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
value |
|---|---|---|---|---|---|---|
NeuralSpeech | NeuralSpeech-master/BinauralGrad/src/binauralgrad/warping.py | """
Copyright (c) Facebook, Inc. and its affiliates.
All rights reserved.
This source code is licensed under the license found in the
LICENSE file in the root directory of this source tree.
"""
# reference: https://github.com/facebookresearch/BinauralSpeechSynthesis/blob/main/src/warping.py
import torch as th
import... | 4,372 | 37.699115 | 101 | py |
NeuralSpeech | NeuralSpeech-master/BinauralGrad/src/binauralgrad/learner.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import os
import torch
import torch.nn as nn
from torch.nn.parallel import DistributedDataParallel
#from torch.utils.tensorboard import SummaryWriter
from tqdm import tqdm
from binauralgrad.losses import PhaseLoss
from binaura... | 8,812 | 40.375587 | 192 | py |
NeuralSpeech | NeuralSpeech-master/BinauralGrad/src/binauralgrad/model.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import scipy
from scipy.spatial.transform import Rotation as R
from math import sqrt
Linear = nn.Linear
ConvTranspose2d = nn.ConvTranspose2d
def Conv1d(*arg... | 7,085 | 35.715026 | 131 | py |
NeuralSpeech | NeuralSpeech-master/BinauralGrad/src/binauralgrad/dataset.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import os
import random
import torch
import torchaudio
from glob import glob
from torch.utils.data.distributed import DistributedSampler
import torch.nn.functional as F
class BinauralConditionalDataset(torch.utils.data.Datase... | 4,826 | 39.90678 | 117 | py |
NeuralSpeech | NeuralSpeech-master/BinauralGrad/src/binauralgrad/mstft_loss.py | #Reference: https://github.com/csteinmetz1/auraloss
import torch
import numpy as np
import librosa.filters
import scipy.signal
class SumAndDifference(torch.nn.Module):
"""Sum and difference signal extraction module."""
def __init__(self):
"""Initialize sum and difference extraction module."""
... | 24,435 | 35.690691 | 133 | py |
NeuralSpeech | NeuralSpeech-master/BinauralGrad/src/binauralgrad/train.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from argparse import ArgumentParser
from torch.cuda import device_count
from torch.multiprocessing import spawn
from binauralgrad.learner import train, train_distributed
import binauralgrad.params as params_all
def _get_free_port():
import s... | 1,779 | 37.695652 | 107 | py |
NeuralSpeech | NeuralSpeech-master/AdapterASR/e2e_asr_adaptertransformer.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright 2019 Shigeki Karita
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
"""Transformer speech recognition model (pytorch)."""
from argparse import Namespace
from distutils.util import strtobool
import logging
import math
im... | 42,330 | 40.058196 | 177 | py |
NeuralSpeech | NeuralSpeech-master/AdapterASR/balanced_sampler.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Reference: https://github.com/khornlund/pytorch-balanced-sampler
import torch
import torch.utils.data
import random
import collections
import logging
import numpy as np
from torch.utils.data.sampler import BatchSampler, WeightedRandomSampler
... | 2,341 | 38.033333 | 108 | py |
NeuralSpeech | NeuralSpeech-master/AdapterASR/utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
import logging
from espnet.asr.asr_utils import add_results_to_json
import argparse
import numpy as np
import collections
import json
def load_head_from_pretrained_model(model, model_path):
model_dict = torch.load(model_path, m... | 11,240 | 36.47 | 159 | py |
NeuralSpeech | NeuralSpeech-master/AdapterASR/data_load.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from espnet.utils.training.batchfy import make_batchset
from torch.utils.data import DataLoader
from torch.nn.utils.rnn import pad_sequence
import torch
import os
import json
import kaldiio
import random
import logging
import sentencepiece as spm... | 13,293 | 35.223433 | 113 | py |
NeuralSpeech | NeuralSpeech-master/AdapterASR/train.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import logging
import os
import collections
from espnet.bin.asr_train import get_parser
from espnet.utils.dynamic_import import dynamic_import
from espnet.utils.deterministic_utils import set_deterministic_pytorch
from espnet.asr.pytorch_backend.... | 25,635 | 46.650558 | 144 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/modules/diffusion.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# The diffusion acoustic decoder module is based on the DiffWave architecture: https://github.com/lmnt-com/diffwave
