From 37c45ee8d7e4db18d95677c203b3432f3e6dde80 Mon Sep 17 00:00:00 2001
From: nichongjia-2007 <nichongjia@gmail.com>
Date: 星期四, 23 三月 2023 18:33:21 +0800
Subject: [PATCH] add batch interval for saving model
---
funasr/tasks/asr.py | 6 ++++++
funasr/train/trainer.py | 30 +++++++++++++++++++++++++-----
2 files changed, 31 insertions(+), 5 deletions(-)
diff --git a/funasr/tasks/asr.py b/funasr/tasks/asr.py
index e151473..6e0f16a 100644
--- a/funasr/tasks/asr.py
+++ b/funasr/tasks/asr.py
@@ -412,6 +412,12 @@
default="13_15",
help="The range of noise decibel level.",
)
+ parser.add_argument(
+ "--batch_interval",
+ type=int,
+ default=10000,
+ help="The batch interval for saving model.",
+ )
for class_choices in cls.class_choices_list:
# Append --<name> and --<name>_conf.
diff --git a/funasr/train/trainer.py b/funasr/train/trainer.py
index efe2009..4fbdcd9 100644
--- a/funasr/train/trainer.py
+++ b/funasr/train/trainer.py
@@ -94,7 +94,7 @@
wandb_model_log_interval: int
use_pai: bool
oss_bucket: Union[oss2.Bucket, None]
-
+ batch_interval: int
class Trainer:
"""Trainer having a optimizer.
@@ -186,7 +186,10 @@
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()
if trainer_options.use_amp:
@@ -560,13 +563,30 @@
# [For distributed] Because iteration counts are not always equals between
# processes, send stop-flag to the other processes if iterator is finished
iterator_stop = torch.tensor(0).to("cuda" if ngpu > 0 else "cpu")
-
+
+ #get the rank
+ rank = distributed_option.dist_rank
+ #get the num batch updates
+ num_batch_updates = 0
+ #ouput dir
+ output_dir = Path(options.output_dir)
+ #batch interval
+ batch_interval = options.batch_interval
+ assert batch_interval > 0
+
start_time = time.perf_counter()
for iiter, (_, batch) in enumerate(
reporter.measure_iter_time(iterator, "iter_time"), 1
):
assert isinstance(batch, dict), type(batch)
-
+
+ if rank == 0 and hasattr(model.module, "num_updates"):
+ num_batch_updates = model.module.get_num_updates()
+ if (num_batch_updates%batch_interval == 0) and (options.oss_bucket is not None) and options.use_pai:
+ buffer = BytesIO()
+ torch.save(model.state_dict(), buffer)
+ options.oss_bucket.put_object(os.path.join(output_dir, f"{num_batch_updates}batch.pth"), buffer.getvalue())
+
if distributed:
torch.distributed.all_reduce(iterator_stop, ReduceOp.SUM)
if iterator_stop > 0:
@@ -811,4 +831,4 @@
else:
if distributed:
iterator_stop.fill_(1)
- torch.distributed.all_reduce(iterator_stop, ReduceOp.SUM)
\ No newline at end of file
+ torch.distributed.all_reduce(iterator_stop, ReduceOp.SUM)
--
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