def test_fill_cpu_ram(self, timit_like_path, timit_like_datapath,
timit_like_gtpath):
"""Test the fill cpu rarm functionality."""
gt_getter = TimitGroundTruth(timit_like_path, timit_like_datapath,
timit_like_gtpath)
audio_extractor = WindowedAudio(1024,
512,
16000,
normalize=True,
padding=True)
mfcc_extractor = WindowedMFCC(1024,
512,
16000,
n_mfcc=32,
normalize=True)
sampler = WindowedSegmentSampler([audio_extractor, mfcc_extractor],
gt_getter, 8000)
try:
get_dataloader_fixed_size(sampler, 32, "train")
get_dataloader_fixed_size(sampler, 16, "test")
except Exception as exception:
pytest.fail(f"Unexpected error: {exception}")
"""Library usage to create pytorch dataloaders with timit dataset."""
from os.path import join
from pathlib import Path
from audio_loader.features.raw_audio import WindowedAudio
from audio_loader.features.mfcc import WindowedMFCC
from audio_loader.ground_truth.timit import TimitGroundTruth
from audio_loader.samplers.windowed_segments import WindowedSegmentSampler
from audio_loader.dl_frontends.pytorch.fill_ram import get_dataloader_fixed_size
timit_gt = TimitGroundTruth(
join(Path.home(), "data/darpa-timit-acousticphonetic-continuous-speech"))
print("groundtruth loaded")
raw_feature_processor = WindowedAudio(1024, 512, 16000)
raw_sampler = WindowedSegmentSampler([raw_feature_processor],
timit_gt,
8000,
overlap=0.5)
raw_train_dataloader = get_dataloader_fixed_size(raw_sampler, 32, "train")
raw_test_dataloader = get_dataloader_fixed_size(raw_sampler, 32, "test")
print("raw audio done")
mfcc_feature_processor = WindowedMFCC(1024, 512, 16000, 20)
mfcc_sampler = WindowedSegmentSampler([mfcc_feature_processor],
timit_gt,
8000,
overlap=0.5)
mfcc_train_dataloader = get_dataloader_fixed_size(mfcc_sampler, 32, "train")