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Decaying Learning Rate

Decay functions can be applied to learning rate using nn.decay and nn.optimizer utility functions.

nn.decay(fn_name, **kwargs)

**kwargs are passed to the decay function.


decay = nn.decay('exponential', decay_steps=1000, decay_rate=0.96)

optimizer = nn.optimizer('GradientDescent', 0.001, decay=decay)

You can also use a custom function:

def custom_decay(learning_rate, global_step):
    # Custom logic
    return decayed_learning_rate

optimizer = nn.optimizer('GradientDescent', 0.001, decay=custom_decay)

Available Decay Functions

  • exponential
  • inverse_time
  • natural_exp
  • polynomial
  • cosine
  • linear_cosine
  • noisy_linear_cosine

See Also