repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
0xbadc0ffe/FedSimulate | [
"1dfa6554c341ea46c02986fca1b61148ea8cd1f3"
] | [
"FedSimulate.py"
] | [
"from __future__ import print_function, division\nfrom cProfile import label\nfrom logging import raiseExceptions\n\nfrom typing import Mapping, Union, Optional, Callable, Dict\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nimport os\nfrom tqd... | [
[
"matplotlib.pyplot.legend",
"numpy.sum",
"matplotlib.pyplot.title",
"torch.zeros",
"torch.argmax",
"matplotlib.pyplot.plot",
"numpy.random.uniform",
"matplotlib.pyplot.ylabel",
"numpy.round",
"torch.arange",
"torch.device",
"matplotlib.pyplot.xlabel",
"matplotli... |
ygCoconut/volume2stl | [
"bd95fc39620afd21ce08c8c805ac213583d9daaa"
] | [
"1_benchmarking/spinecode/skel.py"
] | [
"import os\nimport collections\nfrom collections import namedtuple\n\nimport scipy.sparse as sp\nfrom scipy.sparse import csgraph\nfrom scipy.spatial import KDTree\nfrom scipy.ndimage.morphology import distance_transform_edt\nimport numpy as np\nimport h5py\nimport kimimaro\nimport cloudvolume as cv\n\nfrom . impor... | [
[
"numpy.hstack",
"scipy.sparse.csgraph.depth_first_order",
"numpy.nonzero",
"scipy.sparse.csgraph.breadth_first_order",
"numpy.ones",
"numpy.all",
"scipy.spatial.KDTree",
"numpy.argmin",
"numpy.argmax",
"numpy.zeros",
"numpy.isin",
"scipy.ndimage.morphology.distance_... |
zakharovas/RecSys2018 | [
"f58ed6716213267ad2cde30d1ff677abc5da96ba"
] | [
"recsys/svd_pp/model.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\nfrom json import loads\nfrom json import dumps\n\nfrom tqdm import tqdm\nfrom itertools import count\nfrom functools import partial\n\n\n# Model params:\nuser_count = 17259\nitem_count = 2149247\n\nbatch_size = 10000\n\nfactor_dim = 32\n\n# Dataset initialization:\n\n... | [
[
"tensorflow.get_variable",
"tensorflow.multiply",
"tensorflow.zeros",
"tensorflow.sigmoid",
"tensorflow.placeholder",
"tensorflow.ConfigProto",
"tensorflow.global_variables_initializer",
"tensorflow.train.AdamOptimizer",
"tensorflow.Session",
"tensorflow.nn.embedding_lookup... |
ndow33/DS-Unit-3-Sprint-2-SQL-and-Databases | [
"14cfe850e68e134057fe56c1fea99c32c4473859"
] | [
"module2-sql-for-analysis/titanic.py"
] | [
"import os\nimport psycopg2\nfrom psycopg2.extras import DictCursor\nfrom psycopg2.extras import execute_values\nfrom dotenv import load_dotenv\nimport pandas as pd\nimport json\nimport numpy as np\n\nload_dotenv() # reads the contents of the .env file and adds them to the environment\n\npsycopg2.extensions.registe... | [
[
"pandas.read_csv"
]
] |
Noonewin/ML_scripts | [
"a7019a2c8f138f3622979afd05d435dbeb319f15"
] | [
"clustering/clustering.py"
] | [
"import os\nimport sys\nimport scipy as sp\nfrom matplotlib.mlab import dist\nfrom sklearn.feature_extraction.text import CountVectorizer\n\nvectorizer = CountVectorizer(min_df=1)\n\n# content = [\"How to format my hard disk\", \" Hard disk format problems \"]\n# X = vectorizer.fit_transform(content)\n# print(vecto... | [
[
"sklearn.feature_extraction.text.CountVectorizer",
"matplotlib.mlab.dist"
]
] |
milwaukee-city-data/budget | [
"1e07b72d0d58abf2e2dcef875d52e1a2af07b252"
] | [
"carceral/trend_with_rate.py"
] | [
"import csv\nimport os\n\nfrom scipy.signal import savgol_filter\n\nfrom gwpy.time import to_gps\nfrom gwpy.timeseries import TimeSeries\n\nfrom matplotlib import use\nuse(\"Agg\")\n\nfrom matplotlib import font_manager, pyplot, rcParams\n\n\n# set font properties\nfont_dir = os.path.join(os.environ[\"HOME\"], \"Do... | [
