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| from pathlib import Path | |
| import pyarrow.parquet as pq | |
| from pydantic import BaseModel, ConfigDict | |
| class InferenceSample(BaseModel): | |
| model_config = ConfigDict(frozen=True) | |
| audio_name: str | |
| audio: bytes | |
| reference: str | |
| def load_inference_samples(input_path: Path) -> list[InferenceSample]: | |
| if input_path.suffix.lower() == ".wav": | |
| return [ | |
| InferenceSample( | |
| audio_name=input_path.name, | |
| audio=input_path.read_bytes(), | |
| reference="", | |
| ) | |
| ] | |
| if input_path.suffix.lower() != ".parquet": | |
| raise ValueError("The input must be a WAV or Parquet file.") | |
| table = pq.read_table(input_path, columns=["audio", "text"]) | |
| samples: list[InferenceSample] = [] | |
| for index, row in enumerate(table.to_pylist(), start=1): | |
| samples.append( | |
| InferenceSample( | |
| audio_name=f"{input_path.name}:{index}", | |
| audio=row["audio"]["bytes"], | |
| reference=row["text"], | |
| ) | |
| ) | |
| if not samples: | |
| raise ValueError("The input parquet contains no samples.") | |
| return samples | |