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Project description Python Management Library


This is a library for uploading machine learning models to

Upload Models

You'll need to create an API token first.

import lukai

# ... your model definition code

sess = tf.Session()

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

# Uploads the model to and creates a training job.
    domain='<your domain>',
    model_type='<your model type>',
    name='Hello World',
    description='This is the first model I've uploaded!',
        num_clients = 10,
        batch_size = 10,
        num_rounds = 100,
        learning_rate = learning_rate,
        num_local_rounds = 10,
      accuracy: lukai.REDUCE_MEAN,
      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()

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

See the full leastsquares example

Project details

Download files

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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
Filename, size lukai-0.6.tar.gz (23.0 kB) File type Source Python version None Upload date Hashes View

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