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add code for parallel preprocessing #270

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add code for parallel preprocessing #270

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cf03e0b
add code for parallel preprocessing
mboyanov Sep 5, 2024
fa310ce
reformat with black
mboyanov Sep 26, 2024
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7 changes: 2 additions & 5 deletions bins/svc/preprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,11 +37,8 @@ def extract_acoustic_features(dataset, output_path, cfg, n_workers=1):
with open(dataset_file, "r") as f:
metadata.extend(json.load(f))

# acoustic_extractor.extract_utt_acoustic_features_parallel(
# metadata, dataset_output, cfg, n_workers=n_workers
# )
acoustic_extractor.extract_utt_acoustic_features_serial(
metadata, dataset_output, cfg
acoustic_extractor.extract_utt_acoustic_features_parallel(
metadata, dataset_output, cfg, n_workers=n_workers
)


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31 changes: 21 additions & 10 deletions processors/acoustic_extractor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,8 +2,9 @@
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.

import os
from functools import partial

import torch
import numpy as np

Expand All @@ -23,6 +24,7 @@
extract_linear_features,
extract_mel_features_tts,
)
from concurrent.futures import as_completed, ProcessPoolExecutor

ZERO = 1e-12

Expand All @@ -39,15 +41,24 @@ def extract_utt_acoustic_features_parallel(metadata, dataset_output, cfg, n_work
Returns:
list: acoustic features
"""
for utt in tqdm(metadata):
if cfg.task_type == "tts":
extract_utt_acoustic_features_tts(dataset_output, cfg, utt)
if cfg.task_type == "svc":
extract_utt_acoustic_features_svc(dataset_output, cfg, utt)
if cfg.task_type == "vocoder":
extract_utt_acoustic_features_vocoder(dataset_output, cfg, utt)
if cfg.task_type == "tta":
extract_utt_acoustic_features_tta(dataset_output, cfg, utt)
extractor = None
if cfg.task_type == "tts":
extractor = partial(extract_utt_acoustic_features_tts, dataset_output, cfg)
if cfg.task_type == "svc":
extractor = partial(extract_utt_acoustic_features_svc, dataset_output, cfg)
if cfg.task_type == "vocoder":
extractor = partial(extract_utt_acoustic_features_vocoder, dataset_output, cfg)
if cfg.task_type == "tta":
extractor = partial(extract_utt_acoustic_features_tta, dataset_output, cfg)

with ProcessPoolExecutor(max_workers=n_workers) as pool:
future_to_utt = {pool.submit(extractor, utt): utt for utt in metadata}
for future in tqdm(as_completed(future_to_utt), total=len(future_to_utt)):
utt = future_to_utt[future]
try:
future.result()
except Exception as exc:
print("%r generated an exception: %s" % (utt, exc))


def avg_phone_feature(feature, duration, interpolation=False):
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