From 1596f6f414f6f41da66506debb1dff19fffeb3ec Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期一, 24 六月 2024 11:55:17 +0800
Subject: [PATCH] fixbug hotwords

---
 funasr/datasets/large_datasets/build_dataloader.py |   54 ++++++++++++++++++++++++++++++++++++++----------------
 1 files changed, 38 insertions(+), 16 deletions(-)

diff --git a/funasr/datasets/large_datasets/build_dataloader.py b/funasr/datasets/large_datasets/build_dataloader.py
index 7889e70..da04717 100644
--- a/funasr/datasets/large_datasets/build_dataloader.py
+++ b/funasr/datasets/large_datasets/build_dataloader.py
@@ -6,11 +6,12 @@
 
 import sentencepiece as spm
 from torch.utils.data import DataLoader
-from typeguard import check_argument_types
 
 from funasr.datasets.large_datasets.dataset import Dataset
-from funasr.iterators.abs_iter_factory import AbsIterFactory
-from funasr.text.abs_tokenizer import AbsTokenizer
+from funasr.datasets.large_datasets.abs_iter_factory import AbsIterFactory
+from funasr.tokenizer.abs_tokenizer import AbsTokenizer
+
+from funasr.register import tables
 
 
 def read_symbol_table(symbol_table_file):
@@ -43,7 +44,6 @@
 
 class SentencepiecesTokenizer(AbsTokenizer):
     def __init__(self, model: Union[Path, str]):
-        assert check_argument_types()
         self.model = str(model)
         self.sp = None
 
@@ -64,24 +64,46 @@
         return self.sp.DecodePieces(list(tokens))
 
 
+@tables.register("dataset_classes", "LargeDataset")
 class LargeDataLoader(AbsIterFactory):
     def __init__(self, args, mode="train"):
-        symbol_table = read_symbol_table(args.token_list) if args.token_list is not None else None
-        seg_dict = load_seg_dict(args.seg_dict_file) if args.seg_dict_file is not None else None
-        punc_dict = load_seg_dict(args.punc_dict_file) if args.punc_dict_file is not None else None
-        bpe_tokenizer = load_seg_dict(args.bpemodel_file) if args.bpemodel_file is not None else None
+        symbol_table, seg_dict, punc_dict, bpe_tokenizer = None, None, None, None
+        if hasattr(args, "token_list") and args.token_list is not None:
+            symbol_table = read_symbol_table(args.token_list)
+        if hasattr(args, "seg_dict_file") and args.seg_dict_file is not None:
+            seg_dict = load_seg_dict(args.seg_dict_file)
+        if hasattr(args, "punc_list") and args.punc_list is not None:
+            punc_dict = read_symbol_table(args.punc_list)
+        if hasattr(args, "bpemodel") and args.bpemodel is not None:
+            bpe_tokenizer = SentencepiecesTokenizer(args.bpemodel)
         self.dataset_conf = args.dataset_conf
-        self.frontend_conf = args.frontend_conf
+        if "frontend_conf" not in args:
+            self.frontend_conf = None
+        else:
+            self.frontend_conf = args.frontend_conf
+        self.speed_perturb = args.speed_perturb if hasattr(args, "speed_perturb") else None
         logging.info("dataloader config: {}".format(self.dataset_conf))
         batch_mode = self.dataset_conf.get("batch_mode", "padding")
-        self.dataset = Dataset(args.data_list, symbol_table, seg_dict, punc_dict, bpe_tokenizer,
-                               self.dataset_conf, self.frontend_conf, speed_perturb=args.speed_perturb,
-                               mode=mode, batch_mode=batch_mode)
+        data_list = args.train_data_file if mode == "train" else args.valid_data_file
+        self.dataset = Dataset(
+            data_list,
+            symbol_table,
+            seg_dict,
+            punc_dict,
+            bpe_tokenizer,
+            self.dataset_conf,
+            self.frontend_conf,
+            speed_perturb=self.speed_perturb if mode == "train" else None,
+            mode=mode,
+            batch_mode=batch_mode,
+        )
 
     def build_iter(self, epoch, shuffle=True):
         self.dataset.set_epoch(epoch)
-        data_loader = DataLoader(self.dataset,
-                                 batch_size=None,
-                                 pin_memory=True,
-                                 num_workers=self.dataset_conf.get("num_workers", 8))
+        data_loader = DataLoader(
+            self.dataset,
+            batch_size=None,
+            pin_memory=True,
+            num_workers=self.dataset_conf.get("num_workers", 8),
+        )
         return data_loader

--
Gitblit v1.9.1