repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
coolhimanshu-verma/evidently | [
"b4c5c282eabf4710343f342bb8aad8daf2f143a0"
] | [
"evidently/analyzers/data_drift_analyzer.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\nfrom evidently.analyzers.base_analyzer import Analyzer\nimport pandas as pd\nfrom pandas.api.types import is_numeric_dtype\nimport numpy as np\n\nfrom scipy.stats import ks_2samp, chisquare, norm\n\ndef proportions_diff_z_stat_ind(ref, curr):\n n1 = len(ref)\n n2 = l... | [
[
"scipy.stats.ks_2samp",
"numpy.abs",
"scipy.stats.norm.cdf",
"numpy.sqrt",
"numpy.isfinite",
"pandas.api.types.is_numeric_dtype",
"scipy.stats.chisquare"
]
] |
gbloss/6.0001-ps0 | [
"668a22743878ae54eeaec36be6ec89a9541b8d1f"
] | [
"ps0.py"
] | [
"from numpy import log2\n\ndef sanitized_input(prompt, input_type=None, input_min=None, input_max=None):\n if input_min is not None and input_max is not None and input_max < input_min:\n raise ValueError(\"Minimum must be less than or equal to the maximum.\")\n while True:\n user_input = input(p... | [
[
"numpy.log2"
]
] |
mrakitin/SRW-gui | [
"9c603d5a407dfa36ba92e8646d1a57151de825ed"
] | [
"uti_plot.py"
] | [
"#############################################################################\n# Simple 1D & 2D plotting utilities package (/ \"wrapper\" of featured scientific plotting libraries).\n# Currently uses matplotlib, but may support other libraries in the future.\n# v 0.01\n#############################################... | [
[
"numpy.linspace",
"matplotlib.use",
"matplotlib.pyplot.ioff",
"numpy.array",
"matplotlib.pyplot.show",
"numpy.loadtxt",
"matplotlib.pyplot.figure"
]
] |
tianqitheodorejiang/MRImageGBM | [
"8b7931c76ac655652ccc4210992cde78da46f3a8",
"8b7931c76ac655652ccc4210992cde78da46f3a8",
"8b7931c76ac655652ccc4210992cde78da46f3a8",
"8b7931c76ac655652ccc4210992cde78da46f3a8",
"8b7931c76ac655652ccc4210992cde78da46f3a8"
] | [
"all code (python source) p3/Database load for tumor treatment evaluation with voxelmorph overlaying actual.py",
"all code (python source) p1/brain mask 13.py",
"all code (python source) p2/brain seg model testing.py",
"all code (python source) p1/precise brain mask.py",
"all code (python source) p1/Using t... | [
"\"\"\"\r\nExample script to register two volumes with VoxelMorph models\r\n\r\nPlease make sure to use trained models appropriately. \r\nLet's say we have a model trained to register subject (moving) to atlas (fixed)\r\nOne could run:\r\n\r\npython register.py --gpu 0 /path/to/test_vol.nii.gz /path/to/atlas_norm.n... | [
[
"tensorflow.ConfigProto",
"tensorflow.device",
"tensorflow.Session"
],
[
"tensorflow.keras.models.load_model",
"numpy.squeeze",
"numpy.round",
"numpy.max",
"scipy.ndimage.interpolation.zoom",
"numpy.where",
"numpy.unique",
"scipy.ndimage.generate_binary_structure",
... |
Darkoon/CapsNet-vs-CNN | [
"2f50e49d687a97c420d9a41454dd4482be676c33"
] | [
"capsnet/singledigitcapsule/mnist_capsulenet.py"
] | [
"\"\"\"\nKeras implementation of CapsNet in Hinton's paper Dynamic Routing Between Capsules.\nThe current version maybe only works for TensorFlow backend. Actually it will be straightforward to re-write to TF code.\nAdopting to other backends should be easy, but I have not tested this. \n\nUsage:\n python cap... | [
[
"numpy.expand_dims",
"tensorflow.reduce_sum",
"matplotlib.pyplot.imread",
"tensorflow.keras.callbacks.LearningRateScheduler",
"numpy.concatenate",
"tensorflow.keras.regularizers.l2",
"numpy.copy",
"numpy.argmax",
"tensorflow.keras.backend.set_image_data_format",
"tensorflow... |
broadinstitute/adapt | [
"ae0346dbd8c77fa9bcefbec5358cc750b146474d"
] | [
"adapt/prepare/cluster.py"
] | [
"\"\"\"Functions for clustering sequences before input.\n\nThis includes computing a distance matrix using MinHash, and\nclustering that matrix.\n\"\"\"\n\nfrom collections import defaultdict\nfrom collections import OrderedDict\nimport logging\nimport operator\n\nimport numpy as np\nfrom scipy.cluster import hiera... | [
[
"scipy.cluster.hierarchy.linkage",
"numpy.exp",
"numpy.zeros",
"scipy.cluster.hierarchy.fcluster"
]
] |
jimpassmore/imagepy | [
"a814bf8a763f9ce427569f3ef5e5188746cc50eb",
"a814bf8a763f9ce427569f3ef5e5188746cc50eb"
] | [
"imagepy/imageplus.py",
"imagepy/menus/Process/Filters/classic_plgs.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import print_function\nimport numpy as np\nfrom .core.manager import WindowsManager, ColorManager\n\ndef get_img_type(imgs):\n if imgs[0].ndim==3:return 'rgb'\n if imgs[0].dtype == np.uint8:return '8-bit'\n if imgs[0].dtype == np.int16:return '16-bit... | [
[
"numpy.zeros",
"scipy.misc.imread",
"numpy.clip"
],
[
"scipy.ndimage.prewitt",
"scipy.ndimage.gaussian_filter",
"numpy.abs",
"numpy.multiply",
"scipy.ndimage.laplace",
"scipy.ndimage.minimum_filter",
"scipy.ndimage.median_filter",
"scipy.ndimage.sobel",
"scipy.n... |
jeremyjliu/spark | [
"5154b7b409d1c39240f25ab32ce35b75ed54a2fa"
] | [
"python/pyspark/sql/dataframe.py"
] | [
"#\n# Licensed to the Apache Software Foundation (ASF) under one or more\n# contributor license agreements. See the NOTICE file distributed with\n# this work for additional information regarding copyright ownership.\n# The ASF licenses this file to You under the Apache License, Version 2.0\n# (the \"License\"); yo... | [
[
"pandas.DataFrame.from_records"
]
] |
Alicegaz/kaldi | [
"7249cc0dd31dce480456b697b6389feeb74c74ab"
] | [
"egs/wsj/s5/steps/tfrnnlm/lstm_fast.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n# Copyright (C) 2017 Intellisist, Inc. (Author: Hainan Xu)\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# ... | [
[
"tensorflow.device",
"tensorflow.concat",
"tensorflow.reduce_sum",
"tensorflow.stack",
"numpy.exp",
"tensorflow.summary.scalar",
"tensorflow.Graph",
"tensorflow.Variable",
"tensorflow.random_uniform_initializer",
"tensorflow.gradients",
"tensorflow.name_scope",
"ten... |
azeme1/retinaface-tf2 | [
"09fe0957be6afce62001198e7c1931543d85b9b9"
] | [
"train.py"
] | [
"from absl import app, flags, logging\nfrom absl.flags import FLAGS\nimport os\nimport tensorflow as tf\n\nfrom modules.models import RetinaFaceModelOriginal as RetinaFaceModel\nfrom modules.lr_scheduler import MultiStepWarmUpLR\nfrom modules.losses import MultiBoxLoss\nfrom modules.anchor import prior_box\nfrom mo... | [
[
"tensorflow.train.CheckpointManager",
"tensorflow.Variable",
"tensorflow.reduce_sum",
"tensorflow.keras.optimizers.SGD",
"tensorflow.get_logger",
"tensorflow.GradientTape",
"tensorflow.summary.scalar",
"tensorflow.summary.create_file_writer"
]
] |
abidikhairi/embedding_with_lrw | [
"8152b3e4b61b197857d1293d5a50bff118804109"
] | [
"node2vec_experiment.py"
] | [
"import argparse\nimport logging\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.linear_model import LogisticRegression\nfrom gensim.models import Word2Vec, KeyedVectors\n\nfrom utils import load_data\n\nlogging.basicConfig(format='... | [
[
"numpy.mean",