# Copyright 2020 LMNT, Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not... | 8,890 | 39.04955 | 185 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/modules/base.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import numpy as np
import torch
class BaseModule(torch.nn.Module):
def __init__(self):
super(BaseModule, self).__init__()
@property
def nparams(self):
"""
Returns number of trainable parameters of the module... | 893 | 26.090909 | 73 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/modules/tts_modules.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import logging
import torch
import torch.nn as nn
from torch.nn import functional as F
from modules.operations import SinusoidalPositionalEmbedding, OPERATIONS_ENCODER, OPERATIONS_DECODER
from tts_utils.hparams import hparams
DEFAULT_MAX_SOURC... | 14,686 | 37.447644 | 116 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/modules/operations.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import math
import torch
from torch import nn
from torch.nn import Parameter
import torch.onnx.operators
import torch.nn.functional as F
import tts_utils
from tts_utils.hparams import hparams
class SelfAttention(nn.Module):
def __init__(sel... | 53,222 | 40.64554 | 120 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/modules/priorgrad.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from modules.operations import *
from modules.tts_modules import DurationPredictor, LengthRegulator, PitchPredictor, EnergyPredictor,\
TransformerEncoderLayer, DEFAULT_MAX_SOURCE_POSITIONS
from modules.diffusion import DiffDecoder
from tts_ut... | 17,248 | 46.913889 | 171 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/stft.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
import numpy as np
import torch.nn.functional as F
from torch.autograd import Variable
from scipy.signal import get_window
from librosa.util import pad_center, tiny
import librosa.util as librosa_util
from torchaudio.transforms impo... | 6,068 | 35.341317 | 97 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/pl_utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import matplotlib
from torch.nn import DataParallel
from torch.nn.parallel import DistributedDataParallel
matplotlib.use('Agg')
import glob
import itertools
import subprocess
import threading
import traceback
from pytorch_lightning.callbacks im... | 58,649 | 34.959534 | 122 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/audio.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import traceback
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import librosa
import librosa.filters
import numpy as np
import torch
from scipy import signal
from scipy.io import wavfile
def save_wav(wav, path, sr, n... | 4,999 | 25.455026 | 116 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/__init__.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import glob
import logging
import re
import time
from collections import defaultdict
import os
import sys
import shutil
import types
import numpy as np
import torch
import torch.nn.functional as F
import torch.distributed as dist
def reduce_ten... | 17,042 | 29.931034 | 114 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/world_utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
##########
# world
##########
import numpy as np
import pysptk
import copy
import torch
gamma = 0
mcepInput = 3 # 0 for dB, 3 for magnitude
alpha = 0.45
en_floor = 10 ** (-80 / 20)
FFT_SIZE = 2048
def code_harmonic(sp, order):
# get mcep... | 2,926 | 26.87619 | 106 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/preprocessor.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import json
import warnings
import torch
from skimage.transform import resize
from tts_utils.world_utils import f0_to_coarse
warnings.filterwarnings("ignore")
import struct
import webrtcvad
from scipy.ndimage.morphology import binary_dilation... | 10,373 | 35.657244 | 115 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tts_utils/tts_utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
import torch.nn.functional as F
import numpy as np
from tts_utils.stft import STFT
def make_pad_mask(lengths, xs=None, length_dim=-1):
"""Make mask tensor containing indices of padded part.
Args:
lengths (LongTensor... | 8,414 | 37.424658 | 82 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/monotonic_align/__init__.py | import numpy as np
import torch
from .monotonic_align.core import maximum_path_c
def maximum_path(value, mask):
""" Cython optimised version.
