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/asr_transducer/joint_network.py | """Transducer joint network implementation."""
import torch
from espnet2.asr_transducer.activation import get_activation
class JointNetwork(torch.nn.Module):
"""Transducer joint network module.
Args:
output_size: Output size.
encoder_size: Encoder output size.
decoder_size: Decoder ... | 2,097 | 29.405797 | 75 | py |
espnet | espnet-master/espnet2/asr_transducer/activation.py | """Activation functions for Transducer models."""
import torch
from packaging.version import parse as V
def get_activation(
activation_type: str,
ftswish_threshold: float = -0.2,
ftswish_mean_shift: float = 0.0,
hardtanh_min_val: int = -1.0,
hardtanh_max_val: int = 1.0,
leakyrelu_neg_slope: f... | 6,737 | 30.485981 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/utils.py | """Utility functions for Transducer models."""
from typing import List, Tuple, Union
import torch
class TooShortUttError(Exception):
"""Raised when the utt is too short for subsampling.
Args:
message: Error message to display.
actual_size: The size that cannot pass the subsampling.
... | 5,616 | 26.26699 | 85 | py |
espnet | espnet-master/espnet2/asr_transducer/beam_search_transducer.py | """Search algorithms for Transducer models."""
from dataclasses import dataclass
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import torch
from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
from espnet2.asr_transducer.joint_network import JointNetwork
@dataclass
clas... | 22,742 | 31.49 | 88 | py |
espnet | espnet-master/espnet2/asr_transducer/error_calculator.py | """Error Calculator module for Transducer."""
from typing import List, Optional, Tuple
import torch
from espnet2.asr_transducer.beam_search_transducer import BeamSearchTransducer
from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
from espnet2.asr_transducer.joint_network import JointNetwork
class Er... | 6,162 | 30.932642 | 88 | py |
espnet | espnet-master/espnet2/asr_transducer/normalization.py | """Normalization modules for Transducer."""
from typing import Dict, Optional, Tuple
import torch
def get_normalization(
normalization_type: str,
eps: Optional[float] = None,
partial: Optional[float] = None,
) -> Tuple[torch.nn.Module, Dict]:
"""Get normalization module and arguments given parameter... | 4,449 | 25.023392 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/espnet_transducer_model.py | """ESPnet2 ASR Transducer model."""
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.frontend.abs_frontend import AbsFrontend
from espnet2.asr.sp... | 21,402 | 32.758675 | 88 | py |
espnet | espnet-master/espnet2/asr_transducer/frontend/online_audio_processor.py | """Online processor for Transducer models chunk-by-chunk streaming decoding."""
from typing import Dict, Tuple
import torch
class OnlineAudioProcessor:
"""OnlineProcessor module definition.
Args:
feature_extractor: Feature extractor module.
normalization_module: Normalization module.
... | 5,265 | 30.159763 | 85 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/building.py | """Set of methods to build Transducer encoder architecture."""
from typing import Any, Dict, List, Optional, Union
from espnet2.asr_transducer.activation import get_activation
from espnet2.asr_transducer.encoder.blocks.branchformer import Branchformer
from espnet2.asr_transducer.encoder.blocks.conformer import Confor... | 12,952 | 29.767221 | 86 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/encoder.py | """Encoder for Transducer model."""
from typing import Any, Dict, List, Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr_transducer.encoder.building import (
build_body_blocks,
build_input_block,
build_main_parameters,
build_positional_encoding,
)
from espnet2.asr_transd... | 5,102 | 27.830508 | 85 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/modules/convolution.py | """Convolution modules for X-former blocks."""
from typing import Dict, Optional, Tuple
import torch
class ConformerConvolution(torch.nn.Module):
"""ConformerConvolution module definition.
Args:
channels: The number of channels.
kernel_size: Size of the convolving kernel.
activation... | 7,416 | 26.675373 | 85 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/modules/multi_blocks.py | """MultiBlocks for encoder architecture."""
from typing import Dict, List, Optional
import torch
class MultiBlocks(torch.nn.Module):
"""MultiBlocks definition.
Args:
block_list: Individual blocks of the encoder architecture.
output_size: Architecture output size.
norm_class: Normali... | 3,435 | 29.40708 | 86 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/modules/positional_encoding.py | """Positional encoding modules."""
import math
import torch
from espnet.nets.pytorch_backend.transformer.embedding import _pre_hook
class RelPositionalEncoding(torch.nn.Module):
"""Relative positional encoding.
