sudo apt-get random-tool

Traceback (most recent call last):

Aborting because there's a fork in the spoon compartment on line 43 in main

Error this script only works on Python 2.7 and maybe 4.1 on line 59 in main

Missing symbols when trying to decipher Sumerian recipe for steamed vegetables on line 67 in main

Cannot open shared object: Your OS is a bully and is hiding my files on line 98 in main

Are you sure all directories matching ^(/)?([^/\0]+(/)?)+$ are in your $PATH on line 268 in main

Your computer is kind of vibrating in an annoying way on line 332 in main

Failing because I'm feeling insecure please hold me on line 587 in main

I'm feeling confused about my sentience when running TensorFlow models on line 682 in main

FUCK

HAS ANYONE EVER MANAGED TO JUST FUCKING INSTALL A PYTHON BASED APPLICATION WITHOUT DEBUGGING RANDOM COMPUTER STATE SHIT AND DEPENDENCIES FOR THREE HOURS?

Very specific and annoying situation here:

- Working on a machine learning project with other people
- I'm on Linux, they use Windows
- We code in python
- We generally use vscode for development, and its python extension

I implement some basic neural networks with tensorflow, and add a bunch of logging for it. I test it on my machine and it works fine.
But, my group mates report that "after a few seconds the entire client hangs".
Apparently it only happens on Windows?
We start debugging the hell out of the code I implemented, added 20 log messages and sat there for a solid hour.

Until I make one very odd realization: the issue doesn't happen when I run the script in my terminal, instead of vscode with the debugger. So I try different debug settings, using an external terminal instead of vscode's built in debug console seems to fix it too.
And I make another observation: In the debug console, some messages don't seem to appear at all, while the external terminal shows them just fine.

So, turns out, that printing an epsilon character: “ε” (U+03B5), causes the entire thing to hang up.

It's the year 2020 and somehow we still can't do unicode.
I'm so done, what on earth.

Arrived today!
I'm using C++ for machine learning purposes using TensorFlow and OpenCV (rip Python, you are too slow 😭)

What are you using C++ for? 😁

Frustrated, tired and a bit lost.

I'm a "Senior PHP Backend Dev", which includes not the greatest tech stack nor the best job title, but it pays fine, and the company is awesome to work for.

I suck at writing features, but I'm great at bitching, and I easily put complex abstract concepts into usable models. So I'm also QA, tester, tech lead, database architect, whatever.

That makes writing PHP less annoying, because I create the rules, and whip devs around when they forget a return type definition or forget to handle an edge case. But I don't write a lot of code anymore, I mostly read (bad) code.

Lately I REALLY feel like doing something else... problem is that I know JS/ES6, but really dislike React/Vue and the whole crappy modern frontend toolchainchootrain of babelifyingwebpackingyarnballs. I know Python/Tensorflow/etc, but don't feel like I want to go into data science or AI. And then I'm awesome at the shit no one uses, like Haskell, Go and Rust (and worse).

I got a job offer which combines a very interesting PHP codebase with a Java infrastructure, where I could learn a lot... and I'm kind of tempted.

Problem is, everyone always shits on Java. I always made a bit of fun of Java myself. Don't even know exactly why, probably some really cruel instinct which causes kids to bully the least popular kid.

I know the basics, I've written the hello world, and a small backend app for a personal project. I know how strict and verbose it can be. I love the strictness in Haskell and Rust.... but those are both also quite terse.

Should I become a Java dev? I'm not talking about Android SDK, but an insane enterprise codebase at a life sciences corporation.

To the pro Java devs: What are the best and worst things about your job, about the weekly processes, about the toolchains? Have you ever considered other languages? Do you unconditionally love and believe in Java, or do you believe Swift, Kotlin, Scala or whatever will eventually make it completely obsolete?

Will Java hasten my decline into the cynical neckbeard I was always destined to be?

There are a lot more fun langauges, but looking at realistic demand and career value...

error message of the day: "InvalidArgumentError: Expected dimension in the range [0, 0) but got 0"

......well, thanks google.

