class LrConfig(oneof.OneOfConfig): """Configuration for lr schedule. Attributes: type: 'str', type of lr schedule to be used, on the of fields below. constant: constant learning rate config. stepwise: stepwise learning rate config. exponential: exponential learning rate config. polynomial: polynomial learning rate config. cosine: cosine learning rate config. power: step^power learning rate config. power_linear: learning rate config of step^power followed by step^power*linear. power_with_offset: power decay with a step offset. """ type: Optional[str] = None constant: lr_cfg.ConstantLrConfig = lr_cfg.ConstantLrConfig() stepwise: lr_cfg.StepwiseLrConfig = lr_cfg.StepwiseLrConfig() exponential: lr_cfg.ExponentialLrConfig = lr_cfg.ExponentialLrConfig() polynomial: lr_cfg.PolynomialLrConfig = lr_cfg.PolynomialLrConfig() cosine: lr_cfg.CosineLrConfig = lr_cfg.CosineLrConfig() power: lr_cfg.DirectPowerLrConfig = lr_cfg.DirectPowerLrConfig() power_linear: lr_cfg.PowerAndLinearDecayLrConfig = ( lr_cfg.PowerAndLinearDecayLrConfig()) power_with_offset: lr_cfg.PowerDecayWithOffsetLrConfig = ( lr_cfg.PowerDecayWithOffsetLrConfig())
class LrConfig(oneof.OneOfConfig): """Configuration for lr schedule. Attributes: type: 'str', type of lr schedule to be used, on the of fields below. stepwise: stepwise learning rate config. exponential: exponential learning rate config. polynomial: polynomial learning rate config. cosine: cosine learning rate config. """ type: Optional[str] = None stepwise: lr_cfg.StepwiseLrConfig = lr_cfg.StepwiseLrConfig() exponential: lr_cfg.ExponentialLrConfig = lr_cfg.ExponentialLrConfig() polynomial: lr_cfg.PolynomialLrConfig = lr_cfg.PolynomialLrConfig() cosine: lr_cfg.CosineLrConfig = lr_cfg.CosineLrConfig()