9334d336f027e8b90d5751458c7794f8a0167559,thinc/shims/mxnet.py,MXNetShim,finish_update,#MXNetShim#Any#,59

Before Change

                if i._grad is not None
            ]
            mxnet.gluon.utils.clip_global_norm(grads, optimizer.grad_clip)
        if self._trainer:
            self._trainer.step(1)
        for param in self._model.collect_params().values():
            param.zero_grad()
        self._update_mxnet_averages(optimizer)

After Change

    def finish_update(self, optimizer: Optimizer):
        for value in self._model.collect_params().values():
            grad = cast(FloatsXd, mxnet2xp(value.grad()))
            param = cast(FloatsXd, mxnet2xp(value.data()))
            param, _ = optimizer((value.name, value.name), param, grad)
            value.set_data(xp2mxnet(param))

    def copy(self, ctx: "mx.context.Context" = None):
        if ctx is None:

Instances