funasr1.0

游雁

2024-01-15 2a0b2c795b161a0bd56e026c53eb605fea9e142c

 funasr/bin/train.py

@@ -64,14 +64,14 @@

   tokenizer = kwargs.get("tokenizer", None)
   if tokenizer is not None:
      tokenizer_class = tables.tokenizer_classes.get(tokenizer.lower())
      tokenizer_class = tables.tokenizer_classes.get(tokenizer)
      tokenizer = tokenizer_class(**kwargs["tokenizer_conf"])
      kwargs["tokenizer"] = tokenizer
   
   # build frontend if frontend is none None
   frontend = kwargs.get("frontend", None)
   if frontend is not None:
      frontend_class = tables.frontend_classes.get(frontend.lower())
      frontend_class = tables.frontend_classes.get(frontend)
      frontend = frontend_class(**kwargs["frontend_conf"])
      kwargs["frontend"] = frontend
      kwargs["input_size"] = frontend.output_size()
@@ -79,7 +79,7 @@
   # import pdb;
   # pdb.set_trace()
   # build model
   model_class = tables.model_classes.get(kwargs["model"].lower())
   model_class = tables.model_classes.get(kwargs["model"])
   model = model_class(**kwargs, **kwargs["model_conf"], vocab_size=len(tokenizer.token_list))


@@ -141,12 +141,12 @@
   # import pdb;
   # pdb.set_trace()
   # dataset
   dataset_class = tables.dataset_classes.get(kwargs.get("dataset", "AudioDataset").lower())
   dataset_class = tables.dataset_classes.get(kwargs.get("dataset", "AudioDataset"))
   dataset_tr = dataset_class(kwargs.get("train_data_set_list"), frontend=frontend, tokenizer=tokenizer, **kwargs.get("dataset_conf"))

   # dataloader
   batch_sampler = kwargs["dataset_conf"].get("batch_sampler", "DynamicBatchLocalShuffleSampler")
   batch_sampler_class = tables.batch_sampler_classes.get(batch_sampler.lower())
   batch_sampler_class = tables.batch_sampler_classes.get(batch_sampler)
   if batch_sampler is not None:
      batch_sampler = batch_sampler_class(dataset_tr, **kwargs.get("dataset_conf"))
   dataloader_tr = torch.utils.data.DataLoader(dataset_tr,