"sklearn.model_selection.train_test_split",
"sklearn.linear_model.LogisticRegression"
]
] |
micmelesse/tensor2tensor | [
"93d34d69092f86b203f0f0a8230fcd9ecbe9086f"
] | [
"tensor2tensor/layers/vq_discrete.py"
] | [
"# coding=utf-8\n# Copyright 2019 The Tensor2Tensor Authors.\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... | [
[
"tensorflow.random_uniform",
"tensorflow.concat",
"tensorflow.control_dependencies",
"tensorflow.zeros",
"tensorflow.colocate_with",
"tensorflow.reduce_sum",
"tensorflow.to_int32",
"tensorflow.python.training.moving_averages.assign_moving_average",
"tensorflow.stop_gradient",
... |
ahmedhussein89/CarND-Advanced-Lane-Lines | [
"65f6998e325ae992b76a45fba9a1926a89a14183"
] | [
"threshold.py"
] | [
"import cv2\nimport numpy as np\nimport matplotlib.image as mpimg\n\n\ndef abs_sobel_thresh(img, orient='x', sobel_kernel=3, thresh=(0, 255)):\n # Apply the following steps to img\n # 1) Convert to grayscale\n gray_image = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n gray_image = cv2.GaussianBlur(gray_image,... | [
[
"numpy.absolute",
"numpy.sqrt",
"numpy.arctan2",
"numpy.max",
"numpy.zeros_like"
]
] |
PawelPamula/ReCirq | [
"79a351310cd98f67524a9df0c4ef9f300bf9eea4"
] | [
"recirq/quantum_chess/controlled_iswap_test.py"
] | [
"# Copyright 2020 Google\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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to i... | [
[
"numpy.set_printoptions"
]
] |
stevezheng23/sequence_labeling_tf | [
"05fcbec15e359e3db86af6c3798c13be8a6c58ee"
] | [
"sequence_labeling/sequence_labeling_run.py"
] | [
"import argparse\nimport os.path\nimport time\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom tensorflow.python import debug as tf_debug\n\nfrom util.default_util import *\nfrom util.param_util import *\nfrom util.model_util import *\nfrom util.eval_util import *\nfrom util.debug_logger import *\nfrom util.t... | [
[
"tensorflow.gfile.Exists",
"tensorflow.global_variables_initializer",
"tensorflow.gfile.MakeDirs",
"tensorflow.Session",
"tensorflow.python.debug.LocalCLIDebugWrapperSession",
"tensorflow.tables_initializer"
]
] |
Matthew-Hiebing/Automatic-Unemployment | [
"ddd2eeac87f22347810e0da50d4115cf3f9eb7c4"
] | [
"Payment_Request.py"
] | [
"import pandas as pd\nimport numpy as np\nimport time\nimport yaml\nimport datetime\nfrom selenium import webdriver\nfrom selenium.webdriver.common.keys import Keys\nfrom selenium.webdriver.support.ui import WebDriverWait as wait\nfrom selenium.webdriver.support import expected_conditions as EC\n\n#----------------... | [
[
"pandas.read_excel",
"pandas.DataFrame"
]
] |
Kyzarok/SNNProject | [
"14b555e221dbdd5100cb4f6333e49030423462ea"
] | [
"brian2/input/spikegeneratorgroup.py"
] | [
"'''\nModule defining `SpikeGeneratorGroup`.\n'''\nimport numpy as np\n\nfrom brian2.core.functions import timestep\nfrom brian2.utils.logger import get_logger\nfrom brian2.core.spikesource import SpikeSource\nfrom brian2.units.fundamentalunits import check_units, Unit, Quantity\nfrom brian2.units.allunits import s... | [
[
"numpy.abs",
"numpy.nonzero",
"numpy.min",
"numpy.asarray",
"numpy.lexsort",
"numpy.finfo",
"numpy.round",
"numpy.max",
"numpy.diff",
"numpy.iinfo"
]
] |
jtraver/dev | [
"c7cd2181594510a8fa27e7325566ed2d79371624"
] | [
"python3/matplotlib/plot1.py"
] | [
"#!/usr/bin/env python3\n#!/usr/bin/python\n\n# https://en.wikipedia.org/wiki/Matplotlib\n\nimport numpy\nimport matplotlib.pyplot as plt\n\nfrom numpy.random import rand\n\na = rand(100)\nb = rand(100)\nplt.scatter(a, b)\nplt.show()\n"
] | [
[
"matplotlib.pyplot.show",
"numpy.random.rand",
"matplotlib.pyplot.scatter"
]
] |
mccarthyryanc/laspy | [
"8bc16f3c91b7ae514923fe197e68904f3def179c"
] | [
"tests/test_common.py"
] | [
"from pathlib import Path\n\nimport numpy as np\nimport pytest\n\nimport laspy\nfrom laspy.lib import write_then_read_again\nfrom . import conftest\n\nsimple_las = conftest.SIMPLE_LAS_FILE_PATH\nsimple_laz = conftest.SIMPLE_LAZ_FILE_PATH\nvegetation1_3_las = conftest.VEGETATION1_3_LAS_FILE_PATH\ntest1_4_las = conft... | [
[
"numpy.all",
"numpy.array",
"numpy.alltrue",
"numpy.allclose"
]
] |
nariaki3551/flopt | [
"681d2f98824a52bb95de73676823d7ae59c6a013"
] | [
"flopt/solvers/scipy_searches/scipy_search.py"
] | [
"from time import time\n\nfrom scipy import optimize as scipy_optimize\nimport numpy as np\n\nfrom flopt.solvers.base import BaseSearch\nfrom flopt.solvers.solver_utils import (\n during_solver_message,\n)\nfrom flopt.env import setup_logger\nfrom flopt.expression import Const\nfrom flopt.solution import Solutio... | [
[
"scipy.optimize.NonlinearConstraint",
"scipy.optimize.Bounds",
"scipy.optimize.minimize"
]
] |
jinbeizame007/planet_pybullet | [
"9b648355fd70a1aade837d835ccc5e33133ae39a"
] | [
"planet/tools/overshooting.py"
] | [
"# Copyright 2019 The PlaNet 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 require... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.nn.dynamic_rnn",
"tensorflow.concat",
"tensorflow.range",
"tensorflow.shape",
"tensorflow.reduce_sum",
"tensorflow.cast",
"tensorflow.reshape",
"tensorflow.zeros_like",
"numpy.prod",
"numpy.array",
"tensorflow.sequence_mas... |
CPJKU/cyolo_score_following | [
"4b34947a9b7cc19a139ce3768eac6079aaff5cfe"
] | [
"cyolo_score_following/dataset.py"
] | [
"\nimport glob\nimport os\nimport random\nimport torch\nimport torchvision\n\nimport numpy as np\n\n\nfrom cyolo_score_following.utils.data_utils import load_sequences, SAMPLE_RATE, FPS, FRAME_SIZE, HOP_SIZE\nfrom cyolo_score_following.utils.dist_utils import is_main_process\nfrom cyolo_score_following.utils.genera... | [
[
"numpy.asarray",
"numpy.stack",
"numpy.concatenate",
"numpy.copy",
"torch.set_grad_enabled",
"numpy.mean",
"torch.FloatTensor",
"torch.device",
"numpy.roll",
"torch.as_tensor"
]
] |
guanghaoyin/Camera-ScreenSR | [
"565075787f34ee5e778ad9fc9511cd960171deb8"
] | [
"Train_DURCAN_withGAN.py"
] | [
"import torch\r\nimport torch.nn as nn\r\nfrom torch.autograd import Variable\r\nimport Data.utils as utils\r\nimport Loss\r\nfrom Loss import tv_loss\r\nimport Model\r\nfrom Model.Net import DURCAN\r\nfrom Data.option import args\r\nfrom importlib import import_module\r\nfrom Data.dataloader import MSDataLoader\r\... | [
[
"torch.manual_seed",
"torch.cuda.empty_cache",
"torch.nn.BCELoss",
"torch.no_grad",
"torch.device"
]
] |
harish-kamath/pytorch-soft-actor-critic | [
"88373d6c67fbc40cd752882d887cff07fc7b189c"
] | [
"main.py"
] | [
"import argparse\nimport datetime\nimport gym\nimport numpy as np\nimport itertools\nimport torch\nfrom .sac import SAC\nfrom torch.utils.tensorboard import SummaryWriter\nfrom .replay_memory import ReplayMemory\nimport random\n\ndevice = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n\ndef cre... | [
[
"torch.from_numpy",
"torch.cuda.is_available"
]
] |
pinkerltm/datacube-ui | [
"325d404a994d49c23922e7de10c7ab244b78500b"
] | [
"apps/dc_algorithm/utils.py"
] | [
