How to concatenate outputs on epoch end

At each train/validation step I am storing the number of TP, FP, TN, FN. On epoch end I would like to concatenate them but it throws me an error, the code:

    def shared_step(self, batch, stage):
        image, mask = batch
        out = self.forward(image)
        loss = self.criterion(out, mask.long())
        tp, fp, fn, tn = smp.metrics.get_stats(torch.argmax(out, 1).unsqueeze(1), mask.long(), mode='multiclass', num_classes = 5)
        self.log(f'{stage}_loss', loss)

        return {"loss": loss, "tp": tp, "fp": fp, "fn": fn, "tn": tn}
    
    def shared_epoch_end(self, outputs, stage):
        
        tp = torch.cat([x["tp"] for x in outputs])
        fp = torch.cat([x["fp"] for x in outputs])
        fn = torch.cat([x["fn"] for x in outputs])
        tn = torch.cat([x["tn"] for x in outputs])

        iou = {f"{stage}_IoU": smp.metrics.iou_score(tp, fp, fn, tn, reduction="micro-imagewise")}
        self.log_dict(iou, prog_bar=True)

    def validation_step(self, batch, batch_idx):
        return self.shared_step(batch, "valid")

    def on_validation_epoch_end(self, outputs):
        return self.shared_epoch_end(outputs, "valid")

And this is the error:

TypeError: on_validation_epoch_end() missing 1 required positional argument: 'outputs'

The hook on_validation_epoch_end does not take any additional arguments. It would need to be defined as

def on_validation_epoch_end(self):
    ...

If you would like to access the outputs from validation step, you need to use

validation_epoch_end (remove the β€œon_”):

def validation_epoch_end(self, outputs):  # note the name without "on_"
    ...
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Everything clear, thank you so much!

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