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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MCUa-Model | MCUa-Model-main/src/networks_N1.py | import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torchvision
class BaseNetwork(nn.Module):
def __init__(self, name, channels=1):
super(BaseNetwork, self).__init__()
self._name = name
self._channels = channels
def name(self):
return self._name
... | 3,718 | 31.622807 | 103 | py |
MCUa-Model | MCUa-Model-main/src/models2_N1.py | import time
import time
import ntpath
import datetime
import matplotlib.pyplot as plt
import torch.optim as optim
import torch.nn.functional as F
import matplotlib.pyplot as ply
from torch.autograd import Variable
from torch.utils.data import DataLoader, TensorDataset
from sklearn.metrics import roc_curve, auc
from skl... | 22,897 | 36.23252 | 170 | py |
MCUa-Model | MCUa-Model-main/src/networks2_P5.py | import numpy as np
import torch.nn as nn
import torch.nn.functional as F
import torchvision
class BaseNetwork2(nn.Module):
def __init__(self, name, channels=1):
super(BaseNetwork2, self).__init__()
self._name = name
self._channels = channels
def name(self):
return self._name
... | 3,678 | 31.27193 | 103 | py |
MCUa-Model | MCUa-Model-main/src/models2_N3.py | import time
import time
import ntpath
import datetime
import matplotlib.pyplot as plt
import torch.optim as optim
import torch.nn.functional as F
import matplotlib.pyplot as ply
from torch.autograd import Variable
from torch.utils.data import DataLoader, TensorDataset
from sklearn.metrics import roc_curve, auc
from skl... | 23,151 | 36.0432 | 170 | py |
MCUa-Model | MCUa-Model-main/src/datasets1.py | import os
import glob
import torch
import numpy as np
from PIL import Image, ImageEnhance
from torch.utils.data import Dataset
from torchvision.transforms import transforms
from .patch_extractor import PatchExtractor
LABELS = ['Normal', 'Benign', 'InSitu', 'Invasive']
#IMAGE_SIZE = (2048, 1536)
PATCH_SIZE = 224
clas... | 5,239 | 34.890411 | 166 | py |
MCUa-Model | MCUa-Model-main/src/models_P6.py | import time
import time
import ntpath
import datetime
import matplotlib.pyplot as plt
import torch.optim as optim
import torch.nn.functional as F
import matplotlib.pyplot as ply
from torch.autograd import Variable
from torch.utils.data import DataLoader, TensorDataset
from sklearn.metrics import roc_curve, auc
from skl... | 22,354 | 35.587561 | 170 | py |
vae-npvc | vae-npvc-master/models.py | import pdb
# from tensorflow.contrib import slim
import tensorflow as tf
from util.layers import GaussianLogDensity, GaussianKLD, \
GaussianSampleLayer, lrelu
# TODO:
# 1. Multi-stream?
# 2. Separate MLP & CNN?
# (or we can also just use CNN by viewing MLP input as D-channels)
# 3. Conditional input as an ... | 3,845 | 31.59322 | 86 | py |
vae-npvc | vae-npvc-master/util/mnist.py | import tensorflow as tf
from tensorflow.contrib import keras
def mnist_batcher_in_tanh_vector(
batch_size,
capacity=256,
min_after_dequeue=128,
):
(x, y), (_, _) = keras.datasets.mnist.load_data()
x = tf.constant(x)
x = tf.cast(x, tf.float32)
x = keras.layers.Flatten()(x) / 127.5 - 1.
