repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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espnet | espnet-master/espnet2/svs/naive_rnn/naive_rnn.py | # Copyright 2021 Carnegie Mellon University (Jiatong Shi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Naive-SVS related modules."""
from typing import Dict, Optional, Tuple
import torch
import torch.nn.functional as F
from typeguard import check_argument_types
from espnet2.svs.abs_svs import AbsS... | 21,296 | 38.005495 | 88 | py |
espnet | espnet-master/espnet2/svs/naive_rnn/naive_rnn_dp.py | # Copyright 2021 Carnegie Mellon University (Jiatong Shi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""NaiveRNN-DP-SVS related modules."""
from typing import Dict, Optional, Tuple
import torch
import torch.nn.functional as F
from typeguard import check_argument_types
from espnet2.svs.abs_svs impor... | 23,391 | 38.986325 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/espnet_model.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""GAN-based text-to-speech ESPnet model."""
from contextlib import contextmanager
from typing import Any, Dict, Optional
import torch
from packaging.version import parse as V
from typeguard import check_argument_types
from ... | 9,364 | 39.021368 | 86 | py |
espnet | espnet-master/espnet2/gan_tts/abs_gan_tts.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""GAN-based TTS abstrast class."""
from abc import ABC, abstractmethod
from typing import Dict, Union
import torch
from espnet2.tts.abs_tts import AbsTTS
class AbsGANTTS(AbsTTS, ABC):
"""GAN-based TTS model abstract c... | 600 | 22.115385 | 70 | py |
espnet | espnet-master/espnet2/gan_tts/jets/alignments.py | # Copyright 2022 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from numba import jit
class AlignmentModule(nn.Module):
"""Alignment Learning Framework proposed for parallel TTS models in:
https://arxi... | 5,279 | 30.807229 | 85 | py |
espnet | espnet-master/espnet2/gan_tts/jets/loss.py | # Copyright 2022 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""JETS related loss module for ESPnet2."""
from typing import Tuple
import numpy as np
import torch
import torch.nn.functional as F
from scipy.stats import betabinom
from typeguard import check_argument_types
from espnet.nets.pyto... | 7,779 | 35.525822 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/jets/jets.py | # Copyright 2022 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""JETS module for GAN-TTS task."""
from typing import Any, Dict, Optional
import torch
from typeguard import check_argument_types
from espnet2.gan_tts.abs_gan_tts import AbsGANTTS
from espnet2.gan_tts.hifigan import (
HiFiGANM... | 24,388 | 36.121766 | 104 | py |
espnet | espnet-master/espnet2/gan_tts/jets/generator.py | # Copyright 2022 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Generator module in JETS."""
import logging
from typing import Any, Dict, List, Optional, Sequence, Tuple
import numpy as np
import torch
import torch.nn.functional as F
from espnet2.gan_tts.hifigan import HiFiGANGenerator
from ... | 35,386 | 43.850444 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/jets/length_regulator.py | # Copyright 2022 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import logging
import torch
class GaussianUpsampling(torch.nn.Module):
"""Gaussian upsampling with fixed temperature as in:
https://arxiv.org/abs/2010.04301
"""
def __init__(self, delta=0.1):
super().__in... | 2,017 | 30.53125 | 83 | py |
espnet | espnet-master/espnet2/gan_tts/melgan/residual_stack.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Residual stack module in MelGAN.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
from typing import Any, Dict
import torch
class ResidualStack(torch.nn.Module):
"""Residual stack modu... | 2,464 | 33.71831 | 85 | py |
espnet | espnet-master/espnet2/gan_tts/melgan/pqmf.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Pseudo QMF modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import numpy as np
import torch
import torch.nn.functional as F
from scipy.signal import kaiser
def design_prototype_fil... | 5,141 | 31.1375 | 84 | py |
espnet | espnet-master/espnet2/gan_tts/melgan/melgan.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""MelGAN Modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import logging
from typing import Any, Dict, List
import numpy as np
import torch
from espnet2.gan_tts.melgan.residual_stack... | 16,694 | 35.058315 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/wavenet/wavenet.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""WaveNet modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import logging
import math
from typing import Optional
import torch
from espnet2.gan_tts.wavenet.residual_block import Conv... | 6,901 | 34.394872 | 87 | py |
espnet | espnet-master/espnet2/gan_tts/wavenet/residual_block.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Residual block modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import math
from typing import Optional, Tuple
import torch
import torch.nn.functional as F
class Conv1d(torch.nn.C... | 5,352 | 30.863095 | 86 | py |
espnet | espnet-master/espnet2/gan_tts/joint/joint_text2wav.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Joint text-to-wav module for end-to-end training."""
