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/espnet/nets/pytorch_backend/transducer/conv1d_nets.py | """Convolution networks definition for custom archictecture."""
from typing import Optional, Tuple, Union
import torch
class Conv1d(torch.nn.Module):
"""1D convolution module for custom encoder.
Args:
idim: Input dimension.
odim: Output dimension.
kernel_size: Size of the convolving... | 7,246 | 27.644269 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transducer/transducer_tasks.py | """Module implementing Transducer main and auxiliary tasks."""
from typing import Any, List, Optional, Tuple
import torch
from espnet.nets.pytorch_backend.nets_utils import pad_list
from espnet.nets.pytorch_backend.transducer.joint_network import JointNetwork
from espnet.nets.pytorch_backend.transformer.label_smooth... | 15,051 | 31.231263 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transducer/transformer_decoder_layer.py | """Transformer decoder layer definition for custom Transducer model."""
from typing import Optional
import torch
from espnet.nets.pytorch_backend.transformer.attention import MultiHeadedAttention
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
from espnet.nets.pytorch_backend.transformer.pos... | 2,702 | 26.865979 | 82 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transducer/error_calculator.py | """CER/WER computation for Transducer model."""
from typing import List, Tuple, Union
import torch
from espnet.nets.beam_search_transducer import BeamSearchTransducer
from espnet.nets.pytorch_backend.transducer.custom_decoder import CustomDecoder
from espnet.nets.pytorch_backend.transducer.joint_network import Joint... | 4,829 | 27.579882 | 79 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transducer/initializer.py | """Parameter initialization for Transducer model."""
import math
from argparse import Namespace
import torch
from espnet.nets.pytorch_backend.initialization import set_forget_bias_to_one
def initializer(model: torch.nn.Module, args: Namespace):
"""Initialize Transducer model.
Args:
model: Transduc... | 1,304 | 29.348837 | 79 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transducer/custom_decoder.py | """Custom decoder definition for Transducer model."""
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from espnet.nets.pytorch_backend.transducer.blocks import build_blocks
from espnet.nets.pytorch_backend.transducer.utils import (
check_batch_states,
check_state,
pad_sequence,
)
... | 9,049 | 29.782313 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transducer/blocks.py | """Set of methods to create custom architecture."""
from typing import Any, Dict, List, Tuple, Union
import torch
from espnet.nets.pytorch_backend.conformer.convolution import ConvolutionModule
from espnet.nets.pytorch_backend.conformer.encoder_layer import (
EncoderLayer as ConformerEncoderLayer,
)
from espnet.... | 16,356 | 29.459963 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/tacotron2/encoder.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Tacotron2 encoder related modules."""
import torch
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
def encoder_init(m):
"""I... | 6,261 | 35.196532 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/tacotron2/decoder.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Tacotron2 decoder related modules."""
import torch
import torch.nn.functional as F
from espnet.nets.pytorch_backend.rnn.attentions import AttForwardTA
d... | 24,375 | 35.059172 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/tacotron2/cbhg.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""CBHG related modules."""
import torch
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from espnet... | 9,068 | 31.978182 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/fastspeech/duration_calculator.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Duration calculator related modules."""
import torch
from espnet.nets.pytorch_backend.e2e_tts_tacotron2 import Tacotron2
from espnet.nets.pytorch_backend.e2e_tts_transformer ... | 3,600 | 35.744898 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/fastspeech/duration_predictor.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Duration predictor related modules."""
import torch
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
class DurationPredictor(torch.nn.Module):
"... | 4,992 | 31.422078 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/fastspeech/length_regulator.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# 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 LengthRegulator(torch.nn.Module):
""... | 2,171 | 30.941176 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/rnn/decoders.py | """RNN decoder module."""
import logging
import math
import random
from argparse import Namespace
import numpy as np
import torch
import torch.nn.functional as F
from espnet.nets.ctc_prefix_score import CTCPrefixScore, CTCPrefixScoreTH
from espnet.nets.e2e_asr_common import end_detect
from espnet.nets.pytorch_backend... | 48,709 | 39.356255 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/rnn/attentions.py | """Attention modules for RNN."""
import math
import torch
import torch.nn.functional as F
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask, to_device
def _apply_attention_constraint(
e, last_attended_idx, backward_window=1, forward_window=3
):
"""Apply monotonic attention constraint.