value: [b, t_x, t_y]
mask: [b, t_x, t_y]
"""
value = value * mask
device = value.device
dtype = value.dtype
value = value.data.cpu().numpy().astype(np.float32... | 608 | 26.681818 | 62 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tasks/base_task.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import matplotlib
matplotlib.use('Agg')
from tts_utils.hparams import hparams, set_hparams
import random
import sys
import numpy as np
import torch.distributed as dist
from pytorch_lightning.loggers import TensorBoardLogger
from tts_utils.pl_uti... | 11,402 | 31.303116 | 98 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tasks/priorgrad_inference.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os, glob, re
from tts_utils.hparams import hparams, set_hparams
from tasks.priorgrad import PriorGradDataset
from tasks.priorgrad import PriorGradTask
import torch
import numpy as np
from tqdm import tqdm
set_hparams()
def get_latest_ckp... | 3,439 | 41.469136 | 142 | py |
NeuralSpeech | NeuralSpeech-master/PriorGrad-acoustic/tasks/priorgrad.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import matplotlib
# matplotlib.use('Agg')
from matplotlib import pyplot as plt
from tts_utils.pl_utils import data_loader
import os, sys
import json
from multiprocessing.pool import Pool
from tqdm import tqdm
from modules.tts_modules import Du... | 44,586 | 48.762277 | 165 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/eval_aishell.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import sys
import torch
import argparse
import re
#from fastcorrect_model import FastCorrectModel
import os
import os.path
import time
import json
import numpy as np
from fairseq import utils
utils.import_user_module(argparse.Namespace(user_dir=... | 4,731 | 41.630631 | 223 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FC_utils/language_pair_dataset.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import logging
import numpy as np
import torch
from fairseq.data im... | 24,146 | 38.455882 | 90 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FC_utils/hub_utils_fc.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
#!/usr/bin/env python3 -u
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
import copy
import logging... | 11,181 | 35.423453 | 95 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FC_utils/binarizer_fc.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
from collections import Counter
import torch
from fairseq... | 4,394 | 33.606299 | 103 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FC_utils/options_fc.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import argparse
from typing import Callable, List, Optional
import ... | 19,822 | 43.346756 | 120 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FC_utils/fastcorrect_generator.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
from collections import namedtuple
import numpy as np
import torch
... | 13,998 | 36.530831 | 163 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FastCorrect/fastcorrect_task.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import itertools
import logging
logger = logging.getLogge... | 13,281 | 34.513369 | 113 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FastCorrect/fc_loss.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import math
import torch
import torch.nn.functional as F
from fairs... | 7,118 | 35.137056 | 119 | py |
NeuralSpeech | NeuralSpeech-master/FastCorrect/FastCorrect/fastcorrect_model.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright (c) Facebook, Inc. and its affiliates.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn.functional as F
from fairseq import uti... | 29,151 | 36.470437 | 215 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/modules/stft_loss.py | # -*- coding: utf-8 -*-
# Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
# Copyright 2019 Tomoki Hayashi
# MIT License (https://opensource.org/licenses/MIT)
"""STFT-based Loss modules."""
import librosa
import torch
from parallel_wavegan.losses import LogSTFTMagnitudeLoss, SpectralConvergen... | 3,470 | 32.375 | 105 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/modules/tts_modules.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import math
import logging
import torch
import torch.nn as nn
from torch.nn import functional as F
from modules.operations import SinusoidalPositionalEmbedding, OPERATIONS_ENCODER, ConvSeparable
from utils.world_utils import build_activation
fr... | 17,051 | 37.579186 | 116 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/modules/lightspeech.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
from modules.operations import *
from modules.tts_modules import TransformerEncoder, LightSpeechDecoder, DurationPredictor, LengthRegulator, PitchPredictor, EnergyPredictor
import utils
from utils.world_utils import f0_to_coarse_torch, restore_pi... | 8,395 | 47.531792 | 139 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/modules/operations.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import math
import torch
from torch import nn
from torch.nn import Parameter
import torch.onnx.operators
import torch.nn.functional as F
import utils
from utils.hparams import hparams
from utils.world_utils import build_activation
def LayerNorm... | 24,598 | 41.930192 | 159 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/stft.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
import numpy as np
import torch.nn.functional as F
from torch.autograd import Variable
from scipy.signal import get_window
from librosa.util import pad_center, tiny
import librosa.util as librosa_util
