repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
durham-abric/RoadDetector | [
"634b21384000abc5223d63f6030c6976263a204c"
] | [
"src/skeleton.py"
] | [
"from skimage.morphology import skeletonize, remove_small_objects, remove_small_holes\r\nfrom skimage import io\r\nimport numpy as np\r\nfrom matplotlib.pylab import plt\r\nimport cv2\r\nfrom other_tools import sknw\r\nimport os\r\nimport pandas as pd\r\nfrom functools import partial\r\nfrom itertools import tee\r\... | [
[
"numpy.array",
"numpy.dot",
"numpy.linalg.norm",
"scipy.spatial.distance.pdist",
"numpy.squeeze",
"pandas.DataFrame",
"numpy.copy",
"matplotlib.pylab.plt.savefig",
"numpy.linalg.det",
"numpy.degrees",
"numpy.any",
"matplotlib.pylab.plt.imshow",
"numpy.argwhere",... |
mskimm/sparkannoy | [
"76f82c5e41fd8ca1d5c186c96437dd8368ead261"
] | [
"data/dump.py"
] | [
"import sys\nimport h5py\nimport numpy as np\n\ntrain = h5py.File(sys.argv[1], 'r')['train']\narr = np.array(train, dtype='f4')\n\nwith open('../data/annoy/sample-glove-25-angular.txt', 'w') as f:\n for i, sample in enumerate(arr[:1000]):\n f.write(str(i) + '\\t' + ','.join([str(x) for x in sample]) + '\\... | [
[
"numpy.array"
]
] |
v-liuwei/USTC2020- | [
"0ec4cf48cbd42a3cd71f8ed7c27201beaee19a8e"
] | [
"Lab1-Logistic_Regression/src/main.py"
] | [
"import numpy as np\nfrom model import LogisticRegression\n\n\n# load data\nx_train = np.load('./data/LR/train_data.npy')[:, 1:]\ny_train = np.load('./data/LR/train_target.npy')\nx_test = np.load('./data/LR/test_data.npy')[:, 1:]\ny_test = np.load('./data/LR/test_target.npy')\n\n# create an LR model and fit it\nlr ... | [
[
"numpy.load"
]
] |
J535D165/asreview-wordcloud | [
"01aba8680f469455ab70dd27965f0507e38fbd7d"
] | [
"asreviewcontrib/wordcloud/entrypoint.py"
] | [
"# Copyright 2020 The ASReview Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requir... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.set_title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.imshow"
]
] |
ukky17/ori_selectivity_CNN | [
"2c32d82c1331cb2a8767ed2de68060f1ac8acea5"
] | [
"utils.py"
] | [
"import numpy as np\n\nfrom keras.datasets import cifar10\nfrom keras.utils import to_categorical\n\ndef prepare_train_test():\n # load\n (x_train, y_train), (x_test, y_test) = cifar10.load_data()\n x_train = x_train.astype('float32')\n x_test = x_test.astype('float32')\n\n # standardization\n x_t... | [
[
"numpy.mean"
]
] |
mshicom/Klampt | [
"79f983a790a0ac201af484ba64f68ebc21acc6c3"
] | [
"Python/klampt/io/numpy_convert.py"
] | [
"\"\"\"Conversions to and from Numpy objects; makes numerical computations much\nmore convenient.\n\"\"\"\n\nimport numpy as np\nfrom klampt.math import so3,se3\nfrom ..model import types\n\nsupportedTypes = set(['Vector3','Point','Matrix3','Rotation','RigidTransform',\n 'Config','Configs','Trajectory',\n ... | [
[
"numpy.hstack",
"numpy.array",
"numpy.dot"
]
] |
evgiz/variational-autoencoder | [
"61cec5d97c30580f073722be1ab4a0eae97067db"
] | [
"util.py"
] | [
"\"\"\"\nAuthor: Sigve Rokenes\nDate: February, 2019\n\nUtility functions for variational autoencoder\n\n\"\"\"\n\nimport skimage as sk\nfrom skimage import io\nimport tensorflow as tf\nimport numpy as np\n\n\n# ===================================== #\n# #\n# Utility ... | [
[
"numpy.array",
"numpy.mean",
"numpy.shape",
"tensorflow.layers.conv2d",
"tensorflow.layers.conv2d_transpose"
]
] |
Terfno/learn_DL | [
"0e1f3049c2c342915e1b7237506029a42539029e"
] | [
"3/nn.py"
] | [
"import numpy as np\n\ndef sigmoid(x):\n return 1 / (1 + np.exp(-x))\n\ndef identity_function(x):\n return x\n\ndef init_network():\n network = {}\n\n network['W1'] = np.array([[0.1, 0.3, 0.5], [0.2, 0.4, 0.6]])\n network['b1'] = np.array([0.1, 0.2, 0.3])\n network['W2'] = np.array([[0.1, 0.4], [0.2, 0.5], [0... | [
[
"numpy.array",
"numpy.dot",
"numpy.exp"
]
] |
SiftScience/transformers | [
"fedfc9853c4d50ac06aa07fda5c28dc625f5c045"
] | [
"transformers/data/processors/utils.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.\n# Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may... | [
[
"pandas.read_parquet"
]
] |
byooooo/dispersant_screening_PAL | [
"e25acc82c18db209fbf29046780ca31835f587d0"
] | [
"work/wandb/run-20200807_173426-1hzb694b/code/work/gp_learning_curves.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import absolute_import\n\nimport os\n\nimport joblib\nimport numpy as np\nimport pandas as pd\nfrom six.moves import range\nfrom sklearn.feature_selection import VarianceThreshold\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import Stand... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.feature_selection.VarianceThreshold",
"sklearn.preprocessing.StandardScaler"
]
] |
Mario-Kart-Felix/nvae | [
"37b954977833198f2946830c68823b094cc00412"
] | [
"nvae/dataset.py"
] | [
"import os\nfrom glob import glob\n\nimport cv2\nimport h5py\nimport torch\nfrom torch.utils.data import Dataset\n\n\nclass ImageH5Dataset(Dataset):\n\n def __init__(self, dataset_path, img_dim):\n self.dataset_path = dataset_path\n self.img_dim = (img_dim, img_dim) if type(img_dim) == int else img... | [
[
"torch.tensor"
]
] |
shadofren/deeposlandia | [
"3dcb511482aff9c62bffd383e92055920c7a7e85"
] | [
"tests/test_generators.py"
] | [
"\"\"\"Unit test related to the generator building and feeding\n\"\"\"\n\nimport pytest\n\nimport numpy as np\n\nfrom deeposlandia import generator, utils\n\n\ndef test_feature_detection_labelling_concise():\n \"\"\"Test `feature_detection_labelling` function in `generator` module by considering a concise\n l... | [
[
"numpy.array",
"numpy.amax",
"numpy.amin"
]
] |
MarcWong/tensorpack | [
"b7e411a75ca252fda46fc3cf1887687c875abe23",
"51ab279480dc1e3ffdc07884a9e8149dea9651e9"
] | [
"examples/OnAVOS/datasets/DAVIS/DAVIS.py",
"examples/CTC-TIMIT/create-lmdb.py"
] | [
"import glob\nimport tensorflow as tf\nfrom datasets.Dataset import ImageDataset\nfrom datasets.Util.Util import username, unique_list\nfrom datasets.Util.Reader import load_label_default\n\nNUM_CLASSES = 2\nVOID_LABEL = 255 # for translation augmentation\nDAVIS_DEFAULT_PATH = \"/fastwork/\" + username() + \"/mywo... | [
[
"tensorflow.reduce_max"
],
[
"numpy.concatenate",
"scipy.io.wavfile.read",
"numpy.asarray"
]
] |
cubensys/pysal | [
"8d50990f6e6603ba79ae1a887a20a1e3a0734e51",
"8d50990f6e6603ba79ae1a887a20a1e3a0734e51",
"8d50990f6e6603ba79ae1a887a20a1e3a0734e51"
] | [
"pysal/contrib/glm/utils.py",
"pysal/spreg/tests/test_error_sp.py",
"pysal/spreg/tests/test_ols_sparse.py"
] | [
"\nfrom __future__ import absolute_import, print_function\nimport numpy as np\nimport warnings\n\n\ndef _bit_length_26(x):\n if x == 0:\n return 0\n elif x == 1:\n return 1\n else:\n return len(bin(x)) - 2\n\n\ntry:\n from scipy.lib._version import NumpyVersion\nexcept ImportError:\... | [
[
"numpy.asarray",
"numpy.sum",