Args:
size: Module size.
max_len: Maximum input length.
dropout_rate: D... | 2,878 | 29.62766 | 82 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/modules/normalization.py | """Normalization modules for X-former blocks."""
from typing import Dict, Optional, Tuple
import torch
def get_normalization(
normalization_type: str,
eps: Optional[float] = None,
partial: Optional[float] = None,
) -> Tuple[torch.nn.Module, Dict]:
"""Get normalization module and arguments given para... | 4,454 | 25.052632 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/modules/attention.py | """Multi-Head attention layers with relative positional encoding."""
import math
from typing import Optional, Tuple
import torch
class RelPositionMultiHeadedAttention(torch.nn.Module):
"""RelPositionMultiHeadedAttention definition.
Args:
num_heads: Number of attention heads.
embed_size: Emb... | 8,228 | 31.270588 | 88 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/blocks/branchformer.py | """Branchformer block for Transducer encoder."""
from typing import Dict, Optional, Tuple
import torch
class Branchformer(torch.nn.Module):
"""Branchformer module definition.
Reference: https://arxiv.org/pdf/2207.02971.pdf
Args:
block_size: Input/output size.
linear_size: Linear layers... | 5,017 | 28.00578 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/blocks/conv1d.py | """Conv1d block for Transducer encoder."""
from typing import Optional, Tuple, Union
import torch
class Conv1d(torch.nn.Module):
"""Conv1d module definition.
Args:
input_size: Input dimension.
output_size: Output dimension.
kernel_size: Size of the convolving kernel.
stride:... | 6,398 | 28.353211 | 85 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/blocks/conformer.py | """Conformer block for Transducer encoder."""
from typing import Dict, Optional, Tuple
import torch
class Conformer(torch.nn.Module):
"""Conformer module definition.
Args:
block_size: Input/output size.
self_att: Self-attention module instance.
feed_forward: Feed-forward module inst... | 5,560 | 27.085859 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/blocks/conv_input.py | """ConvInput block for Transducer encoder."""
from typing import Optional, Tuple, Union
import torch
from espnet2.asr_transducer.utils import get_convinput_module_parameters
class ConvInput(torch.nn.Module):
"""ConvInput module definition.
Args:
input_size: Input size.
conv_size: Convoluti... | 3,412 | 30.311927 | 80 | py |
espnet | espnet-master/espnet2/asr_transducer/encoder/blocks/ebranchformer.py | """E-Branchformer block for Transducer encoder."""
from typing import Dict, Optional, Tuple
import torch
class EBranchformer(torch.nn.Module):
"""E-Branchformer module definition.
Reference: https://arxiv.org/pdf/2210.00077.pdf
Args:
block_size: Input/output size.
linear_size: Linear l... | 6,771 | 29.781818 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/rnn_decoder.py | """RNN decoder definition for Transducer models."""
from typing import List, Optional, Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr_transducer.beam_search_transducer import Hypothesis
from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
class RNNDecoder(AbsDecoder):
... | 7,707 | 28.532567 | 87 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/stateless_decoder.py | """Stateless decoder definition for Transducer models."""
from typing import Any, List, Optional, Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr_transducer.beam_search_transducer import Hypothesis
from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
class StatelessDecod... | 4,095 | 24.128834 | 86 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/abs_decoder.py | """Abstract decoder definition for Transducer models."""
from abc import ABC, abstractmethod
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
class AbsDecoder(torch.nn.Module, ABC):
"""Abstract decoder module."""
@abstractmethod
def forward(self, labels: torch.Tensor) -> torch.Te... | 3,755 | 22.622642 | 76 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/mega_decoder.py | """MEGA decoder definition for Transducer models."""
import math
from typing import Dict, List, Optional, Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr_transducer.activation import get_activation
from espnet2.asr_transducer.beam_search_transducer import Hypothesis
from espnet2.asr_tr... | 11,982 | 31.040107 | 86 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/rwkv_decoder.py | """RWKV decoder definition for Transducer models."""
import math
from typing import Dict, List, Optional, Tuple
import torch
from typeguard import check_argument_types
from espnet2.asr_transducer.beam_search_transducer import Hypothesis
from espnet2.asr_transducer.decoder.abs_decoder import AbsDecoder
from espnet2.a... | 8,252 | 28.370107 | 86 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/modules/mega/feed_forward.py | """Normalized position-wise feed-forward module for MEGA block."""
import torch
class NormalizedPositionwiseFeedForward(torch.nn.Module):
"""NormalizedPositionFeedForward module definition.
Args:
size: Input/Output size.
hidden_size: Hidden size.
normalization: Normalization module.
... | 2,076 | 27.452055 | 79 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/modules/mega/multi_head_damped_ema.py | """Multi-head Damped Exponential Moving Average (EMA) module for MEGA block.
Based/modified from https://github.com/facebookresearch/mega/blob/main/fairseq/modules/moving_average_gated_attention.py
Most variables are renamed according to https://github.com/huggingface/transformers/blob/main/src/transformers/models/me... | 7,009 | 30.576577 | 140 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/modules/mega/positional_bias.py | """Positional bias related modules.
