applyStochasticGradientDescent(learningRate:variable:gradient:name:)
The Stochastic gradient descent performs a gradient descent variable = variable - (learningRate * g) where, g is gradient of error wrt variable this op directly writes to the variable
Declaration
func applyStochasticGradientDescent(learningRate learningRateTensor: MPSGraphTensor, variable: MPSGraphVariableOp, gradient gradientTensor: MPSGraphTensor, name: String?) -> MPSGraphOperationParameters
- learningRateTensor:
Scalar tensor which indicates the learning rate to use with the optimizer
- variable:
Variable operation with trainable parameters
- gradientTensor:
Partial gradient of the trainable parameters with respect to loss
- name:
Name for the operation
Return Value
A valid MPSGraphTensor object.