icefall/egs/yesno/ASR/local/compute_fbank_yesno.py
2022-11-17 09:42:17 -05:00

91 lines
2.8 KiB
Python
Executable File

#!/usr/bin/env python3
"""
This file computes fbank features of the yesno dataset.
It looks for manifests in the directory data/manifests.
The generated fbank features are saved in data/fbank.
"""
import logging
import os
from pathlib import Path
import torch
from lhotse import CutSet, Fbank, FbankConfig, LilcomChunkyWriter
from lhotse.recipes.utils import read_manifests_if_cached
from icefall.utils import get_executor
# Torch's multithreaded behavior needs to be disabled or it wastes a
# lot of CPU and slow things down.
# Do this outside of main() in case it needs to take effect
# even when we are not invoking the main (e.g. when spawning subprocesses).
torch.set_num_threads(1)
torch.set_num_interop_threads(1)
def compute_fbank_yesno():
src_dir = Path("data/manifests")
output_dir = Path("data/fbank")
# This dataset is rather small, so we use only one job
num_jobs = min(1, os.cpu_count())
num_mel_bins = 23
dataset_parts = (
"train",
"test",
)
prefix = "yesno"
suffix = "jsonl.gz"
manifests = read_manifests_if_cached(
dataset_parts=dataset_parts,
output_dir=src_dir,
prefix=prefix,
suffix=suffix,
)
assert manifests is not None
assert len(manifests) == len(dataset_parts), (
len(manifests),
len(dataset_parts),
list(manifests.keys()),
dataset_parts,
)
extractor = Fbank(FbankConfig(sampling_rate=8000, num_mel_bins=num_mel_bins))
with get_executor() as ex: # Initialize the executor only once.
for partition, m in manifests.items():
cuts_file = output_dir / f"{prefix}_cuts_{partition}.{suffix}"
if cuts_file.is_file():
logging.info(f"{partition} already exists - skipping.")
continue
logging.info(f"Processing {partition}")
cut_set = CutSet.from_manifests(
recordings=m["recordings"],
supervisions=m["supervisions"],
)
if "train" in partition:
cut_set = (
cut_set + cut_set.perturb_speed(0.9) + cut_set.perturb_speed(1.1)
)
cut_set = cut_set.compute_and_store_features(
extractor=extractor,
storage_path=f"{output_dir}/{prefix}_feats_{partition}",
# when an executor is specified, make more partitions
num_jobs=num_jobs if ex is None else 1, # use one job
executor=ex,
storage_type=LilcomChunkyWriter,
)
cut_set.to_file(cuts_file)
if __name__ == "__main__":
formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
logging.basicConfig(format=formatter, level=logging.INFO)
compute_fbank_yesno()