def window_sumsquare(window, n... | 6,019 | 35.26506 | 97 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/pl_utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os
import re
import sys
import copy
import glob
import tqdm
import logging
import itertools
import subprocess
import threading
import traceback
from functools import wraps
import numpy as np
import torch
from torch.cuda._utils import _get... | 59,913 | 35.201813 | 122 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/pwg_decode_from_mel.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import logging
import yaml
import numpy as np
from sklearn.preprocessing import StandardScaler
import torch
from torch import nn
import utils
from parallel_wavegan.models import ParallelWaveGANGenerator
from parallel_wavegan.utils import read_h... | 2,401 | 33.811594 | 110 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/__init__.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os
import sys
import glob
import logging
import re
import time
from collections import defaultdict
import shutil
import types
import numpy as np
import torch
import torch.nn.functional as F
import torch.distributed as dist
def reduce_te... | 16,922 | 29.994505 | 114 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/world_utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
##########
# world
##########
import numpy as np
import pysptk
import copy
import math
import torch
import torch.nn as nn
gamma = 0
mcepInput = 3 # 0 for dB, 3 for magnitude
alpha = 0.45
en_floor = 10 ** (-80 / 20)
FFT_SIZE = 2048
def code_h... | 6,554 | 27.25431 | 106 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/preprocessor.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import json
import warnings
import struct
import webrtcvad
from skimage.transform import resize
from scipy.ndimage.morphology import binary_dilation
import pyworld as pw
import numpy as np
import torch
import librosa
import pyloudnorm as pyln
f... | 8,211 | 35.990991 | 107 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/utils/tts_utils.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import torch
from utils.stft import STFT
def make_pad_mask(lengths, xs=None, length_dim=-1):
"""Make mask tensor containing indices of padded part.
Args:
lengths (LongTensor or List): Batch of lengths (B,).
xs (Tensor, o... | 8,863 | 38.048458 | 84 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/tasks/base_task.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os
import sys
import random
import logging
import matplotlib
matplotlib.use('Agg')
import numpy as np
import torch.distributed as dist
from pytorch_lightning.logging import TensorBoardLogger
from torch import nn
import torch.utils.data
i... | 11,465 | 31.207865 | 98 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/tasks/lightspeech_inference.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os, glob, re
from tqdm import tqdm
import numpy as np
import torch
import utils
from utils.hparams import hparams, set_hparams
from tasks.lightspeech import LightSpeechDataset, LightSpeechTask
set_hparams()
def get_latest_ckpt(dir):
... | 2,707 | 37.685714 | 123 | py |
NeuralSpeech | NeuralSpeech-master/LightSpeech/tasks/lightspeech.py | # Copyright (c) Microsoft Corporation.
# Licensed under the MIT License.
import os
import sys
import re
import glob
import logging
import json
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from multiprocessing.pool import Pool
from tqdm import tqdm
import numpy as np
import torch
import torc... | 37,184 | 44.681818 | 131 | py |
lm-scorer | lm-scorer-master/lm_scorer/models/gpt2.py | from typing import * # pylint: disable=wildcard-import,unused-wildcard-import
import torch
from transformers import AutoTokenizer, GPT2LMHeadModel
from transformers import GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP
from transformers.tokenization_utils import BatchEncoding
from .abc.transformers import TransformersLMScorer
... | 3,499 | 39.697674 | 85 | py |
lm-scorer | lm-scorer-master/lm_scorer/models/abc/base.py | from typing import * # pylint: disable=wildcard-import,unused-wildcard-import
from abc import ABC, abstractmethod
import math
import torch
class LMScorer(ABC):
def __init__(self, model_name: str, **kwargs: Any) -> None:
self._build(model_name, kwargs)
@overload
def sentence_score(
self... | 3,273 | 30.480769 | 83 | py |
lm-scorer | lm-scorer-master/lm_scorer/models/abc/batch.py | # pylint: disable=abstract-method
from typing import * # pylint: disable=wildcard-import,unused-wildcard-import
from abc import abstractmethod
import torch
from .base import LMScorer
class BatchedLMScorer(LMScorer):
# @overrides
def _build(self, model_name: str, options: Dict[str, Any]) -> None:
su... | 1,148 | 30.916667 | 78 | py |
lm-scorer | lm-scorer-master/lm_scorer/bin/cli.py | #!/usr/bin/env python3
from typing import * # pylint: disable=wildcard-import,unused-wildcard-import
import argparse
import itertools
import os
import sys
import torch
from ..models.auto import AutoLMScorer as LMScorer
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(
descript... | 5,142 | 28.728324 | 88 | py |
lm-scorer | lm-scorer-master/tests/unit/models/abc/test_base.py | # pylint: disable=missing-module-docstring,missing-function-docstring,unused-variable,too-many-locals,too-many-statements
import math
import pytest # pylint: disable=unused-import
import scipy
import torch
from lm_scorer.models.abc.base import LMScorer
def model(text):
tokens = ["START"] + text.split(" ")
s... | 4,467 | 35.325203 | 121 | py |
espressopp | espressopp-master/src/external/transformations.py | """
***********************************
espressopp.external.transformations
***********************************
Homogeneous Transformation Matrices and Quaternions.
