Replace assert statements with raise in transforms (#2599)

Summary:
Pull Request resolved: https://github.com/pytorch/audio/pull/2599

Bootcamp task T127107566.
Replacing assert statements  with if ... then raise so can be run in optimized mode

Reviewed By: mthrok

Differential Revision: D38370108

fbshipit-source-id: 74eaf5b72c511b62ddbb8e0e3b0ed638ad49e4f2

torchaudio/transforms/_multi_channel.py

@@ -172,11 +172,14 @@ class MVDR(torch.nn.Module):
         online: bool = False,
     ):
         super().__init__()
-        assert solution in [
+        if solution not in [
             "ref_channel",
             "stv_evd",
             "stv_power",
-        ], "Unknown solution provided. Must be one of [``ref_channel``, ``stv_evd``, ``stv_power``]."
+        ]:
+            raise ValueError(
+                "`solution` must be one of ['ref_channel', 'stv_evd', 'stv_power']. Given {}".format(solution)
+            )
         self.ref_channel = ref_channel
         self.solution = solution
         self.multi_mask = multi_mask

torchaudio/transforms/_transforms.py

@@ -256,8 +256,8 @@ class GriffinLim(torch.nn.Module):
     ) -> None:
         super(GriffinLim, self).__init__()
 
-        assert momentum < 1, "momentum={} > 1 can be unstable".format(momentum)
-        assert momentum >= 0, "momentum={} < 0".format(momentum)
+        if not (0 <= momentum < 1):
+            raise ValueError("momentum must be in the range [0, 1). Found: {}".format(momentum))
 
         self.n_fft = n_fft
         self.n_iter = n_iter
@@ -379,7 +379,9 @@ class MelScale(torch.nn.Module):
         self.norm = norm
         self.mel_scale = mel_scale
 
-        assert f_min <= self.f_max, "Require f_min: {} < f_max: {}".format(f_min, self.f_max)
+        if f_min > self.f_max:
+            raise ValueError("Require f_min: {} <= f_max: {}".format(f_min, self.f_max))
+
         fb = F.melscale_fbanks(n_stft, self.f_min, self.f_max, self.n_mels, self.sample_rate, self.norm, self.mel_scale)
         self.register_buffer("fb", fb)
 
@@ -456,7 +458,8 @@ class InverseMelScale(torch.nn.Module):
         self.tolerance_change = tolerance_change
         self.sgdargs = sgdargs or {"lr": 0.1, "momentum": 0.9}
 
-        assert f_min <= self.f_max, "Require f_min: {} < f_max: {}".format(f_min, self.f_max)
+        if f_min > self.f_max:
+            raise ValueError("Require f_min: {} <= f_max: {}".format(f_min, self.f_max))
 
         fb = F.melscale_fbanks(n_stft, self.f_min, self.f_max, self.n_mels, self.sample_rate, norm, mel_scale)
         self.register_buffer("fb", fb)
@@ -476,7 +479,8 @@ class InverseMelScale(torch.nn.Module):
         n_mels, time = shape[-2], shape[-1]
         freq, _ = self.fb.size()  # (freq, n_mels)
         melspec = melspec.transpose(-1, -2)
-        assert self.n_mels == n_mels
+        if self.n_mels != n_mels:
+            raise ValueError("Expected an input with {} mel bins. Found: {}".format(self.n_mels, n_mels))
 
         specgram = torch.rand(
             melspec.size()[0], time, freq, requires_grad=True, dtype=melspec.dtype, device=melspec.device