T... | 73,205 | 36.217082 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/rnn/encoders.py | import logging
import numpy as np
import torch
import torch.nn.functional as F
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
from espnet.nets.e2e_asr_common import get_vgg2l_odim
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask, to_device
class RNNP(torch.nn.Module):
"... | 14,152 | 37.045699 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/lm/transformer.py | """Transformer language model."""
import logging
from typing import Any, List, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from espnet.nets.lm_interface import LMInterface
from espnet.nets.pytorch_backend.transformer.embedding import PositionalEncoding
from espnet.nets.pytorch_backend.tr... | 8,410 | 32.50996 | 86 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/lm/default.py | """Default Recurrent Neural Network Languge Model in `lm_train.py`."""
import logging
from typing import Any, List, Tuple
import torch
import torch.nn as nn
import torch.nn.functional as F
from espnet.nets.lm_interface import LMInterface
from espnet.nets.pytorch_backend.e2e_asr import to_device
from espnet.nets.scor... | 14,561 | 32.865116 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/lm/seq_rnn.py | """Sequential implementation of Recurrent Neural Network Language Model."""
import torch
import torch.nn as nn
import torch.nn.functional as F
from espnet.nets.lm_interface import LMInterface
class SequentialRNNLM(LMInterface, torch.nn.Module):
"""Sequential RNNLM.
See also:
https://github.com/pyto... | 5,940 | 32.189944 | 118 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/conformer/encoder_layer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Johns Hopkins University (Shinji Watanabe)
# Northwestern Polytechnical University (Pengcheng Guo)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encoder self-attention layer definition."""
import torch
from torch import n... | 6,761 | 36.566667 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/conformer/encoder.py | # Copyright 2020 Johns Hopkins University (Shinji Watanabe)
# Northwestern Polytechnical University (Pengcheng Guo)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encoder definition."""
import logging
import torch
from espnet.nets.pytorch_backend.conformer.convolution import Convoluti... | 12,154 | 39.516667 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/conformer/convolution.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Johns Hopkins University (Shinji Watanabe)
# Northwestern Polytechnical University (Pengcheng Guo)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""ConvolutionModule definition."""
from torch import nn
class ConvolutionMod... | 2,193 | 26.425 | 79 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/conformer/contextual_block_encoder_layer.py | # -*- coding: utf-8 -*-
"""
Created on Sat Aug 21 16:57:31 2021.
@author: Keqi Deng (UCAS)
"""
import torch
from torch import nn
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
class ContextualBlockEncoderLayer(nn.Module):
"""Contexutal Block Encoder layer module.
Args:
si... | 11,220 | 35.080386 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/conformer/swish.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Johns Hopkins University (Shinji Watanabe)
# Northwestern Polytechnical University (Pengcheng Guo)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Swish() activation function for Conformer."""
import torch
class Swish(tor... | 483 | 24.473684 | 70 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/maskctc/add_mask_token.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Johns Hopkins University (Shinji Watanabe)
# Waseda University (Yosuke Higuchi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Token masking module for Masked LM."""
import numpy
def mask_uniform(ys_pad, mask_token, eos,... | 1,352 | 32.825 | 74 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/maskctc/mask.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Johns Hopkins University (Shinji Watanabe)
# Waseda University (Yosuke Higuchi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Attention masking module for Masked LM."""
def square_mask(ys_in_pad, ignore_id):
"""Creat... | 803 | 31.16 | 74 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/embedding.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Positional Encoding Module."""
import math
import torch
def _pre_hook(
state_dict,
prefix,
local_metadata,
strict,
missing_keys,
unexpected_keys,
... | 12,758 | 32.054404 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/lightconv2d.py | """Lightweight 2-Dimensional Convolution module."""
import numpy
import torch
import torch.nn.functional as F
from torch import nn
MIN_VALUE = float(numpy.finfo(numpy.float32).min)
class LightweightConvolution2D(nn.Module):
"""Lightweight 2-Dimensional Convolution layer.
