Recently I started this Machine learning (http://course18.fast.ai/ml.html) course. The code provided here is in the old version of fastai (0.7.0). Is there any way that I can run these code with the current version of fastai?
(I'm on ubuntu 19.10 and used to code at google colab).
Related
I'm trying to run the code from this repository: https://github.com/danielgordon10/thor-iqa-cvpr-2018
It has the following requirements
Python 3.5
CUDA 8 or 9
cuDNN
Tensorflow 1.4 or 1.5
Ubuntu 16.04, 18.04
an installation of darknet
My system satisfies neither of these. I don't want to reinstall tf/cuda/cudnn on my machine (especially if have to do that everytime I try to run deep learning code with different tensorflow requirements everytime).
I'm looking for a way to install the requirements and run the code regardless of the host.
To my knowledge that is exactly what Docker is for.
Looking into this there exist docker images from nvidia. For example one called "nvidia/cuda:9.1-cudnn7-runtime". Based on the name I assumed that any image build with this as the base comes with cuda installed. This does not seem to be the case as if I try to install darknet it will fail with the error that "cuda_runtime.h" is missing.
So what my question basicaly boils down to is: How do I keep multiple different versions of cuda and tensorflow on the same machine ? Ideally with docker (or similar) so I won't have to do the process to many times.
It feels like I'm missing and/or don't understand something obvious, because I can't imagine that it can be so hard to run tensorflow code with different versions without reinstalling things from scratch all the time.
I am using a face recognition model based on tensorflow. in my local machine - ubuntu 14.04 - everything works.
when I deploy it using docker, I am getting the following error:
DataLossError: Unable to open table file /data/model/model.ckpt-80000: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you
need to use a different restore operator?
I am using python implementation for tensorflow.
The model is in the old 11.* format (model.meta & model.ckpt-80000) while the tensorflow python version is 12.* . It shouldn't be a problem, as that's the configuration in my local machine, as well as in the place where I took the model from.
The versions of tensorflow, numpy and protobuf are identical in my machine and in the docker machine.
Any advice?
UPDATE
I created a small script that runs perfectly on my machine. Then, I run the same script on the deployed on virtual machine (AWS instance) BUT NOT on docker. It also failed, with the same error.
The deployed machine is ubuntu 16.04.
Seems like i was dealing with a corrupted file
So I have been trying to learn docker for a few days now, I am basically a windows user and I am trying to run docker on a ubuntu VM 14.04 , all I just wanted to ask was , WHAT are the pre-requisites to learning a Docker ?
Just like you can't learn jQuery , without the basics in JavaScript , just like you can't learn a framework like laravel, magento, cakePHP without the basics in PHP , just like you can't learn LESS, SASS, SCSS, without the basics in CSS in place , what would the pre-requisites for Docker be?
Can somebody list it out. Please done that I am not asking for an opinion here, I am asking for an ABSOLUTE DEFINITIVE answer to my question, which is, what are the pre-requisites for learning a tool like Docker?
In order to get Docker working on Ubuntu you should have a basic comprehension of these things
how the bash works (at least how to handle files and folders)
basics of networking on Linux/Ubuntu
apt-get (installing packages like Nodejs or Postgres)
the Unix / Linux philosophy
Since you are a Windows user, I'd recommend sticking to that well-known environment while you learn Docker. Learn one thing at a time.
Having that basic Windows knowledge, you should be able to follow on the Learn Docker book as long as you have the prerequisites stated in the book:
Basic experience creating applications with one of the following technologies: .NET Core, Java, Node.JS, PHP or Python.
Chapter 2 of the book explains how to install Docker on various systems including Windows.
Disclaimer: I'm the author of that book.
I am new to mahout and web services related matters.
I have a huge problem concerning the deployment of a simple recommender as a .war file so far and that is because the steps followed by Manning Mahout Book - the only book found so far concerning mahout- refer to an older version of the platform.
I'm currently using mahout 0.9 which, with which i have created a recommender app that successfully runs on my IDE. However when it comes to the deployment of this project i can't find a step-by-step guide to handle my problem.
Does anyone have a clue on how to deploy a 0.5+ mahout project as a .war file?
The .war packaging was removed years ago. There is no means to deploy this that just gives you a web app. It is a library only.
I installed Ubuntu Desktop 12.04 LTS in VirtualBox on my Macbook Pro (i7, 4gb ram) in order to do development. Shockingly it's not very snappy (quick/responsive). I want to know which distributions of Linux are small/light but can be used for Rails development in Virtualbox.
Thank you
I did the same using Lubuntu (the light version of ubuntu) installed on a virtual disk. Moreover, I m using a portable version of VirtualBox to have everything on a usbstick.
I ran the Lubuntu from the usbstick and began to develop some rails apps but the OI was not that great for user experience so I copied the virtual disk with lubuntu on the harddisk together with the virtualbox folder. With this setup it work realy fine!
Also, I'm using the guest additions in order to keep shared folders on the usbstick to share the projects amongst machine.
Hope it can help you in your experience.
I use arch linux when developing. It is not designed with being “easy to use” as priority bu it is customisable for everything you need. I like the arch linux way.
Linux VM is not necessary for developing RoR apps on OSX.
Try to google on how to develop RoR apps on native OSX.