"numpy.finfo",
"scipy.lib._version.NumpyVersion",
"numpy.linalg.svd"
],
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.reshape",
"numpy.ones",
"scipy.__version__.split",
"numpy.diag"
],
[
"numpy.testing.assert_allclose... |
YuhangSong/pytorch-a2c-ppo-acktr | [
"a018fd9ef640a60cef75f01f9e95ecff383b6a81"
] | [
"model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom running_stat import ObsNorm\nfrom distributions import Categorical, DiagGaussian\n\n\ndef weights_init(m):\n classname = m.__class__.__name__\n if classname.find('Conv') != -1 or classname.find('Linear') != -1:\n nn.init.orthog... | [
[
"torch.nn.Linear",
"torch.nn.init.orthogonal",
"torch.nn.Conv2d",
"torch.nn.init.calculate_gain",
"torch.nn.functional.relu",
"torch.nn.functional.tanh"
]
] |
asl-epfl/sml_icassp2021 | [
"ed64c487c59a53d59f5d8676adbbb7a22d08cf88"
] | [
"social_learning.py"
] | [
"import numpy as np\nimport torch\nimport nn\nfrom parameters import *\nfrom generate_data import *\nimport matplotlib.pyplot as plt\n\n#%%\n\ndef generate_sc_graph(num_agents):\n '''\n Generate strongly connected graph.\n\n Parameters\n ----------\n num_agents: int\n number of agents\n\n R... | [
[
"numpy.array",
"numpy.random.choice",
"numpy.log",
"numpy.sum",
"numpy.eye"
]
] |
bGhorbani/linearized_neural_networks | [
"a6d987d960988595ec1e5ec69e211535f1d4921b"
] | [
"NTK_Kernel_Gen.py"
] | [
"\"\"\"\r\nThis code implements functionalities required for computing the NT Kernel for multi-layer\r\nfully-connected neural networks. The computed kernels are saved to the disk. \r\n\r\nThe code is written for Python 3.6. \r\n\r\nInputs: \r\n\tnoise_id: The index of the noise intensity: valid range 0 to 14.\r\n\... | [
[
"numpy.int",
"numpy.save",
"numpy.zeros"
]
] |
Bhavay192/GANmapper | [
"e059e8485c280d51b70dcfad7fb9c9d1324a9217"
] | [
"options/base_options.py"
] | [
"import argparse\nimport os\nfrom util import util\nimport torch\nimport models\nimport data\n\n\nclass BaseOptions():\n \"\"\"This class defines options used during both training and test time.\n\n It also implements several helper functions such as parsing, printing, and saving the options.\n It also gat... | [
[
"torch.cuda.set_device"
]
] |
DrPanigrahi/RoboND-Perception-Project | [
"5d755c4a82ef4f7e4bc99c836ae5e03dbda03dcd"
] | [
"sensor_stick/scripts/kmeans_clustering.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport cv2\n\n# Define a function to generate clusters\ndef cluster_gen(n_clusters, pts_minmax=(10, 100), x_mult=(1, 4), y_mult=(1, 3), \n x_off=(0, 50), y_off=(0, 50)):\n \n # n_clusters = number of clusters to generate\n # pts_minmax = ... | [
[
"numpy.max",
"numpy.concatenate",
"numpy.zeros_like",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"numpy.min",
"numpy.random.randn",
"matplotlib.pyplot.figure",
"numpy.random.randint",
"matplotlib.pyplot.s... |
alvii147/stumpy | [
"5f192a0a41fbb44f144cc4b676d525f19aaeaa98"
] | [
"stumpy/stump.py"
] | [
"# STUMPY\n# Copyright 2019 TD Ameritrade. Released under the terms of the 3-Clause BSD license.\n# STUMPY is a trademark of TD Ameritrade IP Company, Inc. All rights reserved.\n\nimport logging\n\nimport numpy as np\nfrom numba import njit, prange\nimport numba\n\nfrom . import core, config\nfrom .aamp import aamp... | [
[
"numpy.full",
"numpy.ceil",
"numpy.dot",
"numpy.empty",
"numpy.arange",
"numpy.sqrt",
"numpy.abs"
]
] |
rmst/rlrd | [
"05a5329066dcabfb7278ec8745890bc2e7edce15"
] | [
"rlrd/dcac.py"
] | [
"# Delay Correcting Actor-Critic\n\nfrom copy import deepcopy\nfrom dataclasses import dataclass\nfrom functools import reduce\nimport torch\nfrom torch.nn.functional import mse_loss\nimport rlrd.sac\nfrom rlrd.memory import TrajMemoryNoHidden\nfrom rlrd.nn import no_grad, exponential_moving_average\nfrom rlrd.util... | [
[
"torch.zeros",
"torch.stack",
"torch.min",
"torch.max",
"torch.no_grad",
"torch.ones",
"torch.nn.functional.mse_loss",
"torch.where"
]
] |
aadland6/OutlierScores | [
"9044b4638f0383429d2ce67a893a4c8daceef7f1"
] | [
"outlier_detection.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Oct 16 08:15:33 2017\n\n@author: maadland\n\"\"\"\nimport pandas as pd\nimport numpy as np\nfrom sklearn.datasets import load_digits\nfrom sklearn.decomposition import PCA\nfrom sklearn.ensemble import IsolationForest\nfrom sklearn.neighbors.lof import LocalOutlierFa... | [
[
"numpy.random.RandomState",
"numpy.median",
"numpy.percentile",
"sklearn.neighbors.lof.LocalOutlierFactor",
"sklearn.ensemble.IsolationForest",
"numpy.abs",
"pandas.concat",
"pandas.read_csv",
"sklearn.decomposition.PCA"
]
] |
Weakcat/Reinforcement-Learning | [
"9368e13571480053a58f40f3b4fbe5b94927f3bc"
] | [
"chapter06/cliff_walking.py"
] | [
"#######################################################################\n# Copyright (C) #\n# 2016-2018 Shangtong Zhang(zhangshangtong.cpp@gmail.com) #\n# 2016 Kenta Shimada(hyperkentakun@gmail.com) #\n# Permission given to m... | [
[
"matplotlib.use",
"numpy.max",
"numpy.random.binomial",
"numpy.random.choice",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"numpy.c... |
colinpoler/case-name-changer | [
"e3cd3880607f2eacb567e97188f04da7b2728f3e"
] | [
"nameutils.py"
] | [
"import re\nimport pandas as pd\nimport json\nimport random\nfrom functools import partial\n\n# Tzioumis, Konstantinos (2018) Demographic aspects of first names, Scientific Data, 5:180025 [dx.doi.org/10.1038/sdata.2018.25].\nfirstnames=pd.read_csv('firstnames.csv')\n# https://github.com/fivethirtyeight/data/tree/ma... | [
[
"pandas.read_csv"
]
] |
BU-Lisp/ogb | [
"882786c0b71f5c836275c03b8554ad919bfe34e4",
"1d6dde8080261931bc6ce2491e9149298af1ea98"
] | [
"examples/linkproppred/wikikg2/run.py",
"examples/graphproppred/code/main_pyg.py"
] | [
"#!/usr/bin/python3\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport argparse\nimport json\nimport logging\nimport os\nimport re\nimport random\n\nimport numpy as np\nimport torch\n\nfrom torch.utils.data import DataLoader\n\nfrom model impo... | [
[
"numpy.concatenate",
"numpy.full",
"numpy.array",
"torch.load"
],
[
"torch.device",
"numpy.array",
"torch.cat",
"torch.argmax",
"numpy.sum",
"torch.save",
"torch.no_grad",
"torch.cuda.is_available",
"torch.nn.CrossEntropyLoss"
]
] |
OsmanMalik/TM-GCN | [
"275d057a7261d8e6b544dad66b7daa7943d11c4f",
"275d057a7261d8e6b544dad66b7daa7943d11c4f"
] | [
"TM-GCN-master/experiment_amlsim_baseline.py",
"TM-GCN-master/embedding_help_functions.py"
] | [
"# This version of the amlsim experiment imports data preprocessed in Matlab, and uses the GCN baseline\n\n# Imports and aliases\nimport pickle\nimport torch as t\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision\nimport torchvision.datasets as datasets\nimport numpy as np\nimport matplotl... | [
[
"numpy.max",
"torch.Size",
"torch.zeros",
"torch.argmax",
"numpy.zeros",
