Merge pull request #74 from sp-nitech/update

Minor update

diffsptk/misc/utils.py

@@ -103,9 +103,9 @@ def replicate1(x, left=True, right=True):
     return y
 
 
-def remove_gain(a, return_gain=False):
+def remove_gain(a, return_gain=False, value=1):
     K, a1 = torch.split(a, [1, a.size(-1) - 1], dim=-1)
-    a = F.pad(a1, (1, 0), value=1)
+    a = F.pad(a1, (1, 0), value=value)
     if return_gain:
         ret = (K, a)
     else:

diffsptk/modules/mglsadf.py

@@ -20,6 +20,7 @@
 from ..misc.utils import Lambda
 from ..misc.utils import check_size
 from ..misc.utils import get_gamma
+from ..misc.utils import remove_gain
 from .b2mc import MLSADigitalFilterCoefficientsToMelCepstrum
 from .gnorm import GeneralizedCepstrumGainNormalization
 from .istft import InverseShortTimeFourierTransform
@@ -221,6 +222,9 @@ def __init__(
         self.phase = phase
         self.taylor_order = taylor_order
 
+        if alpha == 0 and gamma == 0:
+            cep_order = filter_order
+
         if self.phase == "minimum":
             self.pad = nn.ConstantPad1d((cep_order, 0), 0)
         elif self.phase == "maximum":
@@ -241,7 +245,7 @@ def __init__(
     def forward(self, x, mc):
         c = self.mgc2c(mc)
         if self.ignore_gain:
-            c[..., 0] = 0
+            c = remove_gain(c, value=0)
 
         if self.phase == "minimum":
             c = c.flip(-1)
@@ -320,7 +324,7 @@ def forward(self, x, mc):
             c = self.mgc2c(mc)
             c[..., 1:] *= 0.5
             if self.ignore_gain:
-                c[..., 0] = 0
+                c = remove_gain(c, value=0)
             h = self.c2ir(c)
         else:
             h = self.mgc2ir(mc)