This implementation is based on
... | 4,229 | 33.112903 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/encoder_layer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encoder self-attention layer definition."""
import torch
from torch import nn
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
class EncoderLayer(nn... | 4,261 | 34.516667 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/label_smoothing_loss.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Label smoothing module."""
import torch
from torch import nn
class LabelSmoothingLoss(nn.Module):
"""Label-smoothing loss.
:param int size: the number of class
... | 2,164 | 32.828125 | 75 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/positionwise_feed_forward.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Positionwise feed forward layer definition."""
import torch
class PositionwiseFeedForward(torch.nn.Module):
"""Positionwise feed forward layer.
Args:
idim (... | 983 | 28.818182 | 85 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/encoder_mix.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encoder Mix definition."""
import torch
from espnet.nets.pytorch_backend.transducer.vgg2l import VGG2L
from espnet.nets.pytorch_backend.transformer.attention import MultiHead... | 6,407 | 38.801242 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/argument.py | # Copyright 2020 Hirofumi Inaguma
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Transformer common arguments."""
from distutils.util import strtobool
def add_arguments_transformer_common(group):
"""Add Transformer common arguments."""
group.add_argument(
"--transformer-init",
... | 5,280 | 27.701087 | 83 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/subsampling.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Subsampling layer definition."""
import torch
from espnet.nets.pytorch_backend.transformer.embedding import PositionalEncoding
class TooShortUttError(Exception):
"""Rai... | 14,351 | 31.544218 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/encoder.py | # Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encoder definition."""
import logging
import torch
from espnet.nets.pytorch_backend.nets_utils import rename_state_dict
from espnet.nets.pytorch_backend.transducer.vgg2l import VGG2L
from espnet.nets.pytorch_backend.trans... | 15,107 | 38.757895 | 124 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/longformer_attention.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2022 Roshan Sharma (Carnegie Mellon University)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Longformer based Local Attention Definition."""
from longformer.longformer import LongformerConfig, LongformerSelfAttention
from torch import nn
... | 2,070 | 35.982143 | 81 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/contextual_block_encoder_layer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2020 Emiru Tsunoo
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Encoder self-attention layer definition."""
import torch
from torch import nn
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
class ContextualBlockEn... | 8,899 | 34.177866 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/lightconv.py | """Lightweight Convolution Module."""
import numpy
import torch
import torch.nn.functional as F
from torch import nn
MIN_VALUE = float(numpy.finfo(numpy.float32).min)
class LightweightConvolution(nn.Module):
"""Lightweight Convolution layer.
This implementation is based on
https://github.com/pytorch/fa... | 3,589 | 31.053571 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/multi_layer_conv.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Layer modules for FFT block in FastSpeech (Feed-forward Transformer)."""
import torch
class MultiLayeredConv1d(torch.nn.Module):
"""Multi-layered conv1d for Transformer ... | 3,164 | 28.858491 | 80 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/subsampling_without_posenc.py | # Copyright 2020 Emiru Tsunoo
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Subsampling layer definition."""
import math
import torch
class Conv2dSubsamplingWOPosEnc(torch.nn.Module):
"""Convolutional 2D subsampling.
Args:
idim (int): Input dimension.
odim (int): Output di... | 1,899 | 29.15873 | 70 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/repeat.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Repeat the same layer definition."""
import torch
class MultiSequential(torch.nn.Sequential):
"""Multi-input multi-output torch.nn.Sequential."""
def __init__(self,... | 1,299 | 26.659574 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/decoder.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Decoder definition."""
import logging
from typing import Any, List, Tuple
import torch
from espnet.nets.pytorch_backend.nets_utils import rename_state_dict
from espnet.nets.... | 13,734 | 39.756677 | 124 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/plot.py | # Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import logging
import os
import numpy
from espnet.asr import asr_utils
def _plot_and_save_attention(att_w, filename, xtokens=None, ytokens=None):
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot... | 5,718 | 34.968553 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/layer_norm.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Layer normalization module."""
import torch
class LayerNorm(torch.nn.LayerNorm):
"""Layer normalization module.