Based/modified from https://github.com/facebookresearch/mega/blob/main/fairseq/modules/relative_positional_bias.py
""" # noqa
import math
from typing import Tuple
import torch
class RelativePositionBias(torch.nn.Module):
"""RelativePositionBias module definition.
Args:... | 5,037 | 26.232432 | 114 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/modules/rwkv/feed_forward.py | """Feed-forward (channel mixing) module for RWKV block.
Based/Modified from https://github.com/BlinkDL/RWKV-LM/blob/main/RWKV-v4/src/model.py
Some variables are renamed according to https://github.com/huggingface/transformers/blob/main/src/transformers/models/rwkv/modeling_rwkv.py.
""" # noqa
from typing import Li... | 3,038 | 30.329897 | 140 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/modules/rwkv/attention.py | """Attention (time mixing) modules for RWKV block.
Based/Modified from https://github.com/BlinkDL/RWKV-LM/blob/main/RWKV-v4/src/model.py.
Some variables are renamed according to https://github.com/huggingface/transformers/blob/main/src/transformers/models/rwkv/modeling_rwkv.py.
""" # noqa
import math
from importli... | 11,396 | 29.886179 | 140 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/blocks/rwkv.py | """Receptance Weighted Key Value (RWKV) block definition.
Based/modified from https://github.com/BlinkDL/RWKV-LM/blob/main/RWKV-v4/src/model.py
"""
from typing import Dict, Optional, Tuple
import torch
from espnet2.asr_transducer.decoder.modules.rwkv.attention import SelfAttention
from espnet2.asr_transducer.decod... | 2,602 | 30.743902 | 85 | py |
espnet | espnet-master/espnet2/asr_transducer/decoder/blocks/mega.py | """Moving Average Equipped Gated Attention (MEGA) block definition.
Based/modified from https://github.com/facebookresearch/mega/blob/main/fairseq/modules/moving_average_gated_attention.py
Most variables are renamed according to https://github.com/huggingface/transformers/blob/main/src/transformers/models/mega/modeli... | 9,571 | 32.704225 | 140 | py |
espnet | espnet-master/espnet2/schedulers/noam_lr.py | """Noam learning rate scheduler module."""
import warnings
from typing import Union
import torch
from torch.optim.lr_scheduler import _LRScheduler
from typeguard import check_argument_types
from espnet2.schedulers.abs_scheduler import AbsBatchStepScheduler
class NoamLR(_LRScheduler, AbsBatchStepScheduler):
"""T... | 2,068 | 30.348485 | 85 | py |
espnet | espnet-master/espnet2/schedulers/abs_scheduler.py | from abc import ABC, abstractmethod
import torch.optim.lr_scheduler as L
class AbsScheduler(ABC):
@abstractmethod
def step(self, epoch: int = None):
pass
@abstractmethod
def state_dict(self):
pass
@abstractmethod
def load_state_dict(self, state):
pass
# If you need... | 1,664 | 18.821429 | 70 | py |
espnet | espnet-master/espnet2/schedulers/warmup_reducelronplateau.py | """ReduceLROnPlateau (with Warm up) learning rate scheduler module."""
from typing import Union
import torch
from torch import inf
from typeguard import check_argument_types
from espnet2.schedulers.abs_scheduler import (
AbsBatchStepScheduler,
AbsValEpochStepScheduler,
)
class WarmupReduceLROnPlateau(AbsBat... | 6,832 | 32.826733 | 88 | py |
espnet | espnet-master/espnet2/schedulers/warmup_lr.py | """Warm up learning rate scheduler module."""
from typing import Union
import torch
from torch.optim.lr_scheduler import _LRScheduler
from typeguard import check_argument_types
from espnet2.schedulers.abs_scheduler import AbsBatchStepScheduler
class WarmupLR(_LRScheduler, AbsBatchStepScheduler):
"""The WarmupLR... | 1,495 | 28.333333 | 86 | py |
espnet | espnet-master/espnet2/schedulers/warmup_step_lr.py | """Step (with Warm up) learning rate scheduler module."""
from typing import Union
import torch
from torch.optim.lr_scheduler import _LRScheduler
from typeguard import check_argument_types
from espnet2.schedulers.abs_scheduler import AbsBatchStepScheduler
class WarmupStepLR(_LRScheduler, AbsBatchStepScheduler):
... | 2,699 | 31.53012 | 88 | py |
espnet | espnet-master/espnet2/utils/sized_dict.py | import collections
import sys
from torch import multiprocessing
def get_size(obj, seen=None):
"""Recursively finds size of objects
Taken from https://github.com/bosswissam/pysize
"""
size = sys.getsizeof(obj)
if seen is None:
seen = set()
obj_id = id(obj)
if obj_id in seen:
... | 2,027 | 25.684211 | 86 | py |
espnet | espnet-master/espnet2/utils/griffin_lim.py | #!/usr/bin/env python3
"""Griffin-Lim related modules."""
