repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
Retrieval-based-Voice-Conversion-WebUI | train/dataset/extract_hubert_feature.py | .py | import os
import sys
import traceback
device = sys.argv[1]
n_part = int(sys.argv[2])
i_part = int(sys.argv[3])
if len(sys.argv) == 7:
exp_dir = sys.argv[4]
version = sys.argv[5]
is_half = sys.argv[6].lower() == "true"
else:
i_gpu = sys.argv[4]
exp_dir = sys.argv[5]
os.environ["CUDA_VISIBLE_DEVI... | 155 | 4,582 |
Retrieval-based-Voice-Conversion-WebUI | train/dataset/slicer2.py | .py | import numpy as np
# This function is obtained from librosa.
def get_rms(
y,
frame_length=2048,
hop_length=512,
pad_mode="constant",
):
padding = (int(frame_length // 2), int(frame_length // 2))
y = np.pad(y, padding, mode=pad_mode)
axis = -1
# put our new within-frame axis at the end... | 261 | 9,150 |
Retrieval-based-Voice-Conversion-WebUI | i18n/i18n.py | .py | import json
import locale
import os
from tools.file_io import read_text
def load_language_list(language):
return json.loads(read_text(f"./i18n/locale/{language}.json"))
class I18nAuto:
def __init__(self, language=None):
if language in ["Auto", None]:
language = locale.getdefaultlocale()[... | 27 | 754 |
Retrieval-based-Voice-Conversion-WebUI | tools/progress.py | .py | import math
from i18n.i18n import I18nAuto
i18n = I18nAuto()
def should_report(index, total, max_updates=12):
if total <= 0:
return False
if total <= max_updates:
return True
interval = max(1, math.ceil(total / max_updates))
return index == 0 or index + 1 == total or (index + 1) % i... | 47 | 1,215 |
Retrieval-based-Voice-Conversion-WebUI | tools/cuda_graph.py | .py | import logging
import os
import threading
import time
from collections import OrderedDict
import torch
logger = logging.getLogger(__name__)
ENV_NAME = "RVC_CUDA_GRAPH"
MAX_CACHE_ENV = "RVC_CUDA_GRAPH_MAX_CACHE"
_probe_lock = threading.Lock()
_probe_result = None
def _device_type(device):
if isinstance(device,... | 228 | 7,721 |
Retrieval-based-Voice-Conversion-WebUI | tools/file_io.py | .py | def read_text(path, errors="strict", newline=None):
last_error = None
for encoding in (None, "utf8", "gbk"):
try:
kwargs = {"errors": "strict", "newline": newline}
if encoding is not None:
kwargs["encoding"] = encoding
with open(path, "r", **kwargs) as... | 16 | 602 |
Retrieval-based-Voice-Conversion-WebUI | tools/multispeaker.py | .py | import hashlib
import json
import os
import re
AUDIO_EXTENSIONS = {
".wav",
".flac",
".mp3",
".m4a",
".ogg",
".opus",
".aac",
".wma",
".mp4",
".mkv",
".webm",
}
SPEAKER_ID_MIN = 0
SPEAKER_ID_MAX = 109
MANIFEST_VERSION = 1
SPEAKER_DIR_RE = re.compile(r"^(.+)_(\d+)_(\d+)$")
... | 254 | 8,370 |
Retrieval-based-Voice-Conversion-WebUI | tools/process_utils.py | .py | import logging
import os
import signal
import subprocess
import time
logger = logging.getLogger(__name__)
def kill_process_tree(process, process_name="", task_logger=None):
"""Terminate a Popen process and every child process it created."""
if process is None:
return False
try:
if proces... | 72 | 2,075 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_webui.py | .py | import gc
import json
import logging
import os
import subprocess
import sys
import tempfile
import threading
import time
import traceback
import uuid
from collections import deque
from concurrent.futures import ThreadPoolExecutor, wait
from dataclasses import dataclass
from pathlib import Path
import numpy as np
impor... | 1,116 | 39,357 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/checkpoint.py | .py | """Checkpoint helpers shared by inference and training frontends."""
from __future__ import annotations
from pathlib import Path
from types import ModuleType
from typing import Any
import torch
STATE_DICT_KEYS = ("state", "state_dict", "model_state_dict")
def unwrap_state_dict(checkpoint: Any) -> Any:
"""Ret... | 128 | 4,161 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/utils.py | .py | """Model construction helpers."""
from __future__ import annotations
from .config import load_config
def get_model_from_config(model_type, config_path, model_kwargs_override=None):
"""Instantiate a separation model from a model configuration file."""
model_kwargs_override = model_kwargs_override or {}
c... | 54 | 1,922 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/__init__.py | .py | """Core model, configuration, and checkpoint API for music source separation.