Args:
nout (int): Output dim size.
d... | 958 | 21.302326 | 59 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/add_sos_eos.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Unility functions for Transformer."""
import torch
def add_sos_eos(ys_pad, sos, eos, ignore_id):
"""Add <sos> and <eos> labels.
:param torch.Tensor ys_pad: batch of... | 957 | 28.9375 | 74 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/attention.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Multi-Head Attention layer definition."""
import math
import torch
from torch import nn
class MultiHeadedAttention(nn.Module):
"""Multi-Head Attention layer.
Args:... | 11,646 | 37.062092 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/decoder_layer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Decoder self-attention layer definition."""
import torch
from torch import nn
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
class DecoderLayer(nn... | 4,877 | 35.133333 | 87 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/dynamic_conv2d.py | """Dynamic 2-Dimensional Convolution module."""
import numpy
import torch
import torch.nn.functional as F
from torch import nn
MIN_VALUE = float(numpy.finfo(numpy.float32).min)
class DynamicConvolution2D(nn.Module):
"""Dynamic 2-Dimensional Convolution layer.
This implementation is based on
https://git... | 4,862 | 34.23913 | 86 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/mask.py | # Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Mask module."""
import torch
def subsequent_mask(size, device="cpu", dtype=torch.bool):
"""Create mask for subsequent steps (size, size).
:param int size: size of mask
:param str device: "cpu" or "cuda" or to... | 1,037 | 27.833333 | 77 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/dynamic_conv.py | """Dynamic Convolution module."""
import numpy
import torch
import torch.nn.functional as F
from torch import nn
MIN_VALUE = float(numpy.finfo(numpy.float32).min)
class DynamicConvolution(nn.Module):
"""Dynamic Convolution layer.
This implementation is based on
https://github.com/pytorch/fairseq/tree/m... | 4,243 | 32.952 | 86 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/initializer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Parameter initialization."""
import torch
from espnet.nets.pytorch_backend.transformer.layer_norm import LayerNorm
def initialize(model, init_type="pytorch"):
"""Initia... | 1,383 | 29.755556 | 75 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/transformer/optimizer.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Optimizer module."""
import torch
class NoamOpt(object):
"""Optim wrapper that implements rate."""
def __init__(self, model_size, factor, warmup, optimizer):
... | 2,094 | 26.565789 | 76 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/frontends/dnn_wpe.py | from typing import Tuple
import torch
from pytorch_wpe import wpe_one_iteration
from torch_complex.tensor import ComplexTensor
from espnet.nets.pytorch_backend.frontends.mask_estimator import MaskEstimator
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
class DNN_WPE(torch.nn.Module):
def __ini... | 2,851 | 29.340426 | 78 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/frontends/feature_transform.py | from typing import List, Tuple, Union
import librosa
import numpy as np
import torch
from torch_complex.tensor import ComplexTensor
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
class FeatureTransform(torch.nn.Module):
def __init__(
self,
# Mel options,
fs: int = 16000... | 7,935 | 29.290076 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/frontends/beamformer.py | import torch
from torch_complex import functional as FC
from torch_complex.tensor import ComplexTensor
def get_power_spectral_density_matrix(
xs: ComplexTensor, mask: torch.Tensor, normalization=True, eps: float = 1e-15
) -> ComplexTensor:
"""Return cross-channel power spectral density (PSD) matrix
Args:... | 2,731 | 31.141176 | 81 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/frontends/mask_estimator.py | from typing import Tuple
import numpy as np
import torch
from torch.nn import functional as F
from torch_complex.tensor import ComplexTensor
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
from espnet.nets.pytorch_backend.rnn.encoders import RNN, RNNP
class MaskEstimator(torch.nn.Module):
def _... | 2,637 | 33.25974 | 85 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/frontends/frontend.py | from typing import List, Optional, Tuple, Union
import numpy
import torch
import torch.nn as nn
from torch_complex.tensor import ComplexTensor
from espnet.nets.pytorch_backend.frontends.dnn_beamformer import DNN_Beamformer
from espnet.nets.pytorch_backend.frontends.dnn_wpe import DNN_WPE
class Frontend(nn.Module):
... | 4,557 | 29.590604 | 88 | py |
espnet | espnet-master/espnet/nets/pytorch_backend/frontends/dnn_beamformer.py | """DNN beamformer module."""
