From 6427c834dfd97b1f05c6659cdc7ccf010bf82fe1 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期一, 24 四月 2023 19:50:07 +0800
Subject: [PATCH] update
---
funasr/bin/train.py | 83 +++++++++++++++++++++++++++++++++++------
1 files changed, 71 insertions(+), 12 deletions(-)
diff --git a/funasr/bin/train.py b/funasr/bin/train.py
old mode 100644
new mode 100755
index e861199..9c8f672
--- 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 +14,12 @@
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.nested_dict_action import NestedDictAction
from funasr.utils.prepare_data import prepare_data
from funasr.utils.types import str2bool
from funasr.utils.types import str_or_none
@@ -24,7 +27,7 @@
def get_parser():
- parser = config_argparse.ArgumentParser(
+ parser = argparse.ArgumentParser(
description="FunASR Common Training Parser",
)
@@ -74,6 +77,12 @@
default=False,
help="Whether to use the find_unused_parameters in "
"torch.nn.parallel.DistributedDataParallel ",
+ )
+ parser.add_argument(
+ "--gpu_id",
+ type=int,
+ default=0,
+ help="local gpu id.",
)
# cudnn related
@@ -277,10 +286,47 @@
default=[],
)
parser.add_argument(
+ "--train_shape_file",
+ type=str, action="append",
+ default=[],
+ )
+ parser.add_argument(
+ "--valid_shape_file",
+ type=str,
+ action="append",
+ default=[],
+ )
+ parser.add_argument(
"--use_preprocessor",
type=str2bool,
default=True,
help="Apply preprocessing to data or not",
+ )
+
+ # optimization related
+ parser.add_argument(
+ "--optim",
+ type=lambda x: x.lower(),
+ default="adam",
+ help="The optimizer type",
+ )
+ parser.add_argument(
+ "--optim_conf",
+ action=NestedDictAction,
+ default=dict(),
+ help="The keyword arguments for optimizer",
+ )
+ parser.add_argument(
+ "--scheduler",
+ type=lambda x: str_or_none(x.lower()),
+ default=None,
+ help="The lr scheduler type",
+ )
+ parser.add_argument(
+ "--scheduler_conf",
+ action=NestedDictAction,
+ default=dict(),
+ help="The keyword arguments for lr scheduler",
)
# most task related
@@ -380,17 +426,15 @@
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:
+ args = build_args(args, parser, extra_task_params)
+ # args = argparse.Namespace(**vars(args), **vars(task_args))
# set random seed
set_all_random_seed(args.seed)
@@ -399,6 +443,7 @@
torch.backends.cudnn.deterministic = args.cudnn_deterministic
# ddp init
+ os.environ['CUDA_VISIBLE_DEVICES'] = str(args.gpu_id)
args.distributed = args.dist_world_size > 1
distributed_option = build_distributed(args)
@@ -420,16 +465,16 @@
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 +488,18 @@
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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