question: Code not printing values in trained_epoch_end
context: My code is not printing print('train acc loss',acc,loss) in trained_epoch_end but its printing print('val acc loss',acc,loss) in validation_epoch_end
  class Model(LightningModule):
    def __init__(self):
      super(Model,self).__init__()
      self.model=ResneT(21)
      self.lr=1e-3
      self.bs=128
      self.worker=6
      self.acc=torchmetrics.Accuracy()
      self.creterion=nn.BCEWithLogitsLoss()
      self.scheduler='lambda'
    def forward(self,x):
      x=self.model(x)
      return x
  
    def configure_optimizers(self):
      opt=torch.optim.AdamW(params=self.parameters(),lr=self.lr )
      return opt
  
    def train_dataloader(self):
      dataset=DataReader(train_df)
      dataloader=DataLoader(dataset,batch_size=self.bs,num_workers=self.worker,shuffle=True,
                           pin_memory=True,collate_fn=collate_fn)
      return dataloader
  
    def training_step(self,batch,batch_idx):
      signal,label=batch
      out=self(signal.float())
      loss=self.creterion(out.flatten(),label.float().flatten())
      acc=self.acc(out.flatten(),label.long().flatten())
      return {'loss':loss,'acc':acc}
  
    def trained_epoch_end(self,outputs):
      acc=torch.stack([x['acc'] for x in outputs]).mean().detach().cpu().numpy().round(2)
      loss=torch.stack([x['loss'] for x in outputs]).mean().detach().cpu().numpy().round(2)
      self.log('train acc',acc)
      self.log('train loss',loss)
      print('train acc loss',acc,loss)
  
    def val_dataloader(self):
      dataset=DataReader(val_df)
      dataloader=DataLoader(dataset,batch_size=self.bs,num_workers=self.worker,shuffle=False,
                            pin_memory=True,
                           collate_fn=collate_fn)
      return dataloader
  
    def validation_step(self,batch,batch_idx):
      signal,label=batch
      out=self(signal.float())
      loss=self.creterion(out.flatten(),label.float().flatten())
      acc=self.acc(out.flatten(),label.long().flatten())
      return {'loss':loss,'acc':acc}
  
    def validation_epoch_end(self,outputs):
      acc=torch.stack([x['acc'] for x in outputs]).mean().detach().cpu().numpy().round(2)
      loss=torch.stack([x['loss'] for x in outputs]).mean().detach().cpu().numpy().round(2)
      print('val acc loss',self.current_epoch,acc,loss)
      self.log('val acc',acc)
      self.log('val loss',loss)
answer: You need to implement training_epoch_end, not trained_epoch_end: 
    
      
        pytorch-lightning/pytorch_lightning/core/lightning.py
      
      
           Line 689
        in
        1515ef9
      
    
    
      
  
          
            
             def training_epoch_end(self, outputs: EPOCH_OUTPUT) -> None: