From f838e1e40ef365406be6c853b94e596849f842ac Mon Sep 17 00:00:00 2001 From: Jordan Gong Date: Fri, 12 Aug 2022 18:17:14 +0800 Subject: Make SimCLR evaluation less frequent --- simclr/evaluate.py | 23 ++++++++++++----------- 1 file changed, 12 insertions(+), 11 deletions(-) (limited to 'simclr') diff --git a/simclr/evaluate.py b/simclr/evaluate.py index 0f26e16..5c41b84 100644 --- a/simclr/evaluate.py +++ b/simclr/evaluate.py @@ -222,17 +222,18 @@ class SimCLREvalTrainer(SimCLRTrainer): batch, num_batches, global_batch, iter_, num_iters, optim_c.param_groups[0]['lr'], train_loss.item() )) - metrics = torch.Tensor(list(self.eval(loss_fn, device))).mean(0) - eval_loss = metrics[0].item() - eval_accuracy = metrics[1].item() - epoch_log = self.EpochLogRecord(iter_, num_iters, - eval_loss, eval_accuracy) - self.log(logger, epoch_log) - self.save_checkpoint(epoch_log) - if sched_b is not None and self.finetune: - sched_b.step() - if sched_c is not None: - sched_c.step() + if (iter_ + 1) % (num_iters // 10) == 0: + metrics = torch.Tensor(list(self.eval(loss_fn, device))).mean(0) + eval_loss = metrics[0].item() + eval_accuracy = metrics[1].item() + epoch_log = self.EpochLogRecord(iter_, num_iters, + eval_loss, eval_accuracy) + self.log(logger, epoch_log) + self.save_checkpoint(epoch_log) + if sched_b is not None and self.finetune: + sched_b.step() + if sched_c is not None: + sched_c.step() def eval(self, loss_fn: Callable, device: torch.device): backbone, classifier = self.models.values() -- cgit v1.2.3