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ELBO AI API and Command Line Documentation

Welcome

Making ML stuff cheap and easy 💪

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ELBO.AI is a service that makes training of ML models easier and cheaper. Use our service to train your models, receive timely training notifications, choose compute types that fit your budget and integrate with our API to add the service to your workflow.

Want to jump right in?

Jump in to the quick start docs and get making your first task submission:

Quick Start

Want to deep dive?

Dive a little deeper and start exploring our API reference to get an idea of everything that's possible with the API:

The Configuration file

The ELBO configuration is specified in YAML in a configuration file. Let's look at its contents.

The configuration file, typically named elbo.yaml has the following properties:

Option

Description

Examples

name

The name of your ML training task

Tip: If you are submitting the task for the first time, you may want to run the training task on an Economy class machine and then move to higher classes when you see the model converging after a few epochs.

Here is a sample configuration with comments on what each property means:

Quick Start

Here is the guide to help setup ELBO environment in your local machine.

Good to know: We are just getting started with this service and are actively building it. If you face any problems with the service or API, please reach out to us at

Get your API keys

Reference

API Reference

You can use ELBO Python API to automatically save the state of the training.

PyTorch

We currently support only PyTorch, but please reach out to us if you need other frameworks. There are two main concepts:

The abstract elbo.ElboModel The elbo.ElboEpochIterator

Good to know: These APIs are being built and may change as we enhance them.

The ELBO Tracker

The ELBO tracker allows you to monitor your ML tasks on your Phone using the ELBO Tracker App

The ELBO Tracker API is an easy way to monitor your tasks on your Phone. Using the API you can log messages, key metrics (numbers), and images. These would show up in your task list on your Phone.

Please install the ELBO Tracker App and log in with your authentication token to see the results of your tasks.

To start instantiate an instance of the Tracker

from elbo.tracker.tracker import TaskTracker
tracker = TaskTracker("Hello World")

Where "Hello World" is the experiment name. Now to log a message just do:

tracker.log_message("Hi there! 👋")

That's it! Similarly logging a metric or an image is as simple:

And finally, upload the logs using:

Make sure you don't forget this step. The upload_logs() API can be called as many times as you would like. Each time it will append to the existing logs. For example, if you are training a model, it may make sense to call this API every epoch.

Once this is done, now you can see the results in your App!

The abstract elbo.ElboModel

An ElboModel is an abstract class that allows ELBO service to automatically checkpoint your training.

Extending your model class

Extend the abstractElboModel along with nn.Model in your PyTorch model class. With this you will be required to implement two methods:

save_state - This method should save the state of the model and other state information needed.
load_state - This method should load the state of the model from the input directory.

Good to know: These methods will be called by the training loop at periodic intervals to keep saving the state of training. Please make sure anything thats needed for a training to resume from a previous checkpoint is saved and loaded through this method.

The elbo.ElboEpochIterator

The iterator class is a decorator on top of a traditional Python iterator. Add this to your training epoch loop.

Usage

The elbo.EpochIterator takes the following arguments:

The range of epochs usually - range(0, num_epochs)
The PyTorch model it is training
save_state_interval How often should the model state be saved to artifacts directory. A value of 5 means the model state will be saved every 5 epochs.

CLI Reference

Use the command-line tool to run tasks, show task status, cancel tasks and SSH into tasks.

Help

elbo --help

Start a notebook

elbo notebook

Run a task

elbo run --config <config_file_path>

Cancel a task

elbo kill <task_id>

Show task attributes

elbo show <task_id>

Download task artifacts

elbo download <task_id>

Show running task

elbo ps -r

SSH into a running task

Show ELBO Server Status

elbo.client is starting 'Train MNIST Classifier' submission ...
elbo.client Hey Anu 👋, welcome!
elbo.client is uploading sources from ....
elbo.client upload successful.

