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mmengine.optim

mmengine.optim

Optimizer

AmpOptimWrapper

A subclass of OptimWrapper that supports automatic mixed precision training based on torch.cuda.amp.

OptimWrapper

Optimizer wrapper provides a common interface for updating parameters.

OptimWrapperDict

A dictionary container of OptimWrapper.

DefaultOptimWrapperConstructor

Default constructor for optimizers.

build_optim_wrapper

Build function of OptimWrapper.

Scheduler

_ParamScheduler

Base class for parameter schedulers.

ConstantLR

Decays the learning rate value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: end.

ConstantMomentum

Decays the momentum value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: end.

ConstantParamScheduler

Decays the parameter value of each parameter group by a small constant factor until the number of epoch reaches a pre-defined milestone: end.

CosineAnnealingLR

Set the learning rate of each parameter group using a cosine annealing schedule, where \(\eta_{max}\) is set to the initial value and \(T_{cur}\) is the number of epochs since the last restart in SGDR:

CosineAnnealingMomentum

Set the momentum of each parameter group using a cosine annealing schedule, where \(\eta_{max}\) is set to the initial value and \(T_{cur}\) is the number of epochs since the last restart in SGDR:

CosineAnnealingParamScheduler

Set the parameter value of each parameter group using a cosine annealing schedule, where \(\eta_{max}\) is set to the initial value and \(T_{cur}\) is the number of epochs since the last restart in SGDR:

ExponentialLR

Decays the learning rate of each parameter group by gamma every epoch.

ExponentialMomentum

Decays the momentum of each parameter group by gamma every epoch.

ExponentialParamScheduler

Decays the parameter value of each parameter group by gamma every epoch.

LinearLR

Decays the learning rate of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined milestone: end.

LinearMomentum

Decays the momentum of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined milestone: end.

LinearParamScheduler

Decays the parameter value of each parameter group by linearly changing small multiplicative factor until the number of epoch reaches a pre-defined milestone: end.

MultiStepLR

Decays the specified learning rate in each parameter group by gamma once the number of epoch reaches one of the milestones.

MultiStepMomentum

Decays the specified momentum in each parameter group by gamma once the number of epoch reaches one of the milestones.

MultiStepParamScheduler

Decays the specified parameter in each parameter group by gamma once the number of epoch reaches one of the milestones.

OneCycleLR

Sets the learning rate of each parameter group according to the 1cycle learning rate policy.

OneCycleParamScheduler

Sets the parameters of each parameter group according to the 1cycle learning rate policy.

PolyLR

Decays the learning rate of each parameter group in a polynomial decay scheme.

PolyMomentum

Decays the momentum of each parameter group in a polynomial decay scheme.

PolyParamScheduler

Decays the parameter value of each parameter group in a polynomial decay scheme.

StepLR

Decays the learning rate of each parameter group by gamma every step_size epochs.

StepMomentum

Decays the momentum of each parameter group by gamma every step_size epochs.

StepParamScheduler

Decays the parameter value of each parameter group by gamma every step_size epochs.

ReduceOnPlateauLR

Reduce the learning rate of each parameter group when a metric has stopped improving.

ReduceOnPlateauMomentum

Reduce the momentum of each parameter group when a metric has stopped improving.

ReduceOnPlateauParamScheduler

Reduce the parameters of each parameter group when a metric has stopped improving.

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