[
"matplotlib.font_manager.fontManager.addfont",
"matplotlib.use",
"matplotlib.pyplot.subplots",
"scipy.signal.savgol_filter",
"matplotlib.font_manager.findSystemFonts"
]
] |
ogierpaul/suricate | [
"fd43627e5d2a92fe4bf7b562f65ab89ec07ee49c"
] | [
"tests/pipeindexer/test_pruningpipe.py"
] | [
"from suricate.pipeline.pruningpipe import PruningPipe\nfrom suricate.data.companies import getXst, getytrue\nfrom suricate.explore import Explorer, KBinsCluster\nfrom suricate.dftransformers import DfConnector, VectorizerConnector, ExactConnector\nfrom suricate.sbstransformers import SbsApplyComparator\nfrom sklea... | [
[
"sklearn.pipeline.FeatureUnion",
"sklearn.linear_model.LogisticRegressionCV",
"sklearn.metrics.balanced_accuracy_score",
"sklearn.metrics.precision_score",
"sklearn.impute.SimpleImputer",
"pandas.datetime.now",
"sklearn.metrics.recall_score"
]
] |
Titousensei/pytext-1 | [
"6ea5ce52f5070fc10ac20732f994296c4d445207"
] | [
"pytext/models/representations/pure_doc_attention.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\nfrom typing import Any, Optional, Union\n\nimport torch\nimport torch.nn as nn\nfrom pytext.config import ConfigBase\nfrom pytext.models.decoders.mlp_decoder import MLPDecoder\nfrom pytext.models.module import create_mo... | [
[
"torch.nn.Dropout"
]
] |
LeonOtis/pyscf | [
"98ba8106396ac4c90dc65207059773ce048b0ebf",
"98ba8106396ac4c90dc65207059773ce048b0ebf"
] | [
"pyscf/scf/test/test_uhf.py",
"pyscf/dft/r_numint.py"
] | [
"#!/usr/bin/env python\n# Copyright 2014-2019 The PySCF Developers. 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/LIC... | [
[
"numpy.random.random",
"numpy.allclose",
"numpy.random.seed",
"numpy.einsum",
"numpy.arange",
"numpy.eye",
"numpy.linalg.norm",
"numpy.array",
"numpy.zeros",
"numpy.trace"
],
[
"numpy.einsum",
"numpy.asarray",
"numpy.empty_like",
"numpy.ndarray",
"nu... |
zouwenjiao/DSCI_522_Group304 | [
"fe03bcff23cced5b9934e959355e3bb4e4af007d"
] | [
"src/add_subgroup_info.py"
] | [
"# author: Group 304 (Anny Chih)\n# date: 2020-02-04\n\n\"\"\"This script takes in a cleaned datafile and \nadds a column of values indicating if the school has BOTH Aboriginal and Non Aboriginal Students\n\nUsage: add_subgroup_info.py --clean_data=<clean_data> --new_data=<new_data> \n\nOptions:\n--clean_data=<clea... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
alphadadajuju/online_action_two_stream | [
"b6d717f89e5c36b3c7929b651b30fb1125fc5d42"
] | [
"train-ucf24.py"
] | [
"\n\"\"\" Adapted from:\n @longcw faster_rcnn_pytorch: https://github.com/longcw/faster_rcnn_pytorch\n @rbgirshick py-faster-rcnn https://github.com/rbgirshick/py-faster-rcnn\n Which was adopated by: Ellis Brown, Max deGroot\n https://github.com/amdegroot/ssd.pytorch\n\n Further:\n Updated by Gurk... | [
[
"torch.optim.lr_scheduler.MultiStepLR",
"torch.set_default_tensor_type",
"torch.cuda.synchronize",
"numpy.hstack",
"torch.ones",
"numpy.random.seed",
"torch.load",
"torch.zeros",
"torch.manual_seed",
"numpy.asarray",
"torch.utils.data.DataLoader",
"torch.cuda.manual... |
mohamedameen93/An-Autonomous-Vehicle-System-For-Udacity-s-Carla | [
"a7ecd632c5f91f2d6037cbcb0cabff94e6e74869"
] | [
"ros/src/tl_detector/light_classification/tl_classifier.py"
] | [
