update adavanced clas, including model and dataset

shixian.shi

2023-04-27 aa910b9860d420877d73f36c71302995587b0a49

 funasr/datasets/large_datasets/dataset.py

@@ -28,7 +28,7 @@


class AudioDataset(IterableDataset):
    def __init__(self, scp_lists, data_names, data_types, frontend_conf=None, shuffle=True, mode="train"):
    def __init__(self, scp_lists, data_names, data_types, frontend_conf=None, shuffle=True, mode="train", pre_hwlist=None, pre_prob=0.0):
        self.scp_lists = scp_lists
        self.data_names = data_names
        self.data_types = data_types
@@ -40,6 +40,8 @@
        self.world_size = 1
        self.worker_id = 0
        self.num_workers = 1
        self.pre_hwlist = pre_hwlist
        self.pre_prob = pre_prob

    def set_epoch(self, epoch):
        self.epoch = epoch
@@ -131,6 +133,13 @@
                        sample_dict["sampling_rate"] = sampling_rate
                        if data_name == "speech":
                            sample_dict["key"] = key
                    elif data_type == "text_hotword":
                        text = item
                        segs = text.strip().split()
                        sample_dict[data_name] = segs[1:]
                        if "key" not in sample_dict:
                            sample_dict["key"] = segs[0]
                        sample_dict['hw_tag'] = 1
                    else:
                        text = item
                        segs = text.strip().split()
@@ -167,14 +176,39 @@
    shuffle = conf.get('shuffle', True)
    data_names = conf.get("data_names", "speech,text")
    data_types = conf.get("data_types", "kaldi_ark,text")
    dataset = AudioDataset(scp_lists, data_names, data_types, frontend_conf=frontend_conf, shuffle=shuffle, mode=mode)

    pre_hwfile = conf.get("pre_hwlist", None)
    pre_prob = conf.get("pre_prob", 0)

    hw_config = {"sample_rate": conf.get("sample_rate", 0.6),
                 "double_rate": conf.get("double_rate", 0.1),
                 "hotword_min_length": conf.get("hotword_min_length", 2),
                 "hotword_max_length": conf.get("hotword_max_length", 8)}


    if pre_hwfile is not None:
        pre_hwlist = []
        with open(pre_hwfile, 'r') as fin:
            for line in fin.readlines():
                pre_hwlist.append(line.strip())
    else:
        pre_hwlist = None
        # logging.warning("Previous hwlist: {}".format(pre_hwlist))
    dataset = AudioDataset(scp_lists, 
                           data_names, 
                           data_types, 
                           frontend_conf=frontend_conf, 
                           shuffle=shuffle, 
                           mode=mode, 
                           pre_hwlist=pre_hwlist, 
                           pre_prob=pre_prob)

    filter_conf = conf.get('filter_conf', {})
    filter_fn = partial(filter, **filter_conf)
    dataset = FilterIterDataPipe(dataset, fn=filter_fn)

    if "text" in data_names:
        vocab = {'vocab': dict, 'seg_dict': seg_dict, 'punc_dict': punc_dict, 'bpe_tokenizer': bpe_tokenizer}
        vocab = {'vocab': dict, 'seg_dict': seg_dict, 'punc_dict': punc_dict, 'bpe_tokenizer': bpe_tokenizer, 'hw_config': hw_config}
        tokenize_fn = partial(tokenize, **vocab)
        dataset = MapperIterDataPipe(dataset, fn=tokenize_fn)