kb | Custom firmware for a handwired bluetooth planck keyboard

I want to install packages from poetry.lock file; using poetry install.

However, the majority of packages throw the exact same error, indicating a shared fundamental problem.

What is causing this? What is the standard fix?

Specification:

• Windows 10,
• Visual Studio Code,
• Python 3.8.10 & Poetry 1.1.11,
• Ubuntu Bash.

Terminal:

• rm poetry.lock
• poetry update
• poetry install

I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:

I am new to angular and was following the documentation to build a basic app.

Node - v14.7.3
npm - 7.22.0
Angular CLI: 12.2.4
OS: win32 x64
@angular-devkit/architect 0.1202.4
@angular-devkit/build-angular 12.2.4
@angular-devkit/core 12.2.4
@angular-devkit/schematics 12.2.4
@schematics/angular 12.2.4
rxjs 6.6.7
typescript 4.3.5

So far all I have done is

npm install @angular/cli

followed by ng new firstApp

and ng serve

Following is the error that I am receiving,

I would like to implement forward-chaining reasoning in Prolog. I made up a simple KB of facts and some rules, from which I should be able to get the fact green(fritz). I tried to implement it but somehow, when member fails, it stops going on.

I have a fresh project but was looking to test scheduled functions. Am I missing anything?

I am trying to install Jenkins on my Ubuntu EC2 instance and I performed the following steps to install but couldn't install it.

$sudo apt update $sudo apt install openjdk-8-jdk $wget -q -O - https://pkg.jenkins.io/debian-stable/jenkins.io.key | sudo apt-key add - $sudo sh -c 'echo deb http://pkg.jenkins.io/debian-stable binary/ > /etc/apt/sources.list.d/jenkins.list' $sudo apt update <--------- (Here I am getting below error)

root@ip-172-31-44-187:~# sudo apt update Ign:1 https://pkg.jenkins.io/debian-stable binary/ InRelease Err:2 https://pkg.jenkins.io/debian-stable binary/ Release Certificate verification failed: The certificate is NOT trusted. The certificate chain uses expired certificate. Could not handshake: Error in the certificate verification. [IP: 151.101.154.133 443] Hit:3 http://ap-south-1.ec2.archive.ubuntu.com/ubuntu focal InRelease Get:4 http://ap-south-1.ec2.archive.ubuntu.com/ubuntu focal-updates InRelease [114 kB] Get:5 http://security.ubuntu.com/ubuntu focal-security InRelease [114 kB] Get:6 http://ap-south-1.ec2.archive.ubuntu.com/ubuntu focal-backports InRelease [101 kB] Reading package lists... Done E: The repository 'http://pkg.jenkins.io/debian-stable binary/ Release' does not have a Release file. N: Updating from such a repository can't be done securely, and is therefore disabled by default. N: See apt-secure(8) manpage for repository creation and user configuration details.

I've installed Windows 10 21H2 on both my desktop (AMD 5950X system with RTX3080) and my laptop (Dell XPS 9560 with i7-7700HQ and GTX1050) following the instructions on https://docs.nvidia.com/cuda/wsl-user-guide/index.html:

1. Install CUDA-capable driver in Windows
2. Update WSL2 kernel in PowerShell: wsl --update
3. Install CUDA toolkit in Ubuntu 20.04 in WSL2 (Note that you don't install a CUDA driver in WSL2, the instructions explicitly tell that the CUDA driver should not be installed.):

The code I work on has a substantial amount of floating point arithmetic in it. We have test cases that record the output for given inputs and verify that we don't change the results too much. I had it suggested that I enable -march native to improve performance. However, with that enabled we get test failures because the results have changed. Do the instructions that will be used because of access to more modern hardware enabled by -march native reduce the amount of floating point error? Increase the amount of floating point error? Or a bit of both? Fused multiply add should reduce the amount of floating point error but is that typical of instructions added over time? Or have some instructions been added that while more efficient are less accurate?

The platform I am targeting is x86_64 Linux. The processor information according to /proc/cpuinfo is:

My two submissions for a programming problem differ in just one expression (where anchors is a nonempty list and (getIntegrals n) is a state monad):

Submission 1. replicateM (length anchors - 1) (getIntegrals n)

Submission 2. sequenceA $ const (getIntegrals n) <$> tail anchors

The two expressions' equivalence should be easy to see at compile time itself, I guess. And yet, comparatively the sequenceA one is slower, and more importantly, takes up >10x memory:

^{(with "Memory limit exceeded on test 4" error for the second entry, so it might be even worse).}

Why is it so?

It is becoming quite hard to predict which optimizations are automatic and which are not!

EDIT: As suggested, pasting Submission 1 code below. In this interactive problem, the 'server' has a hidden tree of size n. Our code's job is to find out that tree, with minimal number of queries of the form ? k. Loosely speaking, the server's response to ? k is the row corresponding to node k in the adjacency distance matrix of the tree. Our choices of k are: initially 1, and then a bunch of nodes obtained from getAnchors.