# Copyright 2019 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import logging
from functools import partial
from typing import Optional
import librosa
import numpy as np
import torch
from packaging.version import parse as V
from ... | 5,607 | 28.208333 | 86 | py |
espnet | espnet-master/espnet2/tasks/enh_tse.py | import argparse
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.enh.espnet_model_tse import ESPnetExtractionModel
from espnet2.enh.extractor.abs_extractor import AbsExtractor
from espnet2.en... | 11,924 | 33.665698 | 86 | py |
espnet | espnet-master/espnet2/tasks/enh_s2t.py | import argparse
import copy
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.ctc import CTC
from espnet2.asr.espnet_model import ESPnetASRModel
from espnet2.diar.espnet_mod... | 19,866 | 34.225177 | 88 | py |
espnet | espnet-master/espnet2/tasks/slu.py | import argparse
import logging
from typing import Callable, Dict, Optional, Tuple
import numpy as np
from typeguard import check_argument_types, check_return_type
from espnet2.asr.ctc import CTC
from espnet2.asr.decoder.abs_decoder import AbsDecoder
from espnet2.asr.decoder.mlm_decoder import MLMDecoder
from espnet2.... | 20,979 | 34.260504 | 85 | py |
espnet | espnet-master/espnet2/tasks/st.py | import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.ctc import CTC
from espnet2.asr.decoder.abs_decoder import AbsDecoder
from espnet2.asr.decoder.rnn_decoder ... | 20,374 | 34.068847 | 85 | py |
espnet | espnet-master/espnet2/tasks/hubert.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Thanks to Abdelrahman Mohamed and Wei-Ning Hsu's help in this implementation,
# Their origial Hubert work is in:
# Paper: https://arxiv.org/pdf/2106.07447.pdf
# Code in Fairseq: https://github.com/pytorch/fairseq/tree/master/examples/hubert
import argparse
impor... | 14,204 | 32.266979 | 85 | py |
espnet | espnet-master/espnet2/tasks/svs.py | """Singing-voice-synthesis task."""
import argparse
import logging
from pathlib import Path
from typing import Callable, Collection, Dict, List, Optional, Tuple, Union
import numpy as np
import torch
import yaml
from typeguard import check_argument_types, check_return_type
from espnet2.gan_svs.joint import JointScor... | 17,151 | 34.219713 | 87 | py |
espnet | espnet-master/espnet2/tasks/diar.py | import argparse
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.encoder.abs_encoder import AbsEncoder
from espnet2.asr.encoder.conformer_encoder import ConformerEncoder
from espnet2.asr.... | 9,963 | 31.993377 | 87 | py |
espnet | espnet-master/espnet2/tasks/mt.py | import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.ctc import CTC
from espnet2.asr.decoder.abs_decoder import AbsDecoder
from espnet2.asr.decoder.rnn_decoder ... | 15,892 | 33.85307 | 86 | py |
espnet | espnet-master/espnet2/tasks/asr_transducer.py | """ASR Transducer Task."""
import argparse
import logging
import os
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.frontend.abs_frontend import AbsFrontend
from espnet2.asr.frontend.de... | 13,389 | 29.501139 | 83 | py |
espnet | espnet-master/espnet2/tasks/gan_svs.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 task."""
import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard impor... | 15,786 | 32.305907 | 87 | py |
espnet | espnet-master/espnet2/tasks/asvspoof.py | import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.encoder.abs_encoder import AbsEncoder
# TODO1 (checkpoint 2): import conformer class class
from espnet2.as... | 10,200 | 31.487261 | 83 | py |
espnet | espnet-master/espnet2/tasks/asr.py | import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.ctc import CTC
from espnet2.asr.decoder.abs_decoder import AbsDecoder
from espnet2.asr.decoder.hugging_face... | 21,301 | 33.693811 | 85 | py |
espnet | espnet-master/espnet2/tasks/lm.py | import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.lm.abs_model import AbsLM
from espnet2.lm.espnet_model import ESPnetLanguageModel
from espnet2.lm.seq_rnn_lm im... | 6,804 | 31.716346 | 84 | py |
espnet | espnet-master/espnet2/tasks/uasr.py | import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.asr.frontend.abs_frontend import AbsFrontend
from espnet2.asr.frontend.default import DefaultFrontend
from espn... | 15,031 | 33.796296 | 87 | py |
espnet | espnet-master/espnet2/tasks/tts.py | """Text-to-speech task."""
