Work remotely with PyCharm, TensorFlow and SSH (2022)

Dear reader,

PyCharm has been updated and this tutorial is unfortunately a bit outdated. I hope parts of it are still relevant and can help you.

Wouldn’t it be awesome to sit at a café with your laptop, creating large neural networks in TensorFlow, crunching data with speeds of several terraFLOPS, without even hearing your fan spinning up? This is possible using a remote interpreter in PyCharm, and you get almost the same experience working remotely as working locally.

However, this is currently only possible in PyCharm Professional (Community Edition will not do). If you are a student your University should have an arrangement so you can download it for free, otherwise you’ll have to buy it. Here is how I set it up from scratch (you may want to skip some of the steps):

Work remotely with PyCharm, TensorFlow and SSH (1)

This is your stationary remote machine, perhaps fitted with one or several state-of-the-art GPU:s from Nvidia! (I don’t like the current deep learning monopoly, but TensorFlow can only use Nvidia GPUs). First let’s install the latest Ubuntu, I recommend the desktop version, you can always kill the GUI-service later to free up graphics memory. Connect it to Internet and check you LAN IP-address by opening up a terminal typing ifconfig. I will assume it is 192.168.0.1 in the instructions later.

Setup SSH

In order to be able to communicate with your crunching-machine, you need to install SSH on it. Open up a terminal on your stationary computer and get it:

sudo apt-get install ssh

Enable SSH X11-forwarding so that you can plot things, open the configuration file like this.

sudo gedit /etc/ssh/sshd_config

Then locate the row that says

# X11Forwarding yes

Simply remove the hash-sign to uncomment the line, save and close the file.

Graphics

Next install the graphics drivers, they are usually proprietary, so you need to add a new repository to your package manager. What package you’ll need depend on your graphics card and Ubuntu version. As of writing nvidia-367 is the latest one, see more on this page.

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-367

Cuda and cuDNN

Now it’s time to install Cuda toolkit and and cuDNN, which are required to run TensorFlow. They are available from Nvidia’s webpage, and to download cuDNN you are required to register. As of writing Cuda 8.0 and cuDNN 5.1 are the latest versions. For Cuda I prefer using the built in package manager, it makes it easier to keep track of what you have installed:

sudo dpkg -i cuda-repo-ubuntu1604_8.0.44-1_amd64.deb
sudo apt-get update
sudo apt-get install cuda-toolkit-8.0

Make sure that the symlink is set up correctly:

readlink -f /usr/local/cuda
>> /usr/local/cuda-8.0

This is how to extract the cuDNN headers and copy them into the Cuda folder, and make them readable in the terminal (some of the filenames may be different for you):

tar xvzf cudnn-8.0-linux-x64-v5.1.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

Finally add the environment variables you will need, append them to your .bashrc file and then source it:

echo 'export LD_LIBRARY_PATH=”$LD_LIBRARY_PATH:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64"' >> ~/.bashrc
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc
source ~/.bashrc

Python and TensorFlow

Install some required Python libraries:

sudo apt-get install python-pip python-dev build-essential python-numpy python-scipy python-matplotlib

And then install GPU enabled Tensorflow, check the version you need on this page (TF_BINARY_URL is different for different systems):

export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.11.0rc2-cp27-none-linux_x86_64.whl
pip install --ignore-installed --upgrade $TF_BINARY_URL

Verify that the installation is working by typing the following in your terminal:

(Video) Python PyCharm Remote Development via SSH

python
import tensorflow

You should get output similar to this if you have installed it on a GPU enabled system:

>I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcublas.so locally
>I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcudnn.so locally
>I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcufft.so locally
>I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcuda.so.1 locally
>I tensorflow/stream_executor/dso_loader.cc:111] successfully opened CUDA library libcurand.so locally

Did it work? Great! Let’s move on to your laptop

Work remotely with PyCharm, TensorFlow and SSH (2)

Open up your laptop and connect it to the same local network as your stationary machine.

Install stuff

So I’m using a Macbook and it allows me to install programs with a very nice package manager called Homebrew. Even desktop apps can easily be downloaded with Homebrew Cask.