"import tensorflow as tf\nfrom styx_msgs.msg import TrafficLight\n\n\nPROTOBUG_GRAPH_FILE = 'light_classification/retrained_SSD/frozen_inference_graph.pb'\n\n\nclass TLClassifier(object):\n def __init__(self):\n graph = tf.Graph()\n with graph.as_default():\n od_graph_def = tf.GraphDef()... | [
[
"tensorflow.Graph",
"tensorflow.import_graph_def",
"tensorflow.gfile.GFile",
"tensorflow.Session",
"tensorflow.GraphDef"
]
] |
haokui/octobus | [
"66ba4aaf24cc43cee0f1fec226df09a451b513c1"
] | [
"octobus/base.py"
] | [
"\"\"\"\ncore APIs of the data models\n\"\"\"\nfrom collections import defaultdict\nimport numpy as np\nimport pandas as pd\n\n\nclass FeatureSet:\n \"\"\"\n currently, just a named list of feature names\n \"\"\"\n def __init__(self, feature_names=None, name=None):\n self.feature_names = feature_... | [
[
"pandas.concat",
"pandas.Series"
]
] |
rajvi-tiwari/Vision_for_trash_bot | [
"6ea82d0281d5ef1f6bbc6ad1bce07b43d74cff13"
] | [
"Object_detection_video.py"
] | [
"# This program uses a TensorFlow-trained classifier to perform object detection.\r\n# It loads the classifier and uses it to perform object detection on a video.\r\n# It draws boxes, scores, and labels around the objects of interest in each\r\n# frame of the video.\r\n\r\n## Some of the code is copied from Google'... | [
[
"tensorflow.Graph",
"numpy.expand_dims",
"tensorflow.import_graph_def",
"tensorflow.gfile.GFile",
"numpy.squeeze",
"tensorflow.Session",
"tensorflow.GraphDef"
]
] |
chahuja/aisle | [
"08d854f837767129eb454d32db8814d3b51a071e"
] | [
"src/data/transform.py"
] | [
"import os\nimport sys\nsys.path.append(os.path.dirname(os.path.abspath(__file__)))\nsys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))\n\nimport pickle as pkl\nfrom pathlib import Path\nfrom tqdm import tqdm\nfrom pathlib import Path\nimport sklearn.cluster\nimport sklearn.mixture\nimport... | [
[
"torch.linspace",
"torch.ones",
"torch.Tensor",
"torch.cat",
"torch.zeros",
"torch.utils.data.DataLoader",
"torch.from_numpy",
"torch.zeros_like",
"torch.no_grad",
"numpy.array"
]
] |
sarmstr5/kaggle_intel_mobleODT_cervix_classification | [
"800e713a30827fc3701525b8e64c39ae97b7634a"
] | [
"src/data_explore.py"
] | [
"import platform\nimport os, pickle\nimport pandas as pd\n\n\n\n\ndef get_file_paths():\n if 'c001' in platform.node(): \n# colfax cluster\n abspath_dataset_dir_train_1 = '/data/kaggle/train/Type_1'\n abspath_dataset_dir_train_2 = '/data/kaggle/train/Type_2'\n abspath_dataset_dir_train_3 =... | [
[
"pandas.Series",
"pandas.DataFrame"
]
] |
BloodAxe/segmentation-networks-benchmark | [
"2e3feb560102230be9369ab442b4a59cc86dff61"
] | [
"lib/models/dilated_linknet.py"
] | [
"from torch import nn\nimport torch\nfrom torchvision import models\nimport torchvision\nfrom torch.nn import functional as F\n\nfrom lib.models.dilated_resnet import dilated_resnet34\n\n\nclass DecoderBlockLinkNet(nn.Module):\n def __init__(self, in_channels, n_filters):\n super().__init__()\n\n s... | [
[
"torch.nn.Dropout2d",
"torch.nn.ConvTranspose2d",
"torch.nn.Conv2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
]
] |
manishgit138/numcodecs | [
"322baaca4162c43a6e37d4f4c0d0f0fd51faa554"
] | [
"numcodecs/tests/test_shuffle.py"
] | [
"from multiprocessing import Pool\nfrom multiprocessing.pool import ThreadPool\n\n\nimport numpy as np\nimport pytest\n\n\ntry:\n from numcodecs.shuffle import Shuffle\nexcept ImportError: # pragma: no cover\n pytest.skip(\n \"numcodecs.shuffle not available\", allow_module_level=True\n )\n\n\nfrom... | [
[
"numpy.linspace",
"numpy.random.choice",
"numpy.arange",
"numpy.frombuffer",
