentChecks (packages/ddp/livedata_server.js:1596:1)
I20150116-16:32:36.179(0)?     at packages/ddp/livedata_server.js:648:1
I20150116-16:32:36.179(0)?     at [object Object]..extend.withValue (packages/meteor/dynamics_nodejs.js:56:1)
I20150116-16:32:36.180(0)?     at packages/ddp/livedata_server.js:647:1
I20150116-16:32:36.180(0)?     at [object Object]..extend.withValue (packages/meteor/dynamics_nodejs.js:56:1)
I20150116-16:32:36.180(0)?     at [object Object]._.extend.protocol_handlers.method (packages/ddp/livedata_server.js:646:1)
I20150116-16:32:36.180(0)?     at packages/ddp/livedata_server.js:546:1
Hi there,
I am following the example, butI am getting this error, is there any way to fix?
By the way, how can I pass dynamic column array?
TabularTables = {};
TabularTables.Users = new Tabular.Table({
	 name: "Users",
	collection: this.collection,
	columns: function (){
			var result= [];
			_.map(this.fields,function(field){

				var item = {data:field.name,title:field.name};
				result.push(item);
			});

			return result;
		}
});

It seems doesn't work.

1.0 is released and should fix this. Please see updated README for all features and options.


Update kyc icon

Update KYC icon in collection view to use new icon from the design system:

Love it!


Pattern synonyms cause exceptions, breaking autocompletion & type inspection

I have a module with PatternSynonyms enabled which exports, among other things, pattern AlignThis. This breaks haskell-ghc-mod:
h$HaskellException_msg: "fromParseResult: Parse failed at [<unknown>.hs] (4:11): Parse error: AlignThis"__proto__: h$HaskellExceptionmodule.exports.BufferInfo.parse @ /Users/rob/.atom/packages/haskell-ghc-mod/lib/completion-backend/buffer-info.coffee:63

As an effect of this, both autocompletion and type inspection are broken in this project.

Terribly sorry about long silence, this got completely lost in the pipes.
Type inspection shouldn't be affected at all, provided {-# LANGUAGE PatternSynonyms #-} pragma is present (ghc-mod doesn't do well with cabal-specified pragmas, regrettably)
I will investigate what could be done about autocompletion.

Should be fixed by v1.17.1. Sorry it took so long.

🙇 Thank you very much!
And no need to apologize. I’m very grateful for the time and effort you put into the atom-haskell suite!


Compatibility with mongodb php7 extension

mongodb has a new php7 extension. This is a minimal api and a userland library (https://github.com/mongodb/mongo-php-library) is provided to have all classes available
But this will break some typehints in our code, like https://github.com/bernardphp/bernard/blob/master/src/Driver/MongoDBDriver.php#L23
mongodb tests are currently skipped on php7

We probably have to create two separate drivers then.

Yes indeed, that will be the best solution. Let's first do the split of the current drivers and then see what we can do for the mongodb driver

Moving to bernardphp/drivers#11


Remove known/verified bot support

Pull request checklist:

[x] CHANGELOG.md was updated, if applicable
[x] Documentation in docs/ or install-docs/ was updated, if applicable
[x] I have tested all changes

As established in https://github.com/pajbot/pajbot/discussions/2339, there is no reason for the known/verified bot status to exist in pajbot. This PR removes it, but leaves the base code should there be any different "status'" in future.

Seems to work just fine.


WeakMultiLabels or MajorityVoter function not working as expected

Describe the bug
WeakMultiLabels("test_weak_label") is apparently reading the dataset from Argilla running on my machine, but MajorityVoter function is not getting any dataset.  As a result, the classifier program is not getting formed.
To Reproduce
Steps to reproduce the behavior:

I used the dataset as in attached excel-file: weak_test_classifier.
Create a json-load file out of the data in the excel-file using: create_load_file.py.
Upload the json-load file into a argilla dataset, named: test_weak_label, using: create_rubrix_dataset_new.py.
Define the rules as given in the rules.jpg screenshot.
Run the classifier-program to create a classification-model using: TestClassifier.py.
The output of step-4 is as follows:

(10, 6, 3)
weak_labels type:  <class 'argilla.labeling.text_classification.weak_labels.WeakMultiLabels'> label_model type:  <class 'argilla.labeling.text_classification.label_models.MajorityVoter'>
Empty DataFrame
Columns: []
Index: []
Traceback (most recent call last):
  File "TestClassifier.py", line 50, in <module>
    train_df["label"] = train_df.prediction.map(multi_label_binarizer)
  File "C:\Anaconda3\envs\elasticsearch\lib\site-packages\pandas\core\generic.py", line 5907, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'prediction'