"import matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\n\nimport numpy as np\nfrom collections import Iterable\n\n\ndef create_2d_plot(path, dates=None, datasets=None, data_labels=None, style='', titles=None, vertical=True):\n \"\"\"Create a 2d image and save it to disk\n\n Args:\n ... | [
[
"matplotlib.use",
"matplotlib.pyplot.figure"
]
] |
chaneyddtt/UDA-Animal-Pose | [
"f1ebfda860a2585c60fe86ce1632e910ac97ebc5"
] | [
"train/train_refinenet_mt.py"
] | [
"from __future__ import print_function, absolute_import\n\nimport argparse\nimport time\nimport random\n\nimport torch\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\nimport torch.optim\n\nimport _init_paths\nfrom pose import Bar\nfrom pose.utils.logger import Logger\nfrom pose.utils.evaluation imp... | [
[
"torch.max",
"torch.load",
"torch.utils.data.DataLoader",
"torch.zeros_like",
"torch.tensor",
"torch.nn.BCEWithLogitsLoss",
"torch.no_grad",
"torch.nn.functional.grid_sample",
"torch.cuda.is_available",
"torch.where",
"torch.nn.DataParallel",
"numpy.exp",
"torch... |
cscyuge/medlane | [
"f830cfdb48dac11e447e47cca3f72c106e0e9fe6"
] | [
"Bert/Seq2seq_old.py"
] | [
"import random\n\nimport torch.nn as nn\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\n\nimport torch\nimport numpy as np\nPAD, CLS = '[PAD]', '[CLS]'\nSEP = '[SEP]'\n\nclass Attention(nn.Module):\n r\"\"\"\n Applies an attention mechanism on the output features from the decoder.\n\n ... | [
[
"torch.nn.Dropout",
"torch.LongTensor",
"torch.cat",
"torch.nn.Embedding",
"torch.nn.Linear",
"torch.bmm",
"torch.cuda.is_available",
"numpy.array"
]
] |
jadalilleboe/skyportal | [
"501b7a09e239f03213499df297620c6a8a214cd9"
] | [
"skyportal/handlers/api/internal/plot.py"
] | [
"from baselayer.app.access import auth_or_token\nfrom baselayer.app.env import load_env\nfrom ...base import BaseHandler\nfrom .... import plot\nfrom ....models import ClassicalAssignment, Obj, Telescope\n\nimport numpy as np\nfrom astropy import time as ap_time\nimport astropy.units as u\nimport pandas as pd\nimpo... | [
[
"numpy.linspace",
"pandas.DataFrame"
]
] |
00why00/yolov3-tf2 | [
"9f1a08cb8e8d6897a4552568b2ae16a32e4fd7ee"
] | [
"yolov3/dataset.py"
] | [
"import tensorflow as tf\nfrom absl.flags import FLAGS\n\n\n# 将模型转换为易于部署且高性能的 TensorFlow 图模型\n@tf.function\ndef transform_targets_for_output(y_true, grid_size, anchor_idxs):\n \"\"\"\n 对 label 的 shape 进行转换\n 原始shape (N, boxes, (x1, y1, x2, y2, class, best_anchor))\n 目标shape (N, grid, grid, anchors, [x1,... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.concat",
"tensorflow.cast",
"tensorflow.minimum",
"tensorflow.equal",
"tensorflow.data.Dataset.list_files",
"tensorflow.pad",
"tensorflow.where",
"tensorflow.lookup.TextFileInitializer",
"tensorflow.io.VarLenFeature",
"tensorf... |
BlakeHan01/hacknyu-22 | [
"3140e72635f0d31f58378232efae4ce3f3ca2f3b"
] | [
"prediction.py"
] | [
"import pandas as pd\nimport numpy as np\nimport datetime as dt\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport matplotlib.patches as patches\n# suppress warning\nimport warnings\nwarnings.filterwarnings('ignore')\nimport statsmodels.formula.api as smf\nimport statsmodels.api as sm\nfrom statsmodels.tsa... | [
[
"matplotlib.pyplot.legend",
"pandas.read_csv",
"pandas.to_datetime",
"matplotlib.pyplot.title",
"scipy.stats.normaltest",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.rcParams.update",
"matplotlib.pyplot.show"
]
] |
Lotayou/meta-transfer-learning | [
"c4f74e3ae3a29058f2559634412d9a1bd8a4362a"
] | [
"tensorflow/utils/misc.py"
] | [
"##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++\n## Created by: Yaoyao Liu\n## Modified from: https://github.com/cbfinn/maml\n## Tianjin University\n## liuyaoyao@tju.edu.cn\n## Copyright (c) 2019\n##\n## This source code is licensed under the MIT-style license found in the\n## LICENSE f... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"numpy.reshape",
"tensorflow.maximum",
"matplotlib.pyplot.imread",
"tensorflow.reshape",
"tensorflow.contrib.layers.python.layers.batch_norm",
"numpy.max",
"numpy.copy",
"numpy.argmin",
"tensorflow.square",
"tensorflow.... |
donmezkutay/visjobs | [
"fc42865ef790d309372c6057f1719211376b87a6"
] | [
"visjobs/datas/get_MODEL.py"
] | [
"# -*- coding: utf-8 -*-\n#!/usr/bin/env python\n# coding: utf-8\nimport xarray as xr\nfrom datetime import datetime,timedelta\nimport numpy as np\n\n\n#learn if the latest wanted or the desired date from user?\ndef pick_data(year=None, month=None, day=None, hour=None, latest=False, model='GFS', hourly=False, resol... | [
[
"numpy.array",
"numpy.multiply"
]
] |
Arminkhayati/pySenti4SD | [
"f48838b61dfc3dc3a78cdbfbb7675cc365a0ba87"
] | [
"python/core/classification.py"
] | [
"import os\nimport csv\nimport glob\nfrom multiprocessing import Pool\nfrom collections import OrderedDict\n\nimport numpy as np\nimport pandas as pd\nfrom joblib import Parallel, delayed\nfrom sklearn.preprocessing import LabelEncoder\n\nfrom utils.csv_utils import CsvUtils\nfrom utils.csv_formatter import CsvForm... | [
[
"sklearn.preprocessing.LabelEncoder",
"numpy.array",
"pandas.read_csv"
]
] |
UNIVR-RTI/NeuralRTI | [
"8540cc31528c2dd1da19ee34349ba12f2f0a5d59"
] | [
"train.py"
] | [
"\n\nfrom keras import backend as K\nimport keras\nimport numpy as np\nimport relighting_model as rm\nimport glob\nimport tensorflow as tf\nimport os, errno\nimport computeaph as caph\nimport time\nimport gc\nimport cv2\nimport tensorflowjs as tfjs\nimport argparse\nimport json\nkeras.layers.BatchNormalization(axis... | [
[
"numpy.amax",
"tensorflow.compat.v1.ConfigProto",
"numpy.amin",
"tensorflow.compat.v1.keras.backend.set_session",
"numpy.save",
"tensorflow.compat.v1.Session",
"numpy.shape",
"numpy.zeros"
]
] |
LBNL-ETA/G36SavingsCalculator | [
"14ca4cfa38b3d223f406200be4cbe60942aad6f2"
] | [
"process/mat_to_csv_small.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nThis script can be used to convert a .mat simulation result file into a\n.csv file with a subset of model variables, as defined in the \"outputs\" list.\n\nThe .csv file is saved in the same directory as the .mat file, and is based\non the case, climate, and scenario.\n\n\"\"\"\n\n... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] |
arp95/robot_target_tracking | [
"662f2559893866c73717874ad8e2e5cfee78c731"
] | [
"code/envs/robot_target_tracking_env_sensors.py"
] | [
"\"\"\"\nOpenAI Gym environment with robots and targets\n\nEnvironment source code: https://github.com/ksengin/active-target-localization/blob/master/target_localization/envs/tracking_waypoints_env.py\nModifications: Modified the existing environment with number of robots > 1 and the targets moving case\n\"\"\"\n\n... | [
[
"torch.abs",
"matplotlib.pyplot.contourf",
"numpy.sqrt",
"numpy.linspace",
"torch.zeros",
"torch.sin",
"matplotlib.pyplot.plot",
"numpy.random.randn",
"torch.cuda.is_available",
"torch.norm",
"torch.randn",
"numpy.eye",
"numpy.matmul",
