tfa.optimizers.TriangularCyclicalLearningRate  |  TensorFlow Addons (original) (raw)

tfa.optimizers.TriangularCyclicalLearningRate

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A LearningRateSchedule that uses cyclical schedule.

Inherits From: CyclicalLearningRate

tfa.optimizers.TriangularCyclicalLearningRate(
    initial_learning_rate: Union[FloatTensorLike, Callable],
    maximal_learning_rate: Union[FloatTensorLike, Callable],
    step_size: tfa.types.FloatTensorLike,
    scale_mode: str = 'cycle',
    name: str = 'TriangularCyclicalLearningRate'
)
Args
initial_learning_rate A scalar float32 or float64 Tensor or a Python number. The initial learning rate.
maximal_learning_rate A scalar float32 or float64 Tensor or a Python number. The maximum learning rate.
step_size A scalar float32 or float64 Tensor or a Python number. Step size denotes the number of training iterations it takes to get to maximal_learning_rate
scale_mode ['cycle', 'iterations']. Mode to apply during cyclic schedule
name (Optional) Name for the operation.

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

View source

get_config()

__call__

View source

__call__(
    step
)

Call self as a function.

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Last updated 2023-05-25 UTC.