I work in a contract position and reviewed the code of a senior engineer recently. Regretfully I can't provide context to preserve anonymity.

He wrote awful JavaScript;

- handled a single DOM element with 2 different frontend libraries
- used the logical operator && to 'chain' two methods (it didn't work) instead of returning a boolean value,
- broke everything down into minute detail (a comment box had 7 components!),
- API calls were made for every component update instead of maintaining local component state where it made sense, which meant UI updates were slow,
- animated EVERYTHING, which made my Firefox on Xubuntu i7 64bit with 16GB RAM beg for mercy.

I had a rough couple of months with interviews, with 2nd stage technical interviewers throwing impossible tasks at me.

Example:

1. Create an online Python code editor with Javascript which can compile Python bytecode,
2. Use Mesos and Kafka to create real time architecture for Tensorflow with a Javascript frontend in 1 day. (I asked, and wasn't allowed to use Kubernetes or serverless architecture),
3. Hack a website from the browser's address bar using parameters ( what?!! ),

Obviously, the next time I meet a 'senior', I'm going to tell him talk is cheap;

'SHOW ME YOUR CODE.'

Running a fucking conda environment on windows (an update environment from the previous one that I normally use) gets to be a fucking pain in the fucking ass for no fucking reason.

First: Generate a new conda environment, for FUCKING SHITS AND GIGGLES, DO NOT SPECIFY THE PYTHON VERSION, just to see compatibility, this was an experiment, expected to fail.

Install tensorflow on said environment: It does not fucking work, not detecting cuda, the only requirement? To have the cuda dependencies installed, modified, and inside of the system path, check done, it works on 4 other fucking environments, so why not this one.

Still doesn't work, google around and found some thread on github (the errors) that has a way to fix it, do it that way, fucking magic, shit is fixed.

Very well, tensorflow is installed and detecting cuda, no biggie. HAD TO SWITCH TO PYHTHON 3,8 BECAUSE 3.9 WAS GIVING ISSUES FOR SOME UNKNOWN FUCKING REASON

Ok no problem, done.

Install jupyter lab, for which the first in all other 4 environments it works. Guess what a fuckload of errors upon executing the import of tensorflow. They go on a loop that does not fucking end.

The error: imPoRT eRrOr thE Dll waS noT loAdeD

Ok, fucking which one? who fucking knows.

I FUCKING HATE that the main language for this fucking bullshit is python. I guess the benefits of the repl, I do, but the python repl is fucking HORSESHIT compared to the one you get on: Lisp, Ruby and fucking even NODE in which error messages are still more fucking intelligent than those of fucking bullshit ass Python.

Personally? I am betting on Julia devising a smarter environment, it is a better language already, on a second note: If you are worried about A.I taking your job, don't, it requires a team of fucktards working around common basic system administration tasks to get this bullshit running in the first place.

My dream? Julia or Scala (fuck you) for a primary language in machine learning and AI, in which entire environments, with aaaaaaaaaall of the required dlls and dependencies can be downloaded and installed upon can just fucking run. A single directory structure in which shit just fucking works (reason why I like live environments like Smalltalk, but fuck you on that too) and just run your projects from there, without setting a bunch of bullshit from environment variables, cuda dlls installation phases and what not. Something that JUST FUCKING WORKS.

I.....fucking.....HATE the level of system administration required to run fucking anything nowadays, the reason why we had to create shit like devops jobs, for the sad fuckers that have to figure out environment configurations on a box just to run software.

Fuck me man development turned to shit, this is why go mod, node npm, php composer strict folder structure pipelines were created. Bitch all you want about npm, but if I can create a node_modules setting with all of the required dlls to run a project, even if this bitch weights 2.5GB for a project structure you bet your fucking ass that I would.