"torch.tensor",
"n... |
VIDA-NYU/alphad3m | [
"db40193a448300d87442c451f9da17fa5cb845fd"
] | [
"alphad3m/alphad3m/metalearning/dataset_profiler.py"
] | [
"import logging\nimport pandas as pd\nimport datamart_profiler\nfrom metalearn import Metafeatures\n\nlogger = logging.getLogger(__name__)\n\n\ndef extract_metafeatures(dataset_path, target_column):\n data = pd.read_csv(dataset_path)\n Y = data[target_column]\n Y = pd.Series([str(i) for i in Y], name=targe... | [
[
"pandas.read_csv"
]
] |
StevenGrove/TreeFilter-Torch | [
"46f36024f4522056fb9a3edf90c94f0a86a1352b"
] | [
"model/cityscapes/cityscapes.fcn_32d.R101_v1c.extra/config.py"
] | [
"# encoding: utf-8\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport os.path as osp\nimport sys\nimport time\nimport numpy as np\nfrom easydict import EasyDict as edict\nimport argparse\n\nC = edict()\nconfig = C\ncfg = C\n\nC.seed = 304\n\n\... | [
[
"numpy.array"
]
] |
mfkasim1/pytorch | [
"cf7a0e5af49958c86522fbb556f0aa54077d72fa",
"cf7a0e5af49958c86522fbb556f0aa54077d72fa"
] | [
"test/test_datapipe.py",
"torch/fx/passes/net_min_base.py"
] | [
"import itertools\nimport os\nimport pickle\nimport random\nimport tempfile\nimport warnings\nimport tarfile\nimport zipfile\nimport numpy as np\nfrom PIL import Image\nfrom unittest import skipIf\n\nimport torch\nimport torch.nn as nn\nfrom torch.testing._internal.common_utils import (TestCase, run_tests)\nfrom to... | [
[
"torch.utils.data._typing.issubtype",
"torch.set_default_dtype",
"torch.utils.data._typing.issubinstance",
"torch.utils.data.DataLoader",
"torch.utils.data.datapipes.utils.decoder.imagehandler",
"torch.tensor",
"torch.utils.data.datapipes.iter.ListDirFiles",
"torch.utils.data.datap... |
Forbu/fourier_neural_operator | [
"a70ab4bf177b565373e2d8128054e4da2233660d"
] | [
"fourier_neural_operator/fourier_2d_time.py"
] | [
"\"\"\"\n@author: Zongyi Li\nThis file is the Fourier Neural Operator for 2D problem such as the Navier-Stokes equation discussed in Section 5.3 in the [paper](https://arxiv.org/pdf/2010.08895.pdf),\nwhich uses a recurrent structure to propagates in time.\n\"\"\"\n\n\nimport torch\nimport numpy as np\nimport torch.... | [
[
"numpy.linspace",
"torch.cat",
"torch.einsum",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.fft.rfft2",
"torch.nn.functional.gelu",
"torch.rand",
"torch.nn.BatchNorm2d"
]
] |
nelhage/pytorch | [
"873255c6d95342d144e9d1b633c16410844b934e"
] | [
"torch/fx/experimental/const_fold.py"
] | [
"import operator\nimport re\nfrom typing import Dict, Set, List, Optional, Union\n\nimport torch.fx\nfrom torch.fx.passes.split_module import split_module\n\n\ndef _make_tuple(x):\n \"\"\"\n Helper to convert x into a one item tuple if it's not a tuple already.\n \"\"\"\n return x if isinstance(x, tuple... | [
[
"torch.fx.passes.split_module.split_module"
]
] |
Ramprasad-Group/PSP | [
"6f0df0a052898c8f44a58ef9ab0578731455c4a3"
] | [
"psp/ChainBuilder.py"
] | [
"import numpy as np\nimport pandas as pd\nimport psp.PSP_lib as bd\nfrom openbabel import openbabel as ob\nimport os\nimport shutil\nimport time\nimport multiprocessing\nfrom joblib import Parallel, delayed\nimport psp.output_lib as lib\nfrom tqdm import tqdm\n\nobConversion = ob.OBConversion()\nobConversion.SetInA... | [
[
"numpy.round",
"numpy.arange",
"pandas.DataFrame"
]
] |
vksriharsha/CQA | [
"50021cca2d1d0833a0300bea20fd259dc4871fad"
] | [
"compute_metrics.py"
] | [
"import argparse\nimport json\nimport os\nimport shutil\nimport sys\nfrom collections import defaultdict\n\nimport configs.config_template as CONFIG\nimport torch\n\nparser = argparse.ArgumentParser()\nparser.add_argument('--expt_name', required=True, type=str)\nparser.add_argument('--data_root', default='data', ty... | [
[
"torch.load"
]
] |
LMMV/MolModMT | [
"5725d6d5627b07edcbbd5e55318345a136b28c35"
] | [
"molmodmt/utils/math.py"
] | [
"import numpy as _np\n\nclass serialized_lists():\n\n self.values = None\n self.starts = None\n self.n_values = None\n self.n_lists = None\n\n def __init__ (list_of_lists, fortran=False, dtype=None):\n\n self.values= _np.concatenate(list_of_lists)\n\n self.starts= []\n jj = 0\n ... | [
[
"numpy.concatenate",
"numpy.astype",
"numpy.asfortranarray",
"numpy.array"
]
] |
hengxyz/facenet_class_wise_triplet_loss_pub | [
"ba93e3016006616310decd7e55d554d06ccb0c22"
] | [
"src/train_BP.py"
] | [
"\"\"\"Functions for building the face recognition network.\n\"\"\"\n# MIT License\n# \n# Copyright (c) 2016 David Sandberg\n# \n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software withou... | [
[
"tensorflow.train.AdagradOptimizer",
"tensorflow.control_dependencies",
"tensorflow.train.RMSPropOptimizer",
"tensorflow.get_collection",
"tensorflow.train.AdadeltaOptimizer",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.clip_by_global_norm",
"tensorflow.train.MomentumO... |
bobenxia/Centripetal-SGD | [
"e33350464504085a641a2a969d3c06e3d5cc4765"
] | [
"data/imagenet_data.py"
] | [
"import torch\nimport torchvision.transforms as transforms\nfrom data.dataset_util import DataIterator\nimport os\nimport torchvision.datasets as datasets\n\nIMGNET_TRAIN_DIR = 'imagenet_data'\n\nclass ImgnetStdTrainData(object):\n\n def __init__(self, distributed, batch_size_per_gpu, img_size=224):\n nor... | [
[
"torch.utils.data.DataLoader",
"torch.utils.data.distributed.DistributedSampler"
]
] |
ali-bahjati/incubator-superset | [
"c76993ac47e607062a951186ebb28cdc46f2e8eb"
] | [
"superset/views/core.py"
] | [
"# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.0 (the\n# \"License\"); y... | [
[
"pandas.DataFrame.from_records"
]
] |
b8739/dashApp | [
"fdfb116cb6f6c2674aab307b554404e69b66018b"
] | [
"unused/logic.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Feb 23 14:40:14 2022\n\n@author: s\n\"\"\"\n\n##### 2022-02-15 : BIOGAS PLANT MODEL #####\n\n\nimport os\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom datetime import datetime, timedelta, date\n\nfrom sklearn.m... | [
[
"sklearn.ensemble.RandomForestRegressor",
"pandas.read_excel",
"pandas.to_datetime",
"sklearn.metrics.r2_score",
"pandas.Series",
"pandas.DataFrame",
"sklearn.metrics.mean_squared_error",
"matplotlib.pyplot.plot",
"numpy.where",
"matplotlib.pyplot.gca",
"matplotlib.pypl... |
nihilistsumo/Blackbox_clustering | [
"9257890fb9a945115f249988c9e863654d23551c"
] | [
"experiments/ng20_eval.py"
] | [
"import argparse\nimport pickle\nimport torch\nfrom model.BBCluster import CustomSentenceTransformer\nfrom sklearn.feature_extraction.text import TfidfVectorizer\nfrom sklearn.cluster import AgglomerativeClustering\nfrom sklearn.metrics import adjusted_rand_score, adjusted_mutual_info_score, normalized_mutual_info_... | [
[
"scipy.stats.ttest_rel",
"torch.norm",
"torch.from_numpy",
"sklearn.metrics.normalized_mutual_info_score",
"sklearn.metrics.adjusted_mutual_info_score",
"torch.nn.Tanh",
"sklearn.metrics.cluster._supervised.check_clusterings",
"numpy.int64",
