update torch audio for new stft signature (#55)

torchaudio/transforms.py

@@ -192,7 +192,9 @@ class SPECTROGRAM(object):
         self.sr = sr
         self.ws = ws
         self.hop = hop if hop is not None else ws // 2
-        self.n_fft = n_fft  # number of fft bins
+        # number of fft bins. the returned STFT result will have n_fft // 2 + 1
+        # number of frequecies due to onesided=True in torch.stft
+        self.n_fft = (n_fft - 1) * 2 if n_fft is not None else ws
         self.pad = pad
         self.wkwargs = wkwargs
 
@@ -212,8 +214,17 @@ class SPECTROGRAM(object):
 
         assert sig.dim() == 2
 
-        spec_f = torch.stft(sig, self.ws, self.hop, self.n_fft,
-                            True, True, self.window, self.pad)  # (c, l, n_fft, 2)
+        if self.pad > 0:
+            c, n = sig.size()
+            new_sig = sig.new_empty(c, n + self.pad * 2)
+            new_sig[:, :self.pad].zero_()
+            new_sig[:, -self.pad:].zero_()
+            new_sig.narrow(1, self.pad, n).copy_(sig)
+            sig = new_sig
+
+        spec_f = torch.stft(sig, self.n_fft, self.hop, self.ws,
+                            self.window, center=False,
+                            normalized=True, onesided=True).transpose(1, 2)
         spec_f /= self.window.pow(2).sum().sqrt()
         spec_f = spec_f.pow(2).sum(-1)  # get power of "complex" tensor (c, l, n_fft)
         return spec_f if is_variable else spec_f.data