... | 2,442 | 27.08046 | 75 | py |
SAL | SAL-master/code/training/base_training.py | import utils.general as utils
import os
from datetime import datetime
from pyhocon import ConfigFactory
import sys
import torch
import numpy as np
import json
import logging
class BaseTrainRunner():
def __init__(self,**kwargs):
if (type(kwargs['conf']) == str):
self.conf = ConfigFactory.pars... | 8,716 | 42.80402 | 166 | py |
SAL | SAL-master/code/training/sal_training.py |
import sys
sys.path.append('../code')
from utils.plots import plot_surface
import torch
from training.base_training import BaseTrainRunner
import logging
import time
class SalTrainRunner(BaseTrainRunner):
def run(self):
timing_log = []
for epoch in range(self.start_epoch,self.nepochs + 2):
... | 4,270 | 45.934066 | 174 | py |
SAL | SAL-master/code/datasets/recon_dataset.py | import torch.utils.data as data
from utils.general import *
import trimesh
from trimesh.sample import sample_surface
from scipy.spatial import cKDTree
from tqdm import tqdm
import utils.general as utils
class ReconDataSet(data.Dataset):
def __init__(self,split,dataset_path,dist_file_name):
model = trime... | 2,410 | 32.957746 | 118 | py |
SAL | SAL-master/code/datasets/dfaust_dataset.py |
import torch.utils.data as data
from utils.general import *
import utils.general as utils
import logging
class DFaustDataSet(data.Dataset):
def __init__(self,split,dataset_path,dist_file_name,with_gt = False):
base_dir = dataset_path
self.npyfiles_mnfld = self.get_instance_filenames(base_dir,spli... | 2,392 | 40.982456 | 130 | py |
SAL | SAL-master/code/evaluate/evaluate.py | import argparse
import sys
sys.path.append('../code')
import utils.general as utils
import os
import json
import trimesh
import utils.general as utils
import logging
from datasets.dfaust_dataset import DFaustDataSet
from datasets.recon_dataset import ReconDataSet
import torch
from pyhocon import ConfigFactory
import ut... | 21,265 | 48.803279 | 176 | py |
SAL | SAL-master/code/utils/plots.py | import plotly.graph_objs as go
import plotly.offline as offline
import torch
import numpy as np
from skimage import measure
import os
from tqdm import tqdm
import utils.general as utils
def get_threed_scatter_trace(points,caption = None,colorscale = None,color = None):
# assert points.shape[1] == 3, "3d scatter pl... | 14,459 | 43.767802 | 155 | py |
SAL | SAL-master/code/utils/general.py | import os
import numpy as np
import torch
import trimesh
import logging
from scipy.spatial import cKDTree as KDTree
def mkdir_ifnotexists(directory):
if not os.path.exists(directory):
os.mkdir(directory)
def as_mesh(scene_or_mesh):
"""
Convert a possible scene to a mesh.
If conversion occurs,... | 6,986 | 30.615385 | 103 | py |
SAL | SAL-master/code/model/network.py | import numpy as np
import utils.general as utils
import torch.nn as nn
import torch
import torch.nn.functional as F
from torch import distributions as dist
def maxpool(x, dim=-1, keepdim=False):
out, _ = x.max(dim=dim, keepdim=keepdim)
return out
class SimplePointnet_VAE(nn.Module):
''' PointNet-based e... | 6,434 | 32.868421 | 123 | py |
SAL | SAL-master/code/model/loss.py | from torch import nn
import torch
import utils.general as utils
import numpy as np
#
class GenLoss(nn.Module):
def __init__(self,manifold_pnts_weight):
super().__init__()
self.manifold_pnts_weight = manifold_pnts_weight
class SALLoss(GenLoss):
def __init__(self, manifold_pnts_weight,unsigned):
... | 1,747 | 30.781818 | 140 | py |
action-segmentation | action-segmentation-master/src/models/test_semimarkov.py | import random
import numpy as np
import torch
from scipy.optimize import linear_sum_assignment
from torch.utils.data import Dataset, DataLoader
from torch_struct import SemiMarkov, MaxSemiring
from models.semimarkov.semimarkov_modules import SemiMarkovModule
# device = torch.device("cuda")
device = torch.device("cpu... | 11,849 | 33.955752 | 115 | py |
