This project forked from taki0112/adabound-tensorflow
Simple Tensorflow implementation of "Adaptive Gradient Methods with Dynamic Bound of Learning Rate" (ICLR 2019)
License: Apache License 2.0
Simple Tensorflow implementation of "Adaptive Gradient Methods with Dynamic Bound of Learning Rate" (ICLR 2019)
learning_rate = 0.001final_lr = 0.01beta1 = 0.9beta2 = 0.999 from AdaBound import AdaBoundOptimizer
train_op = AdaBoundOptimizer(learning_rate=0.001, final_lr=0.01, beta1=0.9, beta2=0.999, amsgrad=False).minimize(loss) x = fully_connected(inputs=images, units=100)
x = relu(x)
logits = fully_connected(inputs=x, units=10)
Junho Kim
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