from typing import Any, Dict
import torch
from typeguard import check_argument_types
from espnet2.gan_tts.abs_gan_tts import AbsGANTTS
from espnet2.gan_tts.hifigan impo... | 24,009 | 36.870662 | 104 | py |
espnet | espnet-master/espnet2/gan_tts/style_melgan/tade_res_block.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""StyleMelGAN's TADEResBlock Modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
from functools import partial
import torch
class TADELayer(torch.nn.Module):
"""TADE Layer module."... | 5,864 | 30.532258 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/style_melgan/style_melgan.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""StyleMelGAN Modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import copy
import logging
import math
from typing import Any, Dict, List, Optional
import numpy as np
import torch
impo... | 12,076 | 33.309659 | 86 | py |
espnet | espnet-master/espnet2/gan_tts/hifigan/loss.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""HiFiGAN-related loss modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
from typing import List, Optional, Tuple, Union
import torch
import torch.nn.functional as F
from espnet2.tts.... | 10,182 | 33.636054 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/hifigan/residual_block.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""HiFiGAN Residual block modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
from typing import Any, Dict, List
import torch
class ResidualBlock(torch.nn.Module):
"""Residual block... | 3,313 | 32.816327 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/hifigan/hifigan.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""HiFi-GAN Modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import copy
import logging
from typing import Any, Dict, List, Optional
import numpy as np
import torch
import torch.nn.fun... | 31,567 | 36.182568 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/utils/get_random_segments.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Function to get random segments."""
from typing import Optional, Tuple
import torch
def get_random_segments(
x: torch.Tensor,
x_lengths: torch.Tensor,
segment_size: int,
) -> Tuple[torch.Tensor, torch.Tensor]... | 1,440 | 23.423729 | 67 | py |
espnet | espnet-master/espnet2/gan_tts/vits/residual_coupling.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Residual affine coupling modules in VITS.
This code is based on https://github.com/jaywalnut310/vits.
"""
from typing import Optional, Tuple, Union
import torch
from espnet2.gan_tts.vits.flow import FlipFlow
from espnet... | 7,596 | 32.320175 | 85 | py |
espnet | espnet-master/espnet2/gan_tts/vits/flow.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Basic Flow modules used in VITS.
This code is based on https://github.com/jaywalnut310/vits.
"""
import math
from typing import Optional, Tuple, Union
import torch
from espnet2.gan_tts.vits.transform import piecewise_ra... | 9,380 | 29.163987 | 85 | py |
espnet | espnet-master/espnet2/gan_tts/vits/transform.py | """Flow-related transformation.
This code is derived from https://github.com/bayesiains/nflows.
"""
import numpy as np
import torch
from torch.nn import functional as F
DEFAULT_MIN_BIN_WIDTH = 1e-3
DEFAULT_MIN_BIN_HEIGHT = 1e-3
DEFAULT_MIN_DERIVATIVE = 1e-3
# TODO(kan-bayashi): Documentation and type hint
def pie... | 7,504 | 33.585253 | 83 | py |
espnet | espnet-master/espnet2/gan_tts/vits/loss.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""VITS-related loss modules.
This code is based on https://github.com/jaywalnut310/vits.
"""
import torch
import torch.distributions as D
class KLDivergenceLoss(torch.nn.Module):
"""KL divergence loss."""
def for... | 2,215 | 29.356164 | 83 | py |
espnet | espnet-master/espnet2/gan_tts/vits/duration_predictor.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Stochastic duration predictor modules in VITS.
This code is based on https://github.com/jaywalnut310/vits.
"""
import math
from typing import Optional
import torch
import torch.nn.functional as F
from espnet2.gan_tts.vi... | 6,185 | 31.051813 | 86 | py |
espnet | espnet-master/espnet2/gan_tts/vits/vits.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""VITS module for GAN-TTS task."""
from contextlib import contextmanager
from distutils.version import LooseVersion
from typing import Any, Dict, Optional
import torch
from typeguard import check_argument_types
from espnet2... | 23,742 | 36.9888 | 104 | py |
espnet | espnet-master/espnet2/gan_tts/vits/generator.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Generator module in VITS.
