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A LearningRateSchedule that uses an exponential decay schedule.
Inherits From: LearningRateSchedule
tf.keras.optimizers.schedules.ExponentialDecay(
initial_learning_rate, decay_steps, decay_rate, staircase=False, name=None
)
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
intervalsname
: String. Optional name of the operation. Defaults to
'ExponentialDecay'.__call__
__call__(
step
)
Call self as a function.
from_config
@classmethod
from_config(
config
)
Instantiates a LearningRateSchedule
from its config.
config
: Output of get_config()
.A LearningRateSchedule
instance.
get_config
get_config()