A UI based callback for tf-keras
This project is supported by Segmind
This is a UI based hyper-parameter controller, which let's you control the following.
- start, pause and stop a live training.
- reset the learning rate on dynamically while training is in progress.
- take a snapshot at will
more functionalities are to be added
This package depends on MQTT protocol for communication. So, it is expected that an MQTT broker is up and running in 'localhost' at port 1883(default port).
Install it by :
sudo apt-get update sudo apt-get install mosquitto sudo apt-get install mosquitto-clients
- python >= 3.6.8
- tensorflow >= 1.14
Note: This package is intended and tested for tensorflow-keras api and NOT keras with tensorflow 'backend'
you can try the following example
save the follwing example fashion_mnist_jukebox.py
from __future__ import absolute_import, division, print_function, unicode_literals import tensorflow as tf from tensorflow import keras # import the callback from keras_jukebox import JukeBoxCallback fashion_mnist = keras.datasets.fashion_mnist (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data() train_images = train_images / 255.0 test_images = test_images / 255.0 model = keras.Sequential([ keras.layers.Flatten(input_shape=(28, 28)), keras.layers.Dense(128, activation='relu'), keras.layers.Dense(10, activation='softmax') ]) model.compile(optimizer='adam', loss='sparse_categorical_crossentropy', metrics=['accuracy']) # pass the jukebox callback to model.fit method model.fit(train_images, train_labels, epochs=10, callbacks=[JukeBoxCallback(verbose=1)])
and run it. You will notice that the script starts but training doesn't, which is because it is paused and needs a JukeBox-UI to start.
Now, open a new terminal(Alt+ctrl+T) and start the JukeBox by typing:
and you should see the UI pop up, note the algorithm is in pause mode by default. Hit the play button to start the training.
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