repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/__init__.py | ITMO_FS/filters/__init__.py | from .multivariate import *
from .univariate import *
from .unsupervised import *
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/TraceRatioFisher.py | ITMO_FS/filters/multivariate/TraceRatioFisher.py | from logging import getLogger
import numpy as np
from sklearn.metrics.pairwise import pairwise_distances
from ...utils import BaseTransformer, generate_features
class TraceRatioFisher(BaseTransformer):
"""Creates TraceRatio(similarity based) feature selection filter
performed in supervised way, i.e. fisher v... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/STIR.py | ITMO_FS/filters/multivariate/STIR.py | from logging import getLogger
import numpy as np
from sklearn.metrics import pairwise_distances
from sklearn.preprocessing import MinMaxScaler
from ...utils import knn_from_class, BaseTransformer
class STIR(BaseTransformer):
"""Feature selection using STIR algorithm.
Parameters
----------
n_feature... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/DISRwithMassive.py | ITMO_FS/filters/multivariate/DISRwithMassive.py | from logging import getLogger
import numpy as np
from sklearn.metrics import pairwise_distances
from ...utils import BaseTransformer, generate_features
from ...utils.information_theory import (entropy, joint_entropy,
mutual_information)
def _complementarity(x_i, x_j, y):
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/MultivariateFilter.py | ITMO_FS/filters/multivariate/MultivariateFilter.py | from logging import getLogger
import numpy as np
from sklearn.base import TransformerMixin
from .measures import (MEASURE_NAMES, mutual_information,
matrix_mutual_information)
from ...utils import BaseTransformer, generate_features
class MultivariateFilter(BaseTransformer):
"""Provides ba... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/FCBF.py | ITMO_FS/filters/multivariate/FCBF.py | from logging import getLogger
import numpy as np
from ...utils import BaseTransformer, generate_features
from ...utils.information_theory import entropy, conditional_entropy
class FCBFDiscreteFilter(BaseTransformer):
"""Create FCBF (Fast Correlation Based filter) feature selection filter
based on mutual inf... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/measures.py | ITMO_FS/filters/multivariate/measures.py | from ...utils.information_theory import *
def MIM(selected_features, free_features, x, y, **kwargs):
"""Mutual Information Maximization feature scoring criterion. This
criterion focuses only on increase of relevance. Given set of already
selected features and set of remaining features on dataset X with la... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/__init__.py | ITMO_FS/filters/multivariate/__init__.py | from .DISRwithMassive import *
from .FCBF import *
from .MultivariateFilter import MultivariateFilter
from .measures import *
from .TraceRatioFisher import TraceRatioFisher
from .STIR import STIR
from .mimaga import MIMAGA
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/multivariate/mimaga.py | ITMO_FS/filters/multivariate/mimaga.py | import numpy as np
import random
from sklearn.metrics import f1_score
from sklearn.pipeline import make_pipeline
from sklearn.preprocessing import StandardScaler
from sklearn.svm import SVC
from sklearn.model_selection import train_test_split
from functools import partial
from ...utils.information_theory import *
from ... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/VDM.py | ITMO_FS/filters/univariate/VDM.py | import numpy as np
from ITMO_FS.utils.functions import cartesian
from ...utils import BaseTransformer
# TODO some optimization and sklearn-like API
class VDM(BaseTransformer):
"""
Creates Value Difference Metric builder.
For continious features discretesation requered.
Parameters
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/NDFS.py | ITMO_FS/filters/univariate/NDFS.py | from logging import getLogger
import numpy as np
from sklearn.cluster import KMeans
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.neighbors import NearestNeighbors
from sklearn.preprocessing import OneHotEncoder
from ...utils import l21_norm, matrix_norm, power_neg_half, BaseTransformer
class... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/measures.py | ITMO_FS/filters/univariate/measures.py | from functools import partial, update_wrapper
from math import exp
import numpy as np
from scipy.sparse import lil_matrix
from scipy.stats import rankdata
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics.pairwise import pairwise_distances, euclidean_distances
from sklearn.neighbors import NearestNei... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | true |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/UnivariateFilter.py | ITMO_FS/filters/univariate/UnivariateFilter.py | from logging import getLogger
import numpy as np
from .measures import CR_NAMES, MEASURE_NAMES
from ...utils import (BaseTransformer, generate_features, check_restrictions,
apply_cr)
class UnivariateFilter(BaseTransformer):
"""Basic interface for using univariate measures for feature selec... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/RFS.py | ITMO_FS/filters/univariate/RFS.py | from logging import getLogger
import numpy as np
from sklearn.preprocessing import OneHotEncoder
from ...utils import l21_norm, matrix_norm, BaseTransformer
class RFS(BaseTransformer):
"""Robust Feature Selection via Joint L2,1-Norms Minimization algorithm.