"torch.no_grad",
"scipy.io.loadmat",
"torch.tensor",
"torch.sparse.sum",
"torch.nn.CrossEntropyLoss",
"torch.sum"
],
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.SELU",
"torch.nn... |
NuriaValls/PSO-2RW-Applications | [
"129b75ec72fcb32bc9bf43c0ad3bf55c44423092"
] | [
"Base_PSO/Visualization/boxplot.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\n\nfile1 = open('parabola.txt')\nfile2 = open('ackley.txt')\nfile3 = open('mmaxmmin.txt')\nfile4 = open('rosenbrock.txt')\n\n\nit1 = []\nit2 = []\nit3 = []\nit4 = []\np = 0\n\nfor line in file1:\n aux = line.rstrip('\\n').split(' ')\n it1.append(int(aux[2... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
ytchx1999/MAXP_DGL_Graph | [
"01ea0dc3e6f957b8c7a9b6958df02559f1866b32"
] | [
"gnn/utils.py"
] | [
"# -*- coding:utf-8 -*-\n\n\"\"\"\n Utilities to handel graph data\n\"\"\"\n\nimport os\nimport dgl\nimport pickle\nimport numpy as np\nimport torch as th\nfrom ogb.nodeproppred import DglNodePropPredDataset\n\n\ndef load_dgl_graph(base_path):\n \"\"\"\n 读取预处理的Graph，Feature和Label文件，并构建相应的数据供训练代码使用。\n\n ... | [
[
"torch.from_numpy"
]
] |
wangzhen263/allennlp | [
"309b2b572aeb0677511b4f972281ac265d7477a9"
] | [
"allennlp/nn/cov_beam_search.py"
] | [
"from typing import List, Callable, Tuple, Dict\nimport warnings\n\nimport torch\nimport ipdb\n\nfrom allennlp.common.checks import ConfigurationError\n\n\nStateType = Dict[str, torch.Tensor] # pylint: disable=invalid-name\nStepFunctionType = Callable[[torch.Tensor, StateType], Tuple[torch.Tensor, StateType]] # p... | [
[
"torch.isfinite",
"torch.where"
]
] |
huuthieu/pytorch-yolov4-tiny | [
"fac82da75e161221af74b56242272a42cf64c17e"
] | [
"utils/utils_bbox.py"
] | [
"import torch\r\nimport torch.nn as nn\r\nfrom torchvision.ops import nms\r\nimport numpy as np\r\n\r\nclass DecodeBox():\r\n def __init__(self, anchors, num_classes, input_shape, anchors_mask = [[6,7,8], [3,4,5], [0,1,2]]):\r\n super(DecodeBox, self).__init__()\r\n self.anchors = anchors\r\... | [
[
"numpy.concatenate",
"torch.sigmoid",
"numpy.array",
"torch.cat",
"torch.max",
"numpy.min",
"torch.linspace",
"torch.Tensor",
"torch.exp"
]
] |
yzh211/pgmpy | [
"f3abe04abb75db9f51f333ecf9429a8700477b55",
"f3abe04abb75db9f51f333ecf9429a8700477b55"
] | [
"pgmpy/tests/test_factors/test_continuous/test_Canonical_Factor.py",
"pgmpy/sampling/HMC.py"
] | [
"import unittest\n\nimport numpy as np\nimport numpy.testing as np_test\n\nfrom pgmpy.factors.distributions import GaussianDistribution as JGD\nfrom pgmpy.factors.continuous import CanonicalDistribution\n\n\nclass TestCanonicalFactor(unittest.TestCase):\n def test_class_init(self):\n phi = CanonicalDistri... | [
[
"numpy.testing.assert_almost_equal",
"numpy.array",
"numpy.testing.assert_array_equal"
],
[
"numpy.dot",
"numpy.random.rand",
"numpy.log",
"numpy.zeros",
"numpy.exp"
]
] |
inonchiu/PyMaG | [
"ca6146cd354fd35be1eb21669bf505ff1acd3cb5"
] | [
"pymag/utils/matching.py"
] | [
"#!/usr/bin/env python\n\n##################################\n#\n# Utils for PyMag\n#\n##################################\n\nimport numpy as np\nfrom math import *\n\ntry:\n from scipy.spatial import cKDTree as KDT\nexcept ImportError:\n from scipy.spatial import KDTree as KDT\n\n\n\n# ---\n# matching unique ... | [
[
"numpy.array",
"numpy.random.random_integers",
"numpy.sum",
"numpy.shape",
"scipy.spatial.KDTree",
"numpy.arange",
"numpy.in1d"
]
] |
LSSTDESC/firecrown | [
"646c15809b48a528a833d2bef3b180b91c3af189"
] | [
"firecrown/ccl/sources/sources.py"
] | [
"import numpy as np\nfrom scipy.interpolate import Akima1DInterpolator\n\nimport pyccl as ccl\n\nfrom ..core import Source\nfrom ..systematics import IdentityFunctionMOR, TopHatSelectionFunction\n\n\n__all__ = ['WLSource', 'NumberCountsSource', 'ClusterSource', 'CMBLSource']\n\n\nclass WLSource(Source):\n \"\"\"... | [
[
"scipy.interpolate.Akima1DInterpolator",
"numpy.ones_like",
"numpy.argsort"
]
] |
mfrasquet/valenbisi | [
"1af47664bef31df7469645e83f32fd007b2f23d8"
] | [
"plot1.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Oct 9 19:53:39 2019\n\n@author: miguel\n\"\"\"\nimport pandas as pd\nfrom datetime import datetime\nimport matplotlib.pyplot as plt \n\n\ndata=pd.read_csv('bikes.csv', sep='\\t',index_col=False)\n\n\nweek_day=[]\nfor i in range(0,len(data)):\... | [
[
"matplotlib.pyplot.scatter",
"pandas.read_csv",
"matplotlib.pyplot.subplots"
]
] |
BigDataArchitecture/Assignment1 | [
"98c02762c4927cef26a17e55533e94b34671c519"
] | [
"notebooks/eie-sevir/sevir/utils_pytorch.py"
] | [
"import os\nimport numpy as np\nimport pandas as pd\nimport h5py\n\nfrom torch.utils.data import Dataset\nfrom torch.utils.data import DataLoader\n\nos.environ[\"HDF5_USE_FILE_LOCKING\"] = 'FALSE'\nTYPES = ['vis', 'ir069', 'ir107', 'vil', 'lght']\nDEFAULT_CATALOG = '/home/gridsan/groups/EarthIntelligence/datasets/S... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.reshape",
"numpy.zeros",
"pandas.DataFrame",
"numpy.logical_and",
"numpy.digitize",
"numpy.prod",
"numpy.arange",
"torch.utils.data.DataLoader",
"numpy.logical_or.reduce",
"numpy.logical_and.reduce",
"numpy.unique",
... |
siduojiang/BERTVision | [
"01519bea0882fa72e86a1b62f2d0d52d22c26dfc"
] | [
"code/torch/common/trainers/H5_glue_trainer.py"
] | [
"# packages\nimport os, sys, datetime\nsys.path.append(\"C:/BERTVision/code/torch\")\nfrom common.evaluators.H5_glue_evaluator import H5_GLUE_Evaluator\nfrom utils.collate import collate_H5_GLUE\nfrom torch.cuda.amp import autocast\nimport torch\nfrom torch.utils.data import DataLoader\nfrom tqdm.auto import tqdm\n... | [
[
"torch.save",
"torch.cuda.amp.autocast",
"torch.utils.data.DataLoader"
]
] |
mkitti/napari | [
"4e954d30b5a1b70c5e495db1b8f48a3bdda1ff86",
"4e954d30b5a1b70c5e495db1b8f48a3bdda1ff86"
] | [
"napari/layers/points/_tests/test_points.py",
"napari/conftest.py"
] | [
"from copy import copy\nfrom itertools import cycle, islice\n\nimport numpy as np\nimport pandas as pd\nimport pytest\nfrom vispy.color import get_colormap\n\nfrom napari._tests.utils import check_layer_world_data_extent\nfrom napari.layers import Points\nfrom napari.layers.points._points_utils import points_to_squ... | [
[
"numpy.concatenate",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.add",
"numpy.empty",
"numpy.asarray",
"numpy.repeat",
"numpy.testing.assert_equal",
"numpy.random.seed",
"pandas.DataFrame",
"numpy.ix_",
"numpy.random.randint",
"numpy.unique",
"num... |
culebron/erde | [
"9bbaaa1df46629a182c355413a120aa33dc6b377"
] | [
"tests/utils/test_utils.py"
] | [
"import geopandas as gpd\nimport pytest\nfrom erde import utils, read_df\nfrom erde.op import sjoin, buffer\nfrom shapely import wkt\nfrom shapely.geometry import LineString\n\npl1 = wkt.loads('LINESTRING (82.956142 55.050099,83.174036 54.923359,83.019111 54.845166,82.801218 54.963546,82.913163 55.043800,83.124060 ... | [