import argparse
import logging
from pathlib import Path
from typing import Callable, Collection, Dict, List, Optional, Tuple, Union
import numpy as np
import torch
import yaml
from typeguard import check_argument_types, check_return_type
from espnet2.gan_tts.jets import JETS
from espnet2.g... | 14,328 | 33.94878 | 87 | py |
espnet | espnet-master/espnet2/tasks/enh.py | import argparse
import copy
import os
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return_type
from espnet2.diar.layers.abs_mask import AbsMask
from espnet2.diar.layers.multi_mask import MultiMask
from espnet2.di... | 18,429 | 34.717054 | 88 | py |
espnet | espnet-master/espnet2/tasks/gan_tts.py | # Copyright 2021 Tomoki Hayashi
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""GAN-based text-to-speech task."""
import argparse
import logging
from typing import Callable, Collection, Dict, List, Optional, Tuple
import numpy as np
import torch
from typeguard import check_argument_types, check_return... | 13,798 | 31.854762 | 87 | py |
espnet | espnet-master/espnet2/tasks/abs_task.py | """Abstract task module."""
import argparse
import functools
import logging
import os
import sys
from abc import ABC, abstractmethod
from dataclasses import dataclass
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Sequence, Tuple, Union
import humanfriendly
import numpy as np
import t... | 71,532 | 36.432234 | 91 | py |
espnet | espnet-master/espnet2/asvspoof/espnet_model.py | # Copyright 2022 Jiatong Shi (Carnegie Mellon University)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import logging
from contextlib import contextmanager
from itertools import permutations
from typing import Dict, Optional, Tuple
import numpy as np
import torch
import torch.nn.functional as F
from pa... | 6,487 | 33.510638 | 87 | py |
espnet | espnet-master/espnet2/asvspoof/loss/binary_loss.py | import torch
from espnet2.asvspoof.loss.abs_loss import AbsASVSpoofLoss
from espnet.nets.pytorch_backend.nets_utils import to_device
class ASVSpoofBinaryLoss(AbsASVSpoofLoss):
"""Binary loss for ASV Spoofing."""
def __init__(
self,
weight: float = 1.0,
):
super().__init__()
... | 854 | 27.5 | 77 | py |
espnet | espnet-master/espnet2/asvspoof/loss/abs_loss.py | from abc import ABC, abstractmethod
import torch
EPS = torch.finfo(torch.get_default_dtype()).eps
class AbsASVSpoofLoss(torch.nn.Module, ABC):
"""Base class for all ASV Spoofing loss modules."""
# the name will be the key that appears in the reporter
@property
def name(self) -> str:
return ... | 646 | 19.870968 | 59 | py |
espnet | espnet-master/espnet2/asvspoof/loss/am_softmax_loss.py | import torch
from espnet2.asvspoof.loss.abs_loss import AbsASVSpoofLoss
from espnet.nets.pytorch_backend.nets_utils import to_device
class ASVSpoofAMSoftmaxLoss(AbsASVSpoofLoss):
"""Binary loss for ASV Spoofing."""
def __init__(
self,
weight: float = 1.0,
enc_dim: int = 128,
... | 2,180 | 33.619048 | 83 | py |
espnet | espnet-master/espnet2/asvspoof/loss/oc_softmax_loss.py | import torch
from espnet2.asvspoof.loss.abs_loss import AbsASVSpoofLoss
from espnet.nets.pytorch_backend.nets_utils import to_device
class ASVSpoofOCSoftmaxLoss(AbsASVSpoofLoss):
"""Binary loss for ASV Spoofing."""
def __init__(
self,
weight: float = 1.0,
enc_dim: int = 128,
... | 1,850 | 31.473684 | 81 | py |
espnet | espnet-master/espnet2/asvspoof/decoder/linear_decoder.py | from typing import Optional
import torch
from espnet2.asvspoof.decoder.abs_decoder import AbsDecoder
class LinearDecoder(AbsDecoder):
"""Linear decoder for speaker diarization"""
def __init__(
self,
encoder_output_size: int,
):
super().__init__()
# TODO1 (checkpoint3): i... | 805 | 25.866667 | 74 | py |
espnet | espnet-master/espnet2/asvspoof/decoder/abs_decoder.py | from abc import ABC, abstractmethod
from typing import Tuple
import torch
class AbsDecoder(torch.nn.Module, ABC):
@abstractmethod
def forward(
self,
input: torch.Tensor,
ilens: torch.Tensor,
) -> Tuple[torch.Tensor, torch.Tensor]:
raise NotImplementedError
| 304 | 19.333333 | 43 | py |
espnet | espnet-master/utils/generate_wav_from_fbank.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""This code is based on https://github.com/kan-bayashi/PytorchWaveNetVocoder."""