A library for calculating 4x4 matrices for translating, rotating, reflecting,
scaling, shearing, projecting, orthogonalizing, and superimposing arrays of... | 61,424 | 32.602298 | 79 | py |
espressopp | espressopp-master/doc/ug/conf.py | # -*- coding: utf-8 -*-
#
# ESPResSo++ documentation build configuration file, created by
# sphinx-quickstart on Sat Jan 23 13:11:32 2010.
#
# 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
# autogenerated file.
#
# ... | 7,631 | 32.038961 | 92 | py |
Dataset-3DPOP | Dataset-3DPOP-main/Examples/SampleTrainingImages.py | # !/usr/bin/env python3
"""Sample images and save annotaitons to json to be read by pytorch dataloader"""
import sys
sys.path.append("./")
from POP3D_Reader import Trial
import os
import cv2
import numpy as np
import math
import pandas as pd
import random
from tqdm import tqdm
import json
random.seed(10)
def GetInst... | 14,223 | 40.228986 | 164 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/test.py | import os
from skimage import io, transform
import torch
import torchvision
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms#, utils
# import torch.optim as optim
import numpy as np
from PIL imp... | 5,710 | 29.704301 | 136 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/train.py | import torch
import torchvision
from torch.autograd import Variable
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import Dataset, DataLoader
from torchvision import transforms, utils
import torch.optim as optim
import torchvision.transforms as standard_transforms
from tensorboardX import ... | 20,692 | 40.05754 | 160 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/evaluation/metrics.py | import numpy as np
import torch
from sklearn.metrics import average_precision_score
class AverageMeter(object):
"""Computes and stores the average and current value"""
def __init__(self):
self.reset()
def reset(self):
self.val = 0
self.avg = 0
self.sum = 0
self.co... | 3,678 | 31.557522 | 107 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/networks/DIRL.py | import torch
import torch.nn as nn
from torchvision import models
import torch.nn.functional as F
import scipy.stats as st
import numpy as np
from torch.nn.parameter import Parameter
from networks.blocks import Conv2dBlock, BasicBlock, BasicConv
import cv2
import copy
import os
## ---------------------Bi-directional F... | 18,647 | 40.44 | 134 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/networks/iHDRNet.py | import math
import torch
import torch.nn.functional as F
from torch import nn
from torch.nn import Parameter
from networks.blocks import Conv2d_cd, ResNetBlock, Conv2dBlock
import numpy as np
class SelfAttention(nn.Module):
""" Self attention Layer"""
def __init__(self,in_dim, mode='self'):
super(Self... | 9,047 | 36.38843 | 122 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/networks/UNet.py | import torch
import torchvision.models as models
import torch.nn.functional as F
import torch.nn as nn
from networks.blocks import BasicBlock, Bottleneck
class DoubleConv(nn.Module):
"""(convolution => [BN] => ReLU) * 2"""
def __init__(self, in_channels, out_channels):
super().__init__()
self... | 5,067 | 34.943262 | 96 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/networks/E_dom.py | import torch
import torch.nn as nn
import torch.nn.functional as F
import numpy as np
from collections import OrderedDict
import torchvision.models as models
from networks.blocks import PartialConv2d
class DomainEncoder(nn.Module):
def __init__(self, style_dim):
super(DomainEncoder, self).__init__()
... | 3,091 | 30.876289 | 106 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/networks/blocks.py | """
Copyright (C) 2019 NVIDIA Corporation. All rights reserved.
