b30cdf3a1a977927345f407a4c25be2884cfee7f,scripts/segmentation/train.py,Trainer,validation,#Trainer#Any#,156

Before Change

        save_checkpoint(self.net.module, self.args, False)

    def validation(self, epoch):
        total_inter, total_union, total_correct, total_label = 0, 0, 0, 0
        tbar = tqdm(self.eval_data)
        for i, (data, target) in enumerate(tbar):
            outputs = self.evaluator(data, target)
            for (correct, labeled, inter, union) in outputs:
                total_correct += correct
                total_label += labeled
                total_inter += inter
                total_union += union
            pixAcc = 1.0 * total_correct / (np.spacing(1) + total_label)
            IoU = 1.0 * total_inter / (np.spacing(1) + total_union)
            mIoU = IoU.mean()
            tbar.set_description("Epoch %d, validation pixAcc: %.3f, mIoU: %.3f"%\
                (epoch, pixAcc, mIoU))

After Change

        tbar = tqdm(self.eval_data)
        for i, (data, target) in enumerate(tbar):
            outputs = self.evaluator(data.astype(args.dtype, copy=False))
            outputs = [x[0] for x in outputs]
            targets = mx.gluon.utils.split_and_load(target, args.ctx)
            self.metric.update(targets, outputs)
            pixAcc, mIoU = self.metric.get()
            tbar.set_description("Epoch %d, validation pixAcc: %.3f, mIoU: %.3f"%\

Instances