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mediapipe_model_maker.model_util.WarmUp
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Applies a warmup schedule on a given learning rate decay schedule.
mediapipe_model_maker.model_util.WarmUp(
initial_learning_rate: float,
decay_schedule_fn: Callable[[Any], Any],
warmup_steps: int,
name: Optional[str] = None
)
Args |
initial_learning_rate
|
learning rate after the warmup.
|
decay_schedule_fn
|
A function maps step to learning rate. Will be applied
for values of step larger than 'warmup_steps'.
|
warmup_steps
|
Number of steps to do warmup for.
|
name
|
TF namescope under which to perform the learning rate calculation.
|
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() -> Dict[str, Any]
__call__
View source
__call__(
step: Union[int, tf.Tensor]
) -> tf.Tensor
Call self as a function.
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Last updated 2024-05-07 UTC.
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