Licensed under the CC BY-NC-SA 4.0 license
(https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
"""
import torch
import torch.nn.functional as F
from torch import nn
import math
def conv3x3(in_planes, out_planes, stride=1):
"3x3 convolution... | 13,469 | 35.016043 | 158 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/dataset/base_dataset.py | """This module implements an abstract base class (ABC) 'BaseDataset' for datasets.
It also includes common transformation functions (e.g., get_transform, __scale_width), which can be later used in subclasses.
"""
import random
import numpy as np
import torch.utils.data as data
#from PIL import Image
import cv2
#import... | 4,950 | 35.138686 | 141 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/dataset/multi_objects_ihd_dataset.py | import os.path
import os
import torch
import torchvision.transforms.functional as tf
from dataset.base_dataset import BaseDataset, get_transform
#from PIL import Image
import cv2
import numpy as np
import torchvision.transforms as transforms
import random
import torch.nn.functional as F
import copy
class MultiObjectsI... | 5,493 | 37.964539 | 141 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/dataset/__init__.py | """This package includes all the modules related to data loading and preprocessing
To add a custom dataset class called 'dummy', you need to add a file called 'dummy_dataset.py' and define a subclass 'DummyDataset' inherited from BaseDataset.
You need to implement four functions:
-- <__init__>: ... | 3,557 | 36.851064 | 176 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/dataset/ihd_dataset.py | import os.path
import os
import torch
import torchvision.transforms.functional as tf
from dataset.base_dataset import BaseDataset, get_transform
#from PIL import Image
import cv2
import numpy as np
import torchvision.transforms as transforms
import random
import torch.nn.functional as F
import copy
class IhdDataset(Ba... | 5,665 | 38.347222 | 141 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/pytorch_iou/__init__.py | import torch
import torch.nn.functional as F
from torch.autograd import Variable
import numpy as np
def _iou(pred, target, size_average = True):
b = pred.shape[0]
IoU = 0.0
for i in range(0,b):
#compute the IoU of the foreground
Iand1 = torch.sum(target[i,:,:,:]*pred[i,:,:,:])
Ior1... | 730 | 24.206897 | 74 | py |
MadisNet-Inharmonious-Region-Localization | MadisNet-Inharmonious-Region-Localization-master/pytorch_ssim/__init__.py | # https://github.com/Po-Hsun-Su/pytorch-ssim/blob/master/pytorch_ssim/__init__.py
import torch
import torch.nn.functional as F
from torch.autograd import Variable
import numpy as np
from math import exp
def gaussian(window_size, sigma):
gauss = torch.Tensor([exp(-(x - window_size//2)**2/float(2*sigma**2)) for x in... | 4,529 | 34.952381 | 104 | py |
thundergbm | thundergbm-master/python/benchmarks/experiments.py | import utils.data_utils as du
from model.catboost_model import CatboostModel
from model.lightgbm_model import LightGBMModel
from model.xgboost_model import XGboostModel
from model.thundergbm_model import ThunderGBMModel
from model.datasets import Dataset
import utils.file_utils as fu
import pandas as pd
import math
imp... | 7,521 | 36.054187 | 112 | py |
thundergbm | thundergbm-master/python/benchmarks/model/xgboost_model.py | from model.base_model import BaseModel
import numpy as np
import xgboost as xgb
import time
import utils.data_utils as du
from model.datasets import Dataset
class XGboostModel(BaseModel):
def __init__(self, use_exact=False, debug_verose=1):
BaseModel.__init__(self)