"numpy.random.normal",
"numpy.array",
"numpy.random.randint"
]
] |
beark007/smarts_ppo | [
"8f6aa33a6fcfb74dc0b8e92951d6b70d6e2874de"
] | [
"benchmark/agents/maac/tf_policy.py"
] | [
"# MIT License\n#\n# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.\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 without restriction, including without ... | [
[
"numpy.product",
"numpy.eye",
"numpy.concatenate",
"numpy.zeros_like",
"numpy.zeros"
]
] |
thcasey3/DeerLab | [
"27ff814fb8c2771740bd7928f283c1f70e88215c"
] | [
"deerlab/model.py"
] | [
"# model.py - DeerLab's modelling interface\r\n# ---------------------------------------------------------------------------\r\n# This file is a part of DeerLab. License is MIT (see LICENSE.md). \r\n# Copyright(c) 2019-2021: Luis Fabregas, Stefan Stoll and other contributors.\r\n\r\nimport numpy as np\r\nfrom scipy... | [
[
"numpy.diag",
"numpy.expand_dims",
"numpy.asarray",
"numpy.squeeze",
"numpy.concatenate",
"numpy.all",
"numpy.any",
"numpy.where",
"numpy.testing.assert_equal",
"numpy.hstack",
"numpy.unique",
"numpy.arange",
"numpy.linalg.slogdet",
"numpy.full",
"numpy.... |
loosolab/Datenanalyse-2021 | [
"2a94f6153a504bd6f1ee205eeeab279b20fb847d"
] | [
"wp3/DefiningTF.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Jan 20 19:51:13 2022\n\n@author: Moritz Hobein\n\"\"\"\nimport pandas as pd\nimport argparse\n\n#parser for using the tool via command-line interface\ndef cliParser():\n parser = argparse.ArgumentParser(description='Script to extract the transcription factors that... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
maslankam/Photometric-Stereo-Assistent | [
"e3af46c8a984df10f37747b77630cdb5125e0b7f"
] | [
"Include/project/light_model.py"
] | [
"from Include.project.segment import Segment\nfrom Include.project.image_reader import ImageReader\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom pathlib import Path\nfrom mpl_toolkits.mplot3d import Axes3D\nimport shutil\n\nimport os, cv2, csv, math\n\n\nclass LightModel(Segment):\n \"\"\"LightMod... | [
[
"numpy.dot",
"matplotlib.pyplot.ylim",
"numpy.max",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.quiver",
"numpy.ndenumerate",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
pavansainov15/MatchPrediction | [
"79a3782dae086586ac699947d66c75f7286ede1d"
] | [
"scrape_data.py"
] | [
"import pandas as pd\nfrom bs4 import BeautifulSoup\nimport requests\n\n# For player ranks\nurl = 'http://www.cricmetric.com/ipl/ranks/'\npd.read_html(requests.get(url).content)[-1].to_csv(\"./Dataset/_player_rank.csv\", index=False, header=None)\n\n# Store the sum of EF score by team.\ndata = pd.read_csv('./Datase... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
AroosaIjaz/Mypennylane | [
"40f2219b5e048d4bd93df815811ca5ed3f5327fa"
] | [
"pennylane/plugins/default_gaussian.py"
] | [
"# Copyright 2018 Xanadu Quantum Technologies Inc.\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 applica... | [
[
"numpy.sqrt",
"numpy.asarray",
"numpy.zeros_like",
"numpy.any",
"numpy.exp",
"numpy.trace",
"numpy.hstack",
"numpy.arange",
"numpy.sin",
"numpy.linalg.det",
"numpy.block",
"scipy.special.factorial",
"numpy.zeros",
"numpy.cosh",
"numpy.linalg.inv",
"n... |
LiangbeiXu/edm2016 | [
"728e3605d1af5113ed75883f11fea2f1271fd427"
] | [
"rnn_prof/run_irt.py"
] | [
