Welcome to hosting your Keras model on Algorithmia! This guide is designed as an introduction to hosting a Keras model and publishing an algorithm even if you’ve never used Algorithmia before.
Before you get started hosting your model on Algorithmia there are a few things you’ll want to do first:
Train and save the model file.
After training your Keras model, you’ll want to save it using
model.save(filepath) so you can upload it to Algorithmia.
Note that when developing a model with Keras, they recommend you to save the model as an
.h5 file so do not use pickle or cPickle to save your model, but use the built in
Create a Data Collection
Here you’ll want to create a data collection to host your model.
To use the Data API, log into your Algorithmia account and create a data collection via the Data Collections page.
Click on “Add Collection” under the “My Collections” section on your data collections page.
After you create your collection you can set the read and write access on your data collection. For more information check out: Data Collection Types
Upload your Model into a Collection
Next, upload your pickled model to your newly created data collection.
Load model by clicking box “Drop files here to upload”
Note the path to your files: data://username/collections_name/pickled_model.pkl
Create your Algorithm
Creating your algorithm is easy!
- To add an algorithm, simply click “Add Algorithm” from the user profile icon.
- Name your algorithm, select the language, choose permissions and make the code either open or closed source.
Note: There is also a checkbox for ‘Standard Execution Environment’ or ‘Advanced GPU’. For deep learning models you will want to check ‘Advanced GPU’.
Set your Dependencies
Now is the time to set your dependencies that your model relies on.
- Click on the “Dependencies” button at the top right of the UI and list your packages under the required ones already listed and click “Save Dependencies” on the bottom right corner.
Load your Model
Here is where you load and run your model which will be called by the apply() function. Our recommendation is to preload your model in a separate function before apply(). The reasoning behind this is because when your model is first loaded it can take some time to load depending on the file size. However, with all subsequent calls only the apply() function gets called which will be much faster since your model is already loaded!
Note that you always want to create valid JSON input and output in your algorithm. For example this algorithm takes a JSON blob passing in a csv file hosted on Algorithmia, Amazon S3, or Dropbox.
Example Hosted Model:
If you are authoring an algorithm, avoid using the ‘.my’ pseudonym in the source code. When the algorithm is executed, ‘.my’ will be interpreted as the user name of the user who called the algorithm, rather than the author’s user name.
Publish your Algorithm
Last is publishing your algorithm. The best part of hosting your model on Algorithmia is that users can access it via an API that takes only a few lines of code to use! Here is what you can set when publishing your algorithm:
Set version permissions to public or private use
Set it to royalty free or set to per-call royalty
Set access permissions to have full access to the internet and ability to call other algorithms
For more information and detailed steps: creating and publishing your algorithm
If you would like to check this demo out on the platform you can find it here: Keras Demo
That’s it for hosting your Keras model on Algorithmia!