Update app.py

app.py

@@ -33,7 +33,7 @@ REFERENCE_CHANNEL = 0
 #creating a random noise for better calculations 
 SAMPLE_NOISE = download_asset("tutorial-assets/mvdr/noise.wav")
 waveform_noise, sr2 = torchaudio.load(SAMPLE_NOISE)
-waveform_noise = waveform_noise.to(torch.double)
+waveform_noise = waveform_noise.to(torch.float32)
 stft_noise = stft(waveform_noise)
 
 def ui(): 
@@ -44,14 +44,14 @@ def ui():
 
     if audio_file is not None:
         waveform_clean,sr=torchaudio.load(audio_file)
-        waveform_clean = waveform_clean.to(torch.double)
+        waveform_clean = waveform_clean.to(torch.float32)
         stft_clean = stft(waveform_clean)
         st.text("Your uploaded audio")
         st.audio(audio_file)
         #creating a mixture of our audio file and the noise file 
         waveform_mix = generate_mixture(waveform_clean, waveform_noise, target_snr)
         #making the files into torch double format 
-        # waveform_mix = waveform_mix.to(torch.double)
+        waveform_mix = waveform_mix.to(torch.float32)
         #computing STFT
         stft_mix = stft(waveform_mix)
         #plotting the spectogram