"sklearn.metrics.cluster.contingency... |
novyantsp/DeBERTa | [
"919cf8146480daa6c39ed8b1afaeb0d5f7775b14"
] | [
"DeBERTa/apps/train.py"
] | [
"# Copyright (c) Microsoft, Inc. 2020\n#\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n#\n# Author: penhe@microsoft.com\n# Date: 01/25/2020\n#\n\n\"\"\"DeBERTa finetuning runner.\"\"\"\n\nimport os\nfrom collections import OrderedDict,... | [
[
"torch.cuda.synchronize",
"numpy.random.seed",
"torch.cat",
"torch.manual_seed",
"torch.distributed.all_gather",
"torch.utils.data.DataLoader",
"torch.zeros_like",
"torch.distributed.is_initialized",
"numpy.copy",
"numpy.append",
"torch.no_grad",
"numpy.savetxt",
... |
dabana/sklearn-jobs | [
"daeaf2827ce0be707b280ec64ecfe852e29409a5"
] | [
"examples/plot_classifier.py"
] | [
"\"\"\"\n============================\nPlotting Template Classifier\n============================\n\nAn example plot of :class:`skljobs.template.TemplateClassifier`\n\"\"\"\nimport numpy as np\nfrom matplotlib import pyplot as plt\nfrom skljobs import TemplateClassifier\n\nX = [[0, 0], [1, 1]]\ny = [0, 1]\nclf = Te... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"numpy.random.RandomState",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
suyashtn/OpenFOAM-custom-scripts | [
"73bdd17f11868ebe313d69b5cf717ad6458d2b40"
] | [
"src/bin/spanwiseAvg/get_spanwise_avg.py"
] | [
"import numpy as np\nimport os\nfrom tqdm import tqdm\nfrom scipy.interpolate import griddata\nfrom scipy.interpolate import InterpolatedUnivariateSpline\n\n__all__ = ['get_yplus', 'get_spanwise_avg']\n\ndef complete_array(data, ycoord):\n try:\n nCols = data.shape[1]\n data = np.insert(data, 0, 0,... | [
[
"numpy.square",
"numpy.sqrt",
"scipy.interpolate.InterpolatedUnivariateSpline",
"numpy.unique",
"numpy.append",
"numpy.mean",
"numpy.insert",
"scipy.interpolate.griddata",
"numpy.meshgrid",
"numpy.zeros"
]
] |
1Harshini/empress | [
"8ccd57b70207d2877cde11755d7e789c61313d0c"
] | [
"empress/taxonomy_utils.py"
] | [
"# ----------------------------------------------------------------------------\n# Copyright (c) 2016-2020, empress development team.\n#\n# Distributed under the terms of the Modified BSD License.\n#\n# The full license is in the file LICENSE, distributed with this software.\n# -------------------------------------... | [
[
"pandas.concat"
]
] |
longodj/T-CVAE-MolGen | [
"adfea2c51466970aab6d15c3e875bc80430c08f6"
] | [
"src/models/modules/jtnn_enc.py"
] | [
"import torch\nimport torch.nn as nn\nfrom utils.cuda import GRUUpdate, cuda, move_dgl_to_cuda\nfrom dgl import batch, bfs_edges_generator\nimport dgl.function as DGLF\nimport numpy as np\n\nMAX_NB = 8\n\ndef level_order(forest, roots):\n try:\n edges = bfs_edges_generator(forest, roots)\n _, leave... | [
[
"torch.nn.Module.__init__",
"torch.cat",
"numpy.cumsum",
"torch.nn.Embedding",
"torch.cuda.FloatTensor",
"torch.nn.Linear"
]
] |
eth-sri/guiding-synthesizers | [
"3622b80eb3bf633be65036dc47e4ed7b98c3fce8"
] | [
"guidesyn/core/models/EnsembleRnnCnn.py"
] | [
"\"\"\"\nCopyright 2019 Software Reliability Lab, ETH Zurich\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n http://www.apache.org/licenses/LICENSE-2.0\nUnless required by applicable la... | [
[
"torch.nn.LSTM",
"torch.cat",
"torch.nn.functional.dropout",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.nn.init.xavier_uniform_"
]
] |
sanghyun-son/srwarp | [
"d7cc08db5ba5ec9103f1813f76d1da825afe1a5b",
"d7cc08db5ba5ec9103f1813f76d1da825afe1a5b"
] | [
"src/data/sr/demo.py",
"src/model/sr/rdn_f.py"
] | [
"from data import common\nfrom data.sr import dataclass\nimport numpy as np\nfrom PIL import Image\n\n_parent_class = dataclass.SRData\n\n\nclass Demo(_parent_class):\n\n def __init__(self, *args, **kwargs):\n super().__init__(*args, **kwargs)\n\n @staticmethod\n def get_kwargs(cfg, train=False):\n ... | [
[
"numpy.array"
],
[
"torch.nn.Sequential",
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.PixelShuffle",
"torch.nn.ReLU"
]
] |
dujiangsu/FasterTransformer | [
"0648b8839be02eafba1cdba511a41b4fd13e2c9e"
] | [
"bert-quantization/bert-tf-quantization/fused_layer_norm.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors.\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 obtain a copy of the License ... | [
[
"tensorflow.shape",
"tensorflow.python.ops.nn.fused_batch_norm",
"tensorflow.contrib.layers.python.layers.utils.get_variable_collections",
"tensorflow.python.ops.init_ops.zeros_initializer",
"tensorflow.python.ops.array_ops.reshape",
"tensorflow.python.ops.init_ops.ones_initializer",
"... |
lfunderburk/Effective-Instructions | [
"ce40f890fb8623ff1ec9c3e9e1190505cbd1e6db"
] | [
"instruction_env/Lib/site-packages/pandas/io/parquet.py"
] | [
"\"\"\" parquet compat \"\"\"\n\nfrom typing import Any, Dict, Optional\nfrom warnings import catch_warnings\n\nfrom pandas.compat._optional import import_optional_dependency\nfrom pandas.errors import AbstractMethodError\n\nfrom pandas import DataFrame, get_option\n\nfrom pandas.io.common import get_filepath_or_bu... | [
[
"pandas.io.common.is_s3_url",
"pandas.io.s3.get_file_and_filesystem",
"pandas.errors.AbstractMethodError",
"pandas.compat._optional.import_optional_dependency",
"pandas.io.common.get_filepath_or_buffer",
"pandas.get_option",
"pandas.io.common.is_gcs_url"
]
] |
iMeleon/CRNN-for-train-in-COLAB | [
"db1b932b243d96c72cd4ed2e2f22c5e6172832eb"
] | [
"train.py"
] | [
"import os\nimport glob\nimport torch\nimport numpy as np\n\nimport albumentations\nfrom sklearn import preprocessing\nfrom sklearn import model_selection\nfrom sklearn import metrics\n\nimport config\nimport dataset\nimport engine\nfrom model import CaptchaModel\n\n\nfrom torch import nn\n\n\ndef remove_duplicates... | [
[
"torch.softmax",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"sklearn.metrics.accuracy_score",
"torch.utils.data.DataLoader",
"sklearn.model_selection.train_test_split",
"numpy.save",
"sklearn.preprocessing.LabelEncoder",
"numpy.array",
"torch.argmax"
]
] |
sx-aurora-dev/weld | [
"80cb8ad4bf14f6daf1b33fe18d34784bd185ae75"
] | [
"python/numpy-0.1.0/weldnumpy/tests/test_multid.py"
] | [
"import numpy as np\nimport py.test\nimport random\nfrom weldnumpy import *\nimport weldnumpy as wn\nfrom test_utils import *\n\n'''\nNeed to add a bunch of _real_shape invariance based tests.\n'''\n\ndef diagonal(ary, offset=0):\n \"\"\"\n from bohrium guys.\n \"\"\"\n if ary.ndim != 2:\n raise ... | [
[
"numpy.log",
"numpy.sqrt",
"numpy.allclose",
"numpy.array_equal",
"numpy.transpose",
"numpy.sum"
]
] |
Ankit-Mehra/perceptron_package | [
"4c37acae9f918cdbac16c024d4822f8c3505004d"
] | [
"src/simple_perceptron/perceptron.py"
] | [
"import os\nimport joblib\nimport numpy as np\nimport logging\n\n#Percpetron Class\nclass Perceptron:\n def __init__(self,eta:float=None,epochs:int=None):\n self.weights = np.random.randn(3)*1e-4 # initialize the weights with small random values \n training = (eta is not None) and (epochs is not No... | [