action-segmentation | action-segmentation-master/src/models/flow.py | # code from Junxian He, https://github.com/jxhe/struct-learning-with-flow/blob/master/modules/projection.py
from __future__ import print_function
import math
import torch
import torch.nn as nn
import torch.nn.functional as F
class ReLUNet(nn.Module):
@classmethod
def add_args(cls, parser):
parser.add... | 4,504 | 34.472441 | 107 | py |
action-segmentation | action-segmentation-master/src/models/model.py | import torch.optim
from torch.utils.data import DataLoader
from data.corpus import Datasplit
def add_training_args(parser):
parser.add_argument('--epochs', type=int, default=60)
parser.add_argument('--batch_accumulation', type=int, default=1)
parser.add_argument('--lr', type=float, default=5e-3)
pars... | 2,895 | 32.674419 | 105 | py |
action-segmentation | action-segmentation-master/src/models/sequential.py | import tqdm
import numpy as np
import torch
import torch.nn as nn
from models.model import Model, make_optimizer, make_data_loader
from utils.utils import all_equal
from data.corpus import Datasplit
class Encoder(nn.Module):
@classmethod
def add_args(cls, parser):
parser.add_argument('--seq_num_layer... | 14,671 | 40.213483 | 130 | py |
action-segmentation | action-segmentation-master/src/models/framewise.py | import tqdm
import numpy as np
import torch
import torch.nn as nn
from models.model import Model, make_optimizer, make_data_loader
from utils.utils import all_equal
from models.semimarkov.semimarkov_utils import semimarkov_sufficient_stats
from collections import Counter
from data.corpus import Datasplit
class Fee... | 10,396 | 42.320833 | 132 | py |
action-segmentation | action-segmentation-master/src/models/semimarkov/semimarkov_utils.py | import numpy as np
import torch
from sklearn.mixture import GaussianMixture
def labels_to_spans(position_labels, max_k):
# position_labels: b x N, LongTensor
assert not (position_labels == -1).any(), "position_labels already appear span encoded (have -1)"
b, N = position_labels.size()
last = position_... | 4,658 | 35.685039 | 116 | py |
action-segmentation | action-segmentation-master/src/models/semimarkov/semimarkov.py | import copy
import numpy as np
import tqdm
import time
import torch
from data.corpus import Datasplit
from models.model import Model, make_optimizer, make_data_loader
from models.semimarkov.semimarkov_modules import SemiMarkovModule, ComponentSemiMarkovModule
from models.semimarkov import semimarkov_utils
from utils.... | 19,890 | 47.396594 | 173 | py |
action-segmentation | action-segmentation-master/src/models/semimarkov/semimarkov_modules.py | from typing import Dict, Set
import pickle
import numpy as np
import torch
import torch.nn.functional as F
from torch import nn
from torch.autograd import Variable
from torch.distributions import MultivariateNormal, Poisson
from torch.nn.init import xavier_uniform_
from torch_struct import SemiMarkovCRF
from models.f... | 43,230 | 43.522142 | 125 | py |
action-segmentation | action-segmentation-master/src/data/corpus.py | # modified from slim_mallow by Anna Kukleva, https://github.com/Annusha/slim_mallow
import os
import copy
import json
import random
import numpy as np
import torch
from torch.utils.data import Dataset, Sampler
from evaluation.accuracy import Accuracy
from evaluation.f1 import F1Score
from utils.logger import logger
... | 31,994 | 38.745342 | 149 | py |
matminer | matminer-master/matminer/featurizers/structure.py | from __future__ import division, unicode_literals, print_function
import os
import sys
import math
import json
import itertools
import warnings
from collections import OrderedDict
from operator import itemgetter
from random import sample
from copy import copy
from functools import lru_cache
import numpy as np
import ... | 154,271 | 39.248369 | 115 | py |
matminer | matminer-master/matminer/featurizers/tests/test_structure.py | # coding: utf-8