Parameters
----------
n_features : int
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/__init__.py | ITMO_FS/filters/univariate/__init__.py | from .UnivariateFilter import UnivariateFilter
from .VDM import VDM
from .measures import anova, fit_criterion_measure, f_ratio_measure, \
gini_index, su_measure, modified_t_score, fechner_corr, \
information_gain, relief_measure, reliefF_measure, chi2_measure, \
spearman_corr, pearson_corr, laplacian_score... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/univariate/SPEC.py | ITMO_FS/filters/univariate/SPEC.py | from logging import getLogger
import numpy as np
from scipy.linalg import eigh
from sklearn.metrics.pairwise import pairwise_distances
from ...utils import l21_norm, matrix_norm, power_neg_half, BaseTransformer
class SPEC(BaseTransformer):
"""Spectral Feature Selection algorithm.
Parameters
----------
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/unsupervised/trace_ratio_laplacian.py | ITMO_FS/filters/unsupervised/trace_ratio_laplacian.py | from logging import getLogger
import numpy as np
from sklearn.metrics.pairwise import pairwise_distances
from sklearn.neighbors import NearestNeighbors
from ...utils import BaseTransformer
class TraceRatioLaplacian(BaseTransformer):
"""TraceRatio(similarity based) feature selection filter performed in
unsupe... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/unsupervised/MCFS.py | ITMO_FS/filters/unsupervised/MCFS.py | from logging import getLogger
import numpy as np
from scipy.linalg import eigh
from sklearn.linear_model import Lars
from sklearn.neighbors import NearestNeighbors
from sklearn.metrics.pairwise import pairwise_distances
from ...utils import BaseTransformer
class MCFS(BaseTransformer):
"""Unsupervised Feature Se... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/unsupervised/UDFS.py | ITMO_FS/filters/unsupervised/UDFS.py | from logging import getLogger
import numpy as np
from scipy.linalg import eigh
from sklearn.neighbors import NearestNeighbors
from ...utils import l21_norm, matrix_norm, BaseTransformer
class UDFS(BaseTransformer):
"""Unsupervised Discriminative Feature Selection algorithm.
Parameters
----------
n_... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/filters/unsupervised/__init__.py | ITMO_FS/filters/unsupervised/__init__.py | from .MCFS import MCFS
from .UDFS import UDFS
from .trace_ratio_laplacian import TraceRatioLaplacian
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/embedded/MOS.py | ITMO_FS/embedded/MOS.py | from logging import getLogger
import numpy as np
from imblearn.over_sampling import SMOTE
from sklearn.base import clone
from ..utils import augmented_rvalue, BaseTransformer
class MOS(BaseTransformer):
"""Perform Minimizing Overlapping Selection under SMOTE (MOSS) or under
No-Sampling (MOSNS) algorithm.
