A wrapper that slows down the updates of trainable weights
Project description
Keras Successive Regularization Wrapper
A wrapper that slows down the updates of trainable weights.
Install
pip install keras-succ-reg-wrapper
Usage
import keras
from keras_succ_reg_wrapper import SuccReg
input_layer = keras.layers.Input(shape=(1,), name='Input')
dense_layer = SuccReg(
layer=keras.layers.Dense(units=1, name='Dense'),
regularizer=keras.regularizers.L1L2(l2=1e-3), # Any regularizer
name='Output',
)(input_layer)
model = keras.models.Model(inputs=input_layer, outputs=dense_layer)
model.compile(optimizer='adam', loss='mse')
model.summary()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Close
Hashes for keras-succ-reg-wrapper-0.4.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | f95e5da1fd1b1f59a8e800dbec4db7582d99abcdcfbde613d4454ec50a844ce9 |
|
MD5 | c7978ce087645c9d45e05ecac6be691a |
|
BLAKE2b-256 | 78317a2847ddf48af8c3aff91b926c2b22c9fb2cb3db12afb92994eeae0195fd |