`pymss_core` contains the shared pieces used by higher-level packages:
configuration loading, model construction, model definitions, and
checkpoint/state-dict helpers. It intentionally does not provide file audio
I/O, inference DSP pipelines... | 26 | 859 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/config.py | .py | import re
import yaml
class ConfigLoader(yaml.FullLoader):
"""YAML loader used by pymss-core model configuration files."""
pass
ConfigLoader.add_implicit_resolver(
"tag:yaml.org,2002:float",
re.compile(
r"""^[-+]?(
([0-9][0-9_]*)?\.[0-9_]+([eE][-+]?[0-9]+)?
|[0-9][0... | 136 | 3,670 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit_mlx.py | .py | import numpy as np
import torch
from .mlx_utils import mlx_periodic_hann_window
from .bandit.tfmodel import ResidualRNN, Transpose
from .bs_roformer.mlx_attention import _gelu, _linear, _mlx_dtype, _torch_to_mlx_array, mlx_to_torch_mps
def torch_to_mlx_input(tensor, dtype):
import mlx.core as mx
return mx.a... | 416 | 16,202 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/legacy_demucs.py | .py | import math
import random
import sys
import types
import warnings
from contextlib import contextmanager
from pathlib import Path
import torch
from torch import nn
from torch.nn import functional as F
import yaml
LEGACY_STEMS_4 = ["drums", "bass", "other", "vocals"]
LEGACY_STEMS_2 = ["vocals", "non_vocals"]
def cen... | 1,553 | 56,479 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/mdx23c_mlx.py | .py | import numpy as np
import torch
from .mlx_utils import mlx_periodic_hann_window
from .bs_roformer.mlx_attention import (
_gelu,
_linear,
_mlx_dtype,
_torch_to_mlx_array,
mlx_to_torch_mps,
)
from .mdx23c_tfc_tdf_v3 import Downscale, TFC_TDF, Upscale
def torch_to_mlx_input(tensor, dtype):
impor... | 304 | 11,119 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/mdx23c_tfc_tdf_v3.py | .py | import torch
import torch.nn as nn
from .spectrogram import SubbandSTFT, forward_subband_mask_model, get_activation
def get_norm(norm_type):
if norm_type == "BatchNorm":
return nn.BatchNorm2d
if norm_type == "InstanceNorm":
return lambda c: nn.InstanceNorm2d(c, affine=True)
if "GroupNorm"... | 176 | 6,138 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/apollo_mlx.py | .py | import torch
from .bs_roformer.mlx_attention import _mlx_dtype, _torch_to_mlx_array, mlx_to_torch_mps
from .look2hear.apollo import BSNet, ConvActNorm1d, ICB, RMSNorm
def torch_to_mlx_input(tensor, dtype):
import mlx.core as mx
return mx.array(tensor.detach().to(dtype=dtype).cpu().numpy())
def _mlx_param(... | 243 | 8,964 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/demucs_local.py | .py | import math
import random
import numpy as np
import torch
from torch import nn
from torch.nn import functional as F
def pad1d(x, paddings, mode="constant", value=0.0):
x0 = x
length = x.shape[-1]
left, right = paddings
if mode == "reflect":
max_pad = max(left, right)
if length <= max_... | 598 | 22,327 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/scnet_mlx.py | .py | import math
import numpy as np
import torch
from .mlx_utils import mlx_periodic_hann_window
from .bs_roformer.mlx_attention import _gelu, _linear, _mlx_dtype, _torch_to_mlx_array, mlx_to_torch_mps
from .scnet.scnet import Swish
def torch_to_mlx_input(tensor, dtype):
import mlx.core as mx
return mx.array(ten... | 412 | 15,197 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/demucs_mlx.py | .py | import math
import numpy as np
import torch
from .mlx_utils import mlx_periodic_hann_window
from .bs_roformer.mlx_attention import _gelu, _linear, _mlx_dtype, _torch_to_mlx_array, mlx_to_torch_mps
from .demucs_local import (
LayerScale,
MyGroupNorm,
)
def torch_to_mlx_input(tensor, dtype):
import mlx.cor... | 606 | 23,207 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/_dsp.py | .py | """Small DSP helpers needed by model definitions."""
from __future__ import annotations
import numpy as np
def hz_to_midi(hz):
"""Convert frequencies in Hz to MIDI note numbers."""
