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Make parameter optional string #641
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Original file line number | Diff line number | Diff line change |
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@@ -336,7 +336,7 @@ def create_fb_matrix( | |
f_max: float, | ||
n_mels: int, | ||
sample_rate: int, | ||
norm: str = "", | ||
norm: Optional[str] = None | ||
) -> Tensor: | ||
r"""Create a frequency bin conversion matrix. | ||
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||
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@@ -346,8 +346,8 @@ def create_fb_matrix( | |
f_max (float): Maximum frequency (Hz) | ||
n_mels (int): Number of mel filterbanks | ||
sample_rate (int): Sample rate of the audio waveform | ||
norm (str): If 'slaney', divide the triangular mel weights by the width of the mel band | ||
(area normalization). (Default: '') | ||
norm (Optional[str]): If 'slaney', divide the triangular mel weights by the width of the mel band | ||
(area normalization). (Default: ``None``) | ||
|
||
Returns: | ||
Tensor: Triangular filter banks (fb matrix) of size (``n_freqs``, ``n_mels``) | ||
|
@@ -356,6 +356,10 @@ def create_fb_matrix( | |
size (..., ``n_freqs``), the applied result would be | ||
``A * create_fb_matrix(A.size(-1), ...)``. | ||
""" | ||
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||
if norm is not None and norm != "slaney": | ||
raise ValueError("norm must be one of None or 'slaney'") | ||
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||
# freq bins | ||
# Equivalent filterbank construction by Librosa | ||
all_freqs = torch.linspace(0, sample_rate // 2, n_freqs) | ||
|
@@ -376,7 +380,7 @@ def create_fb_matrix( | |
up_slopes = slopes[:, 2:] / f_diff[1:] # (n_freqs, n_mels) | ||
fb = torch.max(zero, torch.min(down_slopes, up_slopes)) | ||
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||
if norm == "slaney": | ||
if norm is not None and norm == "slaney": | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I think we should not allow values other than |
||
# Slaney-style mel is scaled to be approx constant energy per channel | ||
enorm = 2.0 / (f_pts[2:n_mels + 2] - f_pts[:n_mels]) | ||
fb *= enorm.unsqueeze(0) | ||
|
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Rather than changing it to
None
, I suggest following the original suggestion of passing string value.