This code is based on https://github.com/jaywalnut310/vits.
"""
import math
from typing import List, Optional, Tuple
import numpy as np
import torch
import torch.nn.functional as F
from espnet2... | 25,456 | 43.273043 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/vits/text_encoder.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Text encoder module in VITS.
This code is based on https://github.com/jaywalnut310/vits.
"""
import math
from typing import Tuple
import torch
from espnet.nets.pytorch_backend.conformer.encoder import Encoder
from espne... | 5,385 | 37.198582 | 86 | py |
espnet | espnet-master/espnet2/gan_tts/vits/posterior_encoder.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Posterior encoder module in VITS.
This code is based on https://github.com/jaywalnut310/vits.
"""
from typing import Optional, Tuple
import torch
from espnet2.gan_tts.wavenet import WaveNet
from espnet2.gan_tts.wavenet.... | 4,037 | 33.512821 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/vits/monotonic_align/__init__.py | """Maximum path calculation module.
This code is based on https://github.com/jaywalnut310/vits.
"""
import warnings
import numpy as np
import torch
from numba import njit, prange
try:
from .core import maximum_path_c
is_cython_avalable = True
except ImportError:
is_cython_avalable = False
warnings... | 2,493 | 30.175 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/parallel_wavegan/parallel_wavegan.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Parallel WaveGAN Modules.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import logging
import math
from typing import Any, Dict, Optional
import numpy as np
import torch
from espnet2.gan... | 12,423 | 34.195467 | 88 | py |
espnet | espnet-master/espnet2/gan_tts/parallel_wavegan/upsample.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Upsampling module.
This code is modified from https://github.com/kan-bayashi/ParallelWaveGAN.
"""
from typing import Any, Dict, List, Optional
import numpy as np
import torch
import torch.nn.functional as F
from espnet2... | 6,161 | 31.951872 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/espnet_model.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""GAN-based Singing-voice-synthesis ESPnet model."""
from contextlib import contextmanager
from typing import Any, Dict, Optional
import torch
from packaging.version import parse as V
from typeguar... | 19,103 | 42.124153 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/abs_gan_svs.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""GAN-based SVS abstrast class."""
from abc import ABC, abstractmethod
from typing import Dict, Union
import torch
from espnet2.svs.abs_svs import AbsSVS
class AbsGANSVS(AbsSVS, ABC):
"""GAN... | 627 | 22.259259 | 70 | py |
espnet | espnet-master/espnet2/gan_svs/uhifigan/sine_generator.py | import numpy as np
import torch
class SineGen(torch.nn.Module):
"""Definition of sine generator
SineGen(samp_rate, harmonic_num = 0,
sine_amp = 0.1, noise_std = 0.003,
voiced_threshold = 0,
flag_for_pulse=False)
sample_rate: sampling rate in Hz
harmonic_num: number... | 5,613 | 38.258741 | 86 | py |
espnet | espnet-master/espnet2/gan_svs/uhifigan/uhifigan.py | # -*- coding: utf-8 -*-
"""Unet-baed HiFi-GAN Modules.
This code is based on https://github.com/jik876/hifi-gan
and https://github.com/kan-bayashi/ParallelWaveGAN.
"""
import logging
from typing import List, Optional
import numpy as np
import torch
import torch.nn.functional as F
try:
from parallel_wavegan.la... | 19,291 | 37.738956 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/joint/joint_score2wav.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Joint text-to-wav module for end-to-end training."""
from typing import Any, Dict, Optional
import torch
from typeguard import check_argument_types
from espnet2.gan_svs.abs_gan_svs import AbsGANSVS
from espnet2.gan_tts.hi... | 33,872 | 41.183064 | 104 | py |
espnet | espnet-master/espnet2/gan_svs/avocodo/avocodo.py | # Copyright 2023 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Avocodo Modules.
This code is modified from https://github.com/ncsoft/avocodo.