[
"numpy.radians"
]
] |
akern40/pyro | [
"8633b7136946ab2ae2e16062503fe51c2aac8c38"
] | [
"pyro/distributions/transforms/planar.py"
] | [
"# Copyright (c) 2017-2019 Uber Technologies, Inc.\n# SPDX-License-Identifier: Apache-2.0\n\nimport math\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.distributions import Transform, constraints\n\nfrom pyro.distributions.conditional import ConditionalTransformModule\nfrom pyro... | [
[
"torch.Tensor",
"torch.nn.functional.softplus"
]
] |
ahjeongseo/MASN---Attend-What-You-Need-Motion-Appearance-Synergistic-Networks-for-Video-Question-Answering | [
"5ca3fc80cf37f7b6124070b1aae5bc599db8fa29"
] | [
"embed_loss.py"
] | [
"# --------------------------------------------------------\n# This code is modified from Jumpin2's repository.\n# https://github.com/Jumpin2/HGA\n# --------------------------------------------------------\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n# __all__ = ['MultipleChoiceLoss', ... | [
[
"torch.tensor",
"torch.max"
]
] |
ZivonZhang/mmdetection | [
"81272a42e606e5ab9d2ec13e91a39e31f78a61b4"
] | [
"mmdet/apis/inference.py"
] | [
"import mmcv\nimport numpy as np\nimport pycocotools.mask as maskUtils\nimport torch\n\nfrom mmdet.core import get_classes\nfrom mmdet.datasets import to_tensor\nfrom mmdet.datasets.transforms import ImageTransform\n\n\ndef _prepare_data(img, img_transform, cfg, device):\n ori_shape = img.shape\n img, img_sha... | [
[
"numpy.concatenate",
"numpy.full",
"torch.no_grad",
"numpy.where",
"numpy.random.randint",
"numpy.vstack"
]
] |
RaphaelDELAIR/traffic | [
"47591f39f83e22aff65ae06987bce238cd2dd353",
"47591f39f83e22aff65ae06987bce238cd2dd353",
"47591f39f83e22aff65ae06987bce238cd2dd353"
] | [
"traffic/core/traffic.py",
"traffic/core/flight.py",
"traffic/algorithms/navigation.py"
] | [
"import logging\nimport warnings\nfrom datetime import timedelta\nfrom pathlib import Path\nfrom typing import (\n TYPE_CHECKING,\n Any,\n Callable,\n Dict,\n Iterable,\n Iterator,\n List,\n Optional,\n Set,\n Type,\n TypeVar,\n Union,\n overload,\n)\n\nimport pandas as pd\nim... | [
[
"pandas.DataFrame.from_records",
"pandas.concat"
],
[
"pandas.to_datetime",
"numpy.pad",
"pandas.Timedelta",
"numpy.ones",
"numpy.where",
"numpy.radians",
"numpy.stack",
"numpy.timedelta64",
"pandas.Series",
"numpy.nanmax"
],
[
"pandas.Timestamp",
"n... |
Gantulga9480/py2048 | [
"4a1f9efab9fab4ab6c77232e2d74eaa326446e57"
] | [
"py2048/game_core.py"
] | [
"import numpy as np\nimport random\nimport copy\n\nUP = 0\nDOWN = 1\nLEFT = 2\nRIGHT = 3\nUNDO = 4 # Experimantal\nACTION_SPACE = 5 # 5 for +UNDO\nINPLACE = 5 # For animation\n\n\nclass Node:\n\n def __init__(self, value) -> None:\n self.value = value\n\n def __eq__(self, __o: object) -> bool:\n ... | [
[
"numpy.zeros"
]
] |
gilbertmike/tugofwar-horserace | [
"504f9129dee1fec88daf3bcbf3714fec3db215cf"
] | [
"tugofwar_horserace/horserace.py"
] | [
"import numpy as np\n\nclass HorseRace:\n def __init__(self, quality_1: float, quality_2: float, thres: int):\n \"\"\"Creates a new simulation instance with two options with qualities\n `quality_1` and `quality_2`. Decision is made when threshold `thres`\n is reached.\n\n Every simula... | [
[
"numpy.random.rand",
"numpy.zeros",
"numpy.exp",
"numpy.logical_and",
"numpy.all"
]
] |
2360673637/AIGames | [
"7d149cc2cff8fa626ee1c9e1ad7c39e1a724a5bb"
] | [
"AIPong/Algorithm_1/main.py"
] | [
"'''\n主函数\n作者: Charles\n公众号: Charles的皮卡丘\n'''\nimport config\nimport tensorflow as tf\nfrom nets.qNet import DQN\n\n\ndef main():\n\tsession = tf.InteractiveSession()\n\tDQN(config.options).train(session)\n\n\nif __name__ == '__main__':\n\tmain()"
] | [
[
"tensorflow.InteractiveSession"
]
] |
manivaradarajan/tensorflow | [
"8ec19e0f48b0bfb74f67bd37c4c1ae2bce1d10f3"
] | [
"tensorflow/python/keras/metrics.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.array_ops.identity",
"tensorflow.python.ops.math_ops.equal",
"tensorflow.python.keras.utils.generic_utils.serialize_keras_object",
"tensorflow.python.keras.utils.tf_utils.is_tensor_or_variable",
"tensorflow.python.ops.math_ops.minimum",
"tensorflow.python.framework.o... |
anushkaray/mmsegmentation | [
"07cb3b809d59bd72cc11afd6a9ce96215e9aaf96"
] | [
"mmseg/apis/train.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport random\nimport warnings\n\nimport mmcv\nimport numpy as np\nimport torch\nimport torch.distributed as dist\nfrom mmcv.parallel import MMDataParallel, MMDistributedDataParallel\nfrom mmcv.runner import HOOKS, build_optimizer, build_runner, get_dist_info\nfrom ... | [
[
"torch.cuda.manual_seed_all",
"numpy.random.seed",
"torch.cuda.current_device",
"torch.manual_seed",
"torch.cuda.is_available",
"numpy.random.randint",
"torch.tensor",
"torch.distributed.broadcast"
]
] |
zabop/lightkurve | [
"d9c4c40f846aae7cb138e8943950058de3ffd8e7"
] | [
"lightkurve/interact_bls.py"
] | [
"\"\"\"This module provides helper functions for the `LightCurve.interact_bls()` feature.\"\"\"\nimport logging\nimport warnings\nimport numpy as np\nfrom astropy.convolution import convolve, Box1DKernel\n\nlog = logging.getLogger(__name__)\n\n# Import the optional AstroPy dependency, or print a friendly error othe... | [
[
"numpy.max",
"numpy.median",
"numpy.round",
"numpy.min",
"numpy.nanmin",
"numpy.nanargmax",
"numpy.argmax",
"numpy.sort",
"numpy.isfinite",
"numpy.argsort",
"numpy.log10",
"numpy.nanmax"
]
] |
RedHeadM/CCT | [
"bece91e7d2f84de96b0975aed12ef64bff833565"
] | [
"base/base_dataset.py"
] | [
"import random, math\nimport numpy as np\nimport cv2\nimport torch\nimport torch.nn.functional as F\nfrom torch.utils.data import Dataset\nfrom PIL import Image\nfrom torchvision import transforms\nfrom scipy import ndimage\nfrom math import ceil\n\nclass BaseDataSet(Dataset):\n def __init__(self, data_dir, spli... | [
[
"numpy.array",
"numpy.uint8",
"numpy.fliplr"
]
] |
VidushB/Housing-Price-Prediction-with-feature-selection-and-linear-regression | [
"929dccf63d760e5ace3b74ed564014d80b674719"
] | [
"model.py"
] | [
"from sklearn.linear_model import LinearRegression\nfrom sklearn.model_selection import train_test_split\nmodel = LinearRegression()\nX=df_train.drop(\"SalePrice\",axis=1)\ny = df_train['SalePrice'].reset_index(drop = True)\nX_train, X_val, y_train, y_val = train_test_split(X, y, test_size=0.33, random_state=42)\nm... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.metrics.mean_squared_error",
"sklearn.linear_model.LinearRegression"
]
] |
robagar/teasneeze | [
"cff6a01de992162f69590decd935dedbcd2145c7"
] | [
"test/digits/collect_data.py"
] | [
"import json\nfrom itertools import count\nimport numpy as np\nfrom sklearn.datasets import load_digits\n\ncounters = []\nfor i in range(10):\n counters.append(count())\n\ndef make_entry(td):\n t,d = td\n i = next(counters[t])\n return {\n 'classification': str(t),\n 'image_path': 'images/... | [
