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Luk.ai management library

Project description

Luk.ai Python Management Library

PyPI

This is a library for uploading machine learning models to Luk.ai.

Upload Models

You'll need to create an API token first.

import lukai

# ... your model definition code

sess = tf.Session()
sess.run(tf.initialize_all_variables())

# Sets the Luk.ai API token.
lukai.set_api_token('<your token>')

# Uploads the model to Luk.ai and creates a training job.
lukai.upload(
    session=sess,
    domain='<your domain>',
    model_type='<your model type>',
    name='Hello World',
    description='This is the first model I've uploaded!',
    hyper_params=lukai.HyperParams(
        num_clients = 10,
        batch_size = 10,
        num_rounds = 100,
        learning_rate = learning_rate,
        num_local_rounds = 10,
    ),
    metrics={
      accuracy: lukai.REDUCE_MEAN,
    },
    event_targets={
      lukai.EVENT_TRAIN: (keep_prob.assign(0.5),),
      lukai.EVENT_INFER: (keep_prob.assign(1.0),),
      lukai.EVENT_EVAL: (keep_prob.assign(1.0),),
    },
)

See the full mnist example.

Export Models

You can also directly output the model.tar.gz file if you'd like.

from lukai import saver

# ... your model definition code

sess = tf.Session()
sess.run(tf.initialize_all_variables())

print('Node names: x = {}, y_ = {}, train_step = {}, w = {}, b = {}, y = {}'.format(
  x.name, y_.name, train_step.name, w.name, b.name, y.name,
))

saver.save(sess)

See the full leastsquares example

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for lukai, version 0.6
Filename, size File type Python version Upload date Hashes
Filename, size lukai-0.6-py3-none-any.whl (47.5 kB) File type Wheel Python version py3 Upload date Hashes View hashes
Filename, size lukai-0.6.tar.gz (23.0 kB) File type Source Python version None Upload date Hashes View hashes

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