from typing import Tuple
import torch
from torch.nn import functional as F
from torch_complex.tensor import ComplexTensor
from espnet.nets.pytorch_backend.frontends.beamformer import ( # noqa: H301
apply_beamforming_vector,
get_mvdr_vector,
get_power_spectral_density_matrix,
... | 5,480 | 30.682081 | 85 | py |
espnet | espnet-master/espnet/mt/pytorch_backend/mt.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2019 Kyoto University (Hirofumi Inaguma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Training/decoding definition for the text translation task."""
import itertools
import json
import logging
import os
import numpy as np
import torch
from chain... | 19,744 | 32.240741 | 88 | py |
espnet | espnet-master/espnet/bin/asr_recog.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""End-to-end speech recognition model decoding script."""
import logging
import os
import random
import sys
import configargparse
import numpy as np
from... | 13,800 | 32.497573 | 88 | py |
espnet | espnet-master/espnet/bin/asr_train.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2017 Tomoki Hayashi (Nagoya University)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Automatic speech recognition model training script."""
import logging
import os
import random
import subprocess
import sys
import configargparse
import numpy as... | 22,288 | 31.163059 | 88 | py |
espnet | espnet-master/espnet/bin/lm_train.py | #!/usr/bin/env python3
# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
# This code is ported from the following implementation written in Torch.
# https://github.com/chainer/chainer/blob/master/examples/ptb/train_ptb_custom_loop.py
"""Language m... | 8,939 | 29.934256 | 88 | py |
espnet | espnet-master/espnet/bin/tts_train.py | #!/usr/bin/env python3
# Copyright 2018 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Text-to-speech model training script."""
import logging
import os
import random
import subprocess
import sys
import configargparse
import numpy as np
from espnet import __versio... | 10,680 | 28.669444 | 88 | py |
espnet | espnet-master/espnet/bin/asr_enhance.py | #!/usr/bin/env python3
import logging
import os
import random
import sys
from distutils.util import strtobool
import configargparse
import numpy as np
from espnet.asr.pytorch_backend.asr import enhance
# NOTE: you need this func to generate our sphinx doc
def get_parser():
parser = configargparse.ArgumentParser... | 5,778 | 29.098958 | 87 | py |
espnet | espnet-master/espnet/bin/vc_train.py | #!/usr/bin/env python3
# Copyright 2020 Nagoya University (Wen-Chin Huang)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Voice conversion model training script."""
import logging
import os
import random
import subprocess
import sys
import configargparse
import numpy as np
from espnet import __vers... | 10,830 | 28.352304 | 88 | py |
espnet | espnet-master/espnet/bin/tts_decode.py | #!/usr/bin/env python3
# Copyright 2018 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""TTS decoding script."""
import logging
import os
import subprocess
import sys
import configargparse
from espnet.utils.cli_utils import strtobool
# NOTE: you need this func to ... | 5,267 | 29.807018 | 87 | py |
espnet | espnet-master/espnet/bin/mt_trans.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2019 Kyoto University (Hirofumi Inaguma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Neural machine translation model decoding script."""
import logging
import os
import random
import sys
import configargparse
import numpy as np
# NOTE: you n... | 5,956 | 30.855615 | 88 | py |
espnet | espnet-master/espnet/bin/vc_decode.py | #!/usr/bin/env python3
# Copyright 2020 Nagoya University (Wen-Chin Huang)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""VC decoding script."""
