mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-08 09:32:20 +00:00
238b45bea8
* initial commit for libriheavy * Data prepare pipeline * Fix train.py * Fix decode.py * Add results * minor fixes * black * black * Incorporate PR https://github.com/k2-fsa/icefall/pull/1269 --------- Co-authored-by: zr_jin <peter.jin.cn@gmail.com>
243 lines
7.2 KiB
Python
Executable File
243 lines
7.2 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
# Copyright 2023 Xiaomi Corp. (authors: Xiaoyu Yang,
|
|
# Wei Kang)
|
|
#
|
|
# See ../../../../LICENSE for clarification regarding multiple authors
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
|
|
"""
|
|
This file computes fbank features of the Libriheavy dataset.
|
|
It looks for manifests in the directory data/manifests.
|
|
|
|
The generated fbank features are saved in data/fbank.
|
|
"""
|
|
|
|
import argparse
|
|
import logging
|
|
import os
|
|
from pathlib import Path
|
|
from typing import Optional
|
|
|
|
import torch
|
|
from lhotse import (
|
|
CutSet,
|
|
Fbank,
|
|
FbankConfig,
|
|
KaldifeatFbank,
|
|
KaldifeatFbankConfig,
|
|
LilcomChunkyWriter,
|
|
)
|
|
|
|
from icefall.utils import get_executor, str2bool
|
|
|
|
# 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 get_args():
|
|
parser = argparse.ArgumentParser()
|
|
|
|
parser.add_argument(
|
|
"--manifest-dir",
|
|
type=str,
|
|
help="""The source directory that contains raw manifests.
|
|
""",
|
|
default="data/manifests",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--fbank-dir",
|
|
type=str,
|
|
help="""Fbank output dir
|
|
""",
|
|
default="data/fbank",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--subset",
|
|
type=str,
|
|
help="""Dataset parts to compute fbank. If None, we will use all""",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--num-workers",
|
|
type=int,
|
|
default=20,
|
|
help="Number of dataloading workers used for reading the audio.",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--batch-duration",
|
|
type=float,
|
|
default=600.0,
|
|
help="The maximum number of audio seconds in a batch."
|
|
"Determines batch size dynamically.",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--perturb-speed",
|
|
type=str2bool,
|
|
default=False,
|
|
help="Whether to use speed perturbation.",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--use-splits",
|
|
type=str2bool,
|
|
default=False,
|
|
help="Whether to compute fbank on splits.",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--num-splits",
|
|
type=int,
|
|
help="""The number of splits of the medium and large subset.
|
|
Only needed when --use-splits is true.""",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--start",
|
|
type=int,
|
|
default=0,
|
|
help="""Process pieces starting from this number (inclusive).
|
|
Only needed when --use-splits is true.""",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--stop",
|
|
type=int,
|
|
default=-1,
|
|
help="""Stop processing pieces until this number (exclusive).
|
|
Only needed when --use-splits is true.""",
|
|
)
|
|
|
|
return parser.parse_args()
|
|
|
|
|
|
def compute_fbank_libriheavy(args):
|
|
src_dir = Path(args.manifest_dir)
|
|
output_dir = Path(args.fbank_dir)
|
|
num_jobs = min(15, os.cpu_count())
|
|
num_mel_bins = 80
|
|
subset = args.subset
|
|
|
|
extractor = Fbank(FbankConfig(num_mel_bins=num_mel_bins))
|
|
|
|
with get_executor() as ex: # Initialize the executor only once.
|
|
output_cuts_path = output_dir / f"libriheavy_cuts_{subset}.jsonl.gz"
|
|
if output_cuts_path.exists():
|
|
logging.info(f"{output_cuts_path} exists - skipping")
|
|
return
|
|
|
|
input_cuts_path = src_dir / f"libriheavy_cuts_{subset}.jsonl.gz"
|
|
assert input_cuts_path.exists(), f"{input_cuts_path} does not exist!"