"\"\"\"\nScript for running basic online IRT\n\"\"\"\nimport logging\n\nimport numpy as np\nimport pandas as pd\nfrom scipy import sparse as sp\n\nfrom .data.constants import (ITEM_IDX_KEY, TEMPLATE_IDX_KEY, USER_IDX_KEY, CORRECT_KEY,\n CONCEPT_IDX_KEY)\nfrom .data.wrapper import DEFAULT... | [
[
"numpy.random.seed",
"scipy.sparse.eye",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.array"
]
] |
epfml/relaysgd | [
"536f809f2a5fed5f5004b3f49857d67462ac89d2",
"536f809f2a5fed5f5004b3f49857d67462ac89d2"
] | [
"tasks/deit/models.py",
"tasks/utils/non_iid_dirichlet.py"
] | [
"# Copyright (c) 2015-present, Facebook, Inc.\n# All rights reserved.\n# https://github.com/facebookresearch/deit/blob/cb29b5efd522a0ac83d64aa8b41fe27cead3a030/models.py\nimport torch\nimport torch.nn as nn\nfrom functools import partial\n\nfrom timm.models.vision_transformer import VisionTransformer, _cfg\nfrom ti... | [
[
"torch.zeros",
"torch.cat",
"torch.nn.Linear",
"torch.nn.Identity",
"torch.hub.load_state_dict_from_url"
],
[
"numpy.split",
"numpy.unique",
"numpy.cumsum",
"numpy.repeat",
"numpy.array",
"numpy.where",
"numpy.random.RandomState"
]
] |
juliendehos/nevergrad | [
"b31a66bdc883e29a6c8572e341b4b56cc4157a9d"
] | [
"nevergrad/benchmark/test_plotting.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\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\nfrom . import plotting # pylint: disable=wrong-import-position, wrong-import-order\nfrom unittest.mock import ... | [
[
"numpy.testing.assert_equal",
"matplotlib.use",
"pandas.DataFrame",
"numpy.testing.assert_array_equal",
"numpy.testing.assert_almost_equal",
"numpy.identity"
]
] |
HDI-Project/DataTracer | [
"4bb0906f1716bbcfeb0881cade5d6d47bca90764"
] | [
"datatracer/column_map/basic.py"
] | [
"import logging\n\nfrom sklearn.ensemble import RandomForestRegressor\n\nfrom datatracer.column_map.base import ColumnMapSolver\nfrom datatracer.column_map.transformer import Transformer\n\nLOGGER = logging.getLogger(__name__)\n\n\nclass BasicColumnMapSolver(ColumnMapSolver):\n \"\"\"Basic Solver for the data li... | [
[
"sklearn.ensemble.RandomForestRegressor"
]
] |
Tongzhenguo/bpr-spark | [
"5ee01ba09b2dc7247052296b6097eb63d52f0dca"
] | [
"bpr.py"
] | [
"import random\nfrom tqdm import tqdm\nimport numpy as np\n\n\ndef _gradient_single_point(user_id, prod_id, prod_id_neg,\n user_mat, prod_mat, lambda_reg, alpha):\n\n x_uij = user_mat[user_id].dot(prod_mat[prod_id]) - \\\n user_mat[user_id].dot(prod_mat[prod_id_neg])\n\n step_... | [
[
"numpy.random.uniform",
"numpy.exp",
"numpy.random.randint"
]
] |
pierreablin/smica | [
"f56d4fac065f88788a0682e68f0121902601f161"
] | [
"smica/core_smican.py"
] | [
"import numpy as np\n\nfrom sklearn.utils import check_random_state\n\nfrom .core_fitter import CovarianceFitNoise\nfrom .utils import fourier_sampling, itakura\n\neps = 1e-12\n\n\ndef wiener(A, powers, noise_inv):\n '''\n The Wiener filter\n '''\n C = np.linalg.pinv(A.T.dot(noise_inv.dot(A)) +\n ... | [
[
"numpy.diag",
"numpy.dot",
"numpy.conj",
"numpy.linalg.inv",
"numpy.arange",
"numpy.fft.ifft",
"numpy.linalg.pinv",
"numpy.mean",
"numpy.zeros",
"sklearn.utils.check_random_state"
]
] |
xuyu0010/ARID_v1 | [
"b03d0975f41547e8aa78929b8e26a62248f8e18f"
] | [
"network/inception_v1_i3d.py"
] | [
"import logging\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport os\n# from mmcv.cnn import constant_init, kaiming_init\n# from mmcv.runner import load_checkpoint\n\n# from ...registry import BACKBONES\n# from mmaction.ops.reflection_pad3d import reflection_pad3d\n\ntry:\n from . i... | [
[
"torch.cat",
