TensorBoardLogger has the wrong epoch numbers much more than the fact

[AlbireoBai]

Bug description

I used the following code to log the metrics, but I found that the epoch recorded in the tensorboard logger is much more than it should have:

def training_step(self, batch, batch_idx):
    x, y  = batch
    y_hat = self.forward(x)
    loss = torch.sqrt(self.loss_fn(y_hat,y))
    self.log("train_loss", loss, logger=True, prog_bar=True, on_epoch=True)
    return loss 
    
def validation_step(self, batch, batch_idx):
    x, y  = batch
    y_hat = self.forward(x)
    loss = torch.sqrt(self.loss_fn(y_hat,y))
    self.log("valid_loss", loss, logger=True, prog_bar=True, on_epoch=True)
    return loss

pl.Train(..., logger=TensorBoardLogger(save_dir='store',version=log_path), ....)

In the configure, I set max_epoch=10000, but in the logger, I got epoches more than 650k:

What version are you seeing the problem on?

v2.1

How to reproduce the bug

def training_step(self, batch, batch_idx):
        x, y  = batch
        y_hat = self.forward(x)
        loss = torch.sqrt(self.loss_fn(y_hat,y))
        self.log("train_loss", loss, logger=True, prog_bar=True, on_epoch=True)
        return loss 
        
    def validation_step(self, batch, batch_idx):
        x, y  = batch
        y_hat = self.forward(x)
        loss = torch.sqrt(self.loss_fn(y_hat,y))
        self.log("valid_loss", loss, logger=True, prog_bar=True, on_epoch=True)
        return loss

   pl.Train(..., logger=TensorBoardLogger(save_dir='store',version=log_path), ....) # u can use any path you like

Error messages and logs

# Error messages and logs here please

Environment

Current environment

#- Lightning Component (e.g. Trainer, LightningModule, LightningApp, LightningWork, LightningFlow): 
#- PyTorch Lightning Version (e.g., 1.5.0): 2.1.3
#- Lightning App Version (e.g., 0.5.2):
#- PyTorch Version (e.g., 2.0):
#- Python version (e.g., 3.9): 2.1.2
#- OS (e.g., Linux):
#- CUDA/cuDNN version:
#- GPU models and configuration:
#- How you installed Lightning(`conda`, `pip`, source): pip 
#- Running environment of LightningApp (e.g. local, cloud):

More info

No response

[ryan597]

The graphs shown are correct, the x-axis is the steps, the y-axis shows your epoch number. In the second image, the x-axis is again the steps.

I can see that your epochs go to 10,000 from the y-axis in the first image

[AlbireoBai]

The graphs shown are correct, the x-axis is the steps, the y-axis shows your epoch number. In the second image, the x-axis is again the steps.

I can see that your epochs go to 10,000 from the y-axis in the first image

The graphs shown are correct, the x-axis is the steps, the y-axis shows your epoch number. In the second image, the x-axis is again the steps.

I can see that your epochs go to 10,000 from the y-axis in the first image

Thanks a lot, I have realised that I need to transfer the y-axis in the 1st image to the x-axis in the 2nd image if I want to get a epoch-val_loss image