| | |
| | | import torch |
| | | from funasr.datasets.small_datasets.dataset import ESPnetDataset |
| | | from funasr.datasets.small_datasets.build_preprocess import build_preprocess |
| | | from funasr.datasets.small_datasets.preprocessor import build_preprocess |
| | | |
| | | def build_dataloader(args): |
| | | if args.frontend_conf is not None: |
| | | dest_sample_rate = args.frontend_conf["fs"] if (args.frontend_conf is not None and "fs" in args.frontend_conf) else 16000 |
| | | preprocess_fn = build_preprocess() |
| | | def build_dataloader(args, train=False): |
| | | preprocess_fn = build_preprocess(args, train=train) |
| | | dest_sample_rate = args.frontend_conf["fs"] if (args.frontend_conf is not None and "fs" in args.frontend_conf) else 16000 |
| | | dataset = ESPnetDataset( |
| | | iter_options.data_path_and_name_and_type, |
| | | float_dtype=args.train_dtype, |
| | | preprocess=preprocess_fn, |
| | | max_cache_size=iter_options.max_cache_size, |
| | | max_cache_fd=iter_options.max_cache_fd, |
| | | max_cache_size=args.max_cache_size, |
| | | max_cache_fd=args.max_cache_fd, |
| | | dest_sample_rate=dest_sample_rate, |
| | | ) |