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/ITMO_FS/embedded/__init__.py | ITMO_FS/embedded/__init__.py | from .MOS import MOS
| python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/unsupervised_filters_test.py | test/unsupervised_filters_test.py | import unittest
import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import Pipeline
import numpy as np
from sklearn.utils.estimator_checks import check_estimator
from ITMO_FS.filters.unsupervised import *
from ITMO_FS.filters.univariate import *
np.random.seed(42)
class T... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/multivariate_filters_test.py | test/multivariate_filters_test.py | import unittest
import pandas as pd
from sklearn.linear_model import LogisticRegression
from sklearn.pipeline import Pipeline
import numpy as np
from sklearn.utils.estimator_checks import check_estimator
from ITMO_FS.filters.multivariate import *
from utils import load_dataset
np.random.seed(42)
class TestCases(u... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/wrapper_test.py | test/wrapper_test.py | import unittest
import pandas as pd
from math import sqrt
from scipy import stats
from sklearn.datasets import load_iris
from sklearn.datasets import make_classification, make_regression
from sklearn.linear_model import LinearRegression, LogisticRegression
from sklearn.metrics import f1_score
from sklearn.model_select... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/utils.py | test/utils.py | import dvc.api
import pandas as pd
datasets = ["arcene.csv",
"dexter.csv",
"dorothea.csv",
"gisette.csv",
"madelon.csv"]
def load_dataset(name): # todo fails to hold header
with dvc.api.open(
'test/datasets/' + name) as fd:
df = pd.read_csv(fd,... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/univariate_filters_test.py | test/univariate_filters_test.py | import unittest
from math import sqrt
import numpy as np
import pandas as pd
from scipy import stats
from sklearn.datasets import load_iris
from sklearn.datasets import make_classification, make_regression
from sklearn.feature_selection import chi2, f_classif, mutual_info_classif
from sklearn.linear_model import Logis... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/Melif_test.py | test/Melif_test.py | import datetime
import unittest
import pandas as pd
from sklearn.datasets import make_classification, make_regression
from sklearn.metrics import f1_score
from sklearn.model_selection import train_test_split
from sklearn.svm import SVC
from sklearn.utils.estimator_checks import check_estimator
from ITMO_FS.ensembles i... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/hybrid_test.py | test/hybrid_test.py | import unittest
from sklearn.linear_model import LogisticRegression
from sklearn.utils.estimator_checks import check_estimator
from sklearn.metrics import make_scorer
from ITMO_FS.filters import *
from ITMO_FS.wrappers import BackwardSelection
from ITMO_FS.utils import f1_scorer
from ITMO_FS.hybrid import FilterWrappe... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/univariate_measures_test.py | test/univariate_measures_test.py | import unittest
from ITMO_FS.filters.univariate.measures import *
from utils import load_dataset
class UnivariateMeasuresTest(unittest.TestCase):
madelon = load_dataset("madelon.csv")
def test_measures(self):
data = self.madelon.drop(['target'], axis=1).values
for f, answer in zip(
... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/ensemble_test.py | test/ensemble_test.py | import time
import unittest
import numpy as np
from sklearn.linear_model import LogisticRegression, RidgeClassifier
from ITMO_FS import BestSum
from utils import load_dataset
from sklearn.datasets import make_classification, make_regression
from sklearn.metrics import f1_score
from sklearn.model_selection import KFol... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/test/embedded_test.py | test/embedded_test.py | import unittest
import pandas as pd
from sklearn.linear_model import LogisticRegression, SGDClassifier
from sklearn.pipeline import Pipeline
import numpy as np
from sklearn.utils.estimator_checks import check_estimator
from ITMO_FS.embedded import *
from ITMO_FS.utils import weight_func
np.random.seed(42)
class T... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
ctlab/ITMO_FS | https://github.com/ctlab/ITMO_FS/blob/a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921/docs/conf.py | docs/conf.py | # Configuration file for the Sphinx documentation builder.