hz = np.asarray(hz)
return 69.0 + 12.0 * np.log2(hz / 440.0)
def midi_to_hz(midi):
"""Convert MIDI note numbers to fr... | 85 | 2,707 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/mlx_utils.py | .py | def mlx_periodic_hann_window(length, dtype):
import mlx.core as mx
length = int(length)
if length <= 0:
return mx.zeros((0,), dtype=dtype)
if length == 1:
return mx.ones((1,), dtype=dtype)
window = mx.hanning(length + 1)[:-1]
return window.astype(dtype)
def mlx_compile_cached(... | 25 | 646 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/spectrogram.py | .py | import torch
import torch.nn as nn
class SubbandSTFT:
def __init__(self, config):
self.n_fft = config.n_fft
self.hop_length = config.hop_length
self.window = torch.hann_window(window_length=self.n_fft, periodic=True)
self.dim_f = config.dim_f
def __call__(self, x):
win... | 88 | 2,684 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/demucs4ht.py | .py | import torch
import math
from torch import nn
from torch.nn import functional as F
from fractions import Fraction
from .demucs_local import (
CrossTransformerEncoder,
HDecLayer,
HEncLayer,
MultiWrap,
ScaledEmbedding,
ispectro,
pad1d,
rescale_module,
spectro,
)
from ..config import t... | 480 | 16,263 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/transformer.py | .py | import torch
from torch import nn
from torch.nn import Module, ModuleList
import torch.nn.functional as F
from .attend import Attend
_CUDA_ATTENTION_BACKEND_ALIASES = {
"auto": "auto",
"torch": "default",
"default": "default",
"sdpa": "default",
"flash": "flash",
"flash_attention": "flash",
... | 358 | 13,171 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/mlx_roformer.py | .py | import numpy as np
import torch
from ..mlx_utils import mlx_periodic_hann_window
from .bands import contiguous_dim_groups, dim_input_offsets
from .bs_roformer_hyperace import BSRoformerHyperACE
from . import hyperace_segm
from .mel_band_roformer import MelBandRoformer
from .mlx_attention import (
_COMPUTE_DTYPE,
... | 670 | 24,472 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/bands.py | .py | import os
from collections import defaultdict
from itertools import accumulate
from typing import Tuple
import torch
from torch import nn
from torch.nn import Module, ModuleList
import torch.nn.functional as F
from .transformer import RMSNorm
EXPERIMENTAL_TRAIN_GROUPED_BANDS_ENV = "PYMSS_CORE_EXPERIMENTAL_TRAIN_GRO... | 757 | 31,526 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/mel_band_roformer.py | .py | import torch
from torch import nn
from torch.nn import Module
from typing import Callable, Optional
from .._dsp import mel_filterbank
from .common import (
MaskEstimator,
RoformerRuntimeMixin,
forward_roformer_mask_core,
forward_spectral_roformer,
ignore_roformer_training_kwargs,
init_roformer... | 192 | 7,159 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/attend.py | .py | from torch import nn, einsum
import torch.nn.functional as F
class Attend(nn.Module):
def __init__(self, dropout=0.0, flash=False, scale=None):
super().__init__()
self.scale = scale
self.dropout = dropout
self.attn_dropout = nn.Dropout(dropout)
self.flash = flash
def f... | 30 | 978 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/bs_roformer.py | .py | from torch.nn import Module
from typing import Callable, Optional, Tuple
from .common import (
DEFAULT_FREQS_PER_BANDS,
MaskEstimator,
RMSNorm,
RoformerRuntimeMixin,
forward_bandsplit_roformer,
forward_roformer_mask_core,
ignore_roformer_training_kwargs,
init_roformer_band_modules,
... | 112 | 3,529 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/mlx_attention.py | .py | import numpy as np
import torch
from ..mlx_utils import mlx_compile_cached
_COMPUTE_DTYPE = torch.float16
_ROTARY_METAL_KERNEL = None
_ROTARY_METAL_UNAVAILABLE = False
def torch_mps_to_mlx(tensor):
import mlx.core as mx
return mx.array(tensor.detach().cpu().numpy())
def mlx_to_torch_mps(array, reference... | 409 | 14,131 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/hyperace_segm.py | .py | from typing import List
import torch
from torch import nn
import torch.nn.functional as F
def autopad(k, p=None):
return p if p is not None else k // 2 if isinstance(k, int) else [x // 2 for x in k]
class Conv(nn.Module):
def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):
super().__init__... | 332 | 13,477 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/bs_roformer_hyperace.py | .py | from typing import Tuple
import torch
from .bs_roformer import BSRoformer
from .common import MaskEstimator as RoformerMaskEstimator
from .hyperace_segm import SegmModel
class MaskEstimator(RoformerMaskEstimator):
def __init__(self, dim, dim_inputs: Tuple[int, ...], depth, mlp_expansion_factor=4):
super... | 44 | 1,507 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bs_roformer/common.py | .py | from functools import partial
from typing import NamedTuple
import torch
from torch import nn
from .bands import BandSplit, MaskEstimator
from .transformer import RMSNorm, Transformer
__all__ = (
"DEFAULT_FREQS_PER_BANDS",
"MaskEstimator",
"RMSNorm",
"RoformerRuntimeMixin",
"forward_bandsplit_ro... | 423 | 14,640 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/scnet/__init__.py | .py | from .scnet import SCNet
__all__ = ("SCNet",)
| 4 | 47 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/scnet/separation.py | .py | import torch
