Using Lasagne with Gradientzoo¶
This doc will demonstrate how to save and load your trained neural network in Python using Lasagne.
Initialization¶
from gradientzoo import LasagneGradientzoo
This is the client that you’ll create to save and load your model to the service.
param username: | The gradientzoo username of the project you want to connect to |
---|---|
param model_slug: | |
The slug (short url-safe name) of the model | |
param api_base: | Optional URL prefix to specify where the gradientzoo API is located, which is especially useful if you are running your own instance of gradientzoo |
param auth_token_id: | |
Your authentication token as provided by the service | |
param default_dir: | |
Optional When a download directory is asked for later, this is what it will default to if you pass None |
Note: For convenience and aesthetics, you can pass both the username and model_slug as username/model_slug
to the username parameter.
# Examples of how to instantiate the client
zoo = LasagneGradientzoo('exampleuser/modelslug')
zoo = LasagneGradientzoo('exampleuser', 'modelslug', auth_token_id='12345af')
zoo = LasagneGradientzoo('exampleuser/modelslug', api_base='https://api2.gradientzoo.com')
Examples
The next few examples will assume zoo
, an instantiated LasagneGradientzoo
client:
from gradientzoo import LasagneGradientzoo
zoo = LasagneGradientzoo('exampleuser/modelslug')
Loading a Model¶
If you want to load a model from the remote cloud, that can be done by calling
the load
method on the client.
param network: | The Lasagne network you want to load the weights into |
---|---|
param filename: | Optional The filename of the thing you would like to download |
param id: | Optional If there is a specific version of the file you want to download, provide the file id (as seen on the website) here |
param dir: | Optional The directory to download the file to |
returns file_model: | |
A dictionary with metadata about the file you downloaded |
# Example of how to load a Lasagne network
zoo.load(your_lasagne_network)
Saving a Model¶
If you want to save your moel to the remote cloud, simply call the
upload_file
method on the client.
param network: | The Lasagne network you want to save the weights for |
---|---|
param filename: | Optional The name of the file you’re uploading |
param metadata: | Optional A bag of key/value pairs to be associated with this file (must be JSON encodable) |
param dir: | Optional The temporary directory to save the model weights to before uploading them |
# Example of how to save a Lasagne network
zoo.save(your_lasagne_network)