How to show the validation loss in progress bar?

[FeryET]

Hi.

I'm trying to come up with ways to get my validation loss shown in the progress bar. My model is defined like this:

class DummyNet(pl.LightningModule):
    def __init__(self, batch_size):
        super().__init__()
        self.batch_size = batch_size
        self.fc = nn.Sequential(
            nn.Dropout(0.5),
            nn.Linear(512, 2)
        )
        # loss
        self.loss_fn = nn.CrossEntropyLoss()
        # metrics
        metrics = torchmetrics.MetricCollection(
            {
                "accuracy": torchmetrics.Accuracy(),
                "precision": torchmetrics.Precision(),
                "recall": torchmetrics.Recall(),
                "auc": torchmetrics.AUC(reorder=True),
            }, 
        )
        self.f1 = nn.ModuleDict({
            "train_f1": torchmetrics.F1(),
            "val_f1": torchmetrics.F1(),
            "test_f1": torchmetrics.F1(),
        })
        self.metrics = nn.ModuleDict({
            f"{k}_metrics": metrics.clone(prefix=k) for k in "train val test".split()
        })
    def forward(self, x):
        x = self.fc(x)
        return x
    
    def loop_step(self, batch, stage):
        x, targets = batch["windows"], batch["diagnosis"]
        logits = self(x)
        loss = self.loss_fn(logits, targets)
        preds = logits.argmax(-1)
        # computing metrics
        f1_str = f"{stage}_f1"
        metric_str = f"{stage}_metrics"
        self.f1[f1_str](preds, targets)
        self.metrics[metric_str](preds, targets)
        # logging metrics
        on_step = False if stage != "train" else True
        self.log(f1_str, self.f1[f1_str], on_step=on_step, on_epoch=True)
        self.log_dict(self.metrics[metric_str], on_step=False, on_epoch=True)   
        self.log(f"{stage}_loss", loss, on_step=on_step, on_epoch=True)
        return loss
    
    def training_step(self, batch, batch_idx):
        return self.loop_step(batch, "train")
    
    def validation_step(self, batch, batch_idx):
        return self.loop_step(batch, "val")

    def testing_step(self, batch, batch_idx):
        return self.loop_step(batch, "test")

    def configure_optimizers(self):
        return torch.optim.AdamW(self.parameters(), lr=0.001, weight_decay=0.01)

But as of now none of my metrics nor my validation loss comes up in the progress bar. Is it because I'm returning loss in the dictionary and not "{stage}_loss"?

Thank you.

[akihironitta]

Hi @FeryET, I believe the below should work as documented in https://pytorch-lightning.readthedocs.io/en/latest/extensions/logging.html#automatic-logging.

self.log(..., prog_bar=True)