aab3902d4a7d55f5a86058854adc36b8a12c873f,catalyst/dl/callbacks/base.py,OptimizerCallback,on_batch_end,#OptimizerCallback#Any#,202

Before Change

            scaled_loss = self.fp16_grad_scale * loss.float()
            scaled_loss.backward()

            master_params = list(optimizer.param_groups[0]["params"])
            model_params = list(
                filter(lambda p: p.requires_grad, model.parameters())
            )

After Change

        // or expose another c"tor argument.
        if hasattr(optimizer, "_amp_stash"):
            from apex import amp
            with amp.scale_loss(loss, optimizer) as scaled_loss:
                scaled_loss.backward()
        else:
            loss.backward()

        if (self._accumulation_counter + 1) % self.accumulation_steps == 0:

Instances