def step()

in hype/rsgd.py [0:0]

• 16 lines of code
• 6 McCabe index (conditional complexity)

    def step(self, lr=None, counts=None, **kwargs):
        """Performs a single optimization step.

        Arguments:
            lr (float, optional): learning rate for the current update.
        """
        loss = None

        for group in self.param_groups:
            for p in group['params']:
                lr = lr or group['lr']
                rgrad = group['rgrad']
                expm = group['expm']

                if p.grad is None:
                    continue
                d_p = p.grad.data
                # make sure we have no duplicates in sparse tensor
                if d_p.is_sparse:
                    d_p = d_p.coalesce()
                d_p = rgrad(p.data, d_p)
                d_p.mul_(-lr)
                expm(p.data, d_p)

        return loss