Expected behavior
I was expecting to develop a classifier model, and output should have been the metrics of the model, as described in your sample ResearchTopics classifier code.
Screenshots
Program output has been already shared.  Attached please find the data-file and 3 python scripts.
Environment (please complete the following information):

OS [e.g. iOS]: Windows
Browser [e.g. chrome, safari]: Chrome
Argilla Version [e.g. 1.0.0]: 1.0.1
ElasticSearch Version [e.g. 7.10.2]: 8.4.3
Docker Image (optional) [e.g. argilla:v1.0.0]: not applicable

Additional context
Please let me know where I'm going wrong or if any other information is required.
weak_test_classifier.xlsx
files.zip

Hi @BiswajitGhoshal, happy new year and sorry for the late response. The holidays were busy. I will take a look this week.

Hi @BiswajitGhoshal, your error was caused by the MajorityVoter.predict() default parameters. However, the code execution is not working correctly, because the behavior is different.
Applies the label model.

Args:
    include_annotated_records: Whether to include annotated records.
    include_abstentions: Whether to include records in the output, for which the label model abstained.
    prediction_agent: String used for the prediction_agent in the returned records. tie_break_policy: Policy to break ties (IGNORED FOR MULTI-LABEL!). You can choose among two policies:

- `abstain`: Do not provide any prediction
- `random`: randomly choose among tied option using deterministic hash
        The last policy can introduce quite a bit of noise, especially when the tie is among many labels, as is the case when all the labeling functions (rules) abstained.

Returns:
    A dataset of records that include the predictions of the label model.

Hi @davidberenstein1957 - Thank you so much for the help with the arguments.  With that I have been able to run the MajorityVote classifier.


.NET Standard support

Expected Behavior :
Currently, we can use last Xamarin.Forms pre release version on .NET Standard, actually is it possible to create pre release CircleImagePlugin version for that .NET Standard?

You can already use it in a .NET Standard library by adding a line of code into the csproj: http://motzcod.es/post/148657853472/installing-a-pcl-into-netstandard-libraries
When forms has it's main version out I will swap over.


Elements are not found with space

Expected behaviour
Elements should get with space
Actual behavior
Not getting the elements with space
Steps to reproduce
Run this script
(async () => {
    try {
        await openBrowser();
        await goto('https://github.com/getgauge/');
        await click('Sign in')
    } catch (e) {
        console.error(e);
    } finally {
        await closeBrowser();
    }
})();

Not able to click on sign in. In html it is written as sign in

This issue has been verified and found fix with the version f0fa3cb


Glavin Wiechert's Assignment Solution

Note that I have my own issues at https://github.com/Glavin001/CSCI3431-MMMExample/issues?q=

Peace out. :v:


Svelte support

Currently Laravel Precognition does not support Svelte or Svelte w/ Inertia. Nowadays, Inertia currently supports Svelte, so this is something I think should be added.

Hi there,
We don't have any plans right now to add a Svelte version.


visual scripting shift + A bug!

@fire
Shift+A shows search box at every screen weather its 2d, 3d or asset library.
When i select a specific function from the search box it hang and crashes the software.
Sequencing drop works fine but it shows some non select-able option like float in physics_process.

Will look into it.

Pushed a fix for part 3. (part 2 is associated with part 1).

Pushed to master.

Fixed by #20450 and #20452.


[SPARK-27580][HOT-FIX] Fix wrong import order in FileScan.scala

What changes were proposed in this pull request?
========================================================================
Running Scala style checks
========================================================================
[info] Checking Scala style using SBT with these profiles:  -Phadoop-2.7 -Pkubernetes -Phive-thriftserver -Pkinesis-asl -Pyarn -Pspark-ganglia-lgpl -Phive -Pmesos
Scalastyle checks failed at following occurrences:
[error] /home/jenkins/workspace/SparkPullRequestBuilder/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/FileScan.scala:29:0: org.apache.spark.sql.sources.Filter is in wrong order relative to org.apache.spark.sql.sources.v2.reader..
[error] Total time: 17 s, completed Apr 29, 2019 3:09:43 AM

https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/104987/console
How was this patch tested?
manual tests:
dev/scalastyle

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/testing-k8s-prb-make-spark-distribution-unified/10290/
Test PASSed.

Test build #104988 has started for PR 24487 at commit f86334a.

cc @loud-fan @gengliangwang

stylecheck passed, I'm merging it, thanks!

Test build #104988 has finished for PR 24487 at commit f86334a.

This patch passes all tests.
This patch merges cleanly.
This patch adds no public classes.

