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Add perceptual_weighting to the MultiResolutionSTFTLoss docstring. #74

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Add perceptual_weighting to the MultiResolutionSTFTLoss docstring. #74

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13 changes: 7 additions & 6 deletions auraloss/freq.py
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Expand Up @@ -373,6 +373,7 @@ class MultiResolutionSTFTLoss(torch.nn.Module):
['mel', 'chroma']
Default: None
n_bins (int, optional): Number of mel frequency bins. Required when scale = 'mel'. Default: None.
perceptual_weighting (bool, optional): Apply perceptual A-weighting (Sample rate must be supplied). Default: False
scale_invariance (bool, optional): Perform an optimal scaling of the target. Default: False
"""

Expand Down Expand Up @@ -449,13 +450,13 @@ class RandomResolutionSTFTLoss(torch.nn.Module):
See [Steinmetz & Reiss, 2020](https://www.christiansteinmetz.com/s/DMRN15__auraloss__Audio_focused_loss_functions_in_PyTorch.pdf)

Args:
resolutions (int): Total number of STFT resolutions.
min_fft_size (int): Smallest FFT size.
max_fft_size (int): Largest FFT size.
min_hop_size (int): Smallest hop size as porportion of window size.
min_hop_size (int): Largest hop size as porportion of window size.
resolutions (int): Total number of STFT resolutions. Default: 3
min_fft_size (int): Smallest FFT size. Default: 16
max_fft_size (int): Largest FFT size. Default: 32768
min_hop_size (int): Smallest hop size as porportion of window size. Default: 0.1
min_hop_size (int): Largest hop size as porportion of window size. Default: 1.0
window (str): Window function type.
randomize_rate (int): Number of forwards before STFTs are randomized.
randomize_rate (int): Number of forwards before STFTs are randomized. Default: 1
"""

def __init__(
Expand Down