41ca64cb4b975a83df082e5d8be7da85b1a15ba1,mmcv/runner/hooks/optimizer.py,OptimizerHook,after_train_iter,#OptimizerHook#Any#,19

Before Change

        runner.optimizer.zero_grad()
        runner.outputs["loss"].backward()
        if self.grad_clip is not None:
            self.clip_grads(runner.model.parameters())
        runner.optimizer.step()

After Change

        runner.optimizer.zero_grad()
        runner.outputs["loss"].backward()
        if self.grad_clip is not None:
            grad_norm = self.clip_grads(runner.model.parameters())
            if grad_norm is not None:
                // Add grad norm to the logger
                runner.log_buffer.update({"grad_norm": grad_norm},
                                         runner.outputs["num_samples"])
        runner.optimizer.step()

Instances