elbo.client number of compute choices - 28
? Please choose: (Use arrow keys)
 »  $ 0.0028/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS (spot)
    $ 0.0150/hour     Standard (for testing)   1 cpu     2Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 0.0770/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS
    $ 0.2700/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS (spot)
    $ 0.6100/hour         Nvidia Quadro 4000  16 cpu    32Gb mem    8Gb gpu-mem TensorDock
    $ 0.9000/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS
    $ 0.9180/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS (spot)
    $ 0.9200/hour         Nvidia Quadro 5000   2 cpu     4Gb mem   16Gb gpu-mem FluidStack
    $ 0.9600/hour               Nvidia A5000   2 cpu    16Gb mem   24Gb gpu-mem TensorDock
    $ 1.4900/hour               Nvidia A4000  12 cpu    64Gb mem   16Gb gpu-mem FluidStack
    $ 1.4940/hour                 Nvidia A40   2 cpu    12Gb mem   48Gb gpu-mem TensorDock
    $ 1.5000/hour         Nvidia Quadro 6000   8 cpu    32Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 1.5140/hour               Nvidia A6000   2 cpu    16Gb mem   48Gb gpu-mem TensorDock
    $ 2.1600/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS (spot)
    $ 3.0000/hour      2x Nvidia Quadro 6000  16 cpu    64Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 3.0600/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS
    $ 3.6720/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS (spot)
    $ 3.7460/hour             7x Nvidia V100   6 cpu     8Gb mem   16Gb gpu-mem TensorDock
    $ 4.3200/hour       16x Nvidia Tesla K80  64 cpu   732Gb mem   12Gb gpu-mem AWS (spot)
    $ 4.5000/hour      3x Nvidia Quadro 6000  20 cpu    96Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 6.0000/hour      4x Nvidia Quadro 6000  24 cpu   128Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 7.3440/hour             8x Nvidia V100  64 cpu   488Gb mem   16Gb gpu-mem AWS (spot)
    $ 7.9200/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS
    $ 9.8318/hour             8x Nvidia A100  96 cpu  1152Gb mem   80Gb gpu-mem AWS (spot)
    $13.0360/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS
    $14.4000/hour       16x Nvidia Tesla K80  64 cpu   732Gb mem   12Gb gpu-mem AWS
    $24.4800/hour             8x Nvidia V100  64 cpu   488Gb mem   16Gb gpu-mem AWS
    $32.7726/hour             8x Nvidia A100  96 cpu  1152Gb mem   80Gb gpu-mem AWS

elbo.client is starting 'Train MNIST Classifier' submission ...
elbo.client Hey Anu 👋, welcome!
elbo.client is uploading sources from ....
elbo.client upload successful.

elbo.client number of compute choices - 28
? Please choose: (Use arrow keys)
 »  $ 0.0028/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS (spot)
    $ 0.0150/hour     Standard (for testing)   1 cpu     2Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 0.0770/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS
    $ 0.2700/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS (spot)
    $ 0.6100/hour         Nvidia Quadro 4000  16 cpu    32Gb mem    8Gb gpu-mem TensorDock
    $ 0.9000/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS
    $ 0.9180/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS (spot)
    $ 0.9200/hour         Nvidia Quadro 5000   2 cpu     4Gb mem   16Gb gpu-mem FluidStack
    $ 0.9600/hour               Nvidia A5000   2 cpu    16Gb mem   24Gb gpu-mem TensorDock
    $ 1.4900/hour               Nvidia A4000  12 cpu    64Gb mem   16Gb gpu-mem FluidStack
    $ 1.4940/hour                 Nvidia A40   2 cpu    12Gb mem   48Gb gpu-mem TensorDock
    $ 1.5000/hour         Nvidia Quadro 6000   8 cpu    32Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 1.5140/hour               Nvidia A6000   2 cpu    16Gb mem   48Gb gpu-mem TensorDock
    $ 2.1600/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS (spot)
    $ 3.0000/hour      2x Nvidia Quadro 6000  16 cpu    64Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 3.0600/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS
    $ 3.6720/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS (spot)
    $ 3.7460/hour             7x Nvidia V100   6 cpu     8Gb mem   16Gb gpu-mem TensorDock
    $ 4.3200/hour       16x Nvidia Tesla K80  64 cpu   732Gb mem   12Gb gpu-mem AWS (spot)
    $ 4.5000/hour      3x Nvidia Quadro 6000  20 cpu    96Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 6.0000/hour      4x Nvidia Quadro 6000  24 cpu   128Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 7.3440/hour             8x Nvidia V100  64 cpu   488Gb mem   16Gb gpu-mem AWS (spot)
    $ 7.9200/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS
    $ 9.8318/hour             8x Nvidia A100  96 cpu  1152Gb mem   80Gb gpu-mem AWS (spot)
    $13.0360/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS
    $14.4000/hour       16x Nvidia Tesla K80  64 cpu   732Gb mem   12Gb gpu-mem AWS
    $24.4800/hour             8x Nvidia V100  64 cpu   488Gb mem   16Gb gpu-mem AWS
    $32.7726/hour             8x Nvidia A100  96 cpu  1152Gb mem   80Gb gpu-mem AWS

The ELBO Tracker

The ELBO tracker allows you to monitor your ML tasks on your Phone using the ELBO Tracker App

The ELBO Tracker API is an easy way to monitor your tasks on your Phone. Using the API you can log messages, key metrics (numbers), and images. These would show up in your task list on your Phone.

