Runtimes
This guide explains the system used by Gradient Notebooks to load workspaces and containers
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Gradient Next
This guide explains the system used by Gradient Notebooks to load workspaces and containers
Last updated
In Gradient Notebooks, a runtime is defined by its container and workspace.
A workspace is the set of files managed by the Gradient Notebooks IDE while a container is the DockerHub or NVIDIA Container Registry image installed by Gradient.
A runtime does not specify a particular machine or instance type. One great benefit of Gradient Notebooks is that runtimes can be swapped across a wide variety of instances.
When creating a new notebook, Gradient offers a list of runtimes to select sorted by Recommended and All. We can use these runtime tiles or we can create our own runtimes.
To explore the details of a particular runtime provided by Gradient, expand the Advanced Options section of the Create a notebook flow.
In this example, we will explore the PyTorch 1.10 runtime tile:
The PyTorch 1.10 tile consists of the following:
Workspace URL - https://github.com/gradient-ai/PyTorch
Container Name - nvcr.io/nvidia/pytorch:21.10-py3
The Workspace URL parameter tells Gradient which files to load into the notebook file manager.
The Container Name parameter tells Gradient where to fetch the container image that will be used to build the notebook.
When we select Start Notebook, Gradient imports the file(s) located in the Workspace URL directory into the file manager and then imports and runs the container image specified defined in the Container Name field.
In this example, our new PyTorch 1.10 notebook contains the files from https://github.com/gradient-ai/PyTorch running on the container from nvcr.io/nvidia/pytorch:21.10-py3.
We can confirm this fact by noticing that our file manager is populated with the contents from the GitHub repository (in this case a single file) and that the bottom bar is displaying the name of the container image as expected.
Paperspace maintains a number of runtimes that make it easy to get started with preloaded notebook files and dependencies. These runtimes are provided as tiles when creating a new notebook in Gradient.
The following is a list of recommended runtimes that Paperspace maintains:
PyTorch 1.10
Latest PyTorch release (1.8) with GPU support.
nvcr.io/nvidia/pytorch:21.09-py3
TensorFlow 2.6.0
TensorFlow 2 with GPU support.
nvcr.io/nvidia/tensorflow:21.09-tf2-py3
Paperspace + Fast.ai
Fast.ai Paperspace's Fast.ai template is built for getting up and running with the enormously popular Fast.ai online MOOC.
paperspace/fastai:2.0-CUDA9.2-fastbook-v0.1.0
NVIDIA RAPIDS
NVIDIA's library to execute end-to-end data science and analytics pipelines on GPU.
nvcr.io/nvidia/rapidsai/rapidsai:0.18-cuda11.0-base-centos7
ClipIt-PixelDraw
A creative library for generating pixel art from simple text prompts.
paperspace/clip-pixeldraw:jupyter
Hugging Face Transformers
A state-of-the-art NLP library from Hugging Face
paperspace/transformers-gpu:0.4.0
These are a sampling of additional runtimes available in the Create a notebook section of the Gradient console. Runtimes are added frequently.
TensorFlow (1.14 GPU)
Official docker images for TensorFlow version 1
paperspace/dl-containers:tensorflow1140-py36-cu100-cdnn7-jupyter
N/A
JupyterLab Data Science Stack
Jupyter Notebook Data Science Stack
jupyter/datascience-notebook
N/A
JupyterLab Data R Stack
Jupyter Notebook R Stack
jupyter/r-notebook
Gradient provides the ability to import a workspace during notebook creation.
Let's say we're interested in working with GFP-GAN, an exciting library that helps us restore and upscale images. Rather than clone the files from GitHub after we create the notebook, we can instantiate the notebook with the files already there.
All we need to do is specify the GFP-GAN GitHub repo in the Workspace URL parameter of Advanced options during notebook creation.
Gradient automatically copies all of the files from the GitHub repo into the notebook IDE.
The resulting notebook looks like this:
A custom workspace can be specified at the time of notebook creation only.
It's also possible to pull files from private or password-protected repositories by filling in Workspace Username and Workspace Password fields.
The same logic can be applied to containers, which is demonstrated in the next section.
A container is a disk image pre-loaded with files and dependencies. Gradient provides the ability to import an image from a container registry such as DockerHub during notebook creation.
In this example, we'll tell Gradient to pull the latest container from NVIDIA RAPIDS by specifying the Docker image in the Container Name field.
Note that the larger the container, the longer it will take for Gradient to pull it into a notebook.
Paperspace recommends using Docker to get the container image from the local machine to Gradient.
jupyter must be run on port 8888 and connections from ip address 0.0.0.0 must be allowed.
If running jupyter notebook, the following flags must be included in the Command field to support the Gradient Notebooks IDE:
If running jupyter lab, these flags should be used in the Command field instead:
The following fields are available in the Container section of Advanced options when creating a new Gradient Notebook:
Container Name
true
Path and tags of image from DockerHub or NVIDIA Container Registry. E.g. ufoym/deepo:all-jupyter-py36
Registry Username
false
Private container registry username. Can be left blank for public images.
Registry Password
false
Private container registry password. Can be left blank for public images. Secrets may be used in this field using the substitution syntax secret:
Command
false
Must be Jupyter compatible. If left blank, defaults to jupyter notebook --allow-root --ip=0.0.0.0 --no-browser --NotebookApp.trust_xheaders=True --NotebookApp.disable_check_xsrf=False --NotebookApp.allow_remote_access=True --NotebookApp.allow_origin='*'
Container User
false
Optional user. Defaults to 'root' if left blank.
Recommended runtimes. We can also select the All option to view a more expansive list of runtimes that work out of the box.Advanced options tab when creating a new notebook.Recommended or All using the blue sorting button.Workspace URL field.Workspace Username and Workspace Password fields are useful for pulling files from private GitHub repositories.Container Name field.Container section of Advanced options in the Create a notebook flow in Gradient.
