( self, band_specs_map: Union[str, Dict[str, List[Tuple[float, float]]]],

( self, stems: List[str], band_specs: Union[str, List[Tuple[float, float]]

( self, stems: List[str], band_specs: Union[str, List[Tuple[float, float]]

( self, in_channel: int, band_specs_map: Union[str, Dict[str, List[Tuple[f

( self, in_channel: int, band_specs_map: Union[str, Dict[str, List[Tuple[f

( self, in_channel: int, stems: List[str], band_specs: Union[s

( self, in_channel: int, stems: List[str], band_specs: Union[s

( self, in_channel: int, stems: List[str], band_specs: Union[s

( self, in_channel: int, stems: List[str], band_specs: Union[s

( self, in_channel: int, stems: List[str], band_specs: Union[s

(self)

( self, n_modules: int = 12, emb_dim: int = 128, rnn_dim: int

( self, emb_dim: int = 128, rnn_dim: int = 256, bidirectional:

( self, n_modules: int = 12, emb_dim: int = 128, rnn_dim: int

( self, emb_dim: int = 128, rnn_dim: int = 256, bidirectional:

( self, n_modules: int = 12, emb_dim: int = 128, rnn_dim: int

( self, dataset: data.Dataset, augmentation: nn.Module = nn.Identity(),

( self, audiomentations: Dict[str, Dict[str, Any]], fix_clipping: bool = T

( self, split: str, stems: List[str], files: List[str], data_p

( self, split: str, stems: List[str], files: List[str],

( self, data_root: str, split: str, target_length: int,

( self, data_root: str, split: str, chunk_size_second: float,

( self, data_root: str, split: str, target_length: int,

( self, split: str, stems: List[str], files: List[str],

( self, data_root: str, split: str, stems: Optional[List[ str]] = None )

( self, data_root: str, split: str, target_stem: str,

( self, analysis_stem: str, output_path: str, fs: int = 44100,

( self, sdr_type: str, p: float = 2.0, zero_mean: bool = True,

( self, time_module: _Loss, freq_module: Optional[_Loss] = None,

( self, time_weight: float = 1.0, freq_weight: float = 1.0, tk

( self, time_weight: float = 1.0, freq_weight: float = 1.0, tk

(self, name: str, kwargs: Any, modality: str = "audio")

(self, module: _Loss)

(self, **kwargs: Any)

(self, channels, depth=2, compress=4, kernel=3)

(self, channels, kernel_size=3, stride=1, padding=1)

(self, channels_in, channels_out, band_configs)

(self, channels_in, channels_out, band_configs)

(self, channels_in, channels_out, band_configs={}, conv_config={}, depths=[3, 2, 1], kernel_size=3)

(self, channels, inverse)

(self, channels, expand=1, num_layers=6)

(self, channels, depth=2, compress=4, kernel=3)

(self, channels, kernel_size=3, stride=1, padding=1)

(self, channels_in, channels_out, band_configs)

(self, channels_in, channels_out, band_configs)

(self, channels_in, channels_out, band_configs={}, conv_config={}, depths=[3, 2, 1], kernel_size=3)

( self, dim, mult=4, dropout=0. )

( self, dim, heads=8, dim_head=64, dropout=0.,

( self, *, dim, depth, dim_head=64, he

(self, channels, inverse)

(self, d_model, time_rotary_embed, freq_rotary_embed, tran_params)

(self, channels, expand=1, num_layers=6, tran_params=None)

(self, channels, depth=2, compress=4, kernel=3)

(self, channels, kernel_size=3, stride=1, padding=1)

(self, channels_in, channels_out, band_configs)

(self, channels_in, channels_out, band_configs)

(self, channels_in, channels_out, band_configs={}, conv_config={}, depths=[3, 2, 1], kernel_size=3)

( self, sources=('drums', 'bass', 'other', 'vocals'), audio_channels=2,

( self, )

( self, in_channels: int, fs: int, band_type: str = "musical", n_bands

( self, emb_dim: int, mlp_dim: int, bandwidth: int, in_channels: Optio

( self, band_specs: List[Tuple[float, float]], emb_dim: int, mlp_dim: int,

( self, in_channels: int, band_specs: List[Tuple[float, float]], freq_weights:

( self, band_specs: List[Tuple[float, float]], emb_dim: int, mlp_dim: int,

(self, nfft: int, fs: int, version: str = "7")

(self, nfft: int, fs: int)

(self, nfft: int, fs: int, version: str = "7")

(self, nfft: int, fs: int)

( self, nfft: int, fs: int, fbank_fn: Callable[[int, int, float, float, int],

( self, nfft: int, fs: int, n_bands: int, f_min: float = 0.0, f_max: float = None )

( self, nfft: int, fs: int, n_bands: int, f_min: float = 0.0, f_max: float = None )

( self, band_specs: List[Tuple[float, float]], emb_dim: int, in_channels: int,

(self)

( self, emb_dim: int, rnn_dim: int, bidirectional: bool = True, rnn_ty

( self, n_modules: int = 12, emb_dim: int = 128, rnn_dim: int = 256, b

(self)

(self, dimension, groups=1)

(self, dimension, groups=1)

(self, input_size, hidden_size, num_head=8, theta=10000, window=10000, input_drop=0., attenti

(self, in_channel, hidden_channel, kernel=7, causal=False)

(self, feature_dim, kernel=7)

( self, sr: int, win: int, feature_dim: int, layer

(self, sample_rate, in_chan=1)

( self, dim, mult=4, dropout=0. )

( self, dim, heads=8, dim_head=64, dropout=0.,

( self, *, dim, dim_head=32, heads=8,

( self, *, dim, depth, dim_head=64, he

( self, dim, dim_inputs: Tuple[int, ...] )

( self, dim, dim_inputs: Tuple[int, ...], depth, m

( self, dim, *, depth, stereo=False, n

( self, dropout = 0., flash = False, scale = None )

(self, dim, mult=4, dropout=0.)

( self, dim, heads=8, dim_head=64, dropout=0., rotary_embed=No

( self, *, dim, dim_head=32, heads=8, scale=8, flash=F

( self, *, dim, depth, dim_head=64, heads=8, attn_drop

(self, dim, mult=4, dropout=0.)

(self, dim, expansion_factor=2, kernel_size=31, dropout=0.)

( self, *, dim, heads=8, dim_head=64, ff_mult=4, attn_

( self, *, dim, depth, dim_head=64, heads=8, attn_drop

(self, dim, dim_inputs: Tuple[int, ...])