# Copyright (c) Pymatgen Development Team.
# Distributed under the terms of the MIT License.
from __future__ import unicode_literals, division
import os
import copy
import unittest
import csv
import json
import numpy as np
import pandas as pd
from multiprocessing import set_start_method
from sklearn.ex... | 41,657 | 44.929438 | 100 | py |
matminer | matminer-master/matminer/featurizers/utils/cgcnn.py | import inspect
import functools
import warnings
import numpy as np
import random
from monty.dev import requires
try:
import torch
from torch.utils.data import Dataset
import cgcnn
import cgcnn.data as cgcnn_data
from cgcnn.data import AtomInitializer
from cgcnn.model import CrystalGraphConvNet
... | 8,242 | 41.932292 | 80 | py |
matminer | matminer-master/matminer/featurizers/utils/tests/test_cgcnn.py | from unittest import TestCase
import unittest
import os
import json
import csv
from matminer.featurizers.utils.cgcnn import CIFDataWrapper, \
CrystalGraphConvNetWrapper, appropriate_kwargs, AtomCustomArrayInitializer
from pymatgen.core import Structure, Lattice
try:
import cgcnn
import torch
except ImportEr... | 4,312 | 40.873786 | 81 | py |
DeepOD | DeepOD-main/deepod/core/base_networks.py | import importlib
import warnings
import math
import torch
import numpy as np
from torch.nn.utils import weight_norm
from deepod.core.base_transformer_network import TSTransformerEncoder
# from deepod.core.base_transformer_network_dev import TSTransformerEncoder
from deepod.core.network_utility import _instantiate_class... | 22,239 | 37.949212 | 113 | py |
DeepOD | DeepOD-main/deepod/core/base_model.py | # -*- coding: utf-8 -*-
"""
Base class for deep Anomaly detection models
some functions are adapted from the pyod library
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
import numpy as np
import torch
import random
import time
from abc import ABCMeta, abstractmethod
from scipy.stats import binom
... | 13,595 | 31.218009 | 111 | py |
DeepOD | DeepOD-main/deepod/core/base_transformer_network.py | # -*- coding: utf-8 -*-
"""
Transformer structure
adapted from https://github.com/gzerveas/mvts_transformer
"""
import math
import torch
from typing import Optional, Any, Union, Callable
from torch.nn.modules import TransformerEncoderLayer
from torch.nn import functional as F
from torch import Tensor
from deepod.core... | 17,235 | 44.357895 | 159 | py |
DeepOD | DeepOD-main/deepod/core/transformer/embed.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.nn.utils import weight_norm
import math
class PositionalEmbedding(nn.Module):
def __init__(self, d_model, max_len=5000):
super(PositionalEmbedding, self).__init__()
# Compute the positional encodings once in log space.
... | 6,401 | 35.793103 | 114 | py |
DeepOD | DeepOD-main/deepod/core/transformer/selfattention_family.py | import torch
import torch.nn as nn
import numpy as np
from math import sqrt
# from reformer_pytorch import LSHSelfAttention
from einops import rearrange, repeat
class DSAttention(nn.Module):
'''De-stationary Attention'''
def __init__(self, mask_flag=True, factor=5, scale=None, attention_dropout=0.1, output_a... | 12,759 | 38.021407 | 137 | py |
DeepOD | DeepOD-main/deepod/model_selection/fmms.py | # -*- coding: utf-8 -*-
"""
Factorization Machine-based Unsupervised Model Selection Method
@Author: Ruyi Zhang & Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
import torch
import torch.utils.data as Data
import numpy as np
from deepod.model_selection.gene_feature import generate_meta_features
from sklea... | 7,894 | 31.356557 | 109 | py |
DeepOD | DeepOD-main/deepod/models/repen.py | # -*- coding: utf-8 -*-
"""
Representation learning-based unsupervised/weakly-supervised anomaly detection
PyTorch's implementation
this script is partially adapted from the official keras's implementation
https://www.google.com/url?q=https%3A%2F%2Fgithub.com%2FGuansongPang%2Fdeep-outlier-detection&sa=D&sntz=1&usg=AOvV... | 9,212 | 38.711207 | 138 | py |
DeepOD | DeepOD-main/deepod/models/devnet.py | # -*- coding: utf-8 -*-
"""
Deep anomaly detection with deviation networks.
PyTorch's implementation
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import get_network
from torch.utils.data import DataLoader, TensorDatase... | 7,510 | 33.934884 | 102 | py |
DeepOD | DeepOD-main/deepod/models/dsad.py | # -*- coding: utf-8 -*-
"""
One-class classification
this is partially adapted from https://github.com/lukasruff/Deep-SAD-PyTorch (MIT license)
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import get_network
from torch... | 8,482 | 32.266667 | 102 | py |
DeepOD | DeepOD-main/deepod/models/rca.py | """
RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection
this script is partially adapted from https://hub.nuaa.cf/illidanlab/RCA
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import MLPnet
from tqdm imp... | 7,861 | 30.198413 | 95 | py |
DeepOD | DeepOD-main/deepod/models/feawad.py | # -*- coding: utf-8 -*-
"""
Feature Encoding with AutoEncoders for Weakly-supervised Anomaly Detection
PyTorch's implementation
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import get_network
from torch.utils.data impo... | 7,417 | 33.826291 | 102 | py |
DeepOD | DeepOD-main/deepod/models/icl.py | # -*- coding: utf-8 -*-
"""
