cf1c64a5f7cffe7a362cc772752f8f226fb04f22,train.py,,validate,#Any#Any#Any#Any#Any#Any#,204

Before Change

        stats["num_updates"] = num_updates

    if hasattr(save_checkpoint, "best"):
        stats["best"] = min(save_checkpoint.best, stats["valid_loss"])

    progress.print(stats)

    return stats["valid_loss"]

After Change

        log_output = trainer.valid_step(sample)

        for k, v in log_output.items():
            if k in ["loss", "nll_loss", "sample_size"]:
                continue
            extra_meters[k].update(v)

    // log validation stats
    stats = get_valid_stats(trainer)

Instances