[
"sklearn.datasets.load_digits"
]
] |
woffett/pytorch-image-models | [
"d6ac5bbc481271efecee8bc8756caa864a253fdd"
] | [
"train.py"
] | [
"\nimport argparse\nimport time\nimport logging\nfrom datetime import datetime\n\ntry:\n from apex import amp\n from apex.parallel import DistributedDataParallel as DDP\n from apex.parallel import convert_syncbn_model\n has_apex = True\nexcept ImportError:\n from torch.nn.parallel import DistributedD... | [
[
"torch.distributed.get_world_size",
"torch.cuda.synchronize",
"torch.nn.SyncBatchNorm.convert_sync_batchnorm",
"torch.distributed.init_process_group",
"torch.no_grad",
"torch.nn.parallel.DistributedDataParallel",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.distributed.... |
ParkerLab/PillowNet | [
"b511c38d62e6b847d6fe0bd9ef855dc458d94b91"
] | [
"predict.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nScript for generating predictions from a trained model.\nUse `predict.py -h` to see an auto-generated description of advanced options.\n\"\"\"\n\nimport argparse\nimport numpy as np\n\nfrom keras.models import load_model\nfrom tqdm import tqdm, trange\nimport pybedtools as pbt\nimpor... | [
[
"numpy.array",
"numpy.arange",
"numpy.zeros"
]
] |
moneypi/SSD-pytorch | [
"25dc91db133a3575d656b2df68ffdf4ef1135233"
] | [
"utils/augmentations.py"
] | [
"import torch\nfrom torchvision import transforms\nimport cv2\nimport numpy as np\nimport types\nfrom numpy import random\n\n\ndef intersect(box_a, box_b):\n max_xy = np.minimum(box_a[:, 2:], box_b[2:])\n min_xy = np.maximum(box_a[:, :2], box_b[:2])\n inter = np.clip((max_xy - min_xy), a_min=0, a_max=np.in... | [
[
"numpy.array",
"numpy.random.choice",
"numpy.minimum",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.clip",
"numpy.maximum"
]
] |
DataverseLabs/pyinterpolate | [
"5e0caf0fd839324932918bb50bf0464fffbefb78"
] | [
"pyinterpolate/test/transform/test_prepare_kriging_data.py"
] | [
"import unittest\nimport numpy as np\nfrom pyinterpolate.transform.prepare_kriging_data import prepare_kriging_data\n\n\nclass TestPrepareKrigingData(unittest.TestCase):\n\n def test_prepare_kriging_data(self):\n EXPECTED_NUMBER_OF_NEIGHBORS = 1\n EXPECTED_OUTPUT = np.array([[13, 10, 9, 3]])\n ... | [
[
"numpy.array",
"numpy.array_equal"
]
] |
ArthurMor4is/grad-cam-covid-19-ct | [
"14474a635e7633c8382839582d2a2cd9ff98eb62"
] | [
"my_functions.py"
] | [
"import os\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow import keras\nimport matplotlib.pyplot as plt\nimport tensorflow_datasets as tfds\nfrom tensorflow.keras import layers\nimport matplotlib.cm as cm\nimport random\nimport glob\nfrom skimage.segmentation import chan_vese\nfrom shutil import copy... | [
[
"tensorflow.keras.preprocessing.image.load_img",
"numpy.true_divide",
"tensorflow.keras.preprocessing.image.array_to_img",
"numpy.uint8",
"tensorflow.GradientTape",
"tensorflow.argmax",
"tensorflow.squeeze",
"numpy.arange",
"matplotlib.pyplot.axis",
"numpy.expand_dims",
... |
JoshDumo/qiskit-terra | [
"6a2602a9ecf9b1a3345de1516b873ac7b3da587f"
] | [
"test/python/circuit/test_circuit_properties.py"
] | [
"# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2017, 2018.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\n#\n# Any modificatio... | [
[
"numpy.int64"
]
] |
JackLonergan97/SOLikeT | [
"314fe3df3a3ccdda69a2b1142b433c5dd5997e44"
] | [
"soliket/gaussian.py"
] | [
"import numpy as np\nfrom typing import Optional, Sequence\n\nfrom cobaya.likelihood import Likelihood\nfrom cobaya.input import merge_info\nfrom cobaya.tools import recursive_update\n# from cobaya.conventions import empty_dict\n\nfrom collections import namedtuple\nfrom types import MappingProxyType\nempty_dict = ... | [
[
"numpy.loadtxt",
"numpy.load"
]
] |
yanhann10/afprop | [
"e7ebf8541d5224f417eb4e9209cf5012ebfe78b7"
] | [
"tests/test_afprop.py"
] | [
"import numpy as np\nimport pandas as pd\nimport pytest\nfrom afprop import afprop_vec\n\n\n# sample data with clusters for testing\nC1 = np.random.multivariate_normal(mean=[0, 0], cov=np.eye(2), size=30)\nC2 = np.random.multivariate_normal(mean=[4, 4], cov=np.eye(2), size=30)\nmydata = np.r_[C1, C2]\n\n\ndef test_... | [
[
"numpy.eye"
]
] |
dani-lbnl/chainercv | [
"223fab7dd0045d57db02041d44368fe3e60ea433"
] | [
"chainercv/datasets/cityscapes/cityscapes_semantic_segmentation_dataset.py"
] | [
"import glob\nimport os\n\nimport numpy as np\n\nfrom chainer import dataset\nfrom chainer.dataset import download\nfrom chainercv.datasets.cityscapes.cityscapes_utils import cityscapes_labels\nfrom chainercv.utils import read_image\n\n\nclass CityscapesSemanticSegmentationDataset(dataset.DatasetMixin):\n\n \"\"... | [
[
"numpy.ones"
]
] |
faheemali1997/SelfDrivingCar | [
"386cdaa063d51dab0409a114fa4b8a3a26b22302"
] | [
"pyipcam.py"
] | [
"import cv2\nimport urllib2\nimport numpy as np\nimport sys\n\nhost = \"192.168.0.220:8080\"\nif len(sys.argv)>1:\n host = sys.argv[1]\n\nhoststr = 'http://' + host + '/video'\nprint ('Streaming ' + hoststr)\n\nstream=urllib2.urlopen(hoststr)\n\nbytes=''\nwhile True:\n bytes+=stream.read(1024)\n a = bytes.... | [
[
"numpy.fromstring"
]
] |
NeerajBhadani/tensorflow | [
"8c849c65503fef22f49f7ab843803fca9c439bdf"
] | [
"tensorflow/python/framework/sparse_tensor_test.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.ops.sparse_ops.sparse_tensor_dense_matmul",
"tensorflow.python.framework.sparse_tensor.is_sparse",
"numpy.array",
"tensorflow.python.eager.context.graph_mode",
"tensorflow.python.platform.googletest.main",
"tensorflow.python.framework.tensor_shape.TensorShape",
"tens... |
scottrdavid/landlab | [
"bb8414df55b4e5fb9198468fadbe3c725ef60601"
] | [
"tests/io/shapefile/test_infer_dtype.py"
] | [
"import hypothesis.extra.numpy as hynp\nimport numpy as np\nimport pytest\nfrom hypothesis import assume, given\nfrom hypothesis.strategies import integers\nfrom numpy.testing import assert_array_equal\n\nfrom landlab.io.shapefile.read_shapefile import _infer_data_type\n\n\n@pytest.mark.parametrize(\"src_type\", [n... | [
[
"numpy.testing.assert_array_equal",
"numpy.asarray",
"numpy.issubdtype"
]
] |
bh107/bohrium | [
"5b83e7117285fefc7779ed0e9acb0f8e74c7e068"
] | [
"bridge/npbackend/bohrium/contexts.py"
] | [
"\"\"\"\nBohrium Contexts\n================\n\"\"\"\nimport sys\nimport os\nfrom . import backend_messaging as messaging\n\n\nclass EnableBohrium:\n \"\"\"Enable Bohrium within the context\"\"\"\n\n def __init__(self):\n # In order to avoid complications, we import common libraries BEFORE enabling Bohr... | [
[
"matplotlib.use"
]
] |
BraunPenguin/InstanceSegmentation-Detectron2 | [
"f26036bffa96901f55f2bbc2fcbdf77839bd5161"
] | [
"Utility/AnalyzeTiltInstance.py"
] | [
