Keras Targeted Dropout
Unofficial implementation of Targeted Dropout with tensorflow backend. Note that there is no model compression in this implementation.
Install
pip install keras-targeted-dropout
Usage
import keras
from keras_targeted_dropout import TargetedDropout
model = keras.models.Sequential()
model.add(TargetedDropout(
layer=keras.layers.Dense(units=2, activation='softmax'),
drop_rate=0.8,
target_rate=0.2,
drop_patterns=['kernel'],
mode=TargetedDropout.MODE_UNIT,
input_shape=(5,),
))
model.compile(optimizer='adam', loss='mse')
model.summary()
drop_rate: Dropout rate for each pixel.target_rate: The proportion of bottom weights selected as candidatesdrop_patterns: A list of names of weights to be dropped.mode:TargetedDropout.MODE_UNITorTargetedDropout.MODE_WEIGHT.
The final dropout rate will be drop_rate times target_rate.
1 maintainer
Metadata
1 maintainer
Release files for keras-targeted-dropout 0.5.0
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