Please install the ELBO Tracker App and log in with your authentication token to see the results of your tasks.

To start instantiate an instance of the Tracker

from elbo.tracker.tracker import TaskTracker
tracker = TaskTracker("Hello World")

Where "Hello World" is the experiment name. Now to log a message just do:

tracker.log_message("Hi there! 👋")

That's it! Similarly logging a metric or an image is as simple:

    tracker.log_key_metric("Accuracy", 100.0)
    
    tracker.log_image("An AI generated image of a Cat 🐱", "images/aicat.png")

And finally, upload the logs using:

Once this is done, now you can see the results in your App!

CLI Reference

Use the command-line tool to run tasks, show task status, cancel tasks and SSH into tasks.

Help

elbo --help

(.venv) joy@elbo ~> elbo
Usage: elbo [OPTIONS] COMMAND [ARGS]...

  elbo.ai - Train more, pay less

Options:
  --help  Show this message and exit.

Commands:
  balance   Show the users balance
  create    Create an instance and get SSH access to it.
  download  Download the artifacts for the task.
  kill      Stop the task.
  login     Login to the ELBO service.
  notebook  Start a Jupyter Lab session.
  ps        Show list of all tasks.
  run       Submit a task specified by the config file.
  show      Show the task.
  ssh       SSH into the machine running the task.
  status    Get ELBO server status.

Start a notebook

elbo notebook

Run a task

elbo run --config <config_file_path>

Cancel a task

elbo kill <task_id>

Show task attributes

elbo show <task_id>

Download task artifacts

elbo download <task_id>

Show running task

elbo ps -r

SSH into a running task

Show ELBO Server Status

(.venv) joy@elbo ~/p/elbo-examples (main)> elbo run --config pytorch/mnist_classifier/elbo.yaml
elbo.client is starting 'Train MNIST Classifier' submission ...
elbo.client Hey Anu 👋, welcome!
elbo.client is uploading sources from pytorch/mnist_classifier/....
elbo.client upload successful.

elbo.client number of compute choices - 27
? Please choose: (Use arrow keys)
 »  $ 0.0028/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS (spot)
    $ 0.0150/hour     Standard (for testing)   1 cpu     2Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 0.0770/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS
    $ 0.2700/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS (spot)
    $ 0.7220/hour               Nvidia A4000   2 cpu     4Gb mem   16Gb gpu-mem TensorDock
    $ 0.9000/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS
    $ 0.9180/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS (spot)
    $ 0.9200/hour         Nvidia Quadro 5000   2 cpu     4Gb mem   16Gb gpu-mem FluidStack
    $ 0.9600/hour               Nvidia A5000   2 cpu    16Gb mem   24Gb gpu-mem TensorDock
    $ 1.4940/hour                 Nvidia A40   2 cpu    12Gb mem   48Gb gpu-mem TensorDock
    $ 1.5000/hour         Nvidia Quadro 6000   8 cpu    32Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 1.5140/hour               Nvidia A6000   2 cpu    16Gb mem   48Gb gpu-mem TensorDock
    $ 2.1600/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS (spot)
    $ 3.0000/hour      2x Nvidia Quadro 6000  16 cpu    64Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 3.0600/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS
    $ 3.6720/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS (spot)
    $ 3.7460/hour             7x Nvidia V100   6 cpu     8Gb mem   16Gb gpu-mem TensorDock
    $ 4.3200/hour       16x Nvidia Tesla K80  64 cpu   732Gb mem   12Gb gpu-mem AWS (spot)
    $ 4.5000/hour      3x Nvidia Quadro 6000  20 cpu    96Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 6.0000/hour      4x Nvidia Quadro 6000  24 cpu   128Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 7.3440/hour             8x Nvidia V100  64 cpu   488Gb mem   16Gb gpu-mem AWS (spot)
    $ 7.9200/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS
    $ 9.8318/hour             8x Nvidia A100  96 cpu  1152Gb mem   80Gb gpu-mem AWS (spot)
    $13.0360/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS.