import torch.nn as nn
from torch.nn.modules.rnn import LSTM
class FeatureConversion(nn.Module):
def __init__(self, channels, inverse):
super().__init__()
self.inverse, self.channels = inverse, channels
def forward(self, x):
x = x.float()
if self.inverse:
... | 65 | 2,273 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/scnet/scnet.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
from collections import deque
from .separation import SeparationNet
import math
class Swish(nn.Module):
def forward(self, x):
return x * x.sigmoid()
class ConvolutionModule(nn.Module):
def __init__(self, channels, depth=2, compress=4... | 267 | 9,937 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/look2hear/__init__.py | .py | from .apollo import Apollo
__all__ = ("Apollo",)
| 4 | 50 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/look2hear/apollo.py | .py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
def _cached_inference_tensor(module, name, tensor, input, version):
if tensor is None:
return None
if tensor.device == input.device and tensor.dtype == input.dtype:
return tensor
key = (name, input.devic... | 550 | 22,011 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit_v2/bandsplit.py | .py | from ..bandit.bandsplit import (
SequentialNormFC as NormFC,
_ConfiguredBandSplitModule,
)
class BandSplitModule(_ConfiguredBandSplitModule):
norm_fc_cls = NormFC
complex_order = "freq_reim"
flatten_input = True
__all__ = ("BandSplitModule", "NormFC")
| 14 | 276 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit_v2/utils.py | .py | from ..bandit.core.model.bsrnn.utils import (
BandsplitSpecification,
BassBandsplitSpecification,
DrumBandsplitSpecification,
MelBandsplitSpecification,
MusicalBandsplitSpecification,
OtherBandsplitSpecification,
PerceptualBandsplitSpecification,
VocalBandsplitSpecification,
band_wid... | 34 | 897 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit_v2/maskestim.py | .py | from typing import Dict, List, Optional, Tuple, Type
import torch
from torch import nn
from ..bandit.maskestim import (
BaseNormMLP,
MaskEstimationModule as _MaskEstimationModule,
MaskEstimationModuleBase,
MaskEstimationModuleSuperBase,
NormMLP as _NormMLP,
OverlappingMaskEstimationModule as _... | 120 | 3,464 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit_v2/bandit.py | .py | from typing import Dict, List, Optional
import torch
from torch import nn
from ..bandit.core.model._spectral import _SpectralComponent
from .bandsplit import BandSplitModule
from .maskestim import OverlappingMaskEstimationModule
from .tfmodel import SeqBandModellingModule
from .utils import MusicalBandsplitSpecifica... | 327 | 10,645 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit_v2/tfmodel.py | .py | from ..bandit.tfmodel import (
ResidualRNN,
TimeFrequencyModellingModule,
Transpose,
_SeqBandModellingPreset,
)
class SeqBandModellingModule(_SeqBandModellingPreset):
@staticmethod
def _preset_runtime_options(n_modules, parallel_mode):
return {
"sequential_transpose": not p... | 19 | 516 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/vocal_remover/__init__.py | .py | from .uvr_lib_v5.vr_network.model_param_init import ModelParameters
from .uvr_lib_v5.vr_network.nets import BaseASPPNet, CascadedASPPNet, determine_model_capacity
from .uvr_lib_v5.vr_network.nets_new import BaseNet, CascadedNet
__all__ = (
"BaseASPPNet",
"BaseNet",
"CascadedASPPNet",
"CascadedNet",
... | 13 | 374 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/vocal_remover/uvr_lib_v5/vr_network/nets_new.py | .py | import torch
from torch import nn
import torch.nn.functional as F
from . import layers_new as layers
class BaseNet(nn.Module):
def __init__(self, nin, nout, nin_lstm, nout_lstm, dilations=((4, 2), (8, 4), (12, 6))):
super(BaseNet, self).__init__()
self.enc1 = layers.Conv2DBNActiv(nin, nout, 3, 1, ... | 119 | 4,338 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/vocal_remover/uvr_lib_v5/vr_network/layers_new.py | .py | import torch
from torch import nn
import torch.nn.functional as F
def crop_center(h1, h2):
h1_time, h2_time = h1.size(3), h2.size(3)
if h1_time == h2_time:
return h1
if h1_time < h2_time:
raise ValueError("h1_shape[3] must be greater than h2_shape[3]")
start = (h1_time - h2_time) // 2
... | 102 | 3,951 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/vocal_remover/uvr_lib_v5/vr_network/nets.py | .py | import torch
from torch import nn
import torch.nn.functional as F
from . import layers
class BaseASPPNet(nn.Module):
def __init__(self, nn_architecture, nin, ch, dilations=(4, 8, 16)):
super(BaseASPPNet, self).__init__()
self.nn_architecture = nn_architecture
self.enc1 = layers.Encoder(n... | 156 | 5,615 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/vocal_remover/uvr_lib_v5/vr_network/layers.py | .py | import torch
from torch import nn
import torch.nn.functional as F
def crop_center(h1, h2):
h1_time, h2_time = h1.size(3), h2.size(3)
if h1_time == h2_time:
return h1
if h1_time < h2_time:
raise ValueError("h1_shape[3] must be greater than h2_shape[3]")
start = (h1_time - h2_time) // 2
... | 136 | 4,689 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/vocal_remover/uvr_lib_v5/vr_network/model_param_init.py | .py | import json
N_BINS = "n_bins"
def int_keys(d):
return {int(key) if key.isdigit() else key: value for key, value in d}
class ModelParameters:
def __init__(self, config_path=""):
