def mfcc_pipeline(source):
data = fn.external_source(source=source)
spectrum = fn.spectrogram(data, nfft=60, window_length=50, window_step=25)
mel = fn.mel_filter_bank(spectrum)
dec = fn.to_decibels(mel)
processed = fn.mfcc(dec)
return processed
def pipe(max_batch_size, input_data, device):
pipe = Pipeline(batch_size=max_batch_size, num_threads=4, device_id=0)
data = fn.external_source(source=input_data, cycle=False, device=device)
spectrum = fn.spectrogram(data, nfft=60, window_length=50, window_step=25)
mel = fn.mel_filter_bank(spectrum)
dec = fn.to_decibels(mel)
processed = fn.mfcc(dec)
pipe.set_outputs(processed)
return pipe
def test_mfcc_cpu():
pipe = Pipeline(batch_size=batch_size, num_threads=4, device_id=None)
data = fn.external_source(source=get_audio_data)
spectrum = fn.spectrogram(data, nfft=60, window_length=50, window_step=25)
mel = fn.mel_filter_bank(spectrum)
dec = fn.to_decibels(mel)
processed = fn.mfcc(dec)
pipe.set_outputs(processed)
pipe.build()
for _ in range(3):
pipe.run()