# Copyright 2019 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import logging
import os
import time
import h5py
import num... | 5,966 | 30.571429 | 87 | py |
espnet | espnet-master/utils/average_checkpoints.py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import argparse
import json
import os
import numpy as np
def main():
if args.log is not None:
with open(args.log) as f:
logs = json.load(f)
val_scores = []
for log in logs:
if log["epoch"] > args.max_epoch:
... | 4,882 | 34.384058 | 88 | py |
espnet | espnet-master/egs/wsj/asr1/local/filtering_samples.py | #!/usr/bin/env python3
# Copyright 2020 Shanghai Jiao Tong University (Wangyou Zhang)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import json
import sys
from functools import reduce
from operator import mul
from espnet.bin.asr_train import get_parser
from espnet.nets.pytorch_backend.nets_utils impor... | 2,983 | 33.298851 | 86 | py |
espnet | espnet-master/doc/conf.py | # -*- coding: utf-8 -*-
# flake8: noqa
#
# ESPnet documentation build configuration file, created by
# sphinx-quickstart on Thu Dec 7 15:46:00 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerat... | 6,528 | 28.677273 | 86 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/feats_cluster_faiss.py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
# Dongji Gao (2022)
#
# Adapted from fairseq/examples/wav2vec/unsupervised/\
# scripts/wav2vec_cluster_faiss.py
# to fit the scp data format
# This source code is licensed under the MIT license in
# https... | 4,160 | 26.019481 | 86 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/merge_clusters.py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
# Dongji Gao (2022)
#
# Adapted from fairseq/examples/wav2vec/unsupervised/\
# scripts/merge_clusters.py
# to fit the scp data format
# This source code is licensed under the MIT license in
# https://gith... | 3,325 | 28.433628 | 87 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/ssl_feature_utils.py | import json
import logging
import os
import re
import sys
from typing import Optional, Union
import numpy as np
import soundfile as sf
import torch
import torchaudio
from espnet2.asr.frontend.s3prl import S3prlFrontend
from espnet.utils.cli_readers import file_reader_helper
from espnet.utils.cli_utils import is_scipy... | 7,609 | 30.97479 | 84 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/dump_km_label.py | # The learn_kmeans.py uses code from Fairseq:
# https://github.com/pytorch/fairseq/blob/master/examples/hubert/simple_kmeans/dump_km_label.py
#
# Thanks to Abdelrahman Mohamed and Wei-Ning Hsu's help in this implementation,
# Their origial Hubert work is in:
# Paper: https://arxiv.org/pdf/2106.07447.pdf
# C... | 5,471 | 30.448276 | 99 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/mean_pool_scp.py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
# Dongji Gao (2022)
#
# Adapted from fairseq/examples/wav2vec/unsupervised/\
# scripts/mean_pool.py
# to fit the scp data format
# This source code is licensed under the MIT license in
# https://github.co... | 3,406 | 30.841121 | 86 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/apply_pca.py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# Adapted from fairseq/examples/wav2vec/unsupervised/scripts/apply_pca.py
# to fit the scp data format
# This source code is licensed under the MIT license in
# https://github.com/facebookresearch/fairseq
import argparse
import math... | 2,291 | 28.384615 | 87 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/feats/feats_apply_cluster_faiss.py | #!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
# Dongji Gao (2022)
#
# Adapted from fairseq/examples/wav2vec/unsupervised/\
# scripts/wav2vec_apply_cluster_faiss.py
# to fit the scp data format
# This source code is licensed under the MIT license in
#... | 4,575 | 28.522581 | 84 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/k2/compile_hlg.py | #!/usr/bin/env python3
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
# 2022 Johns Hopkins University (author: Dongji Gao)
#
# This script is adapted from \
# k2-fsa/icefall/blob/master/egs/librispeech/ASR/local/compile_hlg.py
#
# See https://github.com/k2-fsa/icefall/blob/master/LIC... | 4,986 | 26.860335 | 81 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/k2/prepare_lang.py | #!/usrilbin/env python3
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
# 2022 Johns Hopkins University (author: Dongji Gao)
#
# This script is adapted from \
# k2-fsa/icefall/blob/master/egs/librispeech/ASR/local/prepare_lang.py
#
# See https://github.com/k2-fsa/icefall/blob/master/L... | 14,465 | 28.704312 | 81 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/evaluate_cfsd.py | #!/usr/bin/env python3
# Copyright 2020 Wen-Chin Huang and Tomoki Hayashi
# Copyright 2023 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Evaluate Conditional Frechet Speech Distance
between generated and groundtruth audios
using the s3prl pretrained models."""