"torch.load",
"torch.randn",
"torch.nn.MaxPool3d",
"torch.nn.Conv3d",
"torch.nn.ReLU",
"torch.nn.BatchNorm3d",
"torch.nn.functional.pad"
]
] |
Armandpl/stable-baselines3 | [
"59bec3018058300f8892cc12593fcd1bd164ef48"
] | [
"stable_baselines3/common/distributions.py"
] | [
"\"\"\"Probability distributions.\"\"\"\n\nfrom abc import ABC, abstractmethod\nfrom typing import Any, Dict, List, Optional, Tuple, Union\n\nimport gym\nimport torch as th\nfrom gym import spaces\nfrom torch import nn\nfrom torch.distributions import Bernoulli, Categorical, Normal\n\nfrom stable_baselines3.common.... | [
[
"torch.tanh",
"torch.finfo",
"torch.mm",
"torch.ones",
"torch.sqrt",
"torch.distributions.Bernoulli",
"torch.round",
"torch.bmm",
"torch.distributions.kl_divergence",
"torch.ones_like",
"torch.nn.Parameter",
"torch.zeros_like",
"torch.exp",
"torch.nn.Linear"... |
ksh981214/icml18-jtnn | [
"701c363e24e38a47fc0c4509565fb021b5ba91c6"
] | [
"molopt/optimize.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\n\nimport math, random, sys\nfrom optparse import OptionParser\nfrom collections import deque\n\nimport rdkit\nimport rdkit.Chem as Chem\nfrom rdkit.Chem import Descriptors\nimport sascorer\n\nfrom jtnn import *\n\nlg = rdkit.RDLogger.logger(... | [
[
"torch.load"
]
] |
dkaramit/ASAP | [
"afade2737b332e7dbf0ea06eb4f31564a478ee40"
] | [
"Artificial_Neural_Networks/python/FeedForwardANN/FFANN_VanillaSGD.py"
] | [
"from numpy import sqrt as np_sqrt\nfrom numpy import abs as np_abs\nfrom .FFANN_SGD import StochasticGradientDescent\n\nclass VanillaSGD(StochasticGradientDescent):\n '''\n Not the best (far from it) strategy, but the simplest. Will use it to test if the implementation works.\n '''\n def __init__(self,... | [
[
"numpy.abs",
"numpy.sqrt"
]
] |
TatsukichiShibuya/theoretical_framework_for_target_propagation | [
"b6ee350c238be645e9cb42e12c79606f28f20f11"
] | [
"lib/networks.py"
] | [
"#!/usr/bin/env python3\n# Copyright 2019 Alexander Meulemans\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... | [
[
"torch.randn_like",
"torch.mean",
"numpy.sqrt",
"torch.tanh",
"numpy.mean",
"torch.norm",
"torch.nn.functional.relu",
"torch.autograd.grad",
"torch.sigmoid",
"torch.nn.init.constant_",
"torch.nn.ModuleList",
"torch.nn.init.xavier_normal_",
"torch.nn.Linear",
... |
GiftofHermes/queue_simulation | [
"aeb7ef818e1b2671c55d33179a6dc72e67976351"
] | [
"simulation.py"
] | [
"from abc import ABC\r\nimport numpy as np\r\nfrom collections import deque\r\nimport heapq\r\n\r\nclass Simulation:\r\n \"\"\"\r\n Fill here according to python guidelines\r\n \"\"\"\r\n def __init__(self):\r\n self.event_id = 0\r\n self.time = 0.0\r\n self.event_queue = [] #sh... | [
[
"numpy.random.randint"
]
] |
jayanthkoushik/cmu-ammml-project | [
"d087924b64f91754addb19ef251b5dececb672e3"
] | [
"src/uniimg.py"
] | [
"# coding=utf-8\n# uniimg.py: unimodal image based classifier.\n\nfrom __future__ import print_function\nimport argparse\nimport sys\nimport os\nimport random\nimport glob\nimport cPickle\nimport math\nfrom datetime import datetime\n\nimport numpy as np\nfrom models.vgg16 import VGG16\nfrom keras.optimizers import ... | [
[
"scipy.misc.imread"
]
] |
ajmaurais/peptide_analyzer | [
"62f37d88fefd0a8cfb57a8c157cfc85692956360"
] | [
"complete/main.py"
] | [
"\nimport os\nimport argparse\nimport pandas as pd\n\nimport uniprot\nimport molecular_formula\n\n\n# def main():\n# '''\n# Main method.\n#\n# This is the function which will be executed first when you call the program form the command line.\n# '''\n#\n# # Load and parse command line arguments\n... | [