"""
import logging
from typing import Any, Dict, List, Optional
import torch
import torch.nn.functional as F
from torch.nn import Conv1d
from torc... | 29,046 | 33.172941 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/pits/modules.py | import torch
import torch.nn as nn
class WN(torch.nn.Module):
def __init__(
self,
hidden_channels,
kernel_size,
dilation_rate,
n_layers,
gin_channels=0,
p_dropout=0,
):
super(WN, self).__init__()
assert kernel_size % 2 == 1
self.h... | 3,542 | 34.787879 | 86 | py |
espnet | espnet-master/espnet2/gan_svs/pits/ying_decoder.py | import torch
import torch.nn as nn
import espnet2.gan_svs.pits.modules as modules
# TODO (Yifeng): This comment is generated by ChatGPT, which may not be accurate.
class YingDecoder(nn.Module):
"""Ying decoder module."""
def __init__(
self,
hidden_channels,
kernel_size,
dilat... | 5,184 | 35.77305 | 86 | py |
espnet | espnet-master/espnet2/gan_svs/visinger2/visinger2_vocoder.py | # Copyright 2023 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""VISinger2 HiFi-GAN Modules.
This code is based on https://github.com/zhangyongmao/VISinger2
"""
import logging
import math
from typing import Any, Dict, List, Optional
import numpy as np
import torch
import torch.nn.functiona... | 35,285 | 34.145418 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/visinger2/ddsp.py | import math
import librosa as li
import numpy as np
import torch
import torch.fft as fft
import torch.nn as nn
from scipy.signal import get_window
def safe_log(x):
return torch.log(x + 1e-7)
@torch.no_grad()
def mean_std_loudness(dataset):
mean = 0
std = 0
n = 0
for _, _, l in dataset:
... | 5,159 | 25.597938 | 78 | py |
espnet | espnet-master/espnet2/gan_svs/utils/expand_f0.py | # Copyright 2023 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Function to get random segments."""
from typing import Optional, Tuple
import torch
import torch.nn.functional as F
def expand_f0(f0_frame, hop_length, method="interpolation"):
"""Expand f0 to output wave length.
Arg... | 1,165 | 29.684211 | 86 | py |
espnet | espnet-master/espnet2/gan_svs/vits/phoneme_predictor.py | # Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import torch
from espnet.nets.pytorch_backend.conformer.encoder import Encoder
class PhonemePredictor(torch.nn.Module):
"""
Phoneme Predictor module in VISinger.
"""
def __init__(
self,
vocabs: in... | 4,212 | 39.12381 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/vits/prior_decoder.py | # Copyright 2023 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import torch
from espnet.nets.pytorch_backend.conformer.encoder import Encoder
from espnet.nets.pytorch_backend.nets_utils import make_non_pad_mask
class PriorDecoder(torch.nn.Module):
def __init__(
self,
out_... | 5,294 | 40.367188 | 87 | py |
espnet | espnet-master/espnet2/gan_svs/vits/modules.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import torch
class Projection(torch.nn.Module):
def __init__(self, hidden_channels, out_channels):
super().__init__()
self.hidden_channels = hidden_channels
... | 873 | 29.137931 | 74 | py |
espnet | espnet-master/espnet2/gan_svs/vits/pitch_predictor.py | # Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import torch
from espnet.nets.pytorch_backend.conformer.encoder import Encoder
from espnet.nets.pytorch_backend.nets_utils import make_non_pad_mask
class Decoder(torch.nn.Module):
"""Pitch or Mel decoder module in VISinger 2.... | 4,739 | 38.173554 | 85 | py |
espnet | espnet-master/espnet2/gan_svs/vits/duration_predictor.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Duration predictor modules in VISinger.
"""
import torch
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
class DurationPredictor(torch.nn.Module):
def __init__(
... | 2,729 | 29 | 84 | py |
espnet | espnet-master/espnet2/gan_svs/vits/vits.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""VITS/VISinger module for GAN-SVS task."""
from contextlib import contextmanager
from distutils.version import LooseVersion
from typing import Any, Dict, Optional
import torch
from torch.nn import... | 40,571 | 38.390291 | 104 | py |
espnet | espnet-master/espnet2/gan_svs/vits/generator.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Generator module in VISinger.
This code is based on https://github.com/jaywalnut310/vits.
This is a module of VISinger described in `VISinger: Variational Inference
with Adversarial Lea... | 41,328 | 43.53556 | 88 | py |
espnet | espnet-master/espnet2/gan_svs/vits/text_encoder.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Text encoder module in VISinger.