[
"numpy.dot",
"numpy.where",
"numpy.sum",
"numpy.random.randn"
]
] |
LegenDong/IQIYI_VID_FACE_2019 | [
"258ff9282206e7b7074ed9ada5ef928bc9305ec6"
] | [
"models/losses.py"
] | [
"# -*- coding: utf-8 -*-\n# @Time : 2019/4/21 13:59\n# @Author : LegenDong\n# @User : legendong\n# @File : losses.py\n# @Software: PyCharm\nimport torch\nimport torch.nn as nn\n\n__all__ = ['FocalLoss', ]\n\n\nclass FocalLoss(nn.Module):\n def __init__(self, gamma=0, eps=1e-7):\n super(FocalLoss... | [
[
"torch.exp",
"torch.mean",
"torch.nn.CrossEntropyLoss"
]
] |
RitwickGhosh/Compressed_CNN_Radiology_Image | [
"f082e7b78ab86097e00cde7efe2d1a78482ac5c7"
] | [
"XNORnet/XNORNetLayer.py"
] | [
"import keras.backend as K\nfrom keras.layers import Convolution2D\nfrom keras.engine import InputSpec\nimport numpy as np\n\nfrom CustomOps.customOps import passthroughSign\n\nclass XNORNetConv2D(Convolution2D):\n \"\"\"2D 'XNORNet' convolution layer (e.g. spatial convolution over images).\n\n This is an imp... | [
[
"numpy.abs",
"numpy.multiply",
"numpy.ones",
"numpy.sign",
"numpy.broadcast_to",
"numpy.sum"
]
] |
os-climate/sostrades-value-assessment | [
"ec93df566ef557f2342f6b21db9a0ba3b6097900"
] | [
"value_assessment/tests/l0_test_manufacturer_vb.py"
] | [
"'''\r\nCopyright 2022 Airbus SAS\r\n\r\nLicensed under the Apache License, Version 2.0 (the \"License\");\r\nyou may not use this file except in compliance with the License.\r\nYou may obtain a copy of the License at\r\n\r\n http://www.apache.org/licenses/LICENSE-2.0\r\n\r\nUnless required by applicable law or ... | [
[
"pandas.DataFrame"
]
] |
thibautlouis/psplay | [
"f54e0b88149f1fbb4cc66bb66e916a96b4cea2c7"
] | [
"psplay/tests/test_ps_tools.py"
] | [
"import ps_tools\nimport time\nimport pylab as plt, numpy as np\n\nmap0_info = {\"name\": \"split0_IQU.fits\", \"data_type\": \"IQU\", \"id\": \"split0\", \"cal\": None}\nmap1_info = {\"name\": \"split1_IQU.fits\", \"data_type\": \"IQU\", \"id\": \"split1\", \"cal\": None}\n\nsource_mask = {\"name\": \"source_mask.... | [
[
"numpy.diag",
"numpy.loadtxt"
]
] |
piyushpathak03/Copy-move-Image-forgery-detection- | [
"000a78bdfc785c0a1bfb50b3e98b942e9334e6d7"
] | [
"fine_tune_last_layers_resnet.py"
] | [
"import numpy as np\r\nfrom keras.applications.resnet50 import ResNet50\r\nfrom keras.models import load_model\r\nfrom keras.models import Sequential\r\nfrom keras.layers import Dense, Flatten, Dropout\r\nfrom keras import optimizers\r\n\r\n\r\ndef main():\r\n\tx_train=np.load('train_data/x_train.npy')\r\n\tx_cv=np... | [
[
"numpy.load"
]
] |
ksivasan/PytorchTutorialExamples | [
"5997f17de52b6b6a005e0419c3f9369f83d5f66f"
] | [
"pytorch/binaryclassification.py"
] | [
"# pytorch mlp for binary classification\nfrom numpy import vstack\nfrom pandas import read_csv\nfrom sklearn.preprocessing import LabelEncoder\nfrom sklearn.metrics import accuracy_score\nfrom torch.utils.data import Dataset\nfrom torch.utils.data import DataLoader\nfrom torch.utils.data import random_split\nfrom ... | [
[
"pandas.read_csv",
"torch.Tensor",
"torch.utils.data.DataLoader",
"torch.nn.BCELoss",
"matplotlib.pyplot.plot",
"torch.nn.Linear",
"torch.utils.data.random_split",
"torch.nn.init.kaiming_uniform_",
"torch.nn.Sigmoid",
"torch.nn.init.xavier_uniform_",
"torch.nn.ReLU",
... |
lucaskingjade/RNNTutorial | [
"b641e50014b56bb8e0f8762c76f1178a9a7c911f",
"b641e50014b56bb8e0f8762c76f1178a9a7c911f"
] | [
"rnntutor/lib/python2.7/site-packages/theano/sandbox/gpuarray/tests/test_elemwise.py",
"rnntutor/lib/python2.7/site-packages/theano/sandbox/cuda/opt_util.py"
] | [
"import theano\nfrom theano import scalar, gof\nfrom theano.compat.python2x import all, any\nfrom theano.tests.unittest_tools import SkipTest\n\nfrom theano.tensor.tests.test_elemwise import (test_Broadcast, test_DimShuffle,\n test_CAReduce, T_reduce_dtype)\n\nfrom thea... | [
[
"numpy.random.rand"
],
[
"numpy.asarray"
]
] |
HoloClean/RecordFusion | [
"4094cd9e6c779584b9dbed6f3ae68eb11b13e2b2"
] | [
"repair/featurize/freqfeatfusion_old.py"
] | [
"import torch\nfrom dataset import AuxTables\nfrom .featurizer import Featurizer\nfrom functools import partial\n\n\n#GM\n\nclass FreqFeaturizerFusion_old(Featurizer):\n def specific_setup(self):\n self.name = 'FreqSignal_old'\n self.all_attrs = self.ds.get_attributes()\n self.all_attrs.remo... | [
[
"torch.cat",
"torch.zeros"
]
] |
amandatta16/NN | [
"b2d78fe90623a93c0803dbbd3b4fa1495c50dbc0"
] | [
"utils.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport h5py\n\n\ndef sigmoid(Z):\n \"\"\"\n Implements the sigmoid activation in numpy\n\n Arguments:\n Z -- numpy array of any shape\n\n Returns:\n A -- output of sigmoid(z), same shape as Z\n cache -- returns Z as well, useful during backp... | [
[
"numpy.dot",
"numpy.log",
"numpy.maximum",
"numpy.sqrt",
"numpy.random.seed",
"numpy.squeeze",
"numpy.divide",
"matplotlib.pyplot.subplot",
"numpy.random.randn",
"numpy.where",
"matplotlib.pyplot.axis",
"numpy.exp",
"numpy.array",
"numpy.zeros",
"numpy.s... |
haganta-g/glass_frog_design | [
"06a0e3d3a67d53c5f0bf4fd51e50e7cac58397b7"
] | [
"scripts/fin.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nimport pint\n\nureg = pint.UnitRegistry()\n\ndef si(v):\n return v.to_base_units().m\n\nclass Fin:\n # for a single fin, accurate if using 3 or 4 fins\n def __init__(self, root_chord, tip_chord, span, tube_diameter, mid_chord_sweep):\n\n self.c... | [
[
"matplotlib.pyplot.gca",
"numpy.sqrt",
"numpy.arctan",
"numpy.cos",
"matplotlib.pyplot.plot",
"numpy.tan",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.ylabel"
]
] |
iiSeymour/pyfse | [
"191ee958a0b6b2cb4e233d2c8b71c22abfd01ac7"
] | [
"tests/fse_tests.py"
] | [
"import numpy as np\nfrom unittest import TestCase, main\nfrom numpy.testing import assert_array_equal\n\nfrom fse import fse_encode, fse_decode, huf_encode, huf_decode\n\n\nclass Tests:\n \"\"\" Base test functions for all encoding/decoding functions \"\"\"\n def test_decode(self):\n \"\"\" S1: simple... | [
[
"numpy.testing.assert_array_equal",
"numpy.array",
"numpy.random.randint"
]
] |
JWKennington/CourseNR | [
"c0f62c0e129fd44c3b1c006fce62e4528e59cd8b"
] | [
"nrpsu/hw1/problem_2.py"
] | [
"\"\"\"This script uses the analytical solutions for the Oppenheimer-Snyder\nmodel of spherical dust collapse to plot geodesics \"\"\"\n\nimport numpy\nimport plotly.graph_objects as go\n\n\ndef star_rad(conf_time: float, rad_0: float) -> float:\n \"\"\"Surface of star radial coordinate in conformal time\"\"\"\n... | [
[
"numpy.sqrt",
"numpy.arange",
"numpy.cos",
"numpy.sin",
"numpy.array"
]
] |
MatteoArm/tensorflow | [
"a39ac9de5fdbbb00c7e9b6896c49ed29c2ce2e15"
] | [
"tensorflow/python/keras/engine/functional_test.py"
] | [
"# Copyright 2016 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.keras.engine.sequential.Sequential",
"tensorflow.python.keras.layers.Lambda",
"tensorflow.python.framework.tensor_shape.TensorShape",
"tensorflow.python.ops.array_ops.constant",