with open(config_path, "r") as f:
self.param = json.load(f, object_pairs_hook=int_keys)
for k in ["mi... | 20 | 524 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/bandsplit.py | .py | from typing import List, Tuple
import torch
from torch import nn
from torch.utils.checkpoint import checkpoint_sequential
from .core.model.bsrnn.utils import (
band_widths_from_specs,
check_no_gap,
check_no_overlap,
check_nonzero_bandwidth,
)
class NormFC(nn.Module):
def __init__(
self,
... | 167 | 5,427 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/maskestim.py | .py | from typing import Dict, List, Optional, Tuple, Type
import torch
from torch import nn
from torch.nn.modules import activation
from torch.utils.checkpoint import checkpoint_sequential
from .core.model.bsrnn.utils import (
band_widths_from_specs,
check_no_gap,
check_no_overlap,
check_nonzero_bandwidth,... | 313 | 10,739 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/tfmodel.py | .py | import warnings
import torch
from torch import nn
from torch.nn.modules import rnn
from torch.utils.checkpoint import checkpoint_sequential
class TimeFrequencyModellingModule(nn.Module):
pass
class ResidualRNN(nn.Module):
def __init__(
self,
emb_dim: int,
rnn_dim: int,
bidir... | 195 | 5,894 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/__init__.py | .py | __all__ = ("MultiMaskMultiSourceBandSplitRNNSimple",)
def __getattr__(name):
if name == "MultiMaskMultiSourceBandSplitRNNSimple":
from .model import MultiMaskMultiSourceBandSplitRNNSimple
return MultiMaskMultiSourceBandSplitRNNSimple
raise AttributeError(f"module {__name__!r} has no attribute... | 10 | 332 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/__init__.py | .py | __all__ = ("MultiMaskMultiSourceBandSplitRNNSimple",)
def __getattr__(name):
if name == "MultiMaskMultiSourceBandSplitRNNSimple":
from .bsrnn.wrapper import MultiMaskMultiSourceBandSplitRNNSimple
return MultiMaskMultiSourceBandSplitRNNSimple
raise AttributeError(f"module {__name__!r} has no a... | 10 | 340 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/_spectral.py | .py | from typing import Dict, Optional
import torch
from torch import nn
class _TorchSpectrogram(nn.Module):
def __init__(
self,
n_fft,
win_length,
hop_length,
window_fn,
wkwargs,
normalized,
center,
pad_mode,
onesided,
):
sup... | 96 | 2,739 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/bandsplit.py | .py | from typing import List, Tuple
from ....bandsplit import NormFC, _ConfiguredBandSplitModule
class BandSplitModule(_ConfiguredBandSplitModule):
norm_fc_cls = NormFC
complex_order = "reim_freq"
flatten_input = False
def __init__(
self,
band_specs: List[Tuple[float, float]],
emb... | 33 | 964 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/utils.py | .py | import os
from abc import abstractmethod
from typing import Callable
import numpy as np
import torch
from torch import Tensor
from ....._dsp import hz_to_midi, mel_filterbank as _mel_filterbank, midi_to_hz
def band_widths_from_specs(band_specs):
return [e - i for i, e in band_specs]
def check_nonzero_bandwidt... | 356 | 12,365 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/maskestim.py | .py | from ....maskestim import (
BaseNormMLP,
MaskEstimationModule,
MaskEstimationModuleBase,
MaskEstimationModuleSuperBase,
MultAddNormMLP,
NormMLP,
OverlappingMaskEstimationModule,
)
__all__ = (
"BaseNormMLP",
"MaskEstimationModule",
"MaskEstimationModuleBase",
"MaskEstimation... | 21 | 416 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/__init__.py | .py | from abc import ABC
from typing import Iterable, Mapping, Union
from torch import nn
class BandsplitCoreBase(nn.Module, ABC):
band_split: nn.Module
tf_model: nn.Module
mask_estim: Union[nn.Module, Mapping[str, nn.Module], Iterable[nn.Module]]
def __init__(self) -> None:
super().__init__()
... | 18 | 378 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/tfmodel.py | .py | from ....tfmodel import (
ResidualRNN,
TimeFrequencyModellingModule,
_SeqBandModellingPreset,
)
class SeqBandModellingModule(_SeqBandModellingPreset):
pass
__all__ = ("ResidualRNN", "SeqBandModellingModule", "TimeFrequencyModellingModule")
| 13 | 260 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/wrapper.py | .py | from typing import Dict, List, Optional, Tuple, Union
import torch
from .._spectral import _SpectralComponent
from .core import MultiSourceMultiMaskBandSplitCoreRNN
from .utils import (
BarkBandsplitSpecification,
EquivalentRectangularBandsplitSpecification,
MelBandsplitSpecification,
MusicalBandsplit... | 236 | 8,475 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss_core/modules/bandit/core/model/bsrnn/core.py | .py | from typing import Dict, List, Optional, Tuple
import torch
from torch import nn
from . import BandsplitCoreBase
from .bandsplit import BandSplitModule
from .maskestim import MaskEstimationModule, OverlappingMaskEstimationModule
from .tfmodel import SeqBandModellingModule
__all__ = ("MultiSourceMultiMaskBandSplitCor... | 172 | 6,080 |
Retrieval-based-Voice-Conversion-WebUI | tools/torchgate/torchgate.py | .py | import torch
from infer.rmvpe import STFT
from torch.nn.functional import conv1d, conv2d
from typing import Union, Optional
from .utils import linspace, temperature_sigmoid, amp_to_db
class TorchGate(torch.nn.Module):
"""
A PyTorch module that applies a spectral gate to an input signal.