"YOU JUST DON'T KNOW WHAT YOU ARE DOING" YES I FUCKING DO and I will get this bullshit fixed, I will get it running just like I did the other 4 environments that I fucking use, for different versions of cuda and python and the dependency circle jerk BULLSHIT that I have to manage. But this "follow the guide and it will work, except when it does not and you are looking into obscure github errors" bullshit just takes away from valuable project time when you have a small dedicated group of developers and no sys admin or devops mastermind to resort to.

I have successfully deployed:
Java
Golang
Clojure
Python
Node
PHP
VB/C# .NET
C++
Rails
Django

Projects, and every single fucking time (save for .net, that shit just fucking works on a dedicated windows IIS server) the shit will not work with x..nT reasons. It fucking obliterates me how fucking annoying this bullshit is. And the reason why the ENTIRE FUCKING FIELD of computer science and software engineering is so fucking flawed.

But we can't all just run to simple windows bs in which we have documentation for everything. We have to spend countless hours on fucking Linux figuring shit out (fuck you also, I have been using Linux since I was 18, I am 30 now) for which graphical drivers for machine learning, cuda and whatTheFuckNot require all sorts of sys admin gymnasts to be used.

Y'all fucked up a long time ago. Smalltalk provided an all in one, easily rollable back to previous images, easily administered interfaces for this fileFuckery bullshit, and even though the JVM and the .NET environments did their best to hold shit down, and even though we had npm packages pulling the universe inside, or gomod compiling shit into one place NOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO we had to do whatever the fuck we wanted to feel l337 and wanted.

Fuck all of you, fuck this field, fuck setting boxes for ML/AI and fuck every single OS in existence

Compiling software on Linux:

Python interpreter? Easy peasy, just some dependencies here and there. Make does a good job.

Linux kernel? Piece of cake, 20 years of development will be freshly served on your machine after one hour compiling (I have a pretty powerful computer).

Tensorflow? Fuck this shit I am outta.

What is your story with self-built software? Which piece of code has the most terrible dependency hell?

I was talking to a friend about the current state of machine learning through tensorflow and commented about the use of Javascript as a language.

He discarded the idea as he views Javascript as something that should only be used as a frontend technology rather than something to build backends or deep learning models.

I am thorn. I have always liked Javascript but will admit that I have used it mostly in the area of front end with very few backend instances(i did create a full stack intranet app in Express once, major success for the application it was hosting, it was a very basic api which had its own nosql db with no need to interact with the company's relational data, it was perfect for the occasion and still help maintaining it from time to time)

My boi states that node's biggest issue has always been npm and the quality of packages. I always contradict those statements by saying that if one uses community standards and the best packages then one does not need to worry about the quality(i.e mongoose over some unmaintained mongo wrapper etc)

I sometimes catch myself finding that my way of thinking adapts better to JS than it even does Python (which is his preference for deep learning) and whilst there are some beastly packages for python in terms of quality and usefulness such as matplotlib etc that one can do great things with the equivalent JS.

I mean, tensorflow.js came from the same wizards that did tensorflow (obviously) and i find the functional approach of JS to be more on par with how we develop solutions.

I am no deep learning expert, and sadly I have no professional experience with machine learning. But I venture to say that we should not cast aside the great strides that the JS community has done to the language in terms of evolution and tooling. Today's Js is not your grandaddy's Js and thinking that the language is crippled because of early iterations of the language would be severely biased.

What do you guys(maybe someone with professional experience) think of Js as a language for machine learning?

Do you think the language poses something worth considering in terms of tooling and power for ml?

Downloading a different version of python, for ONE FUCKING LIBRARY

Fuck you tensorflow

Pro tip: always make sure your methods return the correct variable.

I’m currently working with deep neural networks using tensorflow. I needed to generate some test data and wrote a program to create it. I had two text files which each consisted of approximately 5000 lines of text.

I wrote a method that should sort out some words, and make my final data shorter. When I executed the program first time on our server, it spent about 25 minutes, then crashed due to MemoryError (which in Python means that the server didn’t have enough ram). That seemed quite weird since I only had about 10k lines of text, and I even sorted out a bunch of it, and the server has 128gb ram, and nothing’s using it.

