TensorFlow 2 version | View source on GitHub |
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
)
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
from_config
@classmethod
from_config( config )
Instantiates a LearningRateSchedule
from its config.
Args | |
---|---|
config
|
Output of get_config() .
|
Returns | |
---|---|
A LearningRateSchedule instance.
|
get_config
get_config()
__call__
__call__(
step
)
Call self as a function.