scripts/optimizers.py
def _compute_step(self, grad):
        """
        Computes one SGD step based on the given gradient.

        :param grad: the gradient to optimize with
        :return: the step, size [dim]
        """
        step = -self.stepsize * grad
        if self.stepsize > self.min_stepsize:
            self.stepsize *= self.decay
        return step

        Computes one SGD step based on the given gradient.

        :param grad: the gradient to optimize with
        :return: the step, size [dim]
        
Computes one SGD step based on the given gradient.
Computes one SGD step based on the given gradient .
def _compute_step(self, grad):
        step = -self.stepsize * grad
        if self.stepsize > self.min_stepsize:
            self.stepsize *= self.decay
        return step
def _compute_step ( self , grad ) : step = - self . stepsize * grad if self . stepsize > self . min_stepsize : self . stepsize *= self . decay return step
Computes one SGD step based on the given gradient.
Computes one SGD step based on the given gradient .
"""
        Computes one SGD step based on the given gradient.

        :param grad: the gradient to optimize with
        :return: the step, size [dim]
        """
the step, size [dim]
the step size [ dim ]
self
grad
the gradient to optimize with
the gradient to optimize with