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Running on Zero
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5ed07ee | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | """
SVS data preprocessing package.
Provides reusable library code for converting raw SVS data (folder-based or
JSON-based annotations) into preprocessed Arrow format for training.
Key public API:
* :class:`SVSPreprocessor` / :func:`create_lightweight_preprocessor` —
audio VAE encoding and SVS token sequence construction.
* :func:`rebuild_svs_prompt` — reconstruct SVS prompt text from metadata.
* :func:`load_config`, :func:`load_all_datasets` — dataset loading.
* :func:`build_text_tensor`, :func:`estimate_duration_from_notes` — text
tensor construction and duration estimation.
* :func:`process_and_save`, :func:`process_and_save_multigpu` — Arrow
dataset writing (single-GPU and multi-GPU).
"""
from .svs_preprocessor import SVSPreprocessor, create_lightweight_preprocessor
from .svs_prompt import rebuild_svs_prompt
from .data_loaders import (
load_config,
load_samples_from_folder,
load_samples_from_json_file,
load_samples_from_weak_json_file,
load_all_datasets,
reconstruct_lyric_text,
)
from .text_tensor import build_text_tensor, estimate_duration_from_notes
from .arrow_writer import process_and_save, process_and_save_multigpu
__all__ = [
"SVSPreprocessor",
"create_lightweight_preprocessor",
"rebuild_svs_prompt",
"load_config",
"load_samples_from_folder",
"load_samples_from_json_file",
"load_samples_from_weak_json_file",
"load_all_datasets",
"reconstruct_lyric_text",
"build_text_tensor",
"estimate_duration_from_notes",
"process_and_save",
"process_and_save_multigpu",
]
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