tf.keras.optimizers.schedules.PolynomialDecay

TensorFlow 1 version View source on GitHub

A LearningRateSchedule that uses a polynomial decay schedule.

Inherits From: LearningRateSchedule

Used in the notebooks

Used in the tutorials

initial_learning_rate A scalar float32 or float64 Tensor or a Python number. The initial learning rate.
decay_steps A scalar int32 or int64 Tensor or a Python number. Must be positive. See the decay computation above.
end_learning_rate A scalar float32 or float64 Tensor or a Python number. The minimal end learning rate.
power A scalar float32 or float64 Tensor or a Python number. The power of the polynomial. Defaults to linear, 1.0.
cycle A boolean, whether or not it should cycle beyond decay_steps.
name String. Optional name of the operation. Defaults to 'PolynomialDecay'.

Methods

from_config

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Instantiates a LearningRateSchedule from its config.

Args
config Output of get_config().

Returns
A LearningRateSchedule instance.

get_config

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__call__

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Call self as a function.