tf.keras.optimizers.schedules.ExponentialDecay

A LearningRateSchedule that uses an exponential decay schedule.

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.keras.optimizers.schedules.ExponentialDecay, `tf.compat.v2.keras.optimizers.schedules.ExponentialDecay`, `tf.compat.v2.optimizers.schedules.ExponentialDecay`

tf.keras.optimizers.schedules.ExponentialDecay(
    initial_learning_rate, decay_steps, decay_rate, staircase=False, name=None
)

Args
`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.
`decay_rate`	A scalar `float32` or `float64` `Tensor` or a Python number. The decay rate.
`staircase`	Boolean. If `True` decay the learning rate at discrete intervals
`name`	String. Optional name of the operation. Defaults to 'ExponentialDecay'.

Methods

@classmethod
from_config(
    config
)

Instantiates a LearningRateSchedule from its config.

Args
`config`	Output of `get_config()`.

Returns
A `LearningRateSchedule` instance.

get_config()

__call__(
    step
)

Call self as a function.