"import sys\nimport os\nimport pickle\nimport joblib\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as mpatches\nfrom shapely.geometry import Point, LineString, MultiLineString, Polygon\nfrom shapely.strtree import STRtree\nfrom shapely import affinity\nfrom skimage.measure import l... | [
[
"numpy.max",
"numpy.array",
"numpy.ceil",
"numpy.asarray",
"matplotlib.pyplot.autoscale",
"numpy.rad2deg",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure",
"numpy.linspace",
"numpy.mean",
"numpy.std",
"matplotlib.pyplot.scatter... |
dmitryvinn/pytext | [
"43373462d1b9bada3ba02072aed78338d3bb3a12"
] | [
"pytext/models/representations/transformer/luna_sentence_encoder.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\nimport math\nfrom typing import Callable, Optional\n\nimport torch\nfrom fairseq import utils\nfrom fairseq.modules import LayerNorm, PositionalEmbedding, LayerDropModuleList\nfrom fairseq.modules.fairseq_dropout impo... | [
[
"torch.nn.Linear",
"torch.zeros",
"torch.cos",
"torch.nn.ModuleList",
"torch.arange",
"torch.sin",
"torch.nn.init.normal_",
"torch.Tensor",
"torch.nn.Embedding"
]
] |
me-manu/fastespy | [
"7bf1fef68239c7d69c0917a51f24d48e9ad14728",
"7bf1fef68239c7d69c0917a51f24d48e9ad14728"
] | [
"fastespy/io/rootdata.py",
"fastespy/mlkeras/models.py"
] | [
"from __future__ import absolute_import, division, print_function\nimport ROOT as root\nimport glob\nimport os\nimport numpy as np\nimport time\nimport logging\n\n\ndef readgraph(directory, split = '-', overwrite = False, inputid = 'in', prefix = ''):\n \"\"\"\n Read data from a ROOT graph and save as numpy n... | [
[
"numpy.full",
"numpy.zeros",
"numpy.load",
"numpy.save",
"numpy.savez"
],
[
"numpy.exp",
"tensorflow.keras.metrics.FalsePositives",
"tensorflow.keras.Sequential",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.losses.BinaryCrossentropy",
"numpy.log",
"tensor... |
spyroot/shapenet | [
"31b95f25beff5129e0db31e798719ba555661685"
] | [
"shapegnet/model_config.py"
] | [
"# Graph Generator Model Configurator\n#\n# All trainer parameters abstracted in separate entity.\n#\n# - Trainer , Evaluator and the rest this class to configurator and store data.\n# It read yaml config file that users passes either as file name or io.string.\n#\n# Mustafa B\nimport os\nimport sys\nfrom os i... | [
[
"torch.cuda.is_available",
"torch.utils.tensorboard.SummaryWriter",
"torch.load"
]
] |
kristofgiber/lingvo | [
"4c6405a3c8b29764918dbfb599212dd7620ccf9c",
"4c6405a3c8b29764918dbfb599212dd7620ccf9c"
] | [
"lingvo/core/layers_test.py",
"lingvo/core/recurrent_test.py"
] | [
"# Lint as: python2, python3\n# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/... | [
[
"numpy.square",
"numpy.random.normal",
"numpy.array",
"numpy.array_repr",
"numpy.random.rand",
"numpy.asarray",
"numpy.zeros",
"numpy.random.seed",
"numpy.sum",
"numpy.ones",
"tensorflow.python.framework.ops.reset_default_graph",
"numpy.random.randint",
"numpy.a... |
guruprasaad123/all_dl_projects | [
"04c869f7f001ef94c467740260663d91a34815e0"
] | [
"GTSRB/init.py"
] | [
"# The German Traffic Sign Recognition Benchmark\n#\n# sample code for reading the traffic sign images and the\n# corresponding labels\n#\n# example:\n#\n# trainImages, trainLabels = readTrafficSigns('GTSRB/Training')\n# print len(trainLabels), len(trainImages)\n# plt.imshow(trainImages[42])\n# plt.show()\n#\n# hav... | [
[
"numpy.array"
]
] |
sibeshkar/jiminy | [
"7754f86fb0f246e7d039ea0cbfd9950fcae4adfb"
] | [
"jiminy/gym/envs/box2d/car_racing.py"
] | [
"import sys, math\nimport numpy as np\n\nimport Box2D\nfrom Box2D.b2 import (edgeShape, circleShape, fixtureDef, polygonShape, revoluteJointDef, contactListener)\n\nimport jiminy.gym as gym\nfrom jiminy.gym import spaces\nfrom jiminy.gym.envs.box2d.car_dynamics import Car\nfrom jiminy.gym.utils import colorize, see... | [
[
"numpy.square",
"numpy.array",
"numpy.linalg.norm",
"numpy.sign",
"numpy.fromstring"
]
] |
LoopTilingBenchmark/benchmark | [
"52a3d2e70216552a498fd91de02a2fa9cb62122c"
] | [
"ppo/baselines/common/tests/test_doc_examples.py"
] | [
"import pytest\ntry:\n import mujoco_py\n _mujoco_present = True\nexcept BaseException:\n mujoco_py = None\n _mujoco_present = False\n\n\n@pytest.mark.skipif(\n not _mujoco_present,\n reason='error loading mujoco - either mujoco / mujoco key not present, or LD_LIBRARY_PATH is not pointing to mujoc... | [
[
"tensorflow.Session",
"tensorflow.global_variables_initializer"
]
] |
chenzhihan2020/bert | [
"52883d912d1a626d9462a0c2d974761ae5b159e1"
] | [
"run_squad_final.py"
] | [
"# coding=utf-8\r\n# Copyright 2018 The Google AI Language Team Authors.\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE... | [
[
"tensorflow.contrib.tpu.TPUEstimatorSpec",
"tensorflow.data.TFRecordDataset",
"tensorflow.train.Features",
"tensorflow.contrib.tpu.TPUEstimator",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.nn.softmax",
"tensorflow.one_hot",
"tensorflow.logging.warning",
"tensorf... |
JieRen98/rlkit-pmoe | [
"5ef4e056764d2c4a8d6e4c6da89295304b1fec3f"
] | [
"rlkit/torch/sac/sac.py"
] | [
"from collections import OrderedDict\n\nimport numpy as np\nimport torch\nimport torch.optim as optim\nfrom torch import nn as nn\n\nimport rlkit.torch.pytorch_util as ptu\nfrom rlkit.core.eval_util import create_stats_ordered_dict\nfrom rlkit.torch.torch_rl_algorithm import TorchTrainer\n\n\nclass SACTrainer(Torch... | [
[
"numpy.prod",
"torch.nn.MSELoss"
]
] |
ferr26/toolMusicPlagiarism | [
"cc6985d9847ca5589b5a0792845b7e85ce80e634"
] | [
"spectClustering.py"
] | [
"import chars2vec\nimport csv\nfrom sklearn.cluster import SpectralClustering\n\n\ndef spectralClustering():\n words=[]\n\n with open('./datasetFit.csv') as csv_file:\n csv_reader = csv.reader(csv_file, delimiter=',')\n line_count = 0\n for row in csv_reader:\n if line_count ==... | [
[
"sklearn.cluster.SpectralClustering"
]
] |
agamemnonc/axopy | [
"e8c324a4ecfc0abdec3016bca62dcf84d371b6c0"
] | [
"axopy/design.py"
] | [
"\"\"\"Task design containers.\"\"\"\n\nimport numpy\nimport random\nimport pprint\n\n__all__ = ['Design', 'Block', 'Trial', 'Array']\n\n\nclass Design(list):\n \"\"\"Top-level task design container.\n\n The :class:`Design` is a list of :class:`Block` objects, which themselves\n are lists of :class:`Trial`... | [
[
"numpy.empty",
"numpy.zeros"
]
] |
ieuTeamD/pangoro | [
"b093a995e0f4624c56f399ebf563b2b66ed5b700"
] | [
"tests/test.py"
] | [
"import unittest\nfrom pangoro.preprocessing import PangoroDataFrame\nimport pandas as pd\n\n\ndef broken_function():\n raise Exception('This is broken')\n\nclass TestDataFrame(unittest.TestCase):\n def test_simple_dataframe(self):\n df1 = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})\n df2 = pd.Data... | [
[
"pandas.DataFrame",
"pandas.to_numeric"
]
] |
FrancaCassol/ctapipe | [
"1e62e6800bdd52625cc8657a8f47c7dda0bd44e0",
"1e62e6800bdd52625cc8657a8f47c7dda0bd44e0",