|
|
logging.info(f"Loading {input_cuts_path}")
|
|
cut_set = CutSet.from_file(input_cuts_path)
|
|
|
|
logging.info("Computing features")
|
|
|
|
cut_set = cut_set.compute_and_store_features(
|
|
extractor=extractor,
|
|
storage_path=f"{output_dir}/libriheavy_feats_{subset}",
|
|
# when an executor is specified, make more partitions
|
|
num_jobs=num_jobs if ex is None else 80,
|
|
executor=ex,
|
|
storage_type=LilcomChunkyWriter,
|
|
)
|
|
|
|
logging.info(f"Saving to {output_cuts_path}")
|
|
cut_set.to_file(output_cuts_path)
|
|
|
|
|
|
def compute_fbank_libriheavy_splits(args):
|
|
num_splits = args.num_splits
|
|
subset = args.subset
|
|
src_dir = f"{args.manifest_dir}/libriheavy_{subset}_split"
|
|
src_dir = Path(src_dir)
|
|
output_dir = f"{args.fbank_dir}/libriheavy_{subset}_split"
|
|
output_dir = Path(output_dir)
|
|
output_dir.mkdir(parents=True, exist_ok=True)
|
|
|
|
start = args.start
|
|
stop = args.stop
|
|
if stop < start:
|
|
stop = num_splits
|
|
|
|
stop = min(stop, num_splits)
|
|
|
|
device = torch.device("cpu")
|
|
if torch.cuda.is_available():
|
|
device = torch.device("cuda", 0)
|
|
extractor = KaldifeatFbank(KaldifeatFbankConfig(device=device))
|
|
logging.info(f"device: {device}")
|
|
|
|
num_digits = 8 # num_digits is fixed by lhotse split-lazy
|
|
for i in range(start, stop):
|
|
idx = f"{i + 1}".zfill(num_digits)
|
|
logging.info(f"Processing {idx}/{num_splits}")
|
|
|
|
cuts_path = output_dir / f"libriheavy_cuts_{subset}.{idx}.jsonl.gz"
|
|
if cuts_path.is_file():
|
|
logging.info(f"{cuts_path} exists - skipping")
|
|
continue
|
|
|
|
raw_cuts_path = src_dir / f"libriheavy_cuts_{subset}.{idx}.jsonl.gz"
|
|
if not raw_cuts_path.is_file():
|
|
logging.info(f"{raw_cuts_path} does not exist - skipping it")
|
|
continue
|
|
|
|
logging.info(f"Loading {raw_cuts_path}")
|
|
cut_set = CutSet.from_file(raw_cuts_path)
|
|
|
|
logging.info("Computing features")
|
|
if (output_dir / f"libriheavy_feats_{subset}_{idx}.lca").exists():
|
|
logging.info(f"Removing {output_dir}/libriheavy_feats_{subset}_{idx}.lca")
|
|
os.remove(output_dir / f"libriheavy_feats_{subset}_{idx}.lca")
|
|
|
|
cut_set = cut_set.compute_and_store_features_batch(
|
|
extractor=extractor,
|
|
storage_path=f"{output_dir}/libriheavy_feats_{subset}_{idx}",
|
|
num_workers=args.num_workers,
|
|
batch_duration=args.batch_duration,
|
|
overwrite=True,
|
|
)
|
|
|
|
logging.info("About to split cuts into smaller chunks.")
|
|
cut_set = cut_set.trim_to_supervisions(
|
|
keep_overlapping=False, min_duration=None
|
|
)
|
|
|
|
logging.info(f"Saving to {cuts_path}")
|
|
cut_set.to_file(cuts_path)
|
|
logging.info(f"Saved to {cuts_path}")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
|
|
|
|
logging.basicConfig(format=formatter, level=logging.INFO)
|
|
args = get_args()
|
|
logging.info(vars(args))
|
|
|
|
if args.use_splits:
|
|
assert args.num_splits is not None, "Please provide num_splits"
|
|
compute_fbank_libriheavy_splits(args)
|
|
else:
|
|
compute_fbank_libriheavy(args)
|