| | |
|---|
| | | |
|---|
| | | def prepare_data(args, distributed_option): |
|---|
| | | distributed = distributed_option.distributed |
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| | | data_names = args.dataset_conf.get("data_names", "speech,text").split(",") |
|---|
| | | data_types = args.dataset_conf.get("data_types", "sound,text").split(",") |
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| | | file_names = args.data_file_names.split(",") |
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| | | batch_type = args.dataset_conf["batch_conf"]["batch_type"] |
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| | | if not distributed or distributed_option.dist_rank == 0: |
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| | | if hasattr(args, "filter_input") and args.filter_input: |
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| | | filter_wav_text(args.data_dir, args.train_set) |
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| | | filter_wav_text(args.data_dir, args.valid_set) |
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| | | |
|---|
| | | if args.dataset_type == "small": |
|---|
| | | if args.dataset_type == "small" and batch_type != "unsorted": |
|---|
| | | calc_shape(args, args.train_set) |
|---|
| | | calc_shape(args, args.valid_set) |
|---|
| | | |
|---|
| | |
|---|
| | | generate_data_list(args, args.data_dir, args.train_set) |
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| | | generate_data_list(args, args.data_dir, args.valid_set) |
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| | | |
|---|
| | | data_names = args.dataset_conf.get("data_names", "speech,text").split(",") |
|---|
| | | data_types = args.dataset_conf.get("data_types", "sound,text").split(",") |
|---|
| | | file_names = args.data_file_names.split(",") |
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| | | print("data_names: {}, data_types: {}, file_names: {}".format(data_names, data_types, file_names)) |
|---|
| | | assert len(data_names) == len(data_types) == len(file_names) |
|---|
| | | if args.dataset_type == "small": |
|---|