import argparse
import ... | 9,455 | 32.892473 | 88 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/evaluate_secs.py | #!/usr/bin/env python3
# Copyright 2020 Wen-Chin Huang and Tomoki Hayashi
# Copyright 2023 Dan Lim
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Evaluate Speaker Embedding Cosine Similarity
between generated and groundtruth audios using X-vector
of the speechbrain pretrained models"""
import... | 7,171 | 31.6 | 88 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/extract_xvectors.py | #!/usr/bin/env python3
# 2022, Hitachi LTD.; Nelson Yalta
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import logging
import os
import sys
from pathlib import Path
import kaldiio
import librosa
import numpy as np
import torch
from tqdm.contrib import tqdm
from espnet2.fileio.sound_scp... | 6,207 | 32.923497 | 88 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/sklearn_km.py | # The sklearn_km.py uses code from Fairseq:
# https://github.com/pytorch/fairseq/blob/master/examples/hubert/simple_kmeans/learn_kmeans.py
#
# Thanks to Abdelrahman Mohamed and Wei-Ning Hsu's help in this implementation,
# Their origial Hubert work is in:
# Paper: https://arxiv.org/pdf/2106.07447.pdf
# Code... | 6,389 | 27.526786 | 98 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/evaluate_whisper_inference.py | #!/usr/bin/env python3
import argparse
import logging
import os
import sys
from distutils.version import LooseVersion
from pathlib import Path
from typing import Any, List, Optional, Sequence, Tuple, Union
import numpy as np
import torch
import torch.quantization
import whisper
from typeguard import check_argument_typ... | 4,560 | 25.829412 | 82 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/plot_sinc_filters.py | #!/usr/bin/env python3
# 2020, Technische Universität München; Nicolas Lindae, Ludwig Kürzinger
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Visualize Sinc convolution filters.
Description:
This program loads a pretrained Sinc convolution of an ESPnet2 ASR model and
plots filters, as well a... | 11,828 | 32.041899 | 88 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/learn_kmeans.py | # The learn_kmeans.py uses code from Fairseq:
# https://github.com/pytorch/fairseq/blob/master/examples/hubert/simple_kmeans/learn_kmeans.py
#
# Thanks to Abdelrahman Mohamed and Wei-Ning Hsu's help in this implementation,
# Their origial Hubert work is in:
# Paper: https://arxiv.org/pdf/2106.07447.pdf
# Co... | 4,472 | 25.945783 | 98 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/pyscripts/utils/calculate_speech_metrics.py | #!/usr/bin/env python3
import argparse
import logging
import sys
from typing import List, Union
import numpy as np
import torch
from mir_eval.separation import bss_eval_sources
from pystoi import stoi
from typeguard import check_argument_types
from espnet2.enh.encoder.stft_encoder import STFTEncoder
from espnet2.enh.... | 7,320 | 32.582569 | 87 | py |
espnet | espnet-master/egs2/TEMPLATE/asr1/steps/libs/nnet3/xconfig/convolution.py | # Copyright 2018 Johns Hopkins University (Author: Dan Povey)
# 2016 Vijayaditya Peddinti
# Apache 2.0.
""" This module has the implementation of convolutional layers.
"""
from __future__ import print_function
from __future__ import division
import math
import re
import sys
from libs.nnet3.xconfig.ba... | 61,163 | 49.800664 | 107 | py |
espnet | espnet-master/egs2/lrs2/lipreading1/local/feature_extract/video_processing.py | import cvtransforms
import face_alignment
import numpy as np
import skimage.transform
import skvideo.io
import torch
from models import pretrained
def reload_model(model, path=""):
if not bool(path):
return model
else:
model_dict = model.state_dict()
pretrained_dict = torch.load(path, ... | 6,492 | 29.483568 | 88 | py |
espnet | espnet-master/egs2/lrs2/lipreading1/local/feature_extract/models/pretrained.py | # coding: utf-8
import math
import numpy as np
import torch
import torch.nn as nn
from torch.autograd import Variable
def conv3x3(in_planes, out_planes, stride=1):
return nn.Conv2d(
in_planes, out_planes, kernel_size=3, stride=stride, padding=1, bias=False
)
class BasicBlock(nn.Module):
expansi... | 8,286 | 31.498039 | 88 | py |
espnet | espnet-master/egs2/wsj0_2mix/tse1/local/prepare_spk_embs_scp.py | from functools import partial
from pathlib import Path
import numpy as np
import onnxruntime as ort
import torch
import torchaudio