(.venv) joy@elbo ~/p/elbo-examples (main)> elbo run --config pytorch/mnist_classifier/elbo.yaml
elbo.client is starting 'Train MNIST Classifier' submission ...
elbo.client Hey Anu 👋, welcome!
elbo.client is uploading sources from pytorch/mnist_classifier/....
elbo.client upload successful.

elbo.client number of compute choices - 27
? Please choose: (Use arrow keys)
 »  $ 0.0028/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS (spot)
    $ 0.0150/hour     Standard (for testing)   1 cpu     2Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 0.0770/hour        Micro (for testing)   2 cpu     1Gb mem    0Gb gpu-mem AWS
    $ 0.2700/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS (spot)
    $ 0.7220/hour               Nvidia A4000   2 cpu     4Gb mem   16Gb gpu-mem TensorDock
    $ 0.9000/hour           Nvidia Tesla K80   4 cpu    61Gb mem   12Gb gpu-mem AWS
    $ 0.9180/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS (spot)
    $ 0.9200/hour         Nvidia Quadro 5000   2 cpu     4Gb mem   16Gb gpu-mem FluidStack
    $ 0.9600/hour               Nvidia A5000   2 cpu    16Gb mem   24Gb gpu-mem TensorDock
    $ 1.4940/hour                 Nvidia A40   2 cpu    12Gb mem   48Gb gpu-mem TensorDock
    $ 1.5000/hour         Nvidia Quadro 6000   8 cpu    32Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 1.5140/hour               Nvidia A6000   2 cpu    16Gb mem   48Gb gpu-mem TensorDock
    $ 2.1600/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS (spot)
    $ 3.0000/hour      2x Nvidia Quadro 6000  16 cpu    64Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 3.0600/hour                Nvidia V100   8 cpu    61Gb mem   16Gb gpu-mem AWS
    $ 3.6720/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS (spot)
    $ 3.7460/hour             7x Nvidia V100   6 cpu     8Gb mem   16Gb gpu-mem TensorDock
    $ 4.3200/hour       16x Nvidia Tesla K80  64 cpu   732Gb mem   12Gb gpu-mem AWS (spot)
    $ 4.5000/hour      3x Nvidia Quadro 6000  20 cpu    96Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 6.0000/hour      4x Nvidia Quadro 6000  24 cpu   128Gb mem    0Gb gpu-mem Linode (~ 9 mins to provision)
    $ 7.3440/hour             8x Nvidia V100  64 cpu   488Gb mem   16Gb gpu-mem AWS (spot)
    $ 7.9200/hour        8x Nvidia Tesla K80  32 cpu   488Gb mem   12Gb gpu-mem AWS
    $ 9.8318/hour             8x Nvidia A100  96 cpu  1152Gb mem   80Gb gpu-mem AWS (spot)
    $13.0360/hour             4x Nvidia V100  32 cpu   244Gb mem   16Gb gpu-mem AWS.

ELBO AI API and Command Line Documentation

Welcome

hashtagWant to jump right in?

hashtagWant to deep dive?

The Configuration file

Quick Start

hashtagGet your API keys

Reference

API Reference

hashtagPyTorch

The ELBO Tracker

The abstract elbo.ElboModel

hashtagExtending your model class

The elbo.ElboEpochIterator

hashtagUsage

CLI Reference

hashtagHelp

hashtagStart a notebook

hashtagRun a task

hashtagCancel a task

hashtagShow task attributes

hashtagDownload task artifacts

hashtagShow running task

hashtagSSH into a running task

hashtagShow ELBO Server Status

Welcome

hashtagWant to jump right in?

hashtagWant to deep dive?

Quick Start

hashtagGet your API keys

hashtagSetup your Virtual Environment

hashtagInstall the library

hashtagLogin to ELBO

hashtagMake your first task submission

The elbo.ElboEpochIterator

hashtagUsage

The ELBO Tracker

CLI Reference

hashtagHelp

hashtagStart a notebook

hashtagRun a task

hashtagCancel a task

hashtagShow task attributes

hashtagDownload task artifacts

hashtagShow running task

hashtagSSH into a running task

hashtagShow ELBO Server Status

The abstract elbo.ElboModel

hashtagExtending your model class

API Reference

hashtagPyTorch

The Configuration file

Want to jump right in?

Want to deep dive?

Get your API keys

PyTorch

Extending your model class

Usage

Help

Start a notebook

Run a task

Cancel a task

Show task attributes

Download task artifacts

Show running task

SSH into a running task

Show ELBO Server Status

Want to jump right in?

Want to deep dive?

Get your API keys

Setup your Virtual Environment

Install the library

Login to ELBO

Make your first task submission

Usage

Help

Start a notebook

Run a task

Cancel a task

Show task attributes

Download task artifacts

Show running task

SSH into a running task

Show ELBO Server Status

Extending your model class

PyTorch