Merged build finished. Test PASSed.

Test PASSed.
Refer to this link for build results (access rights to CI server needed):
https://amplab.cs.berkeley.edu/jenkins//job/SparkPullRequestBuilder/104988/
Test PASSed.

@wangyum Thanks for the fix!


Add prepare script

Add prepare script to help prevent publishing local garbage.

prepare: Run both BEFORE the package is packed and published, on local npm install without any arguments, and when installing git dependencies

I don't think this is what we want here. Did you mean to use prepublishOnly?

Hm, prepare gets the job done, but prepublishOnly is more specific 🤔

The part that seems less than ideal to me is testing/linting upon install. Generally when I run yarn I haven't done anything yet, so... I have no reason to lint/test. But yeah, it's not the end of the world.


Simplify adding mock processes

When writing tests with mock processes I have regularly the problem that I forgot to add such processes to simulation via sim.add_sync_process. This cause weird issues and burns time to find the bug. Because of that I would like to propose a solution which will be adding such processes automatically to simulation.
It is done using:

AutoRegisterMockMetaclass which collects all mock processes in a list
def_method_mock which marks functions as mock process
TestCaseWithSimulator which adds automaticaly the processes from list to simulation

Sadly there are some cons of such solution:

Typing is not obvious (I haven't checked yet if there are some materials in internet about typing with metaclasses)
This works only if the method mock is defined on the class level (it was the reason for refactor of test/structs_common/test_exception.py)

But when the mocks are defined on the class level then using this solution is strightforward (see test/transactions/test_transaction_lib.py).

Metaclasses generally smell, as they don't compose well. Can't this be handled better by __init_subclass__?

No. Because I want to have consistency between def_method and def_method_mock. In normal Elaboratables we allow to have function names all without meaning (e.g. _):
@def_method(m, method1)
def _(arg):
   ...
@def_method(m, method2)
def _(arg):
   ...

But if we try to do the same with method mocks implemented by __init_subclass__ or class decorators, then each method mock function have to have unique name (otherwise it will be overwritten). Using metaclasses we allow to overwriting the functions because they are captured in the moment of the function creation and not after creation of all functions.

No. Because I want to have consistency between def_method and def_method_mock. In normal Elaboratables we allow to have function names without meaning (e.g. _):

But that's because in def_method, the method is already named. In mocks, this is not the case. Also, we don't have consistency here already, as def_method can't be used at class level.
I generally dislike metaclass solutions, as they tend to obfuscate things and can make refactoring and redesigns harder. But things making people waste less time are great, so if this can't be done any other way, then I'll live with this.
Is it sensible to apply the metaclass to TestCaseWithSimulator directly, instead of its subclasses?  You can forget applying the metaclass as easily as adding mock processes, also exposing metaclass attribute to end users is bad style.

Is it sensible to apply the metaclass to TestCaseWithSimulator directly, instead of its subclasses? You can forget applying the metaclass as easily as adding mock processes, also exposing metaclass attribute to end users is bad style.

Yes. That is my goal. I wanted to get first the acceptance for the idea, before I will do the refactor of all the tests which use def_method_mock.

TODO: Refactor old tests to use new solution.

I have thought one more time about the idea and I decided to drop metaclasses implementation and use instead of that introspection. This caused that mocks processes can not have _ name, but it simplifies a lot and as @tilk stated:

But that's because in def_method, the method is already named. In mocks, this is not the case.

I added also support for auto adding mocks which are defined in function scope. The only situation which left to be handled manually is usage of generators (e.g. test/scheduler/test_scheduler.py) but this is fine for me.
While removing manual mock addition to simulator I have found a lot of tests which are inconsistent with our current way of writing tests, so I did refactor where it was needed and justified.

You changed local mocks to class-level in some tests. Was it necessary? Can the add_local_mocks function you wrote handle this?

You changed local mocks to class-level in some tests. Was it necessary? Can the add_local_mocks function you wrote handle this?

I have first changed that and after that I implemented the add_local_mocks. I have thought about reverting the changes to these tests, but I have decided to leave them as is, because this makes (in my opinion) tests more consistent as class methods are now the prefered method (or I am wrong?).

because this makes (in my opinion) tests more consistent as class methods are now the prefered method (or I am wrong?).

I'm still conflicted about this, but this seems to be just a matter of style, and I agree that consistency is valuable.

I'm also not sure about class level tests, but I think it makes sense to do that - If we have multiple tests in class, class-level processes could be used, test_ methods could override self. variables that would control processes or if completely different behaviour for some process is needed it could be declared locally for each test_ and rest of mocks automatically shared.