#
# This file only contains a selection of the most common options. For a full
# list see the documentation:
# https://www.sphinx-doc.org/en/master/usage/configuration.html
# -- Path setup --------------------------------------------------------------
# If ex... | python | BSD-3-Clause | a2e61e2fabb9dfb34d90a1130fc7f5f162a2c921 | 2026-01-05T07:10:29.546771Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/train.py | train.py | import importlib
import logging
import os
import pathlib
import sys
import click
import lightning.pytorch as pl
import torch.utils.data
import yaml
from lightning.pytorch.loggers import TensorBoardLogger
from utils.config_utils import read_full_config, print_config
from utils.training_utils import (
DsModelCheck... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/export_ckpt.py | export_ckpt.py | import pathlib
import json
import click
import torch
from tqdm import tqdm
from utils import get_latest_checkpoint_path
from utils.config_utils import read_full_config, print_config
@click.command(help='')
@click.option('--exp_name', required=False, metavar='EXP', help='Name of the experiment')
@click.option('--ckpt... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/process.py | process.py | import itertools
import multiprocessing
import pathlib
import random
from concurrent.futures import ProcessPoolExecutor, as_completed
from typing import Tuple, Union
import click
import numpy as np
import torch
import torchaudio
from tqdm import tqdm
from utils.config_utils import read_full_config
from utils.wav2F0 i... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/preprocess/__init__.py | preprocess/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/__init__.py | models/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/nsf_univnet/__init__.py | models/nsf_univnet/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/nsf_univnet/nsfunivnet.py | models/nsf_univnet/nsfunivnet.py | import numpy as np
import torch
import logging
# from modules import LVCBlock
import torch.nn.functional as F
from torch import nn
from modules.univ_ddsp.block import LVCBlock
LRELU_SLOPE = 0.1
from modules.ddsp.vocoder import CombSub, Sins
class SineGen(torch.nn.Module):
""" Definition of sine generator
S... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/ddspgan/ddspgan.py | models/ddspgan/ddspgan.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
from modules.ddsp.vocoder import CombSub, Sins
class DDSPgan(nn.Module):
def __init__(self,config):
super().__init__()
if config['model_args']['typ... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/ddspgan/__init__.py | models/ddspgan/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/HiFivae/models.py | models/HiFivae/models.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
LRELU_SLOPE = 0.1
class Encoder(nn.Module):
def __init__(self, h,
):
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/HiFivae/__init__.py | models/HiFivae/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/ddsp_univnet/ddspunivnet.py | models/ddsp_univnet/ddspunivnet.py |
import torch
import logging
# from modules import LVCBlock
import torch.nn.functional as F
from torch import nn
from modules.univ_ddsp.block import LVCBlock
LRELU_SLOPE = 0.1
from modules.ddsp.vocoder import CombSub, Sins
class DDSP(nn.Module):
def __init__(self,config):
super().__init__()
if ... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/ddsp_univnet/__init__.py | models/ddsp_univnet/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/lvc_ddspgan/__init__.py | models/lvc_ddspgan/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/lvc_ddspgan/lvc_ddspgan.py | models/lvc_ddspgan/lvc_ddspgan.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
from modules.lvc_ddsp.vocoder import CombSub, Sins
class DDSPgan(nn.Module):
def __init__(self, config):
super().__init__()
if config['model_args']... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/nsf_HiFigan/models.py | models/nsf_HiFigan/models.py | import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
from torch.nn.utils import remove_weight_norm, spectral_norm, weight_norm
LRELU_SLOPE = 0.1
class AttrDict(dict):
def __init__(self, *args, **kwargs):
supe... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/nsf_HiFigan/__init__.py | models/nsf_HiFigan/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/univnet/univnet.py | models/univnet/univnet.py |
import torch
import logging
# from modules import LVCBlock
import torch.nn.functional as F
from modules.univ_D.block import LVCBlock
LRELU_SLOPE = 0.1
class GLU(torch.nn.Module):
def __init__(self, dim):
super().__init__()
self.dim = dim
def forward(self, x):
out, gate = x.chunk(2,... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/models/univnet/__init__.py | models/univnet/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/utils/pitch_utils.py | utils/pitch_utils.py | import numpy as np
import torch
f0_bin = 256
f0_max = 1100.0
f0_min = 50.0
f0_mel_min = 1127 * np.log(1 + f0_min / 700)
f0_mel_max = 1127 * np.log(1 + f0_max / 700)
def f0_to_coarse(f0):
is_torch = isinstance(f0, torch.Tensor)
f0_mel = 1127 * (1 + f0 / 700).log() if is_torch else 1127 * np.log(1 + f0 / 700)
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/utils/wav2F0.py | utils/wav2F0.py | import librosa