"1e62e6800bdd52625cc8657a8f47c7dda0bd44e0"
] | [
"ctapipe/visualization/bokeh.py",
"examples/stereo_reconstruction.py",
"ctapipe/image/tests/test_image_cleaner_component.py"
] | [
"import warnings\nimport numpy as np\nfrom bokeh.plotting import figure\nfrom bokeh.events import Tap\nfrom bokeh import palettes\nfrom bokeh.models import (\n ColumnDataSource,\n TapTool,\n Span,\n ColorBar,\n LinearColorMapper,\n)\nfrom ctapipe.utils.rgbtohex import intensity_to_hex\n\nPLOTARGS = d... | [
[
"numpy.full",
"numpy.empty",
"numpy.zeros",
"numpy.ones",
"numpy.nanmin",
"numpy.arange",
"numpy.sqrt",
"numpy.nanmax"
],
[
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"numpy.zeros_li... |
cameronaaron/unintended-ml-bias-analysis | [
"cdf3eb08398b367b4b05245b42551eb03aa848e2"
] | [
"unintended_ml_bias/model_bias_analysis.py"
] | [
"\"\"\"Analysis of model bias.\n\nWe look at differences in model scores as a way to compare bias in different\nmodels.\n\nThe functions in this file expect scored data in a data frame with columns:\n\n<text_col>: Column containing text of the example. This column name is\n passed in as a parameter of any functi... | [
[
"numpy.median",
"pandas.DataFrame",
"matplotlib.pyplot.gca",
"scipy.stats.mannwhitneyu",
"numpy.mean",
"matplotlib.pyplot.figure",
"numpy.std",
"matplotlib.pyplot.hist",
"numpy.subtract",
"pandas.concat",
"matplotlib.pyplot.show",
"numpy.linspace",
"sklearn.metr... |
ryangillard/P-CEAD | [
"d4e95fa17112af07eb99cd581470bd3146d1c8e5"
] | [
"proganomaly_modules/training_module/trainer/export_berg.py"
] | [
"# Copyright 2020 Google Inc. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appl... | [
[
"tensorflow.abs",
"tensorflow.expand_dims",
"tensorflow.math.sigmoid",
"tensorflow.ones_like",
"tensorflow.greater",
"tensorflow.math.reduce_prod",
"tensorflow.cast"
]
] |
mgomesborges/Stone-Soup | [
"39c7f02ce11e10c9b3c612ad359f6d8bca495266",
"39c7f02ce11e10c9b3c612ad359f6d8bca495266"
] | [
"stonesoup/types/tests/test_state.py",
"stonesoup/updater/tests/test_kalman.py"
] | [
"# -*- coding: utf-8 -*-\nimport datetime\n\nimport numpy as np\nimport pytest\n\nfrom ..angle import Bearing\nfrom ..array import StateVector, CovarianceMatrix\nfrom ..numeric import Probability\nfrom ..particle import Particle\nfrom ..state import State, GaussianState, ParticleState, \\\n StateMutableSequence,... | [
[
"numpy.diag",
"numpy.array_equal"
],
[
"numpy.allclose",
"numpy.linalg.inv",
"numpy.array",
"numpy.array_equal"
]
] |
lillekemiker/blmath | [
"817ebec258388e6136765a392972b0835cabce5b"
] | [
"blmath/geometry/primitives/plane.py"
] | [
"import numpy as np\nfrom blmath.numerics import vx\n\nclass Plane(object):\n '''\n A 2-D plane in 3-space (not a hyperplane).\n\n Params:\n - point_on_plane, plane_normal:\n 1 x 3 np.arrays\n '''\n\n def __init__(self, point_on_plane, unit_normal):\n if vx.almost_zero(unit_n... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.asarray",
"scipy.spatial.cKDTree",
"numpy.cov",
"numpy.delete",
"numpy.argmin",
"numpy.logical_and",
"numpy.greater_equal",
"numpy.less_equal",
"numpy.sign",
"numpy.abs",
"numpy.argsort",
"numpy.all... |
myracheng/pronear | [
"a92e97cd860900f3c535a72a1b867d8f5ad096ab"
] | [
"near_code/dsl/library_functions.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom .neural_functions import init_neural_function\n\n\n# TODO allow user to choose device\nif torch.cuda.is_available():\n device = 'cuda:0'\nelse:\n device = 'cpu'\n\nclass LibraryFunction:\n\n def __init__(self, submodules, input_type, output_type, input_size, out... | [
[
"torch.zeros",
"torch.rand",
"torch.cat",
"torch.nn.Linear",
"torch.arange",
"torch.nn.Sigmoid",
"torch.cuda.is_available",
"torch.tensor",
"torch.index_select"
]
] |
tarepan/HiPPO | [
"bc23e2dba13da6c307cb5a4ae248c2d2c56d465f"
] | [
"datasets/utils.py"
] | [
"import math\nimport numpy as np\n\nimport torch\n\n\ndef bitreversal_po2(n):\n m = int(math.log(n)/math.log(2))\n perm = np.arange(n).reshape(n,1)\n for i in range(m):\n n1 = perm.shape[0]//2\n perm = np.hstack((perm[:n1],perm[n1:]))\n return perm.squeeze(0)\n\ndef bitreversal_permutation... | [
[
"numpy.extract",
"numpy.arange",
"numpy.hstack"
]
] |
ryoyop/seldon-core | [
"83717e88717a4030d7f76f87c3a3b713cd73d276"
] | [
"python/seldon_core/seldon_methods.py"
] | [
"import logging\nimport os\nfrom typing import Any, Dict, List, Tuple, Union\n\nimport numpy as np\nimport yaml\nfrom google.protobuf import json_format\n\nfrom seldon_core.flask_utils import SeldonMicroserviceException\nfrom seldon_core.metadata import SeldonInvalidMetadataError, validate_model_metadata\nfrom seld... | [
[
"numpy.array"
]
] |
RaulAstudillo06/BOCF | [
"68d19984385cdb27c9f6c5002c67fc9467bbe705"
] | [
"GPyOpt/optimization/acquisition_optimizer.py"
] | [
"# Copyright (c) 2016, the GPyOpt Authors\n# Licensed under the BSD 3-clause license (see LICENSE.txt)\n\nfrom .optimizer import OptLbfgs, OptSGD, OptDirect, OptCma, apply_optimizer, choose_optimizer, apply_optimizer_inner\nfrom .anchor_points_generator import ObjectiveAnchorPointsGenerator, ThompsonSamplingAnchorP... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.asscalar",
"numpy.vstack",
"numpy.atleast_2d"
]
] |
shishaochen/kfac | [
"3ee1bec8dcd851d50618cd542a8d1aff92512f7c"
] | [
"kfac/python/ops/layer_collection.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.compat.v1.cast",
"tensorflow.compat.v1.colocate_with",
"tensorflow.compat.v1.get_default_graph",
"tensorflow.compat.v1.variable_scope",
"tensorflow.compat.v1.get_variable_scope",
"tensorflow.compat.v1.trainable_variables",
"tensorflow.compat.v1.sqrt",
"tensorflow.python... |
agrawalayan/R-net-1 | [
"1748d108a8248466d99cdf3c3f284619d88bcc73"
] | [
"src/generator_utils.py"
] | [
"from __future__ import print_function\nimport tensorflow as tf\nfrom tensorflow.python.ops import variable_scope\nfrom tensorflow.python.ops import nn_ops\n\ndef add_first_word_prob_to_atten_dists(in_passage_words, phrase_starts, vocab_dist, attn_dist):\n '''\n in_passage_words: [batch_size, passage_length]\... | [
[
"tensorflow.constant_initializer",
"tensorflow.python.ops.variable_scope.variable_scope",
"tensorflow.python.ops.variable_scope.get_variable",
"tensorflow.multinomial",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.zeros_like",
"tensorflow.clip_by_value",
"tensorflow.s... |
mengkai94/training | [
"2a0aa29e700a33e9d3bf2645d13d89fb525e29fc"
] | [
"object_detection/pytorch/tools/train_mlperf.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nr\"\"\"\nBasic training script for PyTorch\n\"\"\"\n\n# Set up custom environment before nearly anything else is imported\n# NOTE: this should be the first import (no not reorder)\nfrom maskrcnn_benchmark.utils.env import setup_environment #... | [
[
"torch.device",
"torch.distributed.get_world_size",
