API Reference - WeightBlocks - Bias

Constructors

new() 


BaseWeightBlock.new({learningRate: number, Optimizer: OptimizerObject, Regularizer: RegularizerObject, nextFunctionBlockArrayIndexArray: {number}, nextFunctionBlockWaitDuration: number, initializationMode: string}): WeightBlockObject

Parameters:

  • learningRate: The speed at which the model learns. Recommended that the value is set between (0 to 1).

  • Optimizer: The optimizer to be used.

  • Regularizer: The regularizer to be used.

  • initializationMode: The mode for the weights to be initialized. Available options are:

    • Zero

    • Random

    • RandomNormal

    • RandomUniformPositive

    • RandomUniformNegative

    • RandomUniformNegativeAndPositive

    • HeUniform

    • HeNormal

    • XavierUniform

    • XavierNormal

    • LeCunUniform

    • LeCunNormal

    • None

Returns

  • WeightBlock: The generated weight block object.

Functions

gradientDescent() 


BaseWeightBlock:gradientDescent(weightLossTensor: tensor, numberOfData: number)

Parameters:

  • weightLossTensor: A tensor containing the weight loss values. This will be used to update the weights.

  • numberOfData: The value to divide with the weight loss tensors.

setWeightTensor() 


BaseWeightBlock:setWeightTensor(weightTensor: tensor, doNotDeepCopy: boolean)

Parameters

  • weightTensor: The tensor to be loaded to the weight block.

  • doNotDeepCopy: Whether or not to deep copy the weight tensor.

getWeightTensor() 


BaseWeightBlock:getWeightTensor(doNotDeepCopy): tensor

Parameters

  • doNotDeepCopy: Whether or not to deep copy the weight tensor.

Returns

  • weightTensor: Tensor to be returned.

setLearningRate() 


BaseWeightBlock:setLearningRate(learningRate: number)

Parameters:

  • learningRate: The speed at which the model learns. Recommended that the value is set between (0 to 1).

getLearningRate(): number 


BaseWeightBlock:getLearningRate()

Returns::

  • learningRate: The speed at which the model learns. Recommended that the value is set between (0 to 1).

setOptimizer() 


BaseWeightBlock:setOptimizer(Optimizer: OptimizerObject)

Parameters:

  • Optimizer: The optimizer to be used.

getOptimizer() 


BaseWeightBlock:getOptimizer(): OptimizerObject

Returns:

  • Optimizer: The optimizer used by the weight block.

setRegularizer() 


BaseWeightBlock:setRegularizer(Regularizer: RegularizerObject)

Parameters:

  • Regularizer: The regularizer to be used.

getRegularizer() 


BaseWeightBlock:getRegularizer(): RegularizerObject

Returns:

  • Regularizer: The regularizer used by the weight block.

Inherited From