Install Homebrew and Cask:

/usr/bin/ruby -e “$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"brew tap caskroom/cask

Get what you need, including the PyCharm IDE.

brew install cask ssh-copy-id python
brew cask install java pycharm xquartz

Setup SSH

Generate a SSH key-pair by executing the command below and then walk trough the guide (if you haven’t done this already):

ssh-keygen -t rsa

Now copy the key to your remote machine so you can connect to it without typing a password every time. On the first time doing this you need to authenticate yourself with the password of your remote machine:

ssh-copy-id [remote username here]@[remote Ip here]

Enable compression and X11-forwarding (useful for plotting data) by appending this to your config file on your local machine.

echo 'ForwardX11 yes' >> ~/.ssh/config
echo 'Compression yes' >> ~/.ssh/config

Verify that everything is working by connecting to your remote machine from your laptop.

ssh [remote username here]@[remote Ip here]

While still logged in, you should disable password login on your remote machine for security reasons. Open the configuration file with your favorite command-line editor.

sudo vim /etc/ssh/sshd_config

And uncomment the following line by removing the hash-sign:

PasswordAuthentication no

Restart your SSH server while still logged in on your remote (you have to authenticate yourself again).

service ssh restart

The final thing you should do while still logged in with SSH on your remote is to find your display environment variable. This will be used later for plotting, I usually get localhost:10.0.

echo $DISPLAY
> localhost:10.0

Remember the output of this command, we will use it later.

Work remotely with PyCharm, TensorFlow and SSH (3)

This is the funny part, how we can set up the remote interpreter so you execute the scripts on your remote machine. Let’s get started, start up PyCharm and create a new Python project.

Interpreter

Open “Preferences > Project > Project Interpreter”. Click on the “Dotted button” in the top-right corner and then “Add remote”.

(Video) Configuring a remote Python interpreter in PyCharm | PyCharm Tutorial

Work remotely with PyCharm, TensorFlow and SSH (4)

Click on the “SSH Credentials” radio-button and input your information. Select “Key pair” on the “Auth type”, and select the “Private Key file”. It should be located in /Users/<your username>/.ssh/id_rsa.

Work remotely with PyCharm, TensorFlow and SSH (5)

Click on “OK > Apply”. Notice the “R” for remote on the Project Interpreter.

Work remotely with PyCharm, TensorFlow and SSH (6)

Deployment

The remote interpreter can not execute a local file, PyCharm have to copy your source files (your project) to a destination folder on your remote server, but this will be done automatically and you don’t need to think about it! While still in the “Preferences” pane, open “Build, Execution, Deployment > Deployment > Options”. Make sure that “Create empty directories” is checked. This way PyCharm will automatically synchronize when you create folders:

Work remotely with PyCharm, TensorFlow and SSH (7)

Now go back to “Build, Execution, Deployment > Deployment” and click on the “Plus button”, select “SFTP” and give a name to your remote. Click on “OK”:

Work remotely with PyCharm, TensorFlow and SSH (8)

Set up the connection by first typing the IP of your remote in “SFTP host”, then selecting “Key pair” on the “Auth type”, and finally selecting the “Private Key file”. It should be located in /Users/<your username>/.ssh/id_rsa, as shown in the screenshot below. You may then click on “Test SFTP connection”. Given that you can successfully connect you should set up mappings. If you’d like you can click on “Autodetect” beside the “Rooth path”, it will then find the place of your home directory on the remote. All paths you specify after this will be relative to this home path. Then go to the “Mappings” tab.

Work remotely with PyCharm, TensorFlow and SSH (9)

As soon as you save or create a file in your local path, it will be copied to the “Deployment path” on your remote server. Perhaps you want to deploy it in a DeployedProjects/ folder as shown below. This will be relative to your “Rooth path” specified earlier, so the absolute deployment path will in our case be be /home/username/DeployedProjects/TestProject/:

Work remotely with PyCharm, TensorFlow and SSH (10)
(Video) Python Remote Debugging using PyCharm SSH Interpreter

Now we are finished with the preferences, click on “Apply” > “OK”, and then click “Tools > Deployment > Automatic Upload” and confirm that it is checked:

Work remotely with PyCharm, TensorFlow and SSH (11)

To do the initial upload, right-click on you project folder in the project explorer and click on “Upload to remote”:

Work remotely with PyCharm, TensorFlow and SSH (12)

You should get a “File transfer” tab on your bottom pane where you can see all the progress:

Work remotely with PyCharm, TensorFlow and SSH (13)

Then click on “Tools > Deployment > Browse Remote Host”. Drag and drop the window just beside the Project tab to the left. That way it will be really simple to switch between your local and remote project.