Arguments:
... | 286 | 11,042 |
Retrieval-based-Voice-Conversion-WebUI | tools/torchgate/utils.py | .py | import torch
from torch.types import Number
@torch.no_grad()
def amp_to_db(
x, eps=torch.finfo(torch.float64).eps, top_db=40
) :
"""
Convert the input tensor from amplitude to decibel scale.
Arguments:
x {[torch.Tensor]} -- [Input tensor.]
Keyword Arguments:
eps {[float]} -- [Sma... | 71 | 2,486 |
Retrieval-based-Voice-Conversion-WebUI | tools/torchgate/__init__.py | .py | """
TorchGating is a PyTorch-based implementation of Spectral Gating
================================================
Author: Asaf Zorea
Contents
--------
torchgate imports all the functions from PyTorch, and in addition provides:
TorchGating --- A PyTorch module that applies a spectral gate to an input signal
... | 14 | 359 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/workflow.py | .py | from __future__ import annotations
import os
import re
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Callable
import numpy as np
import yaml
WORKFLOW_TEMPLATE = """version: 1
defaults:
device: auto
output_format: wav
model_dir: null
inference_params:
normaliz... | 716 | 25,887 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/logger.py | .py | import gzip
import logging
import os
import shutil
import sys
from datetime import datetime
MAX_LOG = 100
LOG_DIR = ".logs"
LOG_ENV_NAME = "PYMSS_LOG_FILE"
def _safe_relpath(pathname):
"""Implement the safe relpath helper.
Args:
pathname (str): Pathname value.
Returns:
Any: Computed res... | 340 | 10,267 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/progress.py | .py | import math
from time import time
from tqdm.auto import tqdm
def _format_progress_time(value):
"""Format progress seconds as mm:ss or hh:mm:ss."""
seconds = max(0, int(round(value or 0)))
hours, remainder = divmod(seconds, 3600)
minutes, seconds = divmod(remainder, 60)
if hours:
return f"... | 180 | 6,386 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/utils.py | .py | from contextlib import contextmanager, nullcontext
import numpy as np
import torch
import torch.nn as nn
from numpy.typing import NDArray
from typing import Dict
from pymss_core import get_model_from_config as _core_get_model_from_config
from .config import load_config
from .progress import _ProgressContext
def _m... | 1,110 | 36,910 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/separator.py | .py | import gc
import os
import logging
import re
from contextlib import contextmanager, nullcontext
from collections import deque
from concurrent.futures import ThreadPoolExecutor
import torch
import numpy as np
import platform
import subprocess
from time import time
from tqdm import tqdm
from .audio_io import load_audio,... | 1,780 | 74,348 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/__init__.py | .py | """Public Python API for pymss.
pymss provides model catalog helpers, model downloading, audio I/O, ensemble
utilities, logging helpers, and the ``MSSeparator`` runtime for music source
separation. Most users can import from this top-level package instead of
importing submodules directly.
Exports:
MSSeparator: Ma... | 69 | 2,590 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/model_registry.py | .py | import json
import os
from dataclasses import dataclass
from functools import lru_cache
from importlib import resources
from pathlib import Path
def _default_model_dir():
"""Implement the default model dir helper.
Args:
None: This callable does not accept user-provided arguments.