"torch.distributed.init_process_group",
"torch.nn.parallel.DistributedDataParallel",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.distributed.is_initialized",
"torch.distributed.broadcast"
]
] |
s-m-e/poliastro | [
"3589806e6b10a5256c9069c5d7efbd4d67ff483a"
] | [
"tests/test_maneuver.py"
] | [
"import warnings\n\nimport numpy as np\nimport pytest\nfrom astropy import units as u\nfrom astropy.tests.helper import assert_quantity_allclose\nfrom astropy.time import Time\nfrom numpy.testing import assert_allclose\n\nfrom poliastro.bodies import Earth, Mercury, Moon\nfrom poliastro.maneuver import Maneuver\nfr... | [
[
"numpy.array",
"numpy.ones",
"numpy.zeros"
]
] |
daliwang/CellMigrationGym | [
"5801024da812fea4bfce68c41e43f63c14c8400b"
] | [
"DRL/main.py"
] | [
"import matplotlib.pyplot as plt\n\n#env related package\nimport gym,pickle,time\nimport numpy as np\nimport pybullet as p\nimport Embryo\n\n#RL related package\nimport torch\n# from stable_baselines.common.vec_env import DummyVecEnv\n# from stable_baselines.deepq.policies import MlpPolicy\n# from stable_baselines ... | [
[
"matplotlib.pyplot.ion",
"torch.cuda.is_available",
"matplotlib.pyplot.figure"
]
] |
Aearsears/mapleai | [
"38e067db2e90a21f941bd3c56d0a329741da9d0f"
] | [
"detect_draw.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Apr 10 14:57:25 2020\n\n\"\"\"\n\nimport numpy as np\nimport tensorflow as tf\nimport pandas as pd\nimport os\nimport csv\nimport cv2\nimport time\nimport matplotlib\nimport matplotlib.pyplot as plt\nfrom PIL import Image, ImageDraw, ImageFont\nfrom six import BytesI... | [
[
"tensorflow.io.gfile.GFile",
"tensorflow.compat.v2.train.Checkpoint",
"matplotlib.image.imsave",
"tensorflow.reshape",
"numpy.expand_dims"
]
] |
Azganoth/unisul-machine-learning | [
"c5c8dd65b0084521e4f5f679f53fedb03207a9a2"
] | [
"marge_skinner.py"
] | [
"import numpy as np\nimport tkinter as tk\nimport tkinter.ttk as ttk\nfrom pathlib import Path\nfrom sklearn.naive_bayes import GaussianNB\nfrom sklearn.tree import DecisionTreeClassifier\nfrom itertools import islice\nfrom tkinter.messagebox import askyesnocancel, showwarning\nfrom tkinter.filedialog import askope... | [
[
"numpy.array",
"sklearn.naive_bayes.GaussianNB",
"sklearn.tree.DecisionTreeClassifier"
]
] |
reddyprasade/Digit-Recognizer-with-Python | [
"75545c9f81889ef561deb7949778f748c0745794"
] | [
"Digit-Recognizer-with Python.py"
] | [
"# geport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport pandas as pd\r\nfrom sklearn.datasets import load_digits\r\n\r\n# Data Set Loading Form Scikit-Learn\r\nData = load_digits()\r\nprint(\"Description of the Data Optical recognition of handwritten digits dataset\",Data.DESCR)\r\nprint(\"Orginal Data\"... | [
[
"matplotlib.pyplot.show",
"sklearn.datasets.load_digits",
"matplotlib.pyplot.imshow"
]
] |
ebt-hpc/cca-ebt | [
"4e8a515207df6f4bc1538c734077b0c01b34effe"
] | [
"python/src/cca/ebt/make_loop_classifier.py"
] | [
"#!/usr/bin/env python3\n\n\n'''\n A script for making loop classifiers\n\n Copyright 2013-2018 RIKEN\n Copyright 2018-2020 Chiba Institute of Technology\n\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a ... | [
[
"numpy.array",
"numpy.random.seed",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.svm.SVC",
"sklearn.preprocessing.scale",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.precision_score",
"sklearn.metrics.f1_score",
"sklearn.metrics.recall_score"
]
] |
int-brain-lab/analysis | [
"effedfd0b5997411f576b4ebcc747c8613715c24"
] | [
"python/RT_analysis/RT_dist_plot.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# Reaction time analysis from wheel data\n#\n# Return all significant wheel velocity changes in each trial\n#\n# Plot histrograms of the reaction times relative to either goCue or stimOn times\n#\n# Author: Naoki Hiratani (N.Hiratani@gmail.com)\n#\nfrom math import *\n\nimport sys\nimpo... | [
[
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.axvline",
"matplotlib.pyplot.subplot"
]
] |
tomxi/guitar-set | [
"82cc1477758f3bc32d6c7fdaae2cdcaccd6cc2b0"
] | [
"mirapie/utils/wav.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCopyright (c) 2015, Antoine Liutkus, Inria\nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n * Redistributions of source code must retain the above copyright\... | [
[
"numpy.fromstring",
"numpy.zeros"
]
] |
fermi-lat/BayesianBlocks | [
"83580da7938cfb7646d659974f727cc001e550cb",
"83580da7938cfb7646d659974f727cc001e550cb"
] | [
"python/test_BB.py",
"python/BayesianBlocks_python.py"
] | [
"\"\"\"\n@brief Comparison of C++ and pure Python implementations for the three\ndifferent modes (unbinned, binned, and point measurement). The\nreconstructions should be identical.\n\n@author J. Chiang\n\"\"\"\n#\n# $Header: /nfs/slac/g/glast/ground/cvs/ScienceTools-scons/BayesianBlocks/python/test_BB.py,v 1.1.1.... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.mean",
"numpy.sqrt",
"numpy.random.random",
"numpy.linspace"
],
[
"numpy.array",
"numpy.ones",
"numpy.zeros",
"numpy.log"
]
] |
mattl1598/testing | [
"cd8124773b83a07301c507ffbb9ccaafbfe7a274",
"cd8124773b83a07301c507ffbb9ccaafbfe7a274",
"cd8124773b83a07301c507ffbb9ccaafbfe7a274",
"cd8124773b83a07301c507ffbb9ccaafbfe7a274",
"cd8124773b83a07301c507ffbb9ccaafbfe7a274"
] | [
"editing files/Portable Python 3.2.5.1/App/Lib/site-packages/pandas/tseries/offsets.py",
"editing files/Portable Python 3.2.5.1/App/Lib/site-packages/matplotlib/tight_bbox.py",
"editing files/Portable Python 3.2.5.1/App/Lib/site-packages/IPython/extensions/rmagic.py",
"editing files/Portable Python 3.2.5.1/Ap... | [
"from datetime import date, datetime, timedelta\n\nfrom pandas.tseries.tools import to_datetime\n\n# import after tools, dateutil check\nfrom dateutil.relativedelta import relativedelta\nimport pandas.lib as lib\nimport pandas.tslib as tslib\n\n__all__ = ['Day', 'BusinessDay', 'BDay',\n 'MonthBegin', 'BMo... | [
[
"pandas.tseries.tools.to_datetime",
"pandas.tseries.frequencies.get_offset",
"pandas.tseries.frequencies.to_offset",
"pandas.tslib.monthrange"
],
[
"matplotlib.transforms.Bbox.from_bounds",
"matplotlib.transforms.Affine2D",
"matplotlib.transforms.TransformedBbox"
],
[
"nump... |
ocNflag/point2seq | [
"710686f576b3df5469a06c66860758b25f852dbd"
] | [
"pcdet/models/dense_heads/e2e_seqfuse_head.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport matplotlib.pyplot as plt\nimport copy\nimport math\n\nfrom pcdet.ops.iou3d_nms.iou3d_nms_utils import boxes_iou3d_gpu\n\nfrom pcdet.models.dense_heads.utils import _sigmoid\n\nfrom ...utils import box_coder_utils, common_utils\nfrom pcdet.utils import... | [
[
"torch.cat",
"torch.stack",
"torch.nn.ModuleList",
"torch.arange",
"torch.no_grad",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.topk"
]
] |
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