cc.factorie.optimize

GradientOptimizer

trait GradientOptimizer extends AnyRef

Base trait for optimizers that update weights according to a gradient.

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  1. abstract def finalizeWeights(weights: WeightsSet): Unit

    Once learning is done, the weights should be copied back into normal tensors.

    Once learning is done, the weights should be copied back into normal tensors.

    weights

    The weights

  2. abstract def initializeWeights(weights: WeightsSet): Unit

    Some optimizers swap out weights with special purpose tensors for e.

    Some optimizers swap out weights with special purpose tensors for e.g. efficient scoring while learning.

    weights

    The weights

  3. abstract def isConverged: Boolean

    Whether the optimizer has converged yet.

  4. abstract def reset(): Unit

    Reset the optimizers internal state (such as Hessian approximation, etc.

    Reset the optimizers internal state (such as Hessian approximation, etc.)

  5. abstract def step(weights: WeightsSet, gradient: WeightsMap, value: Double): Unit

    Updates the weights according to the gradient.

    Updates the weights according to the gradient.

    weights

    The weights

    gradient

    The gradient

    value

    The value

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