import logging
import os
import subprocess
import sys
import configargparse
from espnet.utils.cli_utils import strtobool
# NOTE: you need this func to g... | 5,094 | 29.878788 | 87 | py |
espnet | espnet-master/espnet/bin/asr_align.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2020 Johns Hopkins University (Xuankai Chang)
# 2020, Technische Universität München; Dominik Winkelbauer, Ludwig Kürzinger
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""
This program performs CTC segmentation to align utterances within ... | 13,207 | 35.893855 | 88 | py |
espnet | espnet-master/espnet/bin/st_train.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2019 Kyoto University (Hirofumi Inaguma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""End-to-end speech translation model training script."""
import logging
import os
import random
import subprocess
import sys
import configargparse
import numpy ... | 17,332 | 30.687386 | 88 | py |
espnet | espnet-master/espnet/bin/mt_train.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2019 Kyoto University (Hirofumi Inaguma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Neural machine translation model training script."""
import logging
import os
import random
import subprocess
import sys
import configargparse
import numpy as ... | 14,923 | 30.352941 | 88 | py |
espnet | espnet-master/espnet/bin/st_trans.py | #!/usr/bin/env python3
# encoding: utf-8
# Copyright 2019 Kyoto University (Hirofumi Inaguma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""End-to-end speech translation model decoding script."""
import logging
import os
import random
import sys
import configargparse
import numpy as np
# NOTE: yo... | 5,855 | 30.826087 | 88 | py |
espnet | espnet-master/espnet/st/pytorch_backend/st.py | # Copyright 2019 Kyoto University (Hirofumi Inaguma)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Training/decoding definition for the speech translation task."""
import itertools
import json
import logging
import os
import numpy as np
import torch
from chainer import training
from chainer.training... | 22,845 | 32.795858 | 88 | py |
espnet | espnet-master/espnet/distributed/pytorch_backend/launch.py | #
# SPDX-FileCopyrightText:
# Copyright (c) 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
#
"""This is a helper module for distributed training.
The code uses an official implementation of
distributed data parallel launcher as just a reference.
https://github.com/p... | 7,551 | 31.551724 | 129 | py |
espnet | espnet-master/espnet/asr/asr_utils.py | # Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import copy
import json
import logging
import os
import shutil
import tempfile
import numpy as np
import torch
# * -------------------- training iterator related --------------------... | 34,453 | 32.646484 | 88 | py |
espnet | espnet-master/espnet/asr/asr_mix_utils.py | #!/usr/bin/env python3
"""
This script is used to provide utility functions designed for multi-speaker ASR.
Copyright 2017 Johns Hopkins University (Shinji Watanabe)
Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
Most functions can be directly used as in asr_utils.py:
CompareValueTrigger, restore_snap... | 6,407 | 33.451613 | 86 | py |
espnet | espnet-master/espnet/asr/pytorch_backend/asr_init.py | """Finetuning methods."""
import logging
import os
import re
from collections import OrderedDict
import torch
from espnet.asr.asr_utils import get_model_conf, torch_load
from espnet.nets.asr_interface import ASRInterface
from espnet.nets.mt_interface import MTInterface
from espnet.nets.pytorch_backend.transducer.uti... | 10,707 | 30.40176 | 87 | py |
espnet | espnet-master/espnet/asr/pytorch_backend/recog.py | """V2 backend for `asr_recog.py` using py:class:`espnet.nets.beam_search.BeamSearch`."""
import json
import logging
import torch
from packaging.version import parse as V
from espnet.asr.asr_utils import add_results_to_json, get_model_conf, torch_load
from espnet.asr.pytorch_backend.asr import load_trained_model
from... | 6,635 | 35.262295 | 88 | py |
espnet | espnet-master/espnet/asr/pytorch_backend/asr.py | # Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Training/decoding definition for the speech recognition task."""
import copy
import itertools
import json
import logging
import math
import os
import numpy as np
import torch
import torch.distri... | 61,311 | 35.386944 | 103 | py |
espnet | espnet-master/espnet/asr/pytorch_backend/asr_mix.py | #!/usr/bin/env python3
"""
This script is used for multi-speaker speech recognition.
