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()