"tensorflow.python.keras.layers.Dense",
"tensorflow.python.ops.state_ops.assign_add",
"te... |
joel-shor/addons | [
"27bbb3dd6bb8394a3793ef7a123ed730951f41e4",
"de99c6dd904c475c5c95726911f4aac447c13361",
"b59f0e89ca09837808331be1eee8ae8df8eb9355"
] | [
"tensorflow_addons/activations/hardshrink_test.py",
"tensorflow_addons/text/crf_test.py",
"tensorflow_addons/losses/focal_loss.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.convert_to_tensor",
"tensorflow.constant",
"numpy.random.seed",
"tensorflow.test.main",
"tensorflow.ones",
"tensorflow.test.compute_gradient",
"numpy.random.uniform",
"tensorflow.GradientTape"
],
[
"tensorflow.constant",
"tensorflow.random.uniform",
"ten... |
narutowang/indrnn | [
"434e1200b5e742a0eac92bed661c69e97b8b8711"
] | [
"ptb/ptb_word_lm.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.device",
"tensorflow.concat",
"tensorflow.python.client.device_lib.list_local_devices",
"tensorflow.zeros",
"tensorflow.reduce_sum",
"numpy.exp",
"tensorflow.summary.scalar",
"tensorflow.Graph",
"tensorflow.Variable",
"tensorflow.random_uniform_initializer",
... |
bennorth/python-xml-serdes | [
"fb1c44e1630bdbf1fc0ae97a51fb5adac498ffc0"
] | [
"tests/test_intrusive.py"
] | [
"from __future__ import print_function\n\nimport pytest\n\nfrom xmlserdes import XMLSerializable, XMLSerializableNamedTuple\nfrom xmlserdes.utils import str_from_xml_elt\nfrom xmlserdes.errors import XMLSerDesError, XMLSerDesWrongChildrenError\n\n\nfrom collections import OrderedDict\nimport numpy as np\nfrom lxml ... | [
[
"numpy.arange",
"numpy.array"
]
] |
dhall1995/Hi_C_GNN | [
"e185df3c30cbd67e8860289f5877a91ad0a68181"
] | [
"GrapHiC/utils/parse_cooler.py"
] | [
"from typing import Dict, List, Tuple, Optional\n\nfrom cooler import Cooler\nimport numpy as np\n\n\ndef parse_cooler(\n cooler_file: str, \n regions: Dict[str, np.ndarray]\n) -> Tuple[Cooler, List[np.ndarray]]:\n # Load cooler\n c = Cooler(cooler_file)\n\n # Fetch relevant bin_ids from the cooler f... | [
[
"numpy.array",
"numpy.where",
"numpy.diff"
]
] |
ftnext/atmaCup10-paintings-likes | [
"ef152d761eb5bd4abfa6c9c24e9b14adf86b5a6c"
] | [
"word2vec.py"
] | [
"\"\"\"object_id, nameの形式のCSVについて、object_idごとに固定長のベクトル表現を作る\"\"\"\n\nimport argparse\nimport hashlib\nimport os\nimport pickle\nimport re\nfrom collections import defaultdict\nfrom itertools import combinations\nfrom pathlib import Path\n\nimport numpy as np\nfrom gensim.models import word2vec\nfrom tqdm import tqd... | [
[
"numpy.mean"
]
] |
leandreeberhard/model_stacking | [
"40fc62b838638efec559386c88bbf780d16fe4db"
] | [
"knn_fit.py"
] | [
"########################################\n# KNN classifier\n########################################\nfrom sklearn.neighbors import KNeighborsClassifier\n\nX_train, X_test, y_train, y_test = train_test_split(train_data, train_labels, test_size=0.3)\n\nknn_fitter = KNeighborsClassifier(n_neighbors=5, weights='unifo... | [
[
"sklearn.neighbors.KNeighborsClassifier"
]
] |
Matt711/cudf | [
"4c9ef5161268e2486938546deef00f7fc84c9a95"
] | [
"python/cudf/cudf/tests/test_applymap.py"
] | [
"# Copyright (c) 2018-2021, NVIDIA CORPORATION.\n\nfrom itertools import product\nfrom math import floor\n\nimport numpy as np\nimport pytest\n\nfrom cudf import Series\nfrom cudf.testing import _utils as utils\n\n\n@pytest.mark.parametrize(\n \"nelem,masked\", list(product([2, 10, 100, 1000], [True, False]))\n)... | [
[
"numpy.random.random",
"numpy.random.seed",
"numpy.round",
"numpy.testing.assert_array_equal",
"numpy.array",
"numpy.testing.assert_array_almost_equal"
]
] |
sealneaward/uoit-machine-learning | [
"e80c3b5ad95bd152ad487454e8c0a61e702ebcfc"
] | [
"tutorials/scraping/package/reference/utils.py"
] | [
"# import libraries\nimport pandas as pd\nimport re\nimport math\n\nPLAYER_RE = r'([A-Z].\\s)\\w+'\n\ndef _minute(play):\n \"\"\"\n Get int of minute (out of 48) that it occurs in\n \"\"\"\n minute = (12 - int(play['TIME'].split(':')[0])) + ((int(play['QUARTER']) - 1) * 12) - 1\n return minute\n\n\n#... | [
[
"pandas.read_html",
"pandas.isnull",
"pandas.DataFrame"
]
] |
kimcando/PyTorch-BayesianCNN | [
"ddc4c10c9e5cb33df2e0eaa97bb3ea6991b0081e"
] | [
"layers/BBB_MCMF_LRT/BBBConv.py"
] | [
"import sys\nsys.path.append(\"..\")\n\nimport math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.nn import Parameter\n\nimport utils\nfrom metrics import calculate_kl as KL_DIV\nimport config_bayesian as cfg\nfrom ..misc import ModuleWrapper\n\n\nclass BBBConv2d(ModuleWrapper):\... | [
[
"torch.Tensor",
"torch.sqrt",
"torch.nn.functional.conv2d",
"torch.exp",
"torch.cuda.is_available"
]
] |
kbardool/CarND-Advanced-Lane-Lines | [
"2c3a0b4c1623c4e303b3833c166627a56c260d71"
] | [
"common/plots.py"
] | [
"import numpy as np\nimport matplotlib.image as mpimg\nimport matplotlib.pyplot as plt\n\n\ndef plot_1(pl, legend = 'best', size=(15,7)):\n plt.figure(figsize=size)\n ax = plt.gca()\n min_x = min(pl.imgUndistStats['RGB'])\n max_x = max(pl.imgUndistStats['RGB'])\n len_x = len(pl.imgUndistStats['RGB'])... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.axhline",
"matplotlib.pyplot.axvline",
"numpy.clip",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.hlines",
"matplotlib.pyplot.axhspan",
"matplotlib.pyplot.text",
"numpy.array",
"matplotlib.pyplot.fi... |
Nikhil-Wani/Intelligent-Safety-Driving-Vechicle | [
"6c96a49735291c9a71176eabb3df13b4cb1670a5",
"6c96a49735291c9a71176eabb3df13b4cb1670a5"
] | [
"Game codes/exp4.py",
"Game codes/exp6.py"
] | [
"import numpy as np\r\nfrom PIL import ImageGrab\r\nimport cv2\r\nimport time\r\nfrom directkeys import ReleaseKey, PressKey, W, A, S, D\r\nimport pyautogui\r\n\r\n\r\ndef draw_lines(img, lines):\r\n try:\r\n for line in lines:\r\n coords = line[0]\r\n cv2.line(img, (coords[0],coords... | [
[
"numpy.array",
"numpy.zeros_like"
],
[
"numpy.linalg.lstsq",
"numpy.array",
"numpy.zeros_like"
]
] |
kirtan2605/Coursework_Codes | [
"3455496e8ec0ae3a576cb3fc3b2ed01a055149c5"
] | [
"AS2101_Labwork/4.Submissions/Task 5/gs_orth.py"
] | [
"import numpy as np\nimport math\n\ndef normalize(column):\n \"\"\"\n this function takes a array and normalizes it\n\n input : array\n\n output : normalized array\n \"\"\"\n sq_sum = 0\n for ele in column:\n sq_sum = sq_sum + (ele*ele)\n norm_column = column/math.sqrt(sq_sum)\n\n ... | [
[
"numpy.dot",
"numpy.array"
]
] |
xia-huang-411303/EasyRec | [
"7b2050dddc0bfec9e551e2199a36414a3ee82588"
] | [
"easy_rec/python/layers/dnn.py"
] | [
"# -*- encoding:utf-8 -*-\n# Copyright (c) Alibaba, Inc. and its affiliates.\nimport logging\n\nimport tensorflow as tf\n\nfrom easy_rec.python.utils.load_class import load_by_path\n\nif tf.__version__ >= '2.0':\n tf = tf.compat.v1\n\n\nclass DNN:\n\n def __init__(self, dnn_config, l2_reg, name='dnn', is_training... | [
[
"tensorflow.layers.batch_normalization",
"tensorflow.layers.dense",
"tensorflow.nn.dropout"
]
] |
yxxxxx38324/YOLOX | [
"dd1f99ce228b0c5ad0c5b309c072c9df134ce1ae"