self.use_exact = use_exact
... | 3,015 | 33.272727 | 89 | py |
thundergbm | thundergbm-master/docs/conf.py | # -*- coding: utf-8 -*-
#
# ThunderSVM documentation build configuration file, created by
# sphinx-quickstart on Sat Oct 28 23:38:46 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
# autogenerated file.
#
... | 5,511 | 29.622222 | 79 | py |
PoseTriplet | PoseTriplet-main/estimator/posegan_evaluate.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import math
import multiprocessing
import os
import pickle
import random
from time import time
import numpy as np
import torch... | 19,271 | 43.714617 | 131 | py |
PoseTriplet | PoseTriplet-main/estimator/posegan_train.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import os
import random
from time import time
import numpy as np
import torch
from torch.autograd import Variable
from common... | 11,685 | 43.098113 | 125 | py |
PoseTriplet | PoseTriplet-main/estimator/posegan_basementclass.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import os
import os.path as path
import pickle
from time import time
import numpy as np
import torch
import torch.optim as opt... | 55,174 | 51.647901 | 169 | py |
PoseTriplet | PoseTriplet-main/estimator/function/utils.py | from __future__ import absolute_import, division
import os
import torch
import numpy as np
from tensorboardX import SummaryWriter
# self define tools
class Summary(object):
def __init__(self, directory):
self.directory = directory
self.epoch = 0
self.writer = None
self.phase = 0
... | 7,848 | 33.730088 | 109 | py |
PoseTriplet | PoseTriplet-main/estimator/function/gan_utils.py | import torch.nn as nn
import torch
import numpy as np
import torchgeometry as tgm
'''
function on pose related information extraction.
'''
def get_pose3dbyBoneVec(bones, num_joints=16):
'''
conver bone vect to pose3d，is the inverse of get_bone_vector
:param bones:
:return:
'''
Ctinverse = tor... | 11,075 | 34.386581 | 122 | py |
PoseTriplet | PoseTriplet-main/estimator/common/custom_dataset.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import numpy as np
import copy
from common.skeleton import Skeleton
from common.mocap_dataset import MocapDataset
from common.c... | 4,740 | 33.355072 | 101 | py |
PoseTriplet | PoseTriplet-main/estimator/common/camera.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import numpy as np
import torch
import torchgeometry as tgm
from common.utils import wrap
from common.quaternion import qrot, ... | 11,136 | 31.755882 | 159 | py |
PoseTriplet | PoseTriplet-main/estimator/common/loss.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
import numpy as np
def mpjpe(predicted, target):
"""
Mean per-joint position error (i.e. mean Euclidean d... | 6,020 | 31.722826 | 106 | py |
PoseTriplet | PoseTriplet-main/estimator/common/utils.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
import numpy as np
import hashlib
def wrap(func, *args, unsqueeze=False):
"""
Wrap a torch function so it... | 1,470 | 30.297872 | 77 | py |
PoseTriplet | PoseTriplet-main/estimator/common/model.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
import torch.nn as nn
class TemporalModelBase(nn.Module):
"""
Do not instantiate this class.
"""
... | 8,387 | 40.524752 | 128 | py |
PoseTriplet | PoseTriplet-main/estimator/common/camera2world.py | import torch
import numpy as np
from sklearn.decomposition import PCA
from scipy.spatial.transform import Rotation as R
"""
camera to world:
case 1: assume the camera ID is known for each clip.
A. do PCA for 150 clips to found a gravity approximation
B. assume a stand pose, filter out the stand pose from prediction, d... | 3,850 | 31.91453 | 97 | py |
PoseTriplet | PoseTriplet-main/estimator/common/quaternion.py | # Copyright (c) 2018-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
def qrot(q, v):
"""
Rotate vector(s) v about the rotation described by quaternion(s) q.
