(self, dim)

(self)

( self, kernel_size: Tuple[int, int], dilation: Tuple[int, int] = (1, 1), )

( y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax,

(x)

(kernel_size, dilation=1)

( y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax,

(rea_r, rea_g, imag_r, imag_g)

(self, nband: int, input_channel: int, kernel_size: int=1,

(self, nband: int, feature_dim: int, affine = True,

(y, n_fft, hop_size, win_size)

(log_amplitude_r, log_amplitude_g)

(sampling_rate, n_fft, num_mels, fmin, fmax, win_size, device)

(sampling_rate, n_fft, num_mels, fmin, fmax, win_size, device)

(phase_r, phase_g, n_fft, frames)

(filepath, obj)

(disc_real_outputs, disc_generated_outputs)

(fmap_r, fmap_g)

(disc_outputs)

(self)

(filepath, device)

(spectrogram)

(filepath, pre='g', max_to_keep=5)

(cp_dir, prefix)

( y, n_fft, num_mels, sampling_rate, hop_size, win_size, fmin, fmax,

(self, nrep: int, nband: int, input_channel: int,

(self, nrep: int, nband: int, input_channel: int,

(y, n_fft, hop_size, win_size)

(config, config_name, path)

(x, C=1, clip_val=1e-5)

(x, C=1, clip_val=1e-5)

(x, C=1)

(x, C=1)

(input_training_wav_list, input_validation_wav_list, raw_wavfile_path)

(x, h)

(a, h)

(filepath, device)

(full_path, sample_rate)

(full_path, sample_rate)

()

()

(self)

(self)

(self)

(magnitudes)

(magnitudes)

(magnitudes)

(magnitudes)

(self, x: torch.Tensor)

(rank, a, h)

(self, index)

(self, index)

( self, training_files, segment_size, n_fft, num_mels, h

(self, *args, **kwargs)

(self, *args, **kwargs)

( self, training_files, segment_size, n_fft, num_mels, h

(self, h, )

(self, h, )

(self, period, kernel_size=5, stride=3, use_spectral_norm=False)

(self, mpd_reshapes)

(self, resolutions=((32, 8, 32, 5), (64, 16, 64, 10),

(self, use_spectral_norm=False)

(self)

( self, resolutions=((1024, 256, 1024), (2048, 512, 2048), (512, 128, 512)), num_em

( self, resolution, channels: int = 64, in_channels: int = 1, num

(self, h, hop_length: int, n_octaves:int, bins_per_octave: int)

(self, h)

(self, dim, num_heads, f_win_size, t_win_size

(self, dim, heads=8, dim_head=64, dropout=

(self, dim: int, f_win_size: int, t_win_size: int,

(self, num_channels, ndim=3, affine=True)

(self, num_channels, ndim=3, affine=True)

(self, nband: int, feature_dim: int, affine = True,

(self, in_features: int, out_features: int, num_groups: int, bias: bool = True)

(self, sr: int, win_size: int, hop_size: int, n_ff

(self, sr: int, win_size: int, hop_size: int, n_ff

(self, sr: int, win_size: int, hop_size: int, n_ff

(self, sr: int, win_size: int, hop_size: int, n_f

(self, sr: int, win_size: int, hop_size: int, n_f

(self, sr: int, win_size: int, hop_size: int, n_f

(self, nband: int, input_size: int, squeeze_size: int=64,

(self, input_size: int, hidden_size: int, dropout: float

(self, input_size: int, hidden_size: int, dropout: float

(self, nband: int, nrep: int, input_channel: int,

(self)

(self)

(self, m)

(self, m)

(m)

(config, config_name, path)

(x, C=1, clip_val=1e-5)

(x, C=1, clip_val=1e-5)

(x, C=1)

(x, C=1)