Work remotely with PyCharm, TensorFlow and SSH (14)

These deployment settings will work seamlessly as soon as you save and run a file, it is done so quickly you won’t even notice it.

Setup the Console

Open “Preferences > Build, Execution, Deployment > Console > Python console” and select the “Python interpreter” to be your remote one. Next click on the “Dotted button” and input the required environment variables that we added before to ~/.bashrc when we set up the server. Notice that we also added a value to the “DISPLAY” variable we found out earlier when connecting to the server with SSH:

Work remotely with PyCharm, TensorFlow and SSH (15)

Then go back to “Build, Execution, Deployment >Deployment > Console” and select “Always show the debug console”. It will be very handy when we’re debugging:

Work remotely with PyCharm, TensorFlow and SSH (16)

Create a run configuration

Create a simple test-file called test.py in your project, just containing this.

import tensorflow
print "Tensorflow Imported"

Now go to “Run > Edit Configurations…” Click on the “Plus button” and create a new Python configuration. Name it and select the script to run:

Work remotely with PyCharm, TensorFlow and SSH (17)
(Video) JetBrains Remote Server Deployment

Now enter the required environment variables as before. Tips: You can copy them all from the console settings we specified earlier, by using Ctrl+A and then the copy/paste buttons in the lower left corner. You access them by clicking the “Dotted button” just to the right of the “Environment variables” line.

Work remotely with PyCharm, TensorFlow and SSH (18)

Click on “OK > OK”. It’s time for testing!

Now we should be all done, it’s time to test our setup. First open a terminal and make sure that you have at least one SHH channel with X-forwarding connected your server. If you have had a connections open for a while, you may have to exit and restart them:

ssh [remote username here]@[remote Ip here]

Console

Then open the “Python Console” in the lower bar in PyCharm and type import tensorflow. Then you may type ls / to verify that you are actually executing the commands on your server! This is what the output should be:

Work remotely with PyCharm, TensorFlow and SSH (19)

Running script

Now go over to your test.py script and select “Run > Run…” from the top toolbar. Select your newly create run configuration “Test”. It should output something like this:

Work remotely with PyCharm, TensorFlow and SSH (20)

Plotting

Let’s do some plotting, change your test.py file to this:

import tensorflow
import matplotlib
matplotlib.use('GTKAgg')
import matplotlib.pyplot as plt
import numpy as np

print "Tensorflow Imported"
plt.plot(np.arange(100))
plt.show()

And then run it again with your run configuration “Test”, you should get this plot.

Work remotely with PyCharm, TensorFlow and SSH (21)

The plot is actually done on your remote server, but the window data is forwarded to your local machine. Notice that we changed the backed with matplotlib.use('GTXAgg'), because it’s a X11-supported display backend. You can read more about Matplotlib backends here. You can also change the default behavior in your matplotlibrc-file. Remember that you need to have at least one open SSH-connection in a separate terminal to get this to work, with the correct value of the DISPLAY environment variable. If it didn’t work try to restart your SSH connection.

Debugging script

Finally do some debugging, click on the left bar to put a breakpoint, then go “Run > Debug…” and select the “Test” configuration. You will see that the execution has halted and you are debugging your script remotely.

Work remotely with PyCharm, TensorFlow and SSH (22)
(Video) Introducing JetBrains Remote Development

In order to access your machine over the internet you have to forward ports on you home router, that is different for different vendors. I recommend forwarding a different port than 22 on your router. There are plenty bots out there trying to hack in, and they will check that port by default, and might slow your connection (although you are pretty secure since you have turned of password authentication). So you could perhaps forward port 4343 on your router to port 22 on IP 192.168.0.1 (the default IP of our remote in this tutorial). Also to speed up the plotting you may change to a faster encryption.

