import logging
from audiopreprocessing import triggerlog
#logger = logging.getLogger(__name__)
import sys
logging.basicConfig(format="%(asctime)s/%(levelname)s: [%(module)s] %(message)s", level=logging.INFO, handlers=[logging.FileHandler('test_panns.log'), logging.StreamHandler(sys.stdout)])
from pathlib import Path
from mtafe_panns import mtafe_panns
from dataset_files import random_audio_chunk, serialize_dict_obj
mtafe = mtafe_panns(
    audio_paths=random_audio_chunk(4),
    max_audio_in_queue=4,
    audio_feeder_threads=4,
    feature_extractor_threads=1,
    desired_sr=32000,
    force_mono=False,
    chunk_length=15,
    chunk_overlap=2,
    batch_size=32
)
mtafe.extract()

print("Saving inferenced results to file...")
p = Path('./test_panns.pkl')
serialize_dict_obj(p, mtafe.features)