import torchaudio.compliance.kaldi as kaldi
from tqdm.contrib.concurrent import thread_map
def compute_fbank(
wav_path, num_mel_bins=80, frame_length=25, frame_shift=10, dither=0.0
)... | 2,982 | 27.961165 | 88 | py |
espnet | espnet-master/egs2/l3das22/enh1/local/metric.py | # The implementation of the metric for L3DAS22 in
# Guizzo. et al. "L3DAS22 Challenge: Learning 3D Audio
# Sources in a Real Office Environment"
# The code is based on:
# https://github.com/l3das/L3DAS22/blob/main/metrics.py
import argparse
import os
import sys
import warnings
import jiwer
import numpy as np
import ... | 4,378 | 31.198529 | 87 | py |
espnet | espnet-master/egs2/librispeech/ssl1/local/measure_teacher_quality.py | # The measure_teacher_quality.py uses code from Fairseq:
# https://github.com/pytorch/fairseq/blob/master/examples/hubert/measure_teacher_quality.py
#
# Thanks to Abdelrahman Mohamed and Wei-Ning Hsu's help in this implementation,
# Their origial Hubert work is in:
# Paper: https://arxiv.org/pdf/2106.07447.pdf
... | 6,713 | 26.292683 | 95 | py |
espnet | espnet-master/egs2/slurp_spatialized/asr1/local/multi_to_single.py | import os
import sys
from multiprocessing import Pool
from pathlib import Path
import torchaudio
import tqdm
multi_path = sys.argv[1]
single_path = sys.argv[2]
data_list = ["tr_real", "tr_synthetic", "cv", "tt", "tt_qut"]
def m2s(pf):
if ".wav" not in pf[2]:
return
mwav = os.path.join(pf[0], pf[2])... | 1,386 | 26.74 | 83 | py |
espnet | espnet-master/egs2/chime7_task1/diar_asr1/local/pyannote_diarize.py | import argparse
import glob
import json
import math
import os.path
import re
from pathlib import Path
import numpy as np
import soundfile as sf
import torch
from pyannote.audio import Model, Pipeline
from pyannote.audio.core.inference import Inference
from pyannote.audio.pipelines import SpeakerDiarization
from pyanno... | 14,818 | 32.603175 | 87 | py |
espnet | espnet-master/egs2/chime7_task1/diar_asr1/local/pyannote_finetune.py | import argparse
import os.path
import shutil
from pathlib import Path
from types import MethodType
from pyannote.audio import Inference, Model
from pyannote.audio.tasks import Segmentation
from pyannote.database import FileFinder, get_protocol
from pytorch_lightning import Trainer
from pytorch_lightning.callbacks impo... | 5,429 | 27.429319 | 87 | py |
espnet | espnet-master/egs2/chime7_task1/asr1/local/gss_micrank.py | import argparse
import os
from copy import deepcopy
from pathlib import Path
import lhotse
import soundfile as sf
import torch
import torchaudio
import tqdm
from torch.utils.data import DataLoader, Dataset
class EnvelopeVariance(torch.nn.Module):
"""
Envelope Variance Channel Selection method with
(optio... | 8,190 | 33.707627 | 87 | py |
palbert | palbert-main/src/test.py | import argparse
import logging
import os
import torch
import transformers as t
from tqdm import tqdm, trange
from dataset import get_test_dataloaders, task_to_keys
from modeling.palbert_fast import (AlbertPABEEForSequenceClassification,
PAlbertForSequenceClassification)
from trainer... | 6,993 | 33.97 | 104 | py |
palbert | palbert-main/src/loss.py | import torch
from torch.nn import functional as F
class RegularizationLoss(torch.nn.Module):
def __init__(self, lambda_p: float, max_steps: int = 12, prior_type="geometric"):
super().__init__()
p_g = torch.zeros((max_steps,))
if prior_type == "geometric":
not_halted = 1.0
... | 1,922 | 34.611111 | 85 | py |
palbert | palbert-main/src/dataset.py | import datasets
from torch.utils.data import DataLoader
task_to_keys = {
"cola": ("sentence", None),
"mnli": ("premise", "hypothesis"),
"mrpc": ("sentence1", "sentence2"),
"qnli": ("question", "sentence"),
"qqp": ("question1", "question2"),
"rte": ("sentence1", "sentence2"),
"sst2": ("sente... | 5,500 | 34.262821 | 87 | py |
palbert | palbert-main/src/train.py | import argparse
import logging
import os.path
from collections import defaultdict
from itertools import chain
import numpy as np
import torch
import transformers as t
import wandb
from datasets import load_metric
from torch.optim import Adam
from transformers import AutoConfig, AutoModelForSequenceClassification
from... | 14,261 | 35.757732 | 92 | py |
palbert | palbert-main/src/trainer.py | # coding=utf-8
# Copyright 2022 Tinkoff.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to ... | 15,261 | 37.155 | 95 | py |
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