Expects a ten... | 1,001 | 27.628571 | 78 | py |
PoseTriplet | PoseTriplet-main/estimator/poseaugtool/model_virtualCam/virtualCam.py | import torch
import torchgeometry as tgm
from torch import nn
from poseaugtool.model_conv1d.conv1d import Conv1dBlock
from common.quaternion import qrot
from common.camera import project_to_2d_purelinear
class DoubleLinear(nn.Module):
def __init__(self, linear_size):
super(DoubleLinear, self).__init__()
... | 14,619 | 34.228916 | 128 | py |
PoseTriplet | PoseTriplet-main/estimator/poseaugtool/model_conv1d/conv1d.py | import torch.nn as nn
import torch
import torch.nn.functional as F
##############################################################
class DoubleConv(nn.Module):
"""(convolution => [BN] => ReLU) * 2"""
def __init__(self, in_channels, out_channels, mid_channels=None, kernel_size=3 , padding=1, stride=1):
... | 5,285 | 36.489362 | 122 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/ribpose2bvh.py |
import random
import torch.optim as optim
import os
import datetime
import os.path as path
from torch.autograd import Variable
from progress.bar import Bar
from time import time
from bvh_skeleton import humanoid_1205_skeleton
from bvh_skeleton.camera import world2cam_sktpos, cam2world_sktpos
import torch
import nu... | 3,920 | 26.041379 | 98 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/test.py | import torch
import sys, os
sys.path.insert(0, os.path.dirname(__file__))
from LaFan import LaFan1
from torch.utils.data import Dataset, DataLoader
from model import StateEncoder, \
OffsetEncoder, \
TargetEncoder, \
LSTM, \
Decoder, \
... | 17,898 | 51.336257 | 126 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/py_utils.py | import os
import numpy as np
import torch
def merge_dict(dict_list):
ret = {}
for dict in dict_list:
for key, value in dict.items():
try:
ret[key]
except KeyError:
ret[key] = 0.0
ret[key] += value
return ret
def update_dict(old_d... | 2,734 | 25.553398 | 90 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/functions.py | import torch
import numpy as np
import torch.nn as nn
from quaternion import qeuler_np
from remove_fs import remove_fs
def PLU(x, alpha = 0.1, c = 1.0):
relu = nn.ReLU()
o1 = alpha * (x + c) - c
o2 = alpha * (x - c) + c
o3 = x - relu(x - o2)
o4 = relu(o1 - o3) + o3
return o4
def gen_ztta(dim =... | 2,426 | 36.338462 | 95 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/model.py | import torch
import numpy as np
import torch.nn as nn
from functions import PLU
class StateEncoder(nn.Module):
def __init__(self, in_dim = 128, hidden_dim = 512, out_dim = 256):
super(StateEncoder, self).__init__()
self.in_dim = in_dim
self.hidden_dim = hidden_dim
self.out_dim = ou... | 5,161 | 30.096386 | 86 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/remove_fs.py | import os
import sys
import numpy as np
import torch
import argparse
from tqdm import tqdm
BASEPATH = os.path.dirname(__file__)
from os.path import join as pjoin
sys.path.insert(0, BASEPATH)
sys.path.insert(0, pjoin(BASEPATH, '..'))
import foot_sliding.BVH as BVH
from foot_sliding.InverseKinematics import JacobianInve... | 6,250 | 29.642157 | 115 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/quaternion.py |
import torch
import numpy as np
# PyTorch-backed implementations
def qmul(q, r):
"""
Multiply quaternion(s) q with quaternion(s) r.
Expects two equally-sized tensors of shape (*, 4), where * denotes any number of dimensions.
Returns q*r as a tensor of shape (*, 4).
"""
assert q.shape[-1] == 4... | 6,413 | 32.936508 | 102 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/test-randomfuture-v1.py | import torch
import sys, os
sys.path.insert(0, os.path.dirname(__file__))
from LaFan import LaFan1
from torch.utils.data import Dataset, DataLoader
from model import StateEncoder, \
OffsetEncoder, \
TargetEncoder, \
LSTM, \
Decoder, \
... | 21,956 | 51.154394 | 139 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/skeleton.py | import torch
import os
import numpy as np
import sys
sys.path.insert(0, os.path.dirname(__file__))
from quaternion import qmul_np, qmul, qrot
from torch.utils.data import Dataset, DataLoader
from LaFan import LaFan1
class Skeleton:
def __init__(self, offsets, parents, joints_left=None, joints_right=None):
... | 6,005 | 35.846626 | 110 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/LaFan.py | import torch
from torch.utils.data import Dataset, DataLoader
import sys, os
sys.path.insert(0, os.path.dirname(__file__))
sys.path.append("..")
import numpy as np
from lafan1 import extract, utils, benchmarks
class LaFan1(Dataset):
def __init__(self, bvh_path, train = False, seq_len = 50, offset = 10, debug = F... | 4,399 | 38.285714 | 131 | py |
PoseTriplet | PoseTriplet-main/hallucinator/code_rib/rlpose2bvh.py |
import random
import argparse
import torch.optim as optim
import os
import datetime
import os.path as path
from torch.autograd import Variable
from progress.bar import Bar
from time import time
from bvh_skeleton import humanoid_rib_skeleton
from bvh_skeleton.camera import world2cam_sktpos
import torch
import numpy... | 3,416 | 25.905512 | 98 | py |
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