Returns:
... | 387 | 13,404 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/model_download.py | .py | import hashlib
import json
import os
import shutil
import subprocess
import time
import urllib.error
import urllib.parse
import urllib.request
from pathlib import Path
from tqdm import tqdm
from .model_registry import (
auxiliary_paths_for,
config_path_for,
get_model_entry,
model_path_for,
)
HF_REPO... | 400 | 14,585 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/ensemble.py | .py | from __future__ import annotations
from pathlib import Path
import librosa
import numpy as np
from .audio_io import load_audio, save_audio
ENSEMBLE_ALGORITHMS = (
"avg_wave",
"median_wave",
"min_wave",
"max_wave",
"avg_fft",
"median_fft",
"min_fft",
"max_fft",
)
def _as_channel_fir... | 325 | 12,269 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/audio_io.py | .py | import json
import subprocess
import av
import numpy as np
def _frame_to_audio(frame, mono):
"""Implement the frame to audio helper.
Args:
frame (Any): Frame value.
mono (bool): Mono value.
Returns:
Any: Computed result."""
audio = frame.to_ndarray()
audio = audio[None, ... | 281 | 10,454 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/cli.py | .py | import argparse
import json
import sys
import warnings
from .ensemble import ENSEMBLE_ALGORITHMS, save_ensemble_audio
from .logger import get_separation_logger
from .model_download import download_all, download_model
from .model_registry import create_separator, list_models, resolve_model
from .progress import _CliInf... | 588 | 22,967 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/config.py | .py | from pymss_core.config import AttrDict, ConfigLoader, load_config, to_attrdict, to_plain
__all__ = ("AttrDict", "ConfigLoader", "load_config", "to_attrdict", "to_plain")
| 4 | 171 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/errors.py | .py | class APIError(Exception):
"""Structured HTTP API error used by the pymss server.
Args:
status_code (int): Status code value.
code (str): Code value.
message (str): Message value.
param (str | None, optional): Param value. Defaults to None.
error_type (str, optional): Er... | 30 | 1,105 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/app.py | .py | import asyncio
import base64
import binascii
import json
import logging
from pathlib import Path
from ..model_download import DownloadError, download_model
from ..model_registry import model_root
from .audio import (
decode_pcm,
json_response,
normalize_stems,
parse_int,
validate_common_options,
... | 1,019 | 35,420 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/state.py | .py | from __future__ import annotations
import asyncio
from dataclasses import dataclass, field
from ..config import load_config
from ..logger import get_separation_logger
from ..model_download import download_model
from ..model_registry import create_separator, resolve_model
from ..separator import INFERENCE_PARAM_TARGET... | 386 | 11,698 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/models.py | .py | from __future__ import annotations
from ..model_download import remote_url
from ..model_registry import (
auxiliary_paths_for,
config_path_for,
get_model_entry,
list_models,
model_path_for,
model_root,
)
def _bool_query(value, *, default=False):
"""Implement the bool query helper.
Ar... | 231 | 7,893 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/__init__.py | .py | from .config import ServerConfig
def create_app(config):
"""Create the FastAPI application.
Args:
config (AttrDict | dict): Loaded pymss configuration.
Returns:
FastAPI: Configured application instance.
Example:
>>> app = create_app()"""
from .app import create_app as _c... | 37 | 730 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/webui.py | .py | from __future__ import annotations
from pathlib import Path
from fastapi import HTTPException
from fastapi.responses import FileResponse, JSONResponse, RedirectResponse
WEBUI_STATIC_DIR = Path(__file__).with_name("webui_static")
def _missing_assets_response():
"""Implement the missing assets response helper.
... | 133 | 3,651 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/audio.py | .py | from __future__ import annotations
import base64
import io
import json
import os
import re
import tempfile
import time
import uuid
import zipfile
import numpy as np
from ..audio_io import save_audio
from .errors import APIError
PCM_FORMATS = {
"pcm_f32le": (np.dtype("<f4"), 4),
"pcm_s16le": (np.dtype("<i2"... | 364 | 11,961 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/server/config.py | .py | from dataclasses import dataclass, field
@dataclass
class ServerConfig:
"""Runtime configuration for the pymss HTTP server."""
model: str | None = None
model_dir: str | None = None
source: str = "modelscope"
endpoint: str | None = None
device: str = "auto"
device_ids: list[int] = field(de... | 24 | 677 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/_core_shims.py | .py | from importlib import import_module
import sys
_LOCAL_MODULE_PREFIX = "pymss.modules."
_CORE_MODULE_PREFIX = "pymss_core.modules."
