From abde816a6cd393697eac6ffea300061ec0ed8aae Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期一, 24 四月 2023 17:08:28 +0800
Subject: [PATCH] update
---
funasr/bin/train.py | 38 ++++++++++++++++++++++++++------------
1 files changed, 26 insertions(+), 12 deletions(-)
diff --git a/funasr/bin/train.py b/funasr/bin/train.py
old mode 100644
new mode 100755
index e861199..c54e851
--- a/funasr/bin/train.py
+++ b/funasr/bin/train.py
@@ -1,3 +1,5 @@
+#!/usr/bin/env python3
+
import argparse
import logging
import os
@@ -12,11 +14,11 @@
from funasr.build_utils.build_model import build_model
from funasr.build_utils.build_optimizer import build_optimizer
from funasr.build_utils.build_scheduler import build_scheduler
+from funasr.build_utils.build_trainer import build_trainer
from funasr.text.phoneme_tokenizer import g2p_choices
from funasr.torch_utils.model_summary import model_summary
from funasr.torch_utils.pytorch_version import pytorch_cudnn_version
from funasr.torch_utils.set_all_random_seed import set_all_random_seed
-from funasr.utils import config_argparse
from funasr.utils.prepare_data import prepare_data
from funasr.utils.types import str2bool
from funasr.utils.types import str_or_none
@@ -24,7 +26,7 @@
def get_parser():
- parser = config_argparse.ArgumentParser(
+ parser = argparse.ArgumentParser(
description="FunASR Common Training Parser",
)
@@ -380,17 +382,15 @@
help="oss bucket.",
)
- # task related
- parser.add_argument("--task_name", help="for different task")
-
return parser
if __name__ == '__main__':
parser = get_parser()
- args = parser.parse_args()
- task_args = build_args(args)
- args = argparse.Namespace(**vars(args), **vars(task_args))
+ args, extra_task_params = parser.parse_known_args()
+ if extra_task_params:
+ task_args = build_args(args, extra_task_params)
+ args = argparse.Namespace(**vars(args), **vars(task_args))
# set random seed
set_all_random_seed(args.seed)
@@ -420,16 +420,16 @@
prepare_data(args, distributed_option)
model = build_model(args)
- optimizer = build_optimizer(args, model=model)
- scheduler = build_scheduler(args, optimizer)
+ optimizers = build_optimizer(args, model=model)
+ schedulers = build_scheduler(args, optimizers)
logging.info("world size: {}, rank: {}, local_rank: {}".format(distributed_option.dist_world_size,
distributed_option.dist_rank,
distributed_option.local_rank))
logging.info(pytorch_cudnn_version())
logging.info(model_summary(model))
- logging.info("Optimizer: {}".format(optimizer))
- logging.info("Scheduler: {}".format(scheduler))
+ logging.info("Optimizer: {}".format(optimizers))
+ logging.info("Scheduler: {}".format(schedulers))
# dump args to config.yaml
if not distributed_option.distributed or distributed_option.dist_rank == 0:
@@ -443,4 +443,18 @@
else:
yaml_no_alias_safe_dump(vars(args), f, indent=4, sort_keys=False)
+ # dataloader for training/validation
train_dataloader, valid_dataloader = build_dataloader(args)
+
+ # Trainer, including model, optimizers, etc.
+ trainer = build_trainer(
+ args=args,
+ model=model,
+ optimizers=optimizers,
+ schedulers=schedulers,
+ train_dataloader=train_dataloader,
+ valid_dataloader=valid_dataloader,
+ distributed_option=distributed_option
+ )
+
+ trainer.run()
--
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