From 4ace5a95b052d338947fc88809a440ccd55cf6b4 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期四, 16 十一月 2023 16:39:52 +0800
Subject: [PATCH] funasr pages

---
 funasr/tasks/abs_task.py |   31 +++++++++++++++----------------
 1 files changed, 15 insertions(+), 16 deletions(-)

diff --git a/funasr/tasks/abs_task.py b/funasr/tasks/abs_task.py
index 0fb77a9..f7f13d2 100644
--- a/funasr/tasks/abs_task.py
+++ b/funasr/tasks/abs_task.py
@@ -32,8 +32,6 @@
 import yaml
 from funasr.models.base_model import FunASRModel
 from torch.utils.data import DataLoader
-from typeguard import check_argument_types
-from typeguard import check_return_type
 
 from funasr import __version__
 from funasr.datasets.dataset import AbsDataset
@@ -73,6 +71,7 @@
 from funasr.utils.types import str_or_none
 from funasr.utils.wav_utils import calc_shape, generate_data_list, filter_wav_text
 from funasr.utils.yaml_no_alias_safe_dump import yaml_no_alias_safe_dump
+from funasr.modules.lora.utils import mark_only_lora_as_trainable
 
 try:
     import wandb
@@ -269,7 +268,6 @@
 
     @classmethod
     def get_parser(cls) -> config_argparse.ArgumentParser:
-        assert check_argument_types()
 
         class ArgumentDefaultsRawTextHelpFormatter(
             argparse.RawTextHelpFormatter,
@@ -955,11 +953,22 @@
             default=None,
             help="oss bucket.",
         )
+        group.add_argument(
+            "--enable_lora",
+            type=str2bool,
+            default=False,
+            help="Apply lora for finetuning.",
+        )
+        group.add_argument(
+            "--lora_bias",
+            type=str,
+            default="none",
+            help="lora bias.",
+        )
 
         cls.trainer.add_arguments(parser)
         cls.add_task_arguments(parser)
 
-        assert check_return_type(parser)
         return parser
 
     @classmethod
@@ -1007,7 +1016,6 @@
             return _cls
 
         # This method is used only for --print_config
-        assert check_argument_types()
         parser = cls.get_parser()
         args, _ = parser.parse_known_args()
         config = vars(args)
@@ -1047,7 +1055,6 @@
 
     @classmethod
     def check_required_command_args(cls, args: argparse.Namespace):
-        assert check_argument_types()
         if hasattr(args, "required"):
             for k in vars(args):
                 if "-" in k:
@@ -1077,7 +1084,6 @@
             inference: bool = False,
     ) -> None:
         """Check if the dataset satisfy the requirement of current Task"""
-        assert check_argument_types()
         mes = (
             f"If you intend to use an additional input, modify "
             f'"{cls.__name__}.required_data_names()" or '
@@ -1104,14 +1110,12 @@
 
     @classmethod
     def print_config(cls, file=sys.stdout) -> None:
-        assert check_argument_types()
         # Shows the config: e.g. python train.py asr --print_config
         config = cls.get_default_config()
         file.write(yaml_no_alias_safe_dump(config, indent=4, sort_keys=False))
 
     @classmethod
     def main(cls, args: argparse.Namespace = None, cmd: Sequence[str] = None):
-        assert check_argument_types()
         print(get_commandline_args(), file=sys.stderr)
         if args is None:
             parser = cls.get_parser()
@@ -1148,7 +1152,6 @@
 
     @classmethod
     def main_worker(cls, args: argparse.Namespace):
-        assert check_argument_types()
 
         # 0. Init distributed process
         distributed_option = build_dataclass(DistributedOption, args)
@@ -1256,6 +1259,8 @@
             dtype=getattr(torch, args.train_dtype),
             device="cuda" if args.ngpu > 0 else "cpu",
         )
+        if args.enable_lora:
+            mark_only_lora_as_trainable(model, args.lora_bias)
         for t in args.freeze_param:
             for k, p in model.named_parameters():
                 if k.startswith(t + ".") or k == t:
@@ -1556,7 +1561,6 @@
         - 4 epoch with "--num_iters_per_epoch" == 4
 
         """
-        assert check_argument_types()
         iter_options = cls.build_iter_options(args, distributed_option, mode)
 
         # Overwrite iter_options if any kwargs is given
@@ -1589,7 +1593,6 @@
     def build_sequence_iter_factory(
             cls, args: argparse.Namespace, iter_options: IteratorOptions, mode: str
     ) -> AbsIterFactory:
-        assert check_argument_types()
 
         if hasattr(args, "frontend_conf"):
             if args.frontend_conf is not None and "fs" in args.frontend_conf:
@@ -1683,7 +1686,6 @@
             iter_options: IteratorOptions,
             mode: str,
     ) -> AbsIterFactory:
-        assert check_argument_types()
 
         dataset = ESPnetDataset(
             iter_options.data_path_and_name_and_type,
@@ -1788,7 +1790,6 @@
     def build_multiple_iter_factory(
             cls, args: argparse.Namespace, distributed_option: DistributedOption, mode: str
     ):
-        assert check_argument_types()
         iter_options = cls.build_iter_options(args, distributed_option, mode)
         assert len(iter_options.data_path_and_name_and_type) > 0, len(
             iter_options.data_path_and_name_and_type
@@ -1885,7 +1886,6 @@
             inference: bool = False,
     ) -> DataLoader:
         """Build DataLoader using iterable dataset"""
-        assert check_argument_types()
         # For backward compatibility for pytorch DataLoader
         if collate_fn is not None:
             kwargs = dict(collate_fn=collate_fn)
@@ -1935,7 +1935,6 @@
             device: Device type, "cpu", "cuda", or "cuda:N".
 
         """
-        assert check_argument_types()
         if config_file is None:
             assert model_file is not None, (
                 "The argument 'model_file' must be provided "

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