From 7584bbd6f3e321cc8bc970739a7cfce29ffcc18b Mon Sep 17 00:00:00 2001
From: haoneng.lhn <haoneng.lhn@alibaba-inc.com>
Date: 星期四, 27 四月 2023 00:21:20 +0800
Subject: [PATCH] update paraformer streaming code
---
funasr/train/trainer.py | 13 ++++++++-----
1 files changed, 8 insertions(+), 5 deletions(-)
diff --git a/funasr/train/trainer.py b/funasr/train/trainer.py
index 9574a0d..7c187e9 100644
--- a/funasr/train/trainer.py
+++ b/funasr/train/trainer.py
@@ -186,9 +186,6 @@
logging.warning("No keep_nbest_models is given. Change to [1]")
trainer_options.keep_nbest_models = [1]
keep_nbest_models = trainer_options.keep_nbest_models
-
- #assert batch_interval is set and >0
- assert trainer_options.batch_interval > 0
output_dir = Path(trainer_options.output_dir)
reporter = Reporter()
@@ -585,10 +582,16 @@
if num_batch_updates % batch_interval == 0:
if options.use_pai and options.oss_bucket is not None:
buffer = BytesIO()
- torch.save(model.state_dict(), buffer)
+ if hasattr(model, "module"):
+ torch.save(model.module.state_dict(), buffer)
+ else:
+ torch.save(model.state_dict(), buffer)
options.oss_bucket.put_object(os.path.join(output_dir, f"{num_batch_updates}step.pb"), buffer.getvalue())
else:
- torch.save(model.state_dict(), os.path.join(output_dir, f"{num_batch_updates}step.pb"))
+ if hasattr(model, "module"):
+ torch.save(model.module.state_dict(), os.path.join(output_dir, f"{num_batch_updates}step.pb"))
+ else:
+ torch.save(model.state_dict(), os.path.join(output_dir, f"{num_batch_updates}step.pb"))
if distributed:
torch.distributed.all_reduce(iterator_stop, ReduceOp.SUM)
--
Gitblit v1.9.1