Copyright 2017 Johns Hopkins University (Shinji Watanabe)
Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""
import json
import logging
import os
from itertools import zip_longest as zip_longest
import numpy as np
import ... | 22,054 | 32.723242 | 88 | py |
espnet | espnet-master/espnet/lm/pytorch_backend/extlm.py | #!/usr/bin/env python3
# Copyright 2018 Mitsubishi Electric Research Laboratories (Takaaki Hori)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from espnet.lm.lm_utils import make_lexical_tree
from espnet.nets.pytorch_backe... | 9,546 | 42.593607 | 87 | py |
espnet | espnet-master/espnet/lm/pytorch_backend/lm.py | #!/usr/bin/env python3
# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
# This code is ported from the following implementation written in Torch.
# https://github.com/chainer/chainer/blob/master/examples/ptb/train_ptb_custom_loop.py
"""LM training ... | 14,856 | 35.414216 | 88 | py |
espnet | espnet-master/espnet/tts/pytorch_backend/tts.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2018 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""E2E-TTS training / decoding functions."""
import copy
import json
import logging
import math
import os
import time
import chainer
import kaldiio
import nu... | 26,532 | 34.614765 | 88 | py |
espnet | espnet-master/espnet/utils/spec_augment.py | # -*- coding: utf-8 -*-
"""
This implementation is modified from https://github.com/zcaceres/spec_augment
MIT License
Copyright (c) 2019 Zach Caceres
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Soft... | 18,458 | 35.844311 | 88 | py |
espnet | espnet-master/espnet/utils/dataset.py | #!/usr/bin/env python
# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""pytorch dataset and dataloader implementation for chainer training."""
import torch
import torch.utils.data
class Transform:
"""Transform function container.
lamb... | 3,703 | 27.9375 | 80 | py |
espnet | espnet-master/espnet/utils/fill_missing_args.py | # -*- coding: utf-8 -*-
# Copyright 2018 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import logging
def fill_missing_args(args, add_arguments):
"""Fill missing arguments in args.
Args:
args (Namespace or None): Namesapce containing ... | 1,426 | 29.361702 | 84 | py |
espnet | espnet-master/espnet/utils/deterministic_utils.py | import logging
import os
import chainer
import torch
def set_deterministic_pytorch(args):
"""Ensures pytorch produces deterministic results depending on the program arguments
:param Namespace args: The program arguments
"""
# seed setting
torch.manual_seed(args.seed)
# debug mode setting
... | 1,794 | 31.053571 | 88 | py |
espnet | espnet-master/espnet/utils/training/iterators.py | import chainer
import numpy as np
from chainer.iterators import MultiprocessIterator, SerialIterator, ShuffleOrderSampler
from chainer.training.extension import Extension
class ShufflingEnabler(Extension):
"""An extension enabling shuffling on an Iterator"""
def __init__(self, iterators):
"""Inits th... | 3,526 | 34.626263 | 88 | py |
espnet | espnet-master/espnet/optimizer/pytorch.py | """PyTorch optimizer builders."""
import argparse
import torch
from espnet.optimizer.factory import OptimizerFactoryInterface
from espnet.optimizer.parser import adadelta, adam, sgd
class AdamFactory(OptimizerFactoryInterface):
"""Adam factory."""
@staticmethod
def add_arguments(parser: argparse.Argume... | 2,399 | 25.086957 | 82 | py |
espnet | espnet-master/espnet/optimizer/factory.py | """Import optimizer class dynamically."""
import argparse
from espnet.utils.dynamic_import import dynamic_import
from espnet.utils.fill_missing_args import fill_missing_args
class OptimizerFactoryInterface:
"""Optimizer adaptor."""