Fix casting empty sets to standard library enum types

When making up path_ids for empty sets, we need to keep track of
whether the actual type came from a standard library module, so that
we can propertly figure out whether it is in edgedbstd or edgedbpub.
The issue where this first came up was when casting the result of
json_set: an optional wrapper is being inserted for the
empty_treatment argument in this cast case. (That seems like its own
performance bug, too.)
Fixes #4530.

I think I actually do not like this solution but let's ship it in 2.4 and then clean it up


Support dots in bucket names

This lib was parsing urls like https://www.mysite.com.s3.amazonaws.com/path incorrectly, returning only www as the bucket name. Here is a fix.
This PR fixes (https://github.com/mapbox/mapbox-tile-copy/issues/53).

One problem that will arise here is that these urls can also include regions. For the worst example, a bucket in cn-north-1 would look like:
https://my-bucket.s3.cn-north-1.amazonaws.com.cn/my/key


[DOC] Improve High Availability Guide

Why are the changes needed?

How was this patch tested?

[ ] Add some test cases that check the changes thoroughly including negative and positive cases if possible

[x] Add screenshots for manual tests if appropriate

[x] Run test locally before make a pull request

cc @pan3793

Codecov Report

Merging #1527 (54c1cd9) into master (73ac1b6) will decrease coverage by 0.11%.
The diff coverage is 100.00%.

:exclamation: Current head 54c1cd9 differs from pull request most recent head 0324433. Consider uploading reports for the commit 0324433 to get more accurate results

@@             Coverage Diff              @@
##             master    #1527      +/-   ##
============================================
- Coverage     59.38%   59.26%   -0.12%
  Complexity      172      172
============================================
  Files           237      241       +4
  Lines         12168    12204      +36
  Branches       1492     1496       +4
============================================
+ Hits           7226     7233       +7
- Misses         4331     4359      +28
- Partials        611      612       +1

Impacted Files
Coverage Δ

...la/org/apache/kyuubi/ha/HighAvailabilityConf.scala
98.85% <100.00%> (ø)

...cala/org/apache/kyuubi/session/SessionHandle.scala
46.42% <0.00%> (-34.83%)
:arrow_down:

.../org/apache/kyuubi/operation/OperationHandle.scala
67.44% <0.00%> (-29.23%)
:arrow_down:

...ache/kyuubi/engine/spark/SparkProcessBuilder.scala
84.76% <0.00%> (-2.86%)
:arrow_down:

...ache/kyuubi/operation/KyuubiOperationManager.scala
82.50% <0.00%> (-1.72%)
:arrow_down:

...org/apache/kyuubi/operation/ExecuteStatement.scala
87.35% <0.00%> (-0.56%)
:arrow_down:

...apache/kyuubi/server/api/v1/SessionsResource.scala
78.78% <0.00%> (-0.35%)
:arrow_down:

...main/scala/org/apache/kyuubi/session/package.scala
100.00% <0.00%> (ø)

...a/org/apache/kyuubi/metrics/MetricsConstants.scala
100.00% <0.00%> (ø)

...rg/apache/kyuubi/metrics/JsonReporterService.scala
86.66% <0.00%> (ø)

... and 17 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 73ac1b6...0324433. Read the comment docs.

thanks, merged to master


⚒ Add invisible space in top and bottom of the page for visibility.

After some testing, this improvement don't have need to be done.


pull request for e2e test at 01/07/2017 21:26:10

:white_check_mark: Validation status: passed
For more details, please refer to the build report.
Note: If you changed an existing file name or deleted a file, broken links in other files to the deleted or renamed file are listed only in the full build report.


[Admin] Failure to save shop logo

Matt: When I save, I don't get any notification. I also see this console error.
VM6:1 POST https://dshopapi.ogn.app/shops/test-shop-1/save-files 401
app.9f163fad.js:1 Error
    at app.9f163fad.js:1

Amy: Logo doesn't save/no notification that changes have been made. Favicon/SM/other detail fields worked.

@matthewliu I was not able to reproduce. Could you share the file you tried to save as logo?
Amy: could you please do the same?

@franckc i uploaded this image.
https://dshopapi.ogn.app/test-shop-1/Screen_Shot_2020-07-07_at_4.39.18_PM.png

Steps to reproduce:

Add a Admin (not superadmin) user to the shop
Login as the new admin user
Add something in "About your store" field and then click "Save".

Basically, this is a permission issue, the admin cannot update site's about file (only superadmin can). I'm not sure if we should let that happen. What do you think? @nick @franckc

Have pushed this changeset to a branch. This should allow admin to update about file. Let me know if that behaviour should be changed.