Anomaly Detection for Tabular Data with Internal Contrastive Learning
this script is partially adapted from the supplementary material in
https://openreview.net/forum?id=_hszZbt46bT
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseD... | 9,573 | 32.950355 | 107 | py |
DeepOD | DeepOD-main/deepod/models/dif.py | # -*- coding: utf-8 -*-
"""
Deep isolation forest for anomaly detection
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from sklearn.utils import check_array
from sklearn.preprocessing import StandardScaler
from sklearn.ensemble import IsolationForest
from deepod.core.base_model import BaseDeepAD
... | 13,547 | 36.738162 | 118 | py |
DeepOD | DeepOD-main/deepod/models/rdp.py | # -*- coding: utf-8 -*-
"""
Random distance prediction-based anomaly detection
this script is partially adapted from https://github.com/billhhh/RDP
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import MLPnet
from torch.... | 4,764 | 32.794326 | 95 | py |
DeepOD | DeepOD-main/deepod/models/goad.py | # -*- coding: utf-8 -*-
"""
Classification-based anomaly detection
this script is partially adapted from https://github.com/lironber/GOAD
License: https://github.com/lironber/GOAD/blob/master/LICENSE
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from... | 6,604 | 32.871795 | 115 | py |
DeepOD | DeepOD-main/deepod/models/prenet.py | # -*- coding: utf-8 -*-
"""
Weakly-supervised anomaly detection by pairwise relation prediction task
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import LinearBlock, get_network
import torch
import numpy as np
class ... | 7,979 | 31.704918 | 110 | py |
DeepOD | DeepOD-main/deepod/models/_local_test_.py | from deepod.models import *
from sklearn.metrics import roc_auc_score
import numpy as np
import torch
import pandas as pd
from deepod.utils.utility import cal_metrics
if __name__ == '__main__':
device = 'cuda' if torch.cuda.is_available() else 'cpu'
# # # # random data
# x1 = np.random.rand(10, 1)
# ... | 4,228 | 33.663934 | 100 | py |
DeepOD | DeepOD-main/deepod/models/slad.py | """
scale learning-based deep anomaly detection
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import MLPnet, LinearBlock
from torch.utils.data import DataLoader, TensorDataset
import numpy as np
import torch.nn.function... | 10,063 | 34.814947 | 108 | py |
DeepOD | DeepOD-main/deepod/models/dsvdd.py | # -*- coding: utf-8 -*-
"""
One-class classification
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.base_networks import get_network
from torch.utils.data import DataLoader
import torch
class DeepSVDD(BaseDeepAD):
""" Deep One-c... | 6,642 | 31.886139 | 100 | py |
DeepOD | DeepOD-main/deepod/models/neutral.py | # -*- coding: utf-8 -*-
"""
Neural Transformation Learning-based Anomaly Detection
this script is partially adapted from https://github.com/boschresearch/NeuTraL-AD (AGPL-3.0 license)
@Author: Hongzuo Xu <hongzuoxu@126.com, xuhongzuo13@nudt.edu.cn>
"""
from deepod.core.base_model import BaseDeepAD
from deepod.core.bas... | 6,206 | 30.994845 | 100 | py |
DeepOD | DeepOD-main/deepod/test/test_icl.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 5,663 | 37.27027 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_goad.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 5,655 | 37.216216 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_dsad.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 8,418 | 39.475962 | 93 | py |
DeepOD | DeepOD-main/deepod/test/test_slad.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 5,648 | 37.168919 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_neutral.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 5,652 | 37.195946 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_rdp.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 5,645 | 37.148649 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_dsvdd.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 7,274 | 39.642458 | 100 | py |
DeepOD | DeepOD-main/deepod/test/test_rca.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 5,661 | 37.256757 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_dif.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 6,867 | 38.930233 | 89 | py |
DeepOD | DeepOD-main/deepod/test/test_devnet.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 7,408 | 38.620321 | 107 | py |
DeepOD | DeepOD-main/deepod/test/test_repen.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
import pandas as pd
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy... | 6,862 | 38.67052 | 97 | py |
DeepOD | DeepOD-main/deepod/test/test_feawad.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 7,311 | 38.101604 | 81 | py |
DeepOD | DeepOD-main/deepod/test/test_prenet.py | # -*- coding: utf-8 -*-
from __future__ import division
from __future__ import print_function
import os
import sys
import unittest
# noinspection PyProtectedMember
from numpy.testing import assert_allclose
from numpy.testing import assert_array_less
from numpy.testing import assert_equal
from numpy.testing import ass... | 7,068 | 37.840659 | 83 | py |
YOLOF | YOLOF-master/setup.py | from setuptools import find_packages, setup
import torch
torch_ver = [int(x) for x in torch.__version__.split(".")[:2]]
assert torch_ver >= [1, 3], "Requires PyTorch >= 1.3"