Apparently I returned the wrong variable. That meant that my program tried to save 750 quadrillion lines of text rather than just a few thousand.

Always make sure to return the correct variables!

her: do your worst

me: *applies machine learning*

Finally managed to get my CNN working with proper tensorboard logging. Think I'm starting to understand how it works.

But it got overfitted...

"Python" & TensorFlow (may be a bit later)

Everyone I tell this to, thinks it’s cutting edge, but I see it as a stitched together mess. Regardless:

A micro-service based application that stages machine learning tasks, and is meant to be deployed on 4+ machines. Running with two message queues at its heart and several workers, each worker configured to run optimally for either heavy cpu or gpu tasks.

The technology stack includes rabbitmq, Redis, Postgres, tensorflow, torch and the services are written in nodejs, lua and python. All packaged as a Kubernetes application.

Worked on this for 9 months now. I was the only constant on the project, and the architecture design has been basically re-engineered by myself. Since the last guy underestimated the ask.

!rant

So I trained this model, there must be the training gone wrong. Like how is a flat a Bottle?

The offizial guide to install Tensorflow(Python) on windows is BS. The stackoverflow solution only adds the package, but it wouldn't work.

Time to build it myself...

Used pip install to integrate tensorflow with python 3.5 on windows 10 machine but there were no models available in it. Had to download that separately and add it to tensorflow. Then tried using both inception and clasify_image.py but gives name error cannot find core. But when tested on python idle there were no error there. I don't want to custom create my own classifier but retrain the model. Any solution people?

Spent 2 days installing different versions of nvidia-driver, nvidia-cuda-toolkit, cudnn.
Disassembled pc due to some ram memory problems and pc not starting after freeze.
Looks like sometimes plug out and plug in various components on your motherboard fix pc lol. Destroyed PC casing that collapsed due to me sitting on it.

All of this to just find out tensorflow error and all crashes are from graphics card overheating after keeping it for some time at 82 celsius.

Added time.sleep to python code and looks like it's working, keeping temperature below 65 celsius.

Still ~100 times faster than cpu training so I can live with that.

I have a system design question I was hoping u guys could help me with.

So I want to make a display that shows an animated wallpaper. I want to have a camera in the display that will recognize finger gestures and will change the wallpaper accordingly (shuffle to a new one, etc.)
EX: when the current wallpaper is displaying, when the user shows the camera the peace sign, it will switch the current wallpaper to a random wallpaper.

I used tensorflow and the mediapipe hands library to get the finger gesture recognition to work. I used tensorflow, python, and openCV.

Now that the finger gesture recognition is finished, I moved to the animated wallpapers and I made a couple with p5js.

How could I best combine the two? Should I switch from tensorflow in python to tensorflow.js? Or should I find a way to re-do my animated wallpapers in python?

My original plan was having the foundation of the whole system be python. This is so I can have the finger gesture recognition run on the main thread, and have another thread deal with the wallpapers.

Let me know if u guys have any ideas or if I’m not clear. Thanks!!!

Anyone tell me the all in one website for programming similar to tutorialspoint. 😊

Because tutorials point has no any update regarding Machine Learning and latest package of python tensorflow.

Hello everyone. I'm getting interested in neural networks and I am trying to install the TensorFlow machine learning API using Python's pip package manager but it gives me an error saying that the package couldn't be found. I made sure that I spelled everything correctly and tried using VirtualENV to install it as well, and I uninstalled Python 3.7 and installed 3.6.4. Could anyone help me?

Fucking test, son of a bug I made you finally green. Test Driven Data Science induced RAGE.

Can I blame Trump that my handwriting recognition engine is only predicting at 80%?

Just started with Tensorflow and Python. Have a question, anybody willing to help?

How much time will it take to learn docker?
I want to containerize python deep learning models, which you tensorflow and mxnet.

I'm a noob at Deep Learning. What should be my first project on it? Something I could publish as a paper. Ideas are welcomed :)