stable_baselines3/mpdqn/mpdqn.py
def _update_learning_rate(self, optimizer_q: th.optim.Optimizer, optimizer_parameter: th.optim.Optimizer) -> None:
        """
        Update the optimizers learning rate using the current learning rate schedule
        and the current progress remaining (from 1 to 0).
        :param optimizers:
            An optimizer or a list of optimizers.
        """
        return PDQN._update_learning_rate(self, optimizer_q, optimizer_parameter)

        Update the optimizers learning rate using the current learning rate schedule
        and the current progress remaining (from 1 to 0).
        :param optimizers:
            An optimizer or a list of optimizers.
        
Update the optimizers learning rate using the current learning rate schedule
and the current progress remaining (from 1 to 0).
Update the optimizers learning rate using the current learning rate schedule and the current progress remaining ( from 1 to 0 ) .
def _update_learning_rate(self, optimizer_q: th.optim.Optimizer, optimizer_parameter: th.optim.Optimizer) -> None:
        return PDQN._update_learning_rate(self, optimizer_q, optimizer_parameter)
def _update_learning_rate ( self , optimizer_q : th . optim . Optimizer , optimizer_parameter : th . optim . Optimizer ) -> None : return PDQN . _update_learning_rate ( self , optimizer_q , optimizer_parameter )
Update the optimizers learning rate using the current learning rate schedule
and the current progress remaining (from 1 to 0).
Update the optimizers learning rate using the current learning rate schedule and the current progress remaining ( from 1 to 0 ) .
"""
        Update the optimizers learning rate using the current learning rate schedule
        and the current progress remaining (from 1 to 0).
        :param optimizers:
            An optimizer or a list of optimizers.
        """
self
optimizer_q
th.optim.Optimizer
optimizer_parameter
th.optim.Optimizer
optimizers
An optimizer or a list of optimizers.
An optimizer or a list of optimizers .