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import logging
import os
import tarfile
import zipfile
from typing import Any, List, Optional
import torchaudio
_LG = logging.getLogger(__name__)
def _extract_tar(from_path: str, to_path: Optional[str] = None, overwrite: bool = False) -> List[str]:
if to_path is None:
to_path = os.path.dirname(from_path)
with tarfile.open(from_path, "r") as tar:
files = []
for file_ in tar: # type: Any
file_path = os.path.join(to_path, file_.name)
if file_.isfile():
files.append(file_path)
if os.path.exists(file_path):
_LG.info("%s already extracted.", file_path)
if not overwrite:
continue
tar.extract(file_, to_path)
return files
def _extract_zip(from_path: str, to_path: Optional[str] = None, overwrite: bool = False) -> List[str]:
if to_path is None:
to_path = os.path.dirname(from_path)
with zipfile.ZipFile(from_path, "r") as zfile:
files = zfile.namelist()
for file_ in files:
file_path = os.path.join(to_path, file_)
if os.path.exists(file_path):
_LG.info("%s already extracted.", file_path)
if not overwrite:
continue
zfile.extract(file_, to_path)
return files
def _load_waveform(
root: str,
filename: str,
exp_sample_rate: int,
):
path = os.path.join(root, filename)
waveform, sample_rate = torchaudio.load(path)
if exp_sample_rate != sample_rate:
raise ValueError(f"sample rate should be {exp_sample_rate}, but got {sample_rate}")
return waveform
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