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Retain init args as attributes in MelScale and InverseMelScale #4126

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Retain init args as attributes in MelScale and InverseMelScale #4126

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5ef4fb8
retain arguments from init as properties in MelScale and InverseMelScale
sammlapp Nov 4, 2025
fae5180
Undo unintentional formatting
sammlapp Nov 4, 2025
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15 changes: 12 additions & 3 deletions src/torchaudio/transforms/_transforms.py
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Original file line number Diff line number Diff line change
Expand Up @@ -374,7 +374,8 @@ class MelScale(torch.nn.Module):
:py:func:`torchaudio.functional.melscale_fbanks` - The function used to
generate the filter banks.
"""
__constants__ = ["n_mels", "sample_rate", "f_min", "f_max"]

__constants__ = ["n_mels", "sample_rate", "f_min", "f_max", "n_stft"]

def __init__(
self,
Expand All @@ -391,13 +392,16 @@ def __init__(
self.sample_rate = sample_rate
self.f_max = f_max if f_max is not None else float(sample_rate // 2)
self.f_min = f_min
self.n_stft = n_stft
self.norm = norm
self.mel_scale = mel_scale

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)
fb = F.melscale_fbanks(
self.n_stft, self.f_min, self.f_max, self.n_mels, self.sample_rate, self.norm, self.mel_scale
)
self.register_buffer("fb", fb)

def forward(self, specgram: Tensor) -> Tensor:
Expand Down Expand Up @@ -464,10 +468,13 @@ def __init__(
driver: str = "gels",
) -> None:
super(InverseMelScale, self).__init__()
self.n_stft = n_stft
self.n_mels = n_mels
self.sample_rate = sample_rate
self.f_max = f_max or float(sample_rate // 2)
self.f_min = f_min
self.norm = norm
self.mel_scale = mel_scale
self.driver = driver

if f_min > self.f_max:
Expand All @@ -476,7 +483,9 @@ def __init__(
if driver not in ["gels", "gelsy", "gelsd", "gelss"]:
raise ValueError(f'driver must be one of ["gels", "gelsy", "gelsd", "gelss"]. Found {driver}.')

fb = F.melscale_fbanks(n_stft, self.f_min, self.f_max, self.n_mels, self.sample_rate, norm, mel_scale)
fb = F.melscale_fbanks(
self.n_stft, self.f_min, self.f_max, self.n_mels, self.sample_rate, self.norm, self.mel_scale
)
self.register_buffer("fb", fb)

def forward(self, melspec: Tensor) -> Tensor:
Expand Down
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