Next, let’s do some more TensorFlow, perhaps experimenting with matrix multiplication on the CPU and GPU? (coming soon)

FAQs

Can you ssh from PyCharm? ›

You can launch an SSH Session right from PyCharm. By running commands in a dedicated SSH terminal, you can access data on a remote Web server or the default remote interpreter via an SSH tunnel, mainly upload and download files.

Can I use PyCharm remotely? ›

Since working remotely became a necessity, PyCharm offers the Remote Development functionality to help you code, run, debug, and deploy your projects remotely.

How do I use PyCharm remote GPU? ›

Remotely use server GPU and deep learning development environment with local PyCharm and SSH
  1. Step1: Setup SSH (if you did not install or use ssh before) ...
  2. Step2: Install GPU driver, Cuda, Cudnn (if you did not install)
  3. Step3: Install Anaconda with Keras, Tensorflow, Pytorch on the server (if you did not install)
24 Mar 2019

How do I edit remote files in PyCharm? ›

Open the Remote Host tool window by choosing Tools | Deployment | Browse Remote Host or View | Tool Windows | Remote Host from the main menu. , and in the Deployment dialog that opens configure access to the required server. Double-click the desired file or select Edit Remote File from the context menu.

How do I generate a SSH key in PyCharm? ›

Create SSH configurations
  1. In the Settings/Preferences dialog ( Ctrl+Alt+S ), go to Tools | SSH Configurations.
  2. In the left-hand pane that lists all the existing SSH configurations, click .
  3. Use the Visible only for this project checkbox to configure the visibility of the server access configuration.
17 Mar 2022

Is PyCharm better than VSCode? ›

PyCharm and VSCode provide similar code management features, but PyCharm stands out with the ability to “Search Everywhere.” UI elements, classes, and files are all fair game for Search Everywhere, even if what you're looking for isn't in the current project.

What is remote SSH? ›

SSH is a powerful tool for remote access. It allows you to log in and run commands on a remote machine just as if you were sitting in front of it. Many sysadmins use custom prompts for remote machines to avoid confusing a local terminal with a remote one.

What is PyCharm remote interpreter? ›

The central entry point to remote development with PyCharm is the notion of Remote Interpreters. You can configure PyCharm to use Python interpreter from a remote host and set it as your project interpreter. Then you can configure your run/debug configurations to run, debug or test your applications on the remote host.

What is the difference between PyCharm professional and community? ›

The main difference between Pycharm Community and PyCharm Professional Edition is their subscription fee and features. It can be used at work and can be used in your next employment if you change careers.

How do I deploy a project in PyCharm? ›

This can be done in the following two ways: Open the deployment Options (Settings/Preferences | Deployment | Options or Tools | Deployment | Options from the main menu), and in the Upload changed files automatically to the default server field choose Always, or On explicit save action.

How can I edit a file remotely? ›

For many sysadmins, the "obvious" solution for editing a remote file is to open a secure shell (SSH) on a remote machine. From within that remote shell, you can open a file in a terminal-based text editor like Nano or Vim or Emacs and edit it as if it were on your own computer.

How do I connect PyCharm to GitHub? ›

Press Ctrl+Alt+S to open the IDE settings and select Version Control | GitHub. Select Log In via GitHub. In the browser window that opens, click Create an account and complete the registration process on GitHub. Return to the PyCharm settings, click Cancel, and then repeat steps 2 and 3.

Is PyCharm professional free for students? ›

Professional desktop IDEs: IntelliJ IDEA, PyCharm, and more. A free subscription for students, to be renewed annually.

How do you collaborate in PyCharm? ›

PyCharm creates a link that you can send to guests you want to invite to collaborate. To copy the invitation link, click the Code With Me icon, and select Copy Session Link. Send the link to guests. When a guest clicks the link, PyCharm displays a popup suggesting either to accept or decline the guest.