@staticmethod
def from_args(target, args: argparse.Namespace):
"... | 2,013 | 27.771429 | 83 | py |
espnet | espnet-master/espnet/optimizer/chainer.py | """Chainer optimizer builders."""
import argparse
import chainer
from chainer.optimizer_hooks import WeightDecay
from espnet.optimizer.factory import OptimizerFactoryInterface
from espnet.optimizer.parser import adadelta, adam, sgd
class AdamFactory(OptimizerFactoryInterface):
"""Adam factory."""
@staticme... | 2,588 | 25.690722 | 82 | py |
espnet | espnet-master/espnet/transform/spec_augment.py | """Spec Augment module for preprocessing i.e., data augmentation"""
import random
import numpy
from espnet.transform.functional import FuncTrans
def time_warp(x, max_time_warp=80, inplace=False, mode="PIL"):
"""time warp for spec augment
move random center frame by the random width ~ uniform(-window, wind... | 5,933 | 28.088235 | 88 | py |
espnet | espnet-master/espnet2/svs/espnet_model.py | # Copyright 2020 Nagoya University (Tomoki Hayashi)
# Copyright 2021 Carnegie Mellon University (Jiatong Shi)
# Copyright 2022 Renmin University of China (Yuning Wu)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Singing-voice-synthesis ESPnet model."""
from contextlib import contextmanager
from distu... | 28,411 | 42.443425 | 88 | py |
espnet | espnet-master/espnet2/svs/abs_svs.py | # Copyright 2021 Tomoki Hayashi
# Copyright 2021 Carnegie Mellon University (Jiatong Shi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Singing-voice-synthesis abstrast class."""
from abc import ABC, abstractmethod
from typing import Dict, Tuple
import torch
class AbsSVS(torch.nn.Module, ABC):
... | 1,182 | 24.717391 | 68 | py |
espnet | espnet-master/espnet2/svs/singing_tacotron/singing_tacotron.py | # Copyright 2020 Nagoya University (Tomoki Hayashi)
# Copyright 2023 Renmin University of China (Yuning Wu)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Singing Tacotron related modules for ESPnet2."""
import logging
from typing import Dict, Optional, Sequence, Tuple
import six
import torch
import ... | 28,517 | 39.915352 | 88 | py |
espnet | espnet-master/espnet2/svs/singing_tacotron/encoder.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Nagoya University (Tomoki Hayashi)
# Copyright 2023 Renmin University of China (Yuning Wu)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Singing Tacotron encoder related modules."""
import torch
from torch.nn.utils.rnn import pack_padde... | 8,752 | 32.030189 | 87 | py |
espnet | espnet-master/espnet2/svs/singing_tacotron/decoder.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2019 Nagoya University (Tomoki Hayashi)
# Copyright 2023 Renmin University of China (Yuning Wu)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Singing Tacotron decoder related modules."""
import six
import torch
import torch.nn.functional as ... | 17,363 | 37.932735 | 88 | py |
espnet | espnet-master/espnet2/svs/xiaoice/loss.py | # Copyright 2020 Nagoya University (Tomoki Hayashi)
# Copyright 2023 Renmin University of China (Yuning Wu)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""XiaoiceSing2 related loss module for ESPnet2."""
from typing import Tuple
import torch
from typeguard import check_argument_types
from espnet.net... | 5,424 | 40.730769 | 88 | py |
espnet | espnet-master/espnet2/svs/xiaoice/XiaoiceSing.py | # Copyright 2020 Nagoya University (Tomoki Hayashi)
# Copyright 2021 Renmin University of China (Shuai Guo)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""XiaoiceSing related modules."""
import logging
from typing import Dict, Optional, Tuple
import torch
import torch.nn.functional as F
from typeguar... | 33,849 | 43.422572 | 88 | py |
espnet | espnet-master/espnet2/svs/feats_extract/score_feats_extract.py | from typing import Any, Dict, Optional, Tuple, Union
import torch
from typeguard import check_argument_types
from espnet2.tts.feats_extract.abs_feats_extract import AbsFeatsExtract
from espnet.nets.pytorch_backend.nets_utils import make_pad_mask
def ListsToTensor(xs):
max_len = max(len(x) for x in xs)
ys = ... | 11,227 | 29.51087 | 86 | py |
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