def alias_module(local_name, core_name):
if not local_name.startswith(_LOCAL_MODULE_PREFIX):
raise ValueError(f"invalid local module alias: {local_name}")
if not core_nam... | 21 | 673 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/__init__.py | .py | from ._core_shims import alias_submodules
alias_submodules(
__name__,
"pymss_core.modules",
(
"apollo_mlx",
"bandit_mlx",
"demucs4ht",
"demucs_local",
"demucs_mlx",
"legacy_demucs",
"mdx23c_mlx",
"mdx23c_tfc_tdf_v3",
"mlx_utils",
... | 63 | 1,586 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/__init__.py | .py | from pymss_core.modules.vocal_remover import (
BaseASPPNet,
BaseNet,
CascadedASPPNet,
CascadedNet,
ModelParameters,
determine_model_capacity,
)
from .vr_separator import VRSeparator
__all__ = (
"BaseASPPNet",
"BaseNet",
"CascadedASPPNet",
"CascadedNet",
"ModelParameters",
... | 21 | 372 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/vr_mlx.py | .py | import torch
from ..bs_roformer.mlx_attention import _linear, _mlx_dtype, _torch_to_mlx_array
from pymss_core.modules.vocal_remover.uvr_lib_v5.vr_network import layers, layers_new, nets, nets_new
def _mlx_param(module, name, tensor, dtype):
cache = getattr(module, "_pymss_mlx_full_param_cache", None)
if cach... | 408 | 15,185 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/common_separator.py | .py | class CommonSeparator:
VOCAL_STEM = "Vocals"
OTHER_STEM = "Other"
BASS_STEM = "Bass"
DRUM_STEM = "Drums"
GUITAR_STEM = "Guitar"
PIANO_STEM = "Piano"
SYNTH_STEM = "Synthesizer"
STRINGS_STEM = "Strings"
WOODWINDS_STEM = "Woodwinds"
BRASS_STEM = "Brass"
WIND_INST_STEM = "Wind In... | 54 | 2,019 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/vr_models.py | .py | import os
VR_MODEL_METADATA = {
"10_SP-UVR-2B-32000-1.pth": {"primary_stem": "Instrumental", "secondary_stem": "Vocals", "vr_model_param": "2band_32000"},
"11_SP-UVR-2B-32000-2.pth": {"primary_stem": "Instrumental", "secondary_stem": "Vocals", "vr_model_param": "2band_32000"},
"12_SP-UVR-3B-44100.pth": {"... | 117 | 4,899 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/vr_separator.py | .py | import math
import os
from importlib.resources import files
from pathlib import Path
import numpy as np
import torch
from torch import nn
from torch.nn.utils.fusion import fuse_conv_bn_eval
from tqdm import tqdm
from pymss_core.modules.vocal_remover import ModelParameters, determine_model_capacity
from pymss_core.mod... | 460 | 20,473 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/uvr_lib_v5/__init__.py | .py | from pymss.modules._core_shims import alias_submodules
alias_submodules(
__name__,
"pymss_core.modules.vocal_remover.uvr_lib_v5",
(
"vr_network",
"vr_network.layers",
"vr_network.layers_new",
"vr_network.model_param_init",
"vr_network.nets",
"vr_network.nets_... | 15 | 335 |
Retrieval-based-Voice-Conversion-WebUI | tools/pymss/modules/vocal_remover/uvr_lib_v5/spec_utils.py | .py | import math
import platform
import traceback
import librosa
import numpy as np
import torch
ARM = "arm"
wav_resolution = (
"polyphase" if platform.system() == "Darwin" and (platform.processor() == ARM or ARM in platform.platform()) else "soxr_hq"
)
_HANN_WINDOW_CACHE = {}
_FILTER_MASK_CACHE = {}
def _hann_wi... | 389 | 14,986 |
Retrieval-based-Voice-Conversion-WebUI | infer/rmvpe.py | .py | import os
from typing import List, Optional, Tuple
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from librosa.util import normalize, pad_center, tiny
from scipy.signal import get_window
from tools.cuda_graph import run_cuda_graph
import logging
logger = logging.getLogger(__na... | 659 | 24,108 |
Retrieval-based-Voice-Conversion-WebUI | infer/fcpe.py | .py | import torch
from tools.cuda_graph import cuda_graph_enabled, run_cuda_graph
def _is_directml_device(device):
"""Return whether *device* is the PrivateUse1 device registered by DirectML."""
return getattr(device, "type", None) == "privateuseone" or "privateuseone" in str(
device
).lower()
class... | 162 | 7,273 |
Retrieval-based-Voice-Conversion-WebUI | infer/audio.py | .py | import platform, os
import ffmpeg
import numpy as np
import av
from io import BytesIO
import threading
_USE_TORCHAUDIO_GPU = False
_AUDIO_DEVICE = None
_AUDIO_DTYPE = None
_TORCH = None
_TORCHAUDIO = None
_TORCHAUDIO_RESAMPLE = None
_RESAMPLE_TRANSFORMS = {}
_RESAMPLE_LOCK = threading.Lock()
_FORCE_CPU_AUDIO = os.env... | 342 | 12,135 |
Retrieval-based-Voice-Conversion-WebUI | infer/cli.py | .py | import argparse
import os
import sys
import warnings
from io import BytesIO
from pathlib import Path
warnings.filterwarnings(
"ignore",
message=r"`torch\.nn\.utils\.weight_norm` is deprecated.*",
category=FutureWarning,
)
PROJECT_ROOT = Path(__file__).resolve().parent.parent
os.chdir(PROJECT_ROOT)
os.en... | 300 | 10,734 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.