tf.keras.experimental.CosineDecayRestarts

A LearningRateSchedule that uses a cosine decay schedule with restarts.

Compat aliases for migration

See Migration guide for more details.

tf.keras.experimental.CosineDecayRestarts(
    initial_learning_rate, first_decay_steps, t_mul=2.0, m_mul=1.0, alpha=0.0,
    name=None
)

Args
`initial_learning_rate`	A scalar `float32` or `float64` Tensor or a Python number. The initial learning rate.
`first_decay_steps`	A scalar `int32` or `int64` `Tensor` or a Python number. Number of steps to decay over.
`t_mul`	A scalar `float32` or `float64` `Tensor` or a Python number. Used to derive the number of iterations in the i-th period
`m_mul`	A scalar `float32` or `float64` `Tensor` or a Python number. Used to derive the initial learning rate of the i-th period:
`alpha`	A scalar `float32` or `float64` Tensor or a Python number. Minimum learning rate value as a fraction of the initial_learning_rate.
`name`	String. Optional name of the operation. Defaults to 'SGDRDecay'.

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.