This code is based on https://github.com/jaywalnut310/vits
and https://github.com/zhangyongmao/VISinger2.
"""
import math
from typing import Optional, Tuple
imp... | 7,323 | 36.948187 | 86 | py |
espnet | espnet-master/espnet2/gan_svs/vits/length_regulator.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# Copyright 2022 Yifeng Yu
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Length regulator related modules."""
import logging
import torch
from espnet.nets.pytorch_backend.nets_utils import pad_list
class LengthRegulat... | 3,570 | 31.463636 | 88 | py |
espnet | espnet-master/espnet2/mt/espnet_model.py | import logging
from contextlib import contextmanager
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from typeguard import check_argument_types
from espnet2.asr.decoder.abs_decoder import AbsDecoder
from espnet2.asr.encoder.abs_encoder import AbsEncoder
from... | 10,123 | 34.900709 | 88 | py |
espnet | espnet-master/espnet2/mt/frontend/embedding.py | #!/usr/bin/env python3
# 2020, Technische Universität München; Ludwig Kürzinger
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Embedding Frontend for text based inputs."""
from typing import Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr.frontend.abs_frontend import... | 1,938 | 29.777778 | 82 | py |
espnet | espnet-master/espnet2/enh/espnet_model.py | """Enhancement model module."""
import contextlib
from typing import Dict, List, Optional, OrderedDict, Tuple
import numpy as np
import torch
from packaging.version import parse as V
from typeguard import check_argument_types
from espnet2.diar.layers.abs_mask import AbsMask
from espnet2.enh.decoder.abs_decoder import... | 21,569 | 40.401152 | 88 | py |
espnet | espnet-master/espnet2/enh/espnet_enh_s2t_model.py | import logging
import random
from contextlib import contextmanager
from typing import Dict, List, Tuple, Union
import numpy as np
import torch
import torch.nn.functional as F
from packaging.version import parse as V
from scipy.optimize import linear_sum_assignment
from typeguard import check_argument_types
from espne... | 19,330 | 35.820952 | 88 | py |
espnet | espnet-master/espnet2/enh/abs_enh.py | from abc import ABC, abstractmethod
from collections import OrderedDict
from typing import Tuple
import torch
class AbsEnhancement(torch.nn.Module, ABC):
# @abstractmethod
# def output_size(self) -> int:
# raise NotImplementedError
@abstractmethod
def forward(
self,
input: to... | 643 | 23.769231 | 56 | py |
espnet | espnet-master/espnet2/enh/espnet_model_tse.py | """Enhancement model module."""
import contextlib
from typing import Dict, List, OrderedDict, Tuple
import torch
from typeguard import check_argument_types
from espnet2.enh.decoder.abs_decoder import AbsDecoder
from espnet2.enh.encoder.abs_encoder import AbsEncoder
from espnet2.enh.extractor.abs_extractor import AbsE... | 13,324 | 38.423077 | 88 | py |
espnet | espnet-master/espnet2/enh/separator/dan_separator.py | from collections import OrderedDict
from functools import reduce
from typing import Dict, List, Optional, Tuple, Union
import torch
import torch.nn.functional as Fun
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.separator.abs_separator import A... | 6,012 | 35.005988 | 86 | py |
espnet | espnet-master/espnet2/enh/separator/tfgridnet_separator.py | import math
from collections import OrderedDict
from typing import Dict, List, Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn import init
from torch.nn.parameter import Parameter
from espnet2.enh.decoder.stft_decoder import STFTDecoder
from espnet2.enh.encoder.stft_en... | 14,294 | 35.466837 | 88 | py |
espnet | espnet-master/espnet2/enh/separator/conformer_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.separator.abs_separator import AbsSeparator
from espne... | 7,130 | 39.288136 | 86 | py |
espnet | espnet-master/espnet2/enh/separator/dprnn_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.layers.dprnn import DPRNN, merge_feature, split_featur... | 4,412 | 32.431818 | 86 | py |
espnet | espnet-master/espnet2/enh/separator/fasnet_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple
import torch
from packaging.version import parse as V
from espnet2.enh.layers.fasnet import FaSNet_TAC
from espnet2.enh.layers.ifasnet import iFaSNet
from espnet2.enh.separator.abs_separator import AbsSeparator
is_torch_1_9_plus = V(t... | 3,677 | 30.435897 | 87 | py |
espnet | espnet-master/espnet2/enh/separator/ineube_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.decoder.stft_decoder import STFTDecoder
from espnet2.enh.encoder.stft_encoder import STFTEncoder
from espnet2.... | 11,343 | 37.195286 | 88 | py |
espnet | espnet-master/espnet2/enh/separator/dpcl_e2e_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.separator.abs_separator import AbsSeparator
from espnet.nets.pytorch_backend.rnn.encoders impor... | 6,677 | 33.78125 | 88 | py |
espnet | espnet-master/espnet2/enh/separator/tcn_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.layers.tcn import TemporalConvNet