] | [
"tools/train.py"
] | [
"#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n# Copyright (c) Megvii, Inc. and its affiliates.\nimport pdb\nimport argparse\nimport random\nimport warnings\nfrom loguru import logger\n\nimport torch\nimport torch.backends.cudnn as cudnn\n\nfrom yolox.core import Trainer, launch\nfrom yolox.exp import get_exp\n\n... | [
[
"torch.manual_seed",
"torch.cuda.device_count"
]
] |
MaxBasov/IML.HUJI | [
"2e2982876f9b13ecd204170246a13356d67273f5"
] | [
"IMLearn/learners/regressors/polynomial_fitting.py"
] | [
"from __future__ import annotations\nfrom typing import NoReturn\nfrom . import LinearRegression\nfrom ...base import BaseEstimator\nimport numpy as np\n\n\nclass PolynomialFitting(BaseEstimator):\n \"\"\"\n Polynomial Fitting using Least Squares estimation\n \"\"\"\n def __init__(self, k: int) -> Polyn... | [
[
"numpy.vander"
]
] |
h-mayorquin/camp_india_2016 | [
"a8bf8db7778c39c7ca959a7f876c1aa85f2cae8b"
] | [
"project3_sustained_activity/neuron_model.py"
] | [
"import numpy as np\nfrom brian2 import *\nimport seaborn as sns\nsns.set(font_scale=2.0)\n\nN = 1\n\n# Neuron Parameters\ng_l = 0.05 * msiemens / cm2\nCm = 1.0 * ufarad / cm2 # Specific membrane capacitance\nE_l = -60 * mV # Resting potential\nV_t = -50 * mV # Threshold\ntau_w = 600 * ms # Adaptation time con... | [
[
"numpy.arange",
"numpy.array"
]
] |
flabby1976/Strava-local-heatmap | [
"89163b6b4b2a6573607001864f24e867efadc50c"
] | [
"strava_local_heatmap.py"
] | [
"# Copyright (c) 2018 Remi Salmon\r\n# \r\n# Permission is hereby granted, free of charge, to any person obtaining a copy\r\n# of this software and associated documentation files (the \"Software\"), to deal\r\n# in the Software without restriction, including without limitation the rights\r\n# to use, copy, modify, ... | [
[
"matplotlib.pyplot.imsave",
"numpy.radians",
"scipy.ndimage.gaussian_filter",
"numpy.logical_and",
"matplotlib.pyplot.imread",
"numpy.degrees",
"matplotlib.pyplot.get_cmap",
"numpy.dstack",
"numpy.sinh",
"numpy.round",
"numpy.tan",
"numpy.cos",
"numpy.array",
... |
QianWanghhu/predict_uq | [
"9d2e9c0a9cddef901ef89985497fa94eb36c4c03"
] | [
"src/gp_build.py"
] | [
"#!/usr/bin/env python\nfrom multiprocessing import Pool\nimport numpy as np\nimport os\nimport matplotlib.pyplot as plt\nfrom functools import partial\nimport copy\nimport pandas as pd\nimport pickle\n\nfrom scipy import stats\n# from scipy.optimize import root\nfrom scipy.optimize import bisect\n\nfrom sklearn.ga... | [
[
"pandas.concat",
"pandas.read_csv",
"numpy.abs",
"numpy.asarray",
"numpy.arange",
"numpy.mod",
"numpy.cumsum",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"numpy.ones",
"numpy.where",
"numpy.exp",
"numpy.load",
"sklearn.gaussian_process.kernel... |
Lichang000net/Landslide-classification | [
"1c23251face31b913aca3c3e1cd31555fe77adf8"
] | [
"utils.py"
] | [
"import numpy as np\r\n\r\ndef calculate_all_prediction(confMatrix):\r\n '''\r\n 计算总精度：对角线上所有值除以总数\r\n '''\r\n total_sum = confMatrix.sum()\r\n correct_sum = (np.diag(confMatrix)).sum()\r\n prediction = float(correct_sum) / float(total_sum)\r\n return prediction"
] | [
[
"numpy.diag"
]
] |
litian96/fair-federated-learning | [
"f09797113147b5ae66eb0348e93f575d5d63baed"
] | [
"flearn/trainers/qffedavg.py"
] | [
"import numpy as np\nfrom tqdm import trange, tqdm\nimport tensorflow as tf\n\nfrom .fedbase import BaseFedarated\nfrom flearn.utils.tf_utils import process_grad, cosine_sim, softmax, norm_grad\nfrom flearn.utils.model_utils import batch_data, gen_batch, gen_epoch\n\n\nclass Server(BaseFedarated):\n def __init__... | [
[
"numpy.float_power",
"numpy.asarray",
"numpy.ones",
"tensorflow.train.GradientDescentOptimizer",
"numpy.array"
]
] |
qutang/arus | [
"ee422bbadc72635037944359d00475f698e8fc61"
] | [
"arus/models/splitter.py"
] | [
"from sklearn.model_selection import TimeSeriesSplit\n\n\nclass TimeSeriesEpisodeSplit:\n def __init__(self, fcs_df, fs_names, task_name, n_split=5):\n self.fs_names = fs_names\n self.task_name = task_name\n self.episodes = fcs_df.groupby(task_name)\n self.spliters = {}\n self.... | [
[
"sklearn.model_selection.TimeSeriesSplit"
]
] |
saustinp/3D-CG | [
"8d3e161674273649af1f23b2a0e1d5100971477a"
] | [
"master/pascalindex.py"
] | [
"import numpy as np\n\ndef pascalindex2d(k):\n \"\"\"\n The purpose of this function is to prepare a set of combinations of m and n for the creation of the Jacobi polynomials that satisfy (m+n)<=k.\n k: int, max order of the Jacobi polynomial desired\n\n Returns: array of (ncomb x 2), where each row cor... | [
[
"numpy.fliplr",
"numpy.arange",
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
flekschas/PerceptualSimilarity | [
"3cfaf54a3f3edf55df4ed85a37bbe96321c6d094"
] | [
"models/dist_model.py"
] | [
"\nfrom __future__ import absolute_import\n\nimport numpy as np\nimport torch\nimport os\nfrom collections import OrderedDict\nfrom torch.autograd import Variable\nfrom .base_model import BaseModel\nfrom scipy.ndimage import zoom\nfrom tqdm import tqdm\n\nfrom . import networks_basic as networks\nimport models as u... | [
[
"torch.optim.Adam",
"torch.mean",
"torch.clamp",
"torch.load",
"scipy.ndimage.zoom",
"numpy.cumsum",
"numpy.mean",
"numpy.argsort",
"torch.nn.DataParallel",
"numpy.array",
"numpy.sum",
"torch.autograd.Variable"
]
] |
tin6150/urbansim | [
"0db75668ada0005352b7c7e0a405265f78ccadd7"
] | [
"urbansim/urbanchoice/tests/test_mnl.py"
] | [
"\"\"\"\nTest data and results for this are generated\nby the R script at data/mnl_tests.R.\n\n\"\"\"\nfrom __future__ import division\n\nimport os.path\n\nimport numpy as np\nimport numpy.testing as npt\nimport pandas as pd\nimport pytest\nfrom patsy import dmatrix\n\nfrom .. import mnl\n\n\n@pytest.fixture\ndef n... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.Series",
"numpy.tile",
"pandas.DataFrame",
"numpy.testing.assert_allclose",
"numpy.array"
]
] |
TimS70/WebET_Analysis | [
"32fc2e1b70c2dad5637ee1614a6a651bc8d458b4"
] | [
"utils/rearrange.py"
] | [
"import numpy as np\n\n\ndef pivot_outcome_by_factor(data, factor, outcome):\n if len(data) > len(data['run_id'].unique()):\n outcomes_by_factor = data.groupby(\n ['run_id', factor],\n as_index=False)[outcome].mean()\n else:\n outcomes_by_factor = data[\n np.appe... | [
[
"numpy.append"
]
] |
CorcovadoMing/box-convolutions | [
"9ef77b9ad4d2bab48327b4227a3847ae87da629d"
] | [
"examples/Cityscapes/convnet-runtime-benchmark.py"
] | [
"\"\"\"\n The script I use for benchmarking.\n \n Architectures are optimized for inference as if they were deployed in\n production: BatchNorms and Dropouts are absorbed, \"void\" class is removed.\n \n I managed to fully reproduce Torch7 runtimes from the paper for ENet\n and ERFNet; however,... | [
[
"torch.nn.Sequential",
"torch.cuda.synchronize",
"torch.manual_seed",
"torch.no_grad",
"torch.set_num_threads",
"torch.rand"
]
] |
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