import numpy as np
import parselmouth
import pyworld as pw
import torch
# from utils.pitch_utils import interp_f0
PITCH_EXTRACTORS_ID_TO_NAME = {
1: 'parselmouth',
2: 'harvest',
}
PITCH_EXTRACTORS_NAME_TO_ID = {v: k for k, v in PITCH_EXTRACTORS_ID_TO_NAME.items()}
def norm_f0(f0, uv=None):
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/utils/training_utils.py | utils/training_utils.py | import math
import re
from copy import deepcopy
from pathlib import Path
from typing import Dict
import lightning.pytorch as pl
import numpy as np
import torch
from lightning.pytorch.callbacks import ModelCheckpoint, TQDMProgressBar
from lightning.pytorch.utilities.rank_zero import rank_zero_info
from torch.optim.lr_s... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/utils/__init__.py | utils/__init__.py | from __future__ import annotations
import pathlib
import re
import types
from collections import OrderedDict
import numpy as np
import torch
from utils.training_utils import get_latest_checkpoint_path
def tensors_to_scalars(metrics):
new_metrics = {}
for k, v in metrics.items():
if isinstance(v, to... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/utils/config_utils.py | utils/config_utils.py | from __future__ import annotations
import pathlib
import lightning.pytorch.utilities
import yaml
loaded_config_files = {}
def override_dict(old_config: dict, new_config: dict):
for k, v in new_config.items():
if isinstance(v, dict) and k in old_config:
override_dict(old_config[k], new_confi... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/utils/wav2mel.py | utils/wav2mel.py | import numpy as np
import torch
import torch.nn.functional as F
import torch.utils.data
from librosa.filters import mel as librosa_mel_fn
# from loguru import logger
class PitchAdjustableMelSpectrogram:
def __init__(
self,
sample_rate=44100,
n_fft=2048,
win_length=2048,
ho... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/univnet_nsf.py | training/univnet_nsf.py | # import logging
# import os
import pathlib
import random
# import sys
# from typing import Dict
#
# import lightning.pytorch as pl
# import matplotlib
import numpy as np
import torch.utils.data
# from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import py... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/univnet.py | training/univnet.py | import logging
import os
import pathlib
import random
import sys
from typing import Dict
import lightning.pytorch as pl
import matplotlib
import numpy as np
import torch.utils.data
from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import pyplot as plt
fro... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/HiFivae_task.py | training/HiFivae_task.py | import logging
import os
import pathlib
import random
import sys
from typing import Dict
import lightning.pytorch as pl
import matplotlib
import numpy as np
import torch.utils.data
import torchaudio
from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/nsf_HiFigan_task_one_step_gan.py | training/nsf_HiFigan_task_one_step_gan.py | import pathlib
import random
import numpy as np
import torch.nn.functional as F
import torch.utils.data
import torchaudio
from matplotlib import pyplot as plt
from torch import nn
from torch.utils.data import Dataset
from models.nsf_HiFigan.models import Generator, AttrDict, MultiScaleDiscriminator, MultiPeriodDiscri... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/nsf_HiFigan_mrd_task.py | training/nsf_HiFigan_mrd_task.py | import pathlib
import random
import numpy as np
import torch.nn.functional as F
import torch.utils.data
import torchaudio
from matplotlib import pyplot as plt
from torch import nn
from torch.utils.data import Dataset
from models.nsf_HiFigan.models import Generator, AttrDict, MultiPeriodDiscriminator
from modules.univ... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/lvc_ddspgan_task.py | training/lvc_ddspgan_task.py | import logging
import os
import pathlib
import random
import sys
from typing import Dict
import lightning.pytorch as pl
import matplotlib
import numpy as np
import torch.utils.data
from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import pyplot as plt
fro... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/base_task_gan.py | training/base_task_gan.py | import logging
import os
import pathlib
import sys
from typing import Dict
import lightning.pytorch as pl
import matplotlib
import numpy as np
import torch.utils.data
from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from torch import nn
# torch.nn.utils.weight_norm
from... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/univnet_ddsp.py | training/univnet_ddsp.py | # import logging
# import os
import pathlib
import random
# import sys
# from typing import Dict
#
# import lightning.pytorch as pl
# import matplotlib
import numpy as np
import torch.utils.data
# from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import py... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/nsf_HiFigan_task.py | training/nsf_HiFigan_task.py | import pathlib
import random
import numpy as np
import torch.nn.functional as F
import torch.utils.data
import torchaudio
from matplotlib import pyplot as plt
from torch import nn
from torch.utils.data import Dataset
from models.nsf_HiFigan.models import Generator, AttrDict, MultiScaleDiscriminator, MultiPeriodDiscri... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/univnet_nsf_msd.py | training/univnet_nsf_msd.py | # import logging
# import os
import pathlib
import random
# import sys
# from typing import Dict
#
# import lightning.pytorch as pl
# import matplotlib
import numpy as np
import torch.utils.data
# from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import py... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/__init__.py | training/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/nsf_HiFigan_fast_task.py | training/nsf_HiFigan_fast_task.py | import pathlib
import random
import numpy as np
import torch.nn.functional as F
import torch.utils.data
import torchaudio
from matplotlib import pyplot as plt
from torch import nn
from torch.utils.data import Dataset
from models.nsf_HiFigan.models import Generator, AttrDict
from modules.univ_D.discriminator import Mu... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/ddspgan_task_2.py | training/ddspgan_task_2.py | import logging
import os
import pathlib
import random
import sys
from typing import Dict
import lightning.pytorch as pl
import matplotlib
import numpy as np
import torch.utils.data
from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import pyplot as plt
fro... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/training/ddspgan_task.py | training/ddspgan_task.py | import logging
import os
import pathlib
import random
import sys
from typing import Dict
import lightning.pytorch as pl
import matplotlib
import numpy as np
import torch.utils.data
from lightning.pytorch.utilities.rank_zero import rank_zero_debug, rank_zero_info, rank_zero_only
from matplotlib import pyplot as plt
fro... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/__init__.py | modules/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/univ_ddsp/block.py | modules/univ_ddsp/block.py | import torch
import torch.nn.functional as F
class KernelPredictor(torch.nn.Module):
''' Kernel predictor for the location-variable convolutions
'''
def __init__(self,
cond_channels,
conv_in_channels,
conv_out_channels,
conv_layers,
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/univ_ddsp/__init__.py | modules/univ_ddsp/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/fast_D/discriminator.py | modules/fast_D/discriminator.py | import numpy as np
import torch
import torch.nn.functional as F
import torch.nn as nn
class Transpose(nn.Module):
def __init__(self, dims):
super().__init__()
assert len(dims) == 2, 'dims must be a tuple of two dimensions'
self.dims = dims
def forward(self, x):
return x.tran... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/fast_D/__init__.py | modules/fast_D/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/nsf_univloss.py | modules/loss/nsf_univloss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.ddsp.loss import HybridLoss
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class nsf_univloss(nn.Module):
def __init__(self, config: dict):
super().__init__()
self... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/univloss.py | modules/loss/univloss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class univloss(nn.Module):
def __init__(self, config: dict):
super().__init__()
self.mel = PitchAdjustableMelSpectrogram(sample_r... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/ddsploss_2.py | modules/loss/ddsploss_2.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class ddsploss2(nn.Module):
def __init__(self,config:dict):
super().__init__()
self.mel=PitchAdjustableMelSpectrogram( sample_rat... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/vaeHiFiloss.py | modules/loss/vaeHiFiloss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.ddsp.loss import RSSLoss
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
def kl_loss(logs, m):
kl = 0.5 * (m**2 + torch.exp(logs) - logs - 1).sum(dim=1)
kl = torch.mean(kl)
return ... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/nsf_univloss_msd.py | modules/loss/nsf_univloss_msd.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.ddsp.loss import HybridLoss
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class nsf_univloss_msd(nn.Module):
def __init__(self, config: dict):
super().__init__()
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/ddsploss.py | modules/loss/ddsploss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class ddsploss(nn.Module):
def __init__(self,config:dict):
super().__init__()
self.mel=PitchAdjustableMelSpectrogram( sample_rate... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/__init__.py | modules/loss/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/ddsp_univloss.py | modules/loss/ddsp_univloss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.ddsp.loss import HybridLoss
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class ddsp_univloss(nn.Module):
def __init__(self, config: dict):
super().__init__()
sel... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/stft_loss.py | modules/loss/stft_loss.py | # -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# MIT License (https://opensource.org/licenses/MIT)
"""STFT-based Loss modules."""
import torch
import torch.nn.functional as F
def stft(x, fft_size, hop_size, win_length, window):
"""Perform STFT and convert to magnitude spectrogram.