[
"pandas.read_csv"
]
] |
vishalbelsare/h2o-3 | [
"9322fb0f4c0e2358449e339a434f607d524c69fa"
] | [
"h2o-py/tests/testdir_sklearn/pyunit_sklearn_classification_all_estimators.py"
] | [
"from __future__ import print_function\nfrom collections import defaultdict\nfrom functools import partial\nimport gc, inspect, os, sys\n\nimport numpy as np\nfrom sklearn.datasets import make_classification\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.model_selection import train_test_split\n\nimport ... | [
[
"numpy.sum",
"sklearn.datasets.make_classification",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.accuracy_score"
]
] |
aalto-ics-kepaco/lcms2struct_exp | [
"5baa3edd0e58d24f739efd4086031f6fbdba6ad9"
] | [
"data/import_sirius_scores.py"
] | [
"####\n#\n# The MIT License (MIT)\n#\n# Copyright 2021 Eric Bach <eric.bach@aalto.fi>\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 without restriction, including without limita... | [
[
"numpy.max",
"numpy.random.RandomState",
"numpy.ones_like",
"numpy.min"
]
] |
lpworld/LatentUnexp | [
"55cfa214733d6fd31f8113b8ae47f83e03984f0d"
] | [
"surprise/similarities.py"
] | [
"\"\"\"\nThe :mod:`similarities <surprise.similarities>` module includes tools to\ncompute similarity metrics between users or items. You may need to refer to the\n:ref:`notation_standards` page. See also the\n:ref:`similarity_measures_configuration` section of the User Guide.\n\nAvailable similarity measures:\n\n.... | [
[
"numpy.zeros",
"numpy.sqrt"
]
] |
glynpu/lhotse | [
"1d7807025575fdaa96cb907c451db0fb0fd23cde"
] | [
"test/cut/test_cut_mixing.py"
] | [
"from math import isclose\n\nimport numpy as np\nimport pytest\n\nfrom lhotse.cut import CutSet, MixedCut, MonoCut\nfrom lhotse.supervision import SupervisionSegment\nfrom lhotse.testing.dummies import remove_spaces_from_segment_text\nfrom lhotse.utils import nullcontext as does_not_raise\n\n\n# Note:\n# Definition... | [
[
"numpy.exp",
"numpy.sum"
]
] |
lbeltrame/bcbio-nextgen | [
"1135176df8cb6a47ae39f997ffa4eaac17f8b4ff"
] | [
"bcbio/ngsalign/tophat.py"
] | [
"\"\"\"Next-gen alignments with TopHat a spliced read mapper for RNA-seq experiments.\n\nhttp://tophat.cbcb.umd.edu\n\"\"\"\nimport os\nimport shutil\nimport glob\nimport subprocess\n\nimport numpy\nimport pysam\n\nfrom bcbio.pipeline import config_utils\nfrom bcbio.ngsalign import bowtie, bowtie2\nfrom bcbio.utils... | [
[
"numpy.median"
]
] |
ewulczyn/ewulczyn.github.io | [
"8e77b3a9a6a484696678f5b937b12f5742c05e99"
] | [
"ipython/How_Naive_AB_Testing_Goes_Wrong/abstract_abtest.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom abtest_util import SimStream\nfrom abc import ABCMeta, abstractmethod\n\nclass ABTest(object):\n \"\"\"\n This is the base class for dynamically\n terminating AB tests. The idea is that you define\n a stopping crietion and e... | [
[
"numpy.percentile",
"numpy.mean",
"pandas.DataFrame.from_records",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
janzmazek/langerhansGUI | [
"aa0f3f1636f96964f2172383aadb734a71bc4885"
] | [
"langerhansGUI/view.py"
] | [
"import tkinter as tk\nfrom tkinter import messagebox\nfrom tkinter import filedialog\nfrom tkinter.ttk import Progressbar\nfrom matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\nimport copy\nimport webbrowser\n\n\n# Window parameters\nWIDTH = 1000\nