The fact that this foundation has a bunch of paid, closed, certification courses makes Ciro Santilli not respect them at all. They should be making open access content instead!
Instructions at:
Ubuntu 22.10 setup with tiny dummy manually generated ImageNet and run on ONNX:
sudo apt install pybind11-dev
git clone https://github.com/mlcommons/inference
cd inference
git checkout v2.1
virtualenv -p python3 .venv
. .venv/bin/activate
pip install numpy==1.24.2 pycocotools==2.0.6 onnxruntime==1.14.1 opencv-python==4.7.0.72 torch==1.13.1
cd loadgen
CFLAGS="-std=c++14" python setup.py develop
cd -
cd vision/classification_and_detection
python setup.py develop
wget -q https://zenodo.org/record/3157894/files/mobilenet_v1_1.0_224.onnx
export MODEL_DIR="$(pwd)"
export EXTRA_OPS='--time 10 --max-latency 0.2'
tools/make_fake_imagenet.sh
DATA_DIR="$(pwd)/fake_imagenet" ./run_local.sh onnxruntime mobilenet cpu --accuracyLast line of output on P51, which appears to contain the benchmark resultswhere presumably
TestScenario.SingleStream qps=58.85, mean=0.0138, time=0.136, acc=62.500%, queries=8, tiles=50.0:0.0129,80.0:0.0137,90.0:0.0155,95.0:0.0171,99.0:0.0184,99.9:0.0187qps means queries per second, and is the main results we are interested in, the more the better.Running:produces a tiny ImageNet subset with 8 images under
tools/make_fake_imagenet.shfake_imagenet/.fake_imagenet/val_map.txt contains:val/800px-Porsche_991_silver_IAA.jpg 817
val/512px-Cacatua_moluccensis_-Cincinnati_Zoo-8a.jpg 89
val/800px-Sardinian_Warbler.jpg 13
val/800px-7weeks_old.JPG 207
val/800px-20180630_Tesla_Model_S_70D_2015_midnight_blue_left_front.jpg 817
val/800px-Welsh_Springer_Spaniel.jpg 156
val/800px-Jammlich_crop.jpg 233
val/782px-Pumiforme.JPG 285TODO prepare and test on the actual ImageNet validation set, README says:
Prepare the imagenet dataset to come.
Since that one is undocumented, let's try the COCO dataset instead, which uses COCO 2017 and is also a bit smaller. Note that his is not part of MLperf anymore since v2.1, only ImageNet and open images are used. But still:
wget https://zenodo.org/record/4735652/files/ssd_mobilenet_v1_coco_2018_01_28.onnx
DATA_DIR_BASE=/mnt/data/coco
export DATA_DIR="${DATADIR_BASE}/val2017-300"
mkdir -p "$DATA_DIR_BASE"
cd "$DATA_DIR_BASE"
wget http://images.cocodataset.org/zips/val2017.zip
wget http://images.cocodataset.org/annotations/annotations_trainval2017.zip
unzip val2017.zip
unzip annotations_trainval2017.zip
mv annotations val2017
cd -
cd "$(git-toplevel)"
python tools/upscale_coco/upscale_coco.py --inputs "$DATA_DIR_BASE" --outputs "$DATA_DIR" --size 300 300 --format png
cd -Now:fails immediately with:The more plausible looking:first takes a while to preprocess something most likely, which it does only one, and then fails:
./run_local.sh onnxruntime mobilenet cpu --accuracyNo such file or directory: '/path/to/coco/val2017-300/val_map.txt./run_local.sh onnxruntime mobilenet cpu --accuracy --dataset coco-300Traceback (most recent call last):
File "/home/ciro/git/inference/vision/classification_and_detection/python/main.py", line 596, in <module>
main()
File "/home/ciro/git/inference/vision/classification_and_detection/python/main.py", line 468, in main
ds = wanted_dataset(data_path=args.dataset_path,
File "/home/ciro/git/inference/vision/classification_and_detection/python/coco.py", line 115, in __init__
self.label_list = np.array(self.label_list)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 2 dimensions. The detected shape was (5000, 2) + inhomogeneous part.TODO!
As of 2020, no one knows how to build the major desktop distros fully from source into the ISO, and especially so in a reproducible build way. Everything is done in build servers somewhere with complicated layers of prebuilds. It's crap.
merlijn.sebrechts.be/blog/2020-08-02-why-one-snap-store/ has some very good comments on how
snap is more closed than Flatpak.The basis for Linux Kernel Module Cheat.
On Ubuntu 23.10, a crash led to the creation of:After that simply running apport-cli as: led to the creation of: bugs.launchpad.net/ubuntu/+source/gnome-shell/+bug/2049368 a bug on the
/var/crash/_usr_bin_gnome-shell.1000.crashapport-cli gnome-shellgnome-shell package.Their crash system does not have an amazing user interface.
Tested on Ubuntu 21.10.
After something crashes, look under
/var/crash for a crash file, which helps to determine which package to report under on Launchpad.E.g. a file
/var/crash/_usr_sbin_gdm3.0.crash makes you want to file the bug under gdm at: bugs.launchpad.net/ubuntu/+source/gdm/+filebugThen, while reporting the bug, you want to give the developpers access to that Ubuntu's crash report system has already uploaded the
.crash file. But you can't publicly upload it because it contains memory dumps and could contain secret information. The way to do it is to look at the ID under:sudo cat /var/crash/_usr_sbin_gdm3.0.uploaded.crash for you, so you just have to confirm it and give the ID on the ticket.You can view a list of all your uploaded errors at:and each of those contain a link to:which you yourself cannot see.
xdg-open https://errors.ubuntu.com/user/$(sudo cat /var/lib/whoopsie/whoopsie-id)https://errors.ubuntu.com/oops/<.uloaded error id>askubuntu.com/questions/434431/how-can-i-read-a-crash-file-from-var-crash asks how to read the
.crash files.Running:splits it up into a few files, but does not make any major improvements.
sudo apport-unpack /var/crash/_usr_sbin_gdm3.0.crash /tmp/appapport-retracesudo apt install apport-retrace
sudo chmod 666 /var/crash/_usr_sbin_gdm3.0.crash
apport-retrace -g /var/crash/_usr_sbin_gdm3.0.crashTried:but then
echo "deb http://ddebs.ubuntu.com $(lsb_release -cs) main restricted universe multiverse" | sudo tee -a /etc/apt/sources.list.d/ddebs.list
echo -e "deb http://ddebs.ubuntu.com $(lsb_release -cs)-updates main restricted universe multiverse\ndeb http://ddebs.ubuntu.com $(lsb_release -cs)-proposed main restricted universe multiverse" | sudo tee -a /etc/apt/sources.list.d/ddebs.list
sudo apt install ubuntu-dbgsym-keyringsudo apt update fails with:E: The repository 'http://ddebs.ubuntu.com impish-security Release' does not have a Release file. Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
Intro to OurBigBook
. Source. We have two killer features:
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- a Q&A website like Stack Overflow, where multiple people can give their views on a given topic, and the best ones are sorted by upvote. Except you don't need to wait for someone to ask first, and any topic goes, no matter how narrow or broad
This feature makes it possible for readers to find better explanations of any topic created by other writers. And it allows writers to create an explanation in a place that readers might actually find it.
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Figure 3. Visual Studio Code extension installation.
Figure 4. Visual Studio Code extension tree navigation.
Figure 5. Web editor. You can also edit articles on the Web editor without installing anything locally.Video 3. Edit locally and publish demo. Source. This shows editing OurBigBook Markup and publishing it using the Visual Studio Code extension.Video 4. OurBigBook Visual Studio Code extension editing and navigation demo. Source. 
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Further documentation can be found at: docs.ourbigbook.com
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