tf.keras.optimizers.schedules.ExponentialDecay

TensorFlow 1 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
)

Used in the notebooks

Used in the guide

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

__call__

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__call__(
    step
)

Call self as a function.

from_config

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@classmethod
from_config(
    config
)

Instantiates a LearningRateSchedule from its config.

Args:

  • config: Output of get_config().

Returns:

A LearningRateSchedule instance.

get_config

View source

get_config()