from espnet2.enh.sep... | 4,478 | 31.223022 | 84 | py |
espnet | espnet-master/espnet2/enh/separator/svoice_separator.py | import math
from collections import OrderedDict
from typing import Dict, List, Optional, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from espnet2.enh.layers.dpmulcat import DPMulCat
from espnet2.enh.layers.dprnn import merge_feature, split_feature
from espnet2.enh.separator.abs_separator ... | 7,042 | 34.215 | 114 | py |
espnet | espnet-master/espnet2/enh/separator/transformer_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.separator.abs_separator import AbsSeparator
from espne... | 6,107 | 36.018182 | 86 | py |
espnet | espnet-master/espnet2/enh/separator/neural_beamformer.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.dnn_beamformer import DNN_Beamformer
from espnet2.enh.layers.dnn_wpe import DNN_WPE
from espnet2.enh.separator.abs_separator import AbsSeparator... | 10,439 | 38.24812 | 85 | py |
espnet | espnet-master/espnet2/enh/separator/abs_separator.py | from abc import ABC, abstractmethod
from collections import OrderedDict
from typing import Dict, Optional, Tuple
import torch
class AbsSeparator(torch.nn.Module, ABC):
@abstractmethod
def forward(
self,
input: torch.Tensor,
ilens: torch.Tensor,
additional: Optional[Dict] = Non... | 652 | 21.517241 | 63 | py |
espnet | espnet-master/espnet2/enh/separator/dptnet_separator.py | from collections import OrderedDict
from distutils.version import LooseVersion
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.layers.dptnet import DPTNet
from espnet2.enh.layers.... | 6,828 | 33.145 | 86 | py |
espnet | espnet-master/espnet2/enh/separator/rnn_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.separator.abs_separator import AbsSeparator
from espne... | 4,807 | 29.43038 | 86 | py |
espnet | espnet-master/espnet2/enh/separator/asteroid_models.py | import warnings
from collections import OrderedDict
from typing import Dict, Optional, Tuple
import torch
from espnet2.enh.separator.abs_separator import AbsSeparator
class AsteroidModel_Converter(AbsSeparator):
def __init__(
self,
encoder_output_dim: int,
model_name: str,
num_sp... | 5,364 | 31.91411 | 88 | py |
espnet | espnet-master/espnet2/enh/separator/dc_crn_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex, new_complex_like
from espnet2.enh.layers.dc_crn import DC_CRN
from esp... | 7,510 | 40.960894 | 87 | py |
espnet | espnet-master/espnet2/enh/separator/dccrn_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
import torch.nn as nn
import torch.nn.functional as F
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complexnn import (
ComplexBatchNorm,
Comp... | 13,913 | 37.016393 | 88 | py |
espnet | espnet-master/espnet2/enh/separator/dpcl_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.separator.abs_separator import AbsSeparator
from espnet.nets.pytorch_backend.rnn.encoders impor... | 4,878 | 33.85 | 94 | py |
espnet | espnet-master/espnet2/enh/separator/skim_separator.py | from collections import OrderedDict
from typing import Dict, List, Optional, Tuple, Union
import torch
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet2.enh.layers.skim import SkiM
from espnet2.enh.separator.abs_separator import AbsSeparator
class Sk... | 5,293 | 32.0875 | 84 | py |
espnet | espnet-master/espnet2/enh/layers/skim.py | # An implementation of SkiM model described in
# "SkiM: Skipping Memory LSTM for Low-Latency Real-Time Continuous Speech Separation"
# (https://arxiv.org/abs/2201.10800)
#
import torch
import torch.nn as nn
from espnet2.enh.layers.dprnn import SingleRNN, merge_feature, split_feature
from espnet2.enh.layers.tcn import... | 13,471 | 32.42928 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/dc_crn.py | # Implementation of Densely-connected convolutional recurrent network (DC-CRN)
# [1] Tan et al. "Deep Learning Based Real-Time Speech Enhancement for Dual-Microphone
# Mobile Phones"
# https://web.cse.ohio-state.edu/~wang.77/papers/TZW.taslp21.pdf
from typing import List
import torch
import torch.nn as nn
f... | 18,544 | 35.505906 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/wpe.py | from typing import Tuple, Union
import torch
import torch.nn.functional as F
import torch_complex.functional as FC
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import einsum, matmul, reverse
is_torch_1_9_plus = V(torch.__version__) >= V... | 7,858 | 30.310757 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/dnn_wpe.py | from typing import Tuple, Union
import torch
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import to_double, to_float
from espnet2.enh.layers.mask_estimator import MaskEstimator
from espnet2.enh.layers.wpe import wpe_one_iteration
from espnet.nets.pytorch_backend.nets_utils impo... | 5,512 | 32.412121 | 87 | py |
espnet | espnet-master/espnet2/enh/layers/dpmulcat.py | import torch
import torch.nn as nn
class MulCatBlock(nn.Module):
"""The MulCat block.