setup(
name="yolof",
version="0.1.0",
author="Chensnathan",
url="https://github.com/chensnathan/YOLOF",
description="Code fo... | 422 | 25.4375 | 62 | py |
YOLOF | YOLOF-master/tools/train_net.py | #!/usr/bin/env python
# Copyright (c) Facebook, Inc. and its affiliates.
"""
Detection Training Script.
This scripts reads a given config file and runs the training or evaluation.
It is an entry point that is made to train standard models in detectron2.
In order to let one script support training of many models,
this... | 8,298 | 34.165254 | 79 | py |
YOLOF | YOLOF-master/yolof/data/dataset_mapper.py | from collections import deque
import copy
import logging
from typing import Optional, List, Union
import numpy as np
import torch
from detectron2.config import configurable, CfgNode
from detectron2.data import transforms as T
from detectron2.data import detection_utils as utils
from detectron2.data.dataset_mapper imp... | 13,794 | 41.446154 | 79 | py |
YOLOF | YOLOF-master/yolof/modeling/box_regression.py | import math
from typing import Tuple
import torch
_DEFAULT_SCALE_CLAMP = math.log(1000.0 / 16)
@torch.jit.script
class YOLOFBox2BoxTransform(object):
"""
The box-to-box transform defined in R-CNN. The transformation is
parameterized by 4 deltas: (dx, dy, dw, dh). The transformation scales
the box's ... | 5,283 | 39.335878 | 79 | py |
YOLOF | YOLOF-master/yolof/modeling/uniform_matcher.py | import numpy as np
import torch
from torch import nn
def box_xyxy_to_cxcywh(x):
x0, y0, x1, y1 = x.unbind(-1)
b = [(x0 + x1) / 2, (y0 + y1) / 2,
(x1 - x0), (y1 - y0)]
return torch.stack(b, dim=-1)
class UniformMatcher(nn.Module):
"""
Uniform Matching between the anchors and gt boxes, wh... | 3,887 | 33.714286 | 76 | py |
YOLOF | YOLOF-master/yolof/modeling/utils.py | from functools import partial
import torch.nn as nn
from detectron2.layers import (BatchNorm2d, NaiveSyncBatchNorm,
FrozenBatchNorm2d)
from detectron2.utils import env
def get_norm(norm, out_channels, **kwargs):
"""
Args:
norm (str or callable): either one of BN, SyncB... | 1,656 | 27.084746 | 71 | py |
YOLOF | YOLOF-master/yolof/modeling/encoder.py | from typing import List
from fvcore.nn import c2_xavier_fill
import torch
import torch.nn as nn
from detectron2.layers import ShapeSpec
from .utils import get_activation, get_norm
class DilatedEncoder(nn.Module):
"""
Dilated Encoder for YOLOF.
This module contains two types of components:
- th... | 4,521 | 36.683333 | 79 | py |
YOLOF | YOLOF-master/yolof/modeling/decoder.py | import math
from typing import Tuple
import torch
import torch.nn as nn
from .utils import get_activation, get_norm
class Decoder(nn.Module):
"""
Head Decoder for YOLOF.
