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mediapipe_model_maker.model_util.WarmUp
Applies a warmup schedule on a given learning rate decay schedule.
View aliases
Main aliases
mediapipe_model_maker.face_stylizer.face_stylizer.face_stylizer_options.model_opt.loss_functions.model_util.WarmUp
, mediapipe_model_maker.face_stylizer.face_stylizer.loss_functions.model_util.WarmUp
, mediapipe_model_maker.face_stylizer.face_stylizer.model_opt.loss_functions.model_util.WarmUp
, mediapipe_model_maker.face_stylizer.face_stylizer.model_util.WarmUp
, mediapipe_model_maker.face_stylizer.face_stylizer_options.model_opt.loss_functions.model_util.WarmUp
, mediapipe_model_maker.face_stylizer.model_options.loss_functions.model_util.WarmUp
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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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-05-07 UTC."],[],[]]