Args:
input_size: int, dimension of the input feature.
The input should have shape (batch, seq_len, input_size).
hidden_size: int, dimension of the hidden state.
dropout: float, the dropo... | 6,771 | 34.642105 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/ifasnet.py | # The implementation of iFaSNet in
# Luo. et al. "Implicit Filter-and-sum Network for
# Multi-channel Speech Separation"
#
# The implementation is based on:
# https://github.com/yluo42/TAC
# Licensed under CC BY-NC-SA 3.0 US.
#
import torch
import torch.nn as nn
from espnet2.enh.layers import dprnn
from espnet2.enh.l... | 7,647 | 33.922374 | 87 | py |
espnet | espnet-master/espnet2/enh/layers/beamformer_th.py | """Beamformer module."""
from typing import List, Union
import torch
import torch_complex.functional as FC
import torchaudio
def prepare_beamformer_stats(
signal,
masks_speech,
mask_noise,
powers=None,
beamformer_type="mvdr",
bdelay=3,
btaps=5,
eps=1e-6,
):
"""Prepare necessary st... | 37,803 | 34.166512 | 102 | py |
espnet | espnet-master/espnet2/enh/layers/tcndenseunet.py | import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.torch_utils.get_layer_from_string import get_layer
is_torch_1_9_plus = V(torch.__version__) >= V("1.9.0")
class Conv2DActNorm(torch.nn.Module):
"""Basic Conv2D + activation + instance norm building ... | 14,465 | 30.311688 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/fasnet.py | # The implementation of FaSNet in
# Y. Luo, et al. “FaSNet: Low-Latency Adaptive Beamforming
# for Multi-Microphone Audio Processing”
# The implementation is based on:
# https://github.com/yluo42/TAC
# Licensed under CC BY-NC-SA 3.0 US.
#
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functiona... | 14,366 | 31.213004 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/adapt_layers.py | # noqa E501: Ported from https://github.com/BUTSpeechFIT/speakerbeam/blob/main/src/models/adapt_layers.py
# Copyright (c) 2021 Brno University of Technology
# Copyright (c) 2021 Nippon Telegraph and Telephone corporation (NTT).
# All rights reserved
# By Katerina Zmolikova, August 2021.
from functools import partial
... | 4,373 | 32.906977 | 105 | py |
espnet | espnet-master/espnet2/enh/layers/conv_utils.py | # noqa: E501 ported from https://discuss.pytorch.org/t/utility-function-for-calculating-the-shape-of-a-conv-output/11173/7
import math
def num2tuple(num):
return num if isinstance(num, tuple) else (num, num)
def conv2d_output_shape(h_w, kernel_size=1, stride=1, pad=0, dilation=1):
h_w, kernel_size, stride, ... | 1,462 | 24.224138 | 122 | py |
espnet | espnet-master/espnet2/enh/layers/complexnn.py | import torch
import torch.nn as nn
import torch.nn.functional as F
class NavieComplexLSTM(nn.Module):
def __init__(
self,
input_size,
hidden_size,
projection_dim=None,
bidirectional=False,
batch_first=False,
):
super(NavieComplexLSTM, self).__init__()
... | 14,634 | 32.643678 | 85 | py |
espnet | espnet-master/espnet2/enh/layers/beamformer.py | """Beamformer module."""
