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declearn.optimizer.modules.EWMAModule

Bases: OptiModule

Exponentially Weighted Moving Average module.

This module impements the following algorithm:

Init(beta):
    state = 0
Step(grads):
    state = beta*state + (1-beta)*grads
    grads = state

In other words, gradients are corrected by an exponentially- decaying moving-average of past gradients.

Source code in declearn/optimizer/modules/_momentum.py 
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class EWMAModule(OptiModule):
    """Exponentially Weighted Moving Average module.

    This module impements the following algorithm:

        Init(beta):
            state = 0
        Step(grads):
            state = beta*state + (1-beta)*grads
            grads = state

    In other words, gradients are corrected by an exponentially-
    decaying moving-average of past gradients.
    """

    name: ClassVar[str] = "ewma"

    def __init__(
        self,
        beta: float = 0.9,
    ) -> None:
        """Instantiate the EWMA gradients-adaptation module.

        Parameters
        ----------
        beta: float, default=0.9
            Coefficient parameterizing the (exponentially-
            decaying) moving average of input gradients.
        """
        if not isinstance(beta, float):
            raise TypeError("'beta' should be of type float.")
        if not 0 <= beta < 1:
            raise ValueError("'beta' value should be in [0, 1[.")
        self.beta = beta
        self.state = 0.0  # type: Union[Vector, float]

    def get_config(
        self,
    ) -> Dict[str, Any]:
        return {"beta": self.beta}

    def run(
        self,
        gradients: Vector,
    ) -> Vector:
        self.state = (self.beta * self.state) + ((1 - self.beta) * gradients)
        return self.state

    def get_state(
        self,
    ) -> Dict[str, Any]:
        return {"state": self.state}

    def set_state(
        self,
        state: Dict[str, Any],
    ) -> None:
        if "state" not in state:
            raise KeyError("Missing required state variable 'state'.")
        self.state = state["state"]

__init__(beta=0.9)

Instantiate the EWMA gradients-adaptation module.

Parameters:

Name Type Description Default
beta float

Coefficient parameterizing the (exponentially- decaying) moving average of input gradients.

 0.9
Source code in declearn/optimizer/modules/_momentum.py 
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def __init__(
    self,
    beta: float = 0.9,
) -> None:
    """Instantiate the EWMA gradients-adaptation module.

    Parameters
    ----------
    beta: float, default=0.9
        Coefficient parameterizing the (exponentially-
        decaying) moving average of input gradients.
    """
    if not isinstance(beta, float):
        raise TypeError("'beta' should be of type float.")
    if not 0 <= beta < 1:
        raise ValueError("'beta' value should be in [0, 1[.")
    self.beta = beta
    self.state = 0.0  # type: Union[Vector, float]