[#1511] Add deprecation warning to MelScale for unset weight

test/torchaudio_unittest/transforms/transforms_test_impl.py

@@ -1,3 +1,5 @@
+import warnings
+
 import torch
 import torchaudio.transforms as T
 
@@ -39,7 +41,7 @@ def test_InverseMelScale(self):
             get_whitenoise(sample_rate=sample_rate, duration=1, n_channels=2),
             n_fft=n_fft, power=power).to(self.device, self.dtype)
         input = T.MelScale(
-            n_mels=n_mels, sample_rate=sample_rate
+            n_mels=n_mels, sample_rate=sample_rate, n_stft=n_stft
         ).to(self.device, self.dtype)(expected)
 
         # Run transform
@@ -59,3 +61,19 @@ def test_InverseMelScale(self):
         assert _get_ratio(relative_diff < 1e-1) > 0.2
         assert _get_ratio(relative_diff < 1e-3) > 5e-3
         assert _get_ratio(relative_diff < 1e-5) > 1e-5
+
+    def test_melscale_unset_weight_warning(self):
+        """Issue a warning if MelScale initialized without a weight
+
+        As part of the deprecation of lazy intialization behavior (#1510),
+        issue a warning if `n_stft` is not set.
+        """
+        with warnings.catch_warnings(record=True) as caught_warnings:
+            warnings.simplefilter("always")
+            T.MelScale(n_mels=64, sample_rate=8000)
+        assert len(caught_warnings) == 1
+
+        with warnings.catch_warnings(record=True) as caught_warnings:
+            warnings.simplefilter("always")
+            T.MelScale(n_mels=64, sample_rate=8000, n_stft=201)
+        assert len(caught_warnings) == 0

torchaudio/transforms.py

@@ -283,6 +283,15 @@ def __init__(self,
 
         assert f_min <= self.f_max, 'Require f_min: {} < f_max: {}'.format(f_min, self.f_max)
 
+        if n_stft is None or n_stft == 0:
+            warnings.warn(
+                'Initialization of torchaudio.transforms.MelScale with an unset weight '
+                '`n_stft=None` is deprecated and will be removed from a future release. '
+                'Please set a proper `n_stft` value. Typically this is `n_fft // 2 + 1`. '
+                'Refer to https://github.com/pytorch/audio/issues/1510 '
+                'for more details.'
+            )
+
         fb = torch.empty(0) if n_stft is None else F.create_fb_matrix(
             n_stft, self.f_min, self.f_max, self.n_mels, self.sample_rate, self.norm,
             self.mel_scale)