from typing import List, Union
import torch
from packaging.version import parse as V
from torch_complex import functional as FC
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import (
cat,
complex_norm,
einsum,
inverse,
is_complex,
... | 42,554 | 35.590714 | 102 | py |
espnet | espnet-master/espnet2/enh/layers/dprnn.py | # The implementation of DPRNN in
# Luo. et al. "Dual-path rnn: efficient long sequence modeling
# for time-domain single-channel speech separation."
#
# The code is based on:
# https://github.com/yluo42/TAC/blob/master/utility/models.py
# Licensed under CC BY-NC-SA 3.0 US.
#
import torch
import torch.nn as nn
from to... | 14,234 | 33.635036 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/mask_estimator.py | from typing import Tuple, Union
import numpy as np
import torch
from packaging.version import parse as V
from torch.nn import functional as F
from torch_complex.tensor import ComplexTensor
from espnet2.enh.layers.complex_utils import is_complex
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
from esp... | 3,390 | 34.322917 | 85 | py |
espnet | espnet-master/espnet2/enh/layers/dptnet.py | # The implementation of DPTNet proposed in
# J. Chen, Q. Mao, and D. Liu, “Dual-path transformer network:
# Direct context-aware modeling for end-to-end monaural speech
# separation,” in Proc. ISCA Interspeech, 2020, pp. 2642–2646.
#
# Ported from https://github.com/ujscjj/DPTNet
import torch.nn as nn
from espnet2.en... | 6,539 | 34.351351 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/complex_utils.py | """Beamformer module."""
from typing import Sequence, Tuple, Union
import torch
from packaging.version import parse as V
from torch_complex import functional as FC
from torch_complex.tensor import ComplexTensor
EPS = torch.finfo(torch.double).eps
is_torch_1_8_plus = V(torch.__version__) >= V("1.8.0")
is_torch_1_9_plu... | 6,751 | 34.166667 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/tcn.py | # Implementation of the TCN proposed in
# Luo. et al. "Conv-tasnet: Surpassing ideal time–frequency
# magnitude masking for speech separation."
#
# The code is based on:
# https://github.com/kaituoxu/Conv-TasNet/blob/master/src/conv_tasnet.py
# Licensed under MIT.
#
import torch
import torch.nn as nn
import torch.nn... | 16,165 | 30.268859 | 88 | py |
espnet | espnet-master/espnet2/enh/layers/dnn_beamformer.py | """DNN beamformer module."""
import logging
from typing import List, Optional, Tuple, Union
import torch
from packaging.version import parse as V
from torch.nn import functional as F
from torch_complex.tensor import ComplexTensor
import espnet2.enh.layers.beamformer as bf_v1
import espnet2.enh.layers.beamformer_th as... | 23,362 | 37.174837 | 88 | py |
espnet | espnet-master/espnet2/enh/encoder/abs_encoder.py | from abc import ABC, abstractmethod
from typing import Tuple
import torch
class AbsEncoder(torch.nn.Module, ABC):
@abstractmethod
def forward(
self,
input: torch.Tensor,
ilens: torch.Tensor,
) -> Tuple[torch.Tensor, torch.Tensor]:
raise NotImplementedError
@property
... | 1,041 | 27.162162 | 81 | py |
espnet | espnet-master/espnet2/enh/encoder/null_encoder.py | import torch
from espnet2.enh.encoder.abs_encoder import AbsEncoder
class NullEncoder(AbsEncoder):
"""Null encoder."""
def __init__(self):
super().__init__()
@property
def output_dim(self) -> int:
return 1
def forward(self, input: torch.Tensor, ilens: torch.Tensor):
"""... | 503 | 20 | 64 | py |
espnet | espnet-master/espnet2/enh/encoder/stft_encoder.py | import torch
from packaging.version import parse as V
from torch_complex.tensor import ComplexTensor
from espnet2.enh.encoder.abs_encoder import AbsEncoder
from espnet2.layers.stft import Stft
is_torch_1_9_plus = V(torch.__version__) >= V("1.9.0")
class STFTEncoder(AbsEncoder):
"""STFT encoder for speech enhanc... | 4,672 | 32.378571 | 87 | py |
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