This module contains two types of components:
- A classification head with two 3x3 convolutions and one
classific... | 4,423 | 39.218182 | 79 | py |
YOLOF | YOLOF-master/yolof/modeling/yolof.py | import copy
import logging
import numpy as np
from typing import Dict, List, Tuple
import torch
from fvcore.nn import sigmoid_focal_loss_jit, giou_loss
from torch import Tensor, nn
import torch.distributed as dist
from torchvision.ops.boxes import box_iou
from detectron2.config import configurable
from detectron2.data... | 22,871 | 40.966972 | 79 | py |
YOLOF | YOLOF-master/yolof/modeling/backbone/darknet.py | import logging
import torch
import torch.nn as nn
import torch.nn.functional as F
from detectron2.modeling.backbone import Backbone, BACKBONE_REGISTRY
from detectron2.layers import ShapeSpec
from ..utils import get_norm
try:
from mish_cuda import MishCuda as Mish
except Exception:
logger = logging.getLogger... | 11,903 | 28.392593 | 75 | py |
bert-nmt | bert-nmt-master/setup.py | #!/usr/bin/env python3
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from setupt... | 1,894 | 27.712121 | 78 | py |
bert-nmt | bert-nmt-master/generate.py | #!/usr/bin/env python3 -u
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
"""
Trans... | 7,827 | 38.938776 | 107 | py |
bert-nmt | bert-nmt-master/hubconf.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from fairseq.models.transformer im... | 1,668 | 30.490566 | 79 | py |
bert-nmt | bert-nmt-master/eval_lm.py | #!/usr/bin/env python3 -u
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
"""
Eval... | 8,070 | 34.712389 | 118 | py |
bert-nmt | bert-nmt-master/interactive.py | #!/usr/bin/env python3 -u
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
"""
Trans... | 7,593 | 34.820755 | 103 | py |
bert-nmt | bert-nmt-master/generator.py | #!/usr/bin/env python3 -u
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from col... | 8,776 | 39.447005 | 143 | py |
bert-nmt | bert-nmt-master/train.py | #!/usr/bin/env python3 -u
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
"""
Train... | 11,920 | 36.724684 | 105 | py |
bert-nmt | bert-nmt-master/scripts/average_checkpoints.py | #!/usr/bin/env python3
# Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import argp... | 5,408 | 36.825175 | 134 | py |
bert-nmt | bert-nmt-master/tests/test_train.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import contextlib
from io import S... | 4,799 | 35.363636 | 94 | py |
bert-nmt | bert-nmt-master/tests/test_average_checkpoints.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import collections
import os
impor... | 4,603 | 30.319728 | 80 | py |
bert-nmt | bert-nmt-master/tests/test_sequence_scorer.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import argparse
import unittest
i... | 4,057 | 33.389831 | 78 | py |
bert-nmt | bert-nmt-master/tests/utils.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import argparse
import torch
from... | 7,550 | 30.860759 | 101 | py |
bert-nmt | bert-nmt-master/tests/test_binaries.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import contextlib
from io import S... | 21,672 | 38.120939 | 112 | py |
bert-nmt | bert-nmt-master/tests/test_concat_dataset.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import unittest
import torch
from... | 2,051 | 29.626866 | 78 | py |
bert-nmt | bert-nmt-master/tests/test_noising.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import unittest
from typing import... | 19,887 | 36.595463 | 87 | py |
bert-nmt | bert-nmt-master/tests/test_backtranslation_dataset.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import unittest
import torch
fro... | 4,140 | 33.798319 | 90 | py |
bert-nmt | bert-nmt-master/tests/test_sequence_generator.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import argparse
import unittest
i... | 10,700 | 40.476744 | 96 | py |
bert-nmt | bert-nmt-master/tests/test_label_smoothing.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import argparse
import copy
import... | 4,247 | 40.647059 | 101 | py |
bert-nmt | bert-nmt-master/tests/test_convtbc.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import torch
import unittest
from ... | 1,787 | 34.058824 | 102 | py |
bert-nmt | bert-nmt-master/tests/test_token_block_dataset.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import unittest
import torch
fro... | 3,078 | 37.012346 | 89 | py |
bert-nmt | bert-nmt-master/tests/test_multi_corpus_sampled_dataset.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import unittest
from collections i... | 3,213 | 31.795918 | 79 | py |
bert-nmt | bert-nmt-master/tests/test_dictionary.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import tempfile
import unittest
i... | 1,971 | 26.013699 | 80 | py |
bert-nmt | bert-nmt-master/tests/test_utils.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import unittest
import torch
fro... | 2,239 | 25.046512 | 78 | py |
bert-nmt | bert-nmt-master/tests/test_character_token_embedder.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import torch
import unittest
from... | 1,764 | 35.020408 | 96 | py |
bert-nmt | bert-nmt-master/fairseq/checkpoint_utils.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from collections import OrderedDic... | 12,633 | 36.713433 | 123 | py |
bert-nmt | bert-nmt-master/fairseq/utils.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
from collections import defaultdic... | 10,749 | 31.874618 | 111 | py |
bert-nmt | bert-nmt-master/fairseq/sequence_scorer.py | # Copyright (c) 2017-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. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import torch
import sys
from fair... | 4,364 | 36.307692 | 107 | py |
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