From 873cfae5c347b940e38e853d8579a6b4e85ada05 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期日, 24 三月 2024 00:45:45 +0800
Subject: [PATCH] update
---
funasr/train_utils/trainer.py | 33 ++++++++++++++++++++++++++++++---
1 files changed, 30 insertions(+), 3 deletions(-)
diff --git a/funasr/train_utils/trainer.py b/funasr/train_utils/trainer.py
index 3e83581..d0023fd 100644
--- a/funasr/train_utils/trainer.py
+++ b/funasr/train_utils/trainer.py
@@ -248,8 +248,15 @@
optim.zero_grad()
speed_stats = {}
time5 = time.perf_counter()
-
+ iterator_stop = torch.tensor(0).to(self.device)
+ dist.barrier()
+ print(f"before iter, iterator_stop: {iterator_stop}\n")
+ dataloader_train.batch_sampler.set_epoch(epoch)
for batch_idx, batch in enumerate(dataloader_train):
+ if self.use_ddp or self.use_fsdp:
+ dist.all_reduce(iterator_stop, dist.ReduceOp.SUM)
+ if iterator_stop > 0:
+ break
self.batch_total += 1
time1 = time.perf_counter()
speed_stats["data_load"] = f"{time1-time5:0.3f}"
@@ -356,7 +363,11 @@
if (batch_idx+1) % self.save_checkpoint_interval == 0:
self.save_checkpoint(epoch, model=model, optim=optim, scheduler=scheduler, scaler=scaler, step=batch_idx+1)
-
+ else:
+ if self.use_ddp or self.use_fsdp:
+ iterator_stop.fill_(1)
+ dist.all_reduce(iterator_stop, dist.ReduceOp.SUM)
+
if self.use_ddp or self.use_fsdp:
dist.barrier()
@@ -383,7 +394,16 @@
speed_stats = {}
time5 = time.perf_counter()
+ iterator_stop = torch.tensor(0).to(self.device)
+ dist.barrier()
+ print(f"before iter, iterator_stop: {iterator_stop}\n")
for batch_idx, batch in enumerate(dataloader_val):
+ if self.use_ddp or self.use_fsdp:
+ dist.all_reduce(iterator_stop, dist.ReduceOp.SUM)
+ if epoch >= 1:
+ print(f"iterator_stop: {iterator_stop}\n")
+ if iterator_stop > 0:
+ break
time1 = time.perf_counter()
speed_stats["data_load"] = f"{time1 - time5:0.3f}"
batch = to_device(batch, self.device)
@@ -433,9 +453,16 @@
tag="val",
)
+ else:
+ if self.use_ddp or self.use_fsdp:
+ iterator_stop.fill_(1)
+ dist.all_reduce(iterator_stop, dist.ReduceOp.SUM)
+
self.val_acc_list.append(self.val_acc_avg)
model.train()
-
+
+
+
if self.use_ddp or self.use_fsdp:
dist.barrier()
--
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