Does PyCharm Community Edition support remote development? ›

Is Remote Development or JetBrains Gateway available in the PyCharm Community edition?  They are both available in the PyCharm Professional edition only.

What is SSH key based authentication? ›

Remote connections to a server via Secure Shell (SSH) can be authenticated in two ways. The traditional and default method is to use password authentication. The second approach is key-based authentication, which is based on a private-public key pair.

How do I clone using SSH? ›

4 Steps to clone GitHub over SSH
  1. Create an SSH keypair on your Windows or Linux OS.
  2. Copy the value of the public SSH key to your GitHub account.
  3. Obtain the GitHub SSH URL for the repository to be cloned.
  4. Using Git, clone from GitHub with the SSH URL.
11 Jan 2022

How do I open SSH from terminal in python? ›

There are multiple options to use SSH in Python but Paramiko is the most popular one. Paramiko is an SSHv2 protocol library for Python.
...
Python
  1. Connect to the router with username/password authentication.
  2. Run the show ip route command.
  3. Look for the default route in the output and show it to us.
14 Apr 2020

Is PyCharm better than Jupyter? ›

PyCharm's auto-complete feature really facilitates faster development and workflow, and it's something that Jupyter does not offer. This smart editing feature is why PyCharm is clearly the choice for developers and software engineers, especially those working exclusively in Python.

Is PyCharm faster than VS Code? ›

In the performance criteria, VS Code easily beats PyCharm. Because VS Code doesn't try to be a full IDE and keeps it simple as a text-editor, the memory footprint, startup-time, and overall responsiveness of VS Code is much better than PyCharm.

Is PyCharm the best Python IDE? ›

PyCharm. In industries most professional developers use PyCharm and it has been considered the best IDE for python developers. It was developed by the Czech company JetBrains and it's a cross-platform IDE. It gives daily tips to improve your knowledge of how you can use it more efficiently which is a very good feature.

What can I do with SSH? ›

Secure Shell is used to connect to servers, make changes, perform uploads and exit, either using tools or directly through the terminal. SSH keys can be employed to automate access to servers and often are used in scripts, backup systems and configuration management tools.

What is the need of SSH for remote connections? ›

SSH or Secure Shell is a network protocol that connects users to a remote computer over a secure connection. This allows administrators and other authorized users to connect to secure computers over a network that is not secure, like the Internet.

How does SSH connection work? ›

The way SSH works is by making use of a client-server model to allow for authentication of two remote systems and encryption of the data that passes between them. SSH operates on TCP port 22 by default (though SSH port can be changed if needed).

How do I connect PyCharm to Docker? ›

tip
  1. Press Ctrl+Alt+S to open the IDE settings and select Build, Execution, Deployment | Docker.
  2. Click. to add a Docker configuration and specify how to connect to the Docker daemon. The connection settings depend on your Docker version and operating system. For more information, see Docker configuration settings.
19 Sept 2022

How do I debug Python remotely? ›

Attach remotely from Python Tools
  1. Create a copy of the remote file on the local computer and open it in Visual Studio. ...
  2. (Optional) To have IntelliSense for debugpy on your local computer, install the debugpy package into your Python environment.
  3. Select Debug > Attach to Process.
21 Sept 2022

What is remote interpreting? ›

05/24/22. Video remote interpreting (VRI) is a form of sign language interpreting that allows people who are deaf or hard of hearing to communicate with a hearing person at the same site via videoconferencing instead of live, on-site interpreting.

Is PyCharm good for beginners? ›

The PyCharm IDE is one of the most popular editors used by professional Python developers and programmers. The vast number of PyCharm features doesn't make this IDE difficult to use–just the opposite. Many of the features help make Pycharm a great Python IDE for beginners.

Is PyCharm community good for beginners? ›

PyCharm made developing in Python super easy from beginners to experts. PyCharm is the best Python IDE I have ever used. It is super powerful and makes coding in Python a breeze with smart suggestions and many tools to manage packages.

Do you need a license for PyCharm? ›

PyCharm Community Edition and PyCharm Edu are free and can be used without any license. You cannot upgrade to PyCharm Professional: download and install it separately as described in Install PyCharm.

