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A wrapper that slows down the updates of trainable weights

Project description

Keras Successive Regularization Wrapper

Travis Coverage

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


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keras-succ-reg-wrapper-0.4.0.tar.gz (2.9 kB view hashes)

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