demouse.blogg.se - Nvidia-docker for mac

#Nvidia docker for mac install
#Nvidia docker for mac driver
#Nvidia docker for mac software

In simpler words, Docker is a tool that allows developers, sys-admins etc.

#Nvidia docker for mac software

Written and developed by Prakhar SrivastavĪn open-source project that automates the deployment of software applications inside containers by providing an additional layer of abstraction and automation of OS-level virtualization on Linux. Then reload and restart the SSH daemon (on Ubuntu this was systemctl daemon-reload & systemctl restart sshd).Īdd the following to your SSH config at ~/.Learn to build and deploy your distributed applications easily to the cloud with Docker Note that if you plan on SSH’ing into the Docker host as well (like I did from my laptop to the docker host), you need to set X11Forwarding to yes in /etc/ssh/sshd_config on the docker host as well.

Make sure the SSH server is running when the container starts.

Add the right Python interpreter to the root user’s PATH.

Action Required!!!: Insert your SSH public key so you can SSH into the container.

Allow X forwarding with the SSH server within the container.

This may not be secure, so I don’t advise using on any sort of public facing machine.

Set up the container to allow you to SSH in.

python3-pyqt5 for the QT bindings (installing via pip didn’t seem to work for me).

openssh-server to SSH into the container.

libportaudio2 for audio manipulation (?).

Use the pytorch docker image as our base image.

RUN echo "export PATH=/opt/conda/bin:$PATH" > /root/.profileĮNTRYPOINT

#Nvidia docker for mac install

RUN pip install -r /workspace/requirements.txt & grep "^X11UseLocalhost" /etc/ssh/sshd_config || echo "X11UseLocalhost no" > /etc/ssh/sshd_configĪDD Real-Time-Voice-Cloning/requirements.txt /workspace/requirements.txt & sed -i "s/^.*X11UseLocalhost.*$/X11UseLocalhost no/" /etc/ssh/sshd_config \ & sed -i "s/^.*X11Forwarding.*$/X11Forwarding yes/" /etc/ssh/sshd_config \ & sed -i "s/^.*PasswordAuthentication.*$/PasswordAuthentication no/" /etc/ssh/sshd_config \ & apt-get install -y ffmpeg libportaudio2 openssh-server python3-pyqt5 xauth \ I’ll assume that you’re working from your home directory, and we’ll make a directory called voice for our project to sit in and clone the GitHub repo:

Step 2: Clone the Real-Time-Voice-Cloning project and download pretrained models

#Nvidia docker for mac driver

Note that you’ll need have installed the NVIDIA driver and Docker as well. Some variant of these instructions may allow the project to be ran with just a CPU, but I haven’t investigated that path, so you’re on your own there.įollow the instructions here. Step 0: You should probably have access to a machine with a CUDA-compatible GPU I’m not really sure, as I haven’t tested the following on anything except Linux and macOS. Note that these steps should be more or less compatible with Linux or macOS, but maybe on Windows with the WSL. Docker would do the trick as far as getting it setup, and then through forwarding the X Window System via SSH, I could view and control the program locally as it ran remotely. I’m currently working on a Mac laptop, but I have access to a remote server with some GPUs that could easily run the toolbox, but I wanted an easy way to get everything setup. I came across this awesome project called Real Time Voice Cloning by Corentin Jemine and I wanted to give it a shot.