How do I open SSH from terminal in python? ›

There are multiple options to use SSH in Python but Paramiko is the most popular one. Paramiko is an SSHv2 protocol library for Python.
...
Python
  1. Connect to the router with username/password authentication.
  2. Run the show ip route command.
  3. Look for the default route in the output and show it to us.
14 Apr 2020

Does PyCharm Community Edition support remote development? ›

Is Remote Development or JetBrains Gateway available in the PyCharm Community edition?  They are both available in the PyCharm Professional edition only.

What is PyCharm remote interpreter? ›

The central entry point to remote development with PyCharm is the notion of Remote Interpreters. You can configure PyCharm to use Python interpreter from a remote host and set it as your project interpreter. Then you can configure your run/debug configurations to run, debug or test your applications on the remote host.

How do I connect to a remote server using SSH in Python? ›

How to SSH into a server in Python
  1. host = "test.rebex.net"
  2. port = 22.
  3. username = "demo"
  4. password = "password"
  5. command = "ls"
  6. ssh = paramiko. SSHClient()
  7. ssh. set_missing_host_key_policy(paramiko. AutoAddPolicy())
  8. ssh. connect(host, port, username, password)

How do I run a Python script remotely? ›

Using the paramiko library – a pure python implementation of SSH2 – your python script can connect to a remote host via SSH, copy itself (!) to that host and then execute that copy on the remote host. Stdin, stdout and stderr of the remote process will be available on your local running script.

How do I connect to SSH in Python? ›

Python SSH Client - Paramiko. SSH with Python. - YouTube

How do I run a glue job in Pycharm? ›

To create a role for AWS Glue with limited Amazon S3 read privileges, complete the following steps:
  1. On the IAM console, choose Roles in the navigation pane.
  2. Choose Create role.
  3. For Trusted entity type, select AWS service.
  4. For Use cases for other AWS services, choose Glue.
  5. Choose Next.
22 Apr 2022

How do I install Awsglue in Pycharm? ›

For AWS Glue version 0.9, download the AWS Glue Python library file, PyGlue. zip , from https://s3.amazonaws.com/aws-glue-jes-prod-us-east-1-assets/etl/python/PyGlue.zip to a convenient location on your local machine. For AWS Glue version 1.0 and later, download the AWS Glue Python library file, PyGlue.

How do I add boto3 to Pycharm? ›

3 Answers
  1. Press Ctr + Alt + s.
  2. On left, Project <your project here> > Project Interpreter.
  3. On right, click on +
  4. At the top, search for boto3.
  5. At the bottom, click on Install Package.

What is the difference between PyCharm professional and community? ›

The main difference between Pycharm Community and PyCharm Professional Edition is their subscription fee and features. It can be used at work and can be used in your next employment if you change careers.

What is remote SSH? ›

SSH is a powerful tool for remote access. It allows you to log in and run commands on a remote machine just as if you were sitting in front of it. Many sysadmins use custom prompts for remote machines to avoid confusing a local terminal with a remote one.

How do I deploy a project in PyCharm? ›

This can be done in the following two ways: Open the deployment Options (Settings/Preferences | Deployment | Options or Tools | Deployment | Options from the main menu), and in the Upload changed files automatically to the default server field choose Always, or On explicit save action.

How do I connect PyCharm to Docker? ›

tip
  1. Press Ctrl+Alt+S to open the IDE settings and select Build, Execution, Deployment | Docker.
  2. Click. to add a Docker configuration and specify how to connect to the Docker daemon. The connection settings depend on your Docker version and operating system. For more information, see Docker configuration settings.
19 Sept 2022

Is PyCharm professional free for students? ›

Professional desktop IDEs: IntelliJ IDEA, PyCharm, and more. A free subscription for students, to be renewed annually.

How do I debug Python remotely? ›

Attach remotely from Python Tools
  1. Create a copy of the remote file on the local computer and open it in Visual Studio. ...
  2. (Optional) To have IntelliSense for debugpy on your local computer, install the debugpy package into your Python environment.
  3. Select Debug > Attach to Process.
21 Sept 2022

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