Args:
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/loss/HiFiloss.py | modules/loss/HiFiloss.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from modules.loss.stft_loss import warp_stft
from utils.wav2mel import PitchAdjustableMelSpectrogram
class HiFiloss(nn.Module):
def __init__(self, config: dict):
super().__init__()
self.mel = PitchAdjustableMelSpectrogram(sample_r... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/lvc/lvcnet.py | modules/lvc/lvcnet.py | import torch
import torch.nn as nn
import torch.nn.functional as F
# from SWN import SwitchNorm1d
# class Conv1d(torch.nn.Conv1d):
# """Conv1d module with customized initialization."""
#
# def __init__(self, *args, **kwargs):
# """Initialize Conv1d module."""
# super(Conv1d, self).__init__(*a... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/lvc/__init__.py | modules/lvc/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/univ_D/block.py | modules/univ_D/block.py | import torch
import torch.nn.functional as F
class KernelPredictor(torch.nn.Module):
''' Kernel predictor for the location-variable convolutions
'''
def __init__(self,
cond_channels,
conv_in_channels,
conv_out_channels,
conv_layers,
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/univ_D/discriminator.py | modules/univ_D/discriminator.py | import torch
import torch.nn.functional as F
import torch.nn as nn
from torch.nn import Conv1d, AvgPool1d, Conv2d
from torch.nn.utils import weight_norm, spectral_norm
from modules.loss.stft_loss import stft
# from utils import get_padding
# from stft_loss import stft
LRELU_SLOPE = 0.1
def get_padding(kernel_size, d... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/univ_D/__init__.py | modules/univ_D/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/ddsp/mel2control.py | modules/ddsp/mel2control.py | # import gin
import numpy as np
import torch
import torch.nn as nn
from torch.nn.utils import weight_norm
from .pcmer import PCmer
def split_to_dict(tensor, tensor_splits):
"""Split a tensor into a dictionary of multiple tensors."""
labels = []
sizes = []
for k, v in tensor_splits.items():
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/ddsp/core.py | modules/ddsp/core.py | import torch
import torch.nn as nn
from torch.nn import functional as F
import math
import numpy as np
def get_fft_size(frame_size: int, ir_size: int, power_of_2: bool = True):
"""Calculate final size for efficient FFT.
Args:
frame_size: Size of the audio frame.
ir_size: Size of the convolving impulse res... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/ddsp/pcmer.py | modules/ddsp/pcmer.py | import torch
from torch import nn
import math
from functools import partial
from einops import rearrange, repeat
# from local_attention import LocalAttention
import torch.nn.functional as F
#import fast_transformers.causal_product.causal_product_cuda
class PCmer(nn.Module):
"""The encoder that is used in ... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/ddsp/loss.py | modules/ddsp/loss.py | import numpy as np
import torch
import torch.nn as nn
import torchaudio
from torch.nn import functional as F
from .core import upsample
class HybridLoss(nn.Module):
def __init__(self, block_size, fft_min, fft_max, n_scale, lambda_uv, device):
super().__init__()
self.loss_rss_func = RSSLoss(fft_min... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/ddsp/__init__.py | modules/ddsp/__init__.py | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false | |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/ddsp/vocoder.py | modules/ddsp/vocoder.py | import os
import numpy as np
import yaml
import torch
import torch.nn.functional as F
from librosa.filters import mel as librosa_mel_fn
from .mel2control import Mel2Control
from .core import frequency_filter, upsample, remove_above_fmax
class DotDict(dict):
def __getattr__(*args):
val = dict.get(*... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/lvc_ddsp/mel2control.py | modules/lvc_ddsp/mel2control.py | # import gin
import numpy as np
import torch
import torch.nn as nn
from torch.nn.utils import weight_norm
from .pcmer import PCmer
def split_to_dict(tensor, tensor_splits):
"""Split a tensor into a dictionary of multiple tensors."""
labels = []
sizes = []
for k, v in tensor_splits.items():
... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
openvpi/SingingVocoders | https://github.com/openvpi/SingingVocoders/blob/dbc848fa4de79a9181d359d4656b3634bc79d415/modules/lvc_ddsp/core.py | modules/lvc_ddsp/core.py | import torch
import torch.nn as nn
from torch.nn import functional as F
import math
import numpy as np
def get_fft_size(frame_size: int, ir_size: int, power_of_2: bool = True):
"""Calculate final size for efficient FFT.
Args:
frame_size: Size of the audio frame.
ir_size: Size of the convolving impulse res... | python | MIT | dbc848fa4de79a9181d359d4656b3634bc79d415 | 2026-01-05T07:10:51.192436Z | false |
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