How to know the trained model is correct?
I use PyTorch Lightning for model training, during which I use ModelCheckpoint to save loading points. Finally, I would like to know whether the model is loaded correctly. Let me know if you require further information?
checkpoint_callback = ModelCheckpoint(
        filename='tb1000_{epoch: 02d}-{step}',
        monitor='val/acc@1',
        save_top_k=5,
        mode='max')

wandb_logger = pl.loggers.wandb.WandbLogger(
        name=run_name,
        project=args.project,
        entity=args.entity,
        offline=args.offline,
        log_model='all')

model = BYOL(**args.__dict__, num_classes=dm.num_classes)

trainer = pl.Trainer.from_argparse_args(args, 
         logger=wandb_logger, callbacks=[checkpoint_callback])

trainer.fit(model, dm)

# Loading and testing
model_test = BYOL(**args.__dict__, num_classes=dm.num_classes)
path = &quot;/tb100_epoch= 819-step=39359.ckpt&quot;
model_test.load_from_checkpoint(path)


load_from_checkpoint() will return a model with trained weights, so you need to assign it to a new variable.
model_test = model_test.load_from_checkpoint(path)

or
model_test = BYOL.load_from_checkpoint(path)

