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