I think it does make sense. Admin should have full-control over a shop settings and look & feel.
Marking this as closed.


Error evaluating yaml packages

I know package.yaml files are discouraged, but... our studio still has a bunch of them, and I haven't had a chance to go through and batch convert everything to .py yet (particularly since I don't want to lose comments, etc).
Anyway - if a package.yaml has code like this:
commands:
    rr = 'test'
    env.RR = '{rr}'

...then it will currently error.  Looks like you've already got some code to handle this situation for .py files (you may recognize the example - I pulled it from process_python_objects() in serialise.py), but no such consideration for yaml files.
For our internal use, I set the default for eval_as_function to False, in sourcecode.SourceCode.__init__().  Not sure if this is the best way to handle this, or what other impacts it may have, though, so I didn't bother submitting it as a pull request. Seems to work for us for now, though...

Hey Paul,
Ah yes I see. I'll test that and patch up whatever breaks, will let you
know once merged.
Note though that the @early/@late stuff won't work in yaml files I'm pretty
sure. I need to formalize the fact that yaml is basically deprecated. But
yes, they should still work to the extent that they already were.
Cheers
A
On Tue, Mar 7, 2017 at 1:43 PM, Paul Molodowitch<EMAIL_ADDRESS>wrote:

I know package.yaml files are discouraged, but... our studio still has a
bunch of them, and I haven't had a chance to go through and batch convert
everything to .py yet (particularly since I don't want to lose comments,
etc).
Anyway - if a package.yaml has code like this:
commands:
rr = 'test'
env.RR = '{rr}'
...then it will currently error. Looks like you've already got some code
to handle this situation for .py files (you may recognize the example - I
pulled it from process_python_objects() in serialise.py), but no such
consideration for yaml files.
For our internal use, I set the default for eval_as_function to False, in
sourcecode.SourceCode.init(). Not sure if this is the best way to
handle this, or what other impacts it may have, though, so I didn't bother
submitting it as a pull request. Seems to work for us for now, though...
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/nerdvegas/rez/issues/393, or mute the thread
https://github.com/notifications/unsubscribe-auth/ABjqSvx7OHVb_qsQLil3AcqGpX906f3aks5rjMRfgaJpZM4MU-NL
.

Yeah, there's no point adding @early / @late support to yaml files. Good
way to encourage people to migrate to .py, too, if they haven't already...
it's a nice new feature.
On Mon, Mar 6, 2017 at 8:47 PM allan johns<EMAIL_ADDRESS>wrote:

Hey Paul,
Ah yes I see. I'll test that and patch up whatever breaks, will let you
know once merged.
Note though that the @early/@late stuff won't work in yaml files I'm pretty
sure. I need to formalize the fact that yaml is basically deprecated. But
yes, they should still work to the extent that they already were.
Cheers
A
On Tue, Mar 7, 2017 at 1:43 PM, Paul Molodowitch<EMAIL_ADDRESS>
wrote:

I know package.yaml files are discouraged, but... our studio still has a
bunch of them, and I haven't had a chance to go through and batch convert
everything to .py yet (particularly since I don't want to lose comments,
etc).
Anyway - if a package.yaml has code like this:
commands:
rr = 'test'
env.RR = '{rr}'
...then it will currently error. Looks like you've already got some code
to handle this situation for .py files (you may recognize the example - I
pulled it from process_python_objects() in serialise.py), but no such
consideration for yaml files.
For our internal use, I set the default for eval_as_function to False, in
sourcecode.SourceCode.init(). Not sure if this is the best way to
handle this, or what other impacts it may have, though, so I didn't
bother
submitting it as a pull request. Seems to work for us for now, though...
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/nerdvegas/rez/issues/393, or mute the thread
<
https://github.com/notifications/unsubscribe-auth/ABjqSvx7OHVb_qsQLil3AcqGpX906f3aks5rjMRfgaJpZM4MU-NL
.

—
You are receiving this because you authored the thread.
Reply to this email directly, view it on GitHub
https://github.com/nerdvegas/rez/issues/393#issuecomment-284620776, or mute
the thread
https://github.com/notifications/unsubscribe-auth/AAEYeHIILSlpikxQbj7BmX80DUA4LxV1ks5rjOFPgaJpZM4MU-NL
.

I'll close this one. YAML package definitions are used anymore...


docs: fix collaborators keyword definition

Looks just a typo. 👀
Please close this PR if it is correct and/or intentional.

hey @kachick, i am so sorry about this. I really thought I merged your PR.
My bad. I completely forgot with my chores. Can you please reopen it again, I would love to accept your contribution to my GH action

No problem! I have reopened 👍

Thank you!