batch

游雁

2024-04-29 f57b68121a526baea43b2e93f4540d8a2995f633

 funasr/datasets/audio_datasets/index_ds.py

@@ -14,34 +14,37 @@
@tables.register("index_ds_classes", "IndexDSJsonlRankFull")
@tables.register("index_ds_classes", "IndexDSJsonlRankSplit")
class IndexDSJsonlRankFull(torch.utils.data.Dataset):
    

    def __init__(self, path: str, **kwargs):
        super().__init__()
        self.max_source_length = kwargs.get("max_source_length", 2048)
        self.min_source_length = kwargs.get("min_source_length", 0)
        self.max_target_length = kwargs.get("max_target_length", 2048)
        self.min_target_length = kwargs.get("min_target_length", 0)
        self.max_token_length = kwargs.get("max_token_length", 2200)

        is_training = kwargs.get("is_training", True)
        if not (path.endswith(".jsonl") or path.endswith(".json")):
            # jsonl list file
            data_split_num = kwargs.get("data_split_num", 1)
            data_split_i = kwargs.get("data_split_i", 0)
            

            if not is_training:
                data_split_num = 1
                data_split_i = 0
            with open(path, encoding='utf-8') as fin:
            with open(path, encoding="utf-8") as fin:
                file_list_all = fin.readlines()
    
                num_per_slice = (len(file_list_all)-1) // data_split_num + 1
                file_list = file_list_all[data_split_i * num_per_slice:(data_split_i + 1) * num_per_slice]

                num_per_slice = (len(file_list_all) - 1) // data_split_num + 1
                file_list = file_list_all[
                    data_split_i * num_per_slice : (data_split_i + 1) * num_per_slice
                ]
                logging.info(
                    f"is_training: {is_training}, data_split_num: {data_split_num}, data_split_i: {data_split_i}, \nfile_list: {file_list}, \nfile_list_all: {file_list_all}")
        
                    f"is_training: {is_training}, data_split_num: {data_split_num}, data_split_i: {data_split_i}, \nfile_list: {file_list}, \nfile_list_all: {file_list_all}"
                )

        else:
            file_list = [path]
            

        # total_num = len(file_list)
        # try:
@@ -76,29 +79,42 @@
        # for file_json in file_list_rank:
        contents = []
        for file_json in file_list:
            with open(file_json.strip(), encoding='utf-8') as fin:
            with open(file_json.strip(), encoding="utf-8") as fin:
                for line in fin:
                    data = json.loads(line.strip())
                    if "text" in data:  # for sft
                        contents.append(data['text'])
                        contents.append(data["text"])
                    if "source" in data:  # for speech lab pretrain
                        prompt = data.get("prompt", "<ASR>")
                        source = data["source"].replace("/cpfs01", "/cpfs_speech/data") # only use in alibaba gpu group: .replace("/cpfs01", "/cpfs_speech/data")
                        source = data["source"].replace(
                            "/cpfs01", "/cpfs_speech/data"
                        )  # only use in alibaba gpu group: .replace("/cpfs01", "/cpfs_speech/data")
                        target = data["target"]
                        source_len = data.get("source_len", 1)
                        target_len = data.get("target_len", 0)
                        if "aishell" in source:
                            target = target.replace(" ", "")
                        if source_len < self.min_source_length or source_len > self.max_source_length:
                        if (
                            source_len < self.min_source_length
                            or source_len > self.max_source_length
                        ):
                            continue
                        if target_len < self.min_target_length or target_len > self.max_target_length:
                        if (
                            target_len < self.min_target_length
                            or target_len > self.max_target_length
                        ):
                            continue
                        contents_i = {"source": source,
                                     "prompt": prompt,
                                     "target": target,
                                     "source_len": source_len,
                                     "target_len": target_len,
                                     }

                        if (source_len + target_len) > self.max_token_length:
                            continue

                        contents_i = {
                            "source": source,
                            "prompt": prompt,
                            "target": target,
                            "source_len": source_len,
                            "target_len": target_len,
                        }
                        text_language = data.get("text_language", None)
                        if text_language is not None:
                            contents_i["text_language"] = text_language
@@ -108,23 +124,21 @@
                        contents.append(contents_i)

        self.contents = contents
        
        logging.info(
            "total_num of samplers: {}, {}".format(len(self.contents), path))
    

        logging.info("total_num of samplers: {}, {}".format(len(self.contents), path))

    def __len__(self):
        return len(self.contents)
    

    def __getitem__(self, index):
        

        data = self.contents[index]

        return data
    

    def get_source_len(self, data_dict):
        return data_dict.get("source_len", 1)
    
    def get_target_len(self, data_dict):
        
        return data_dict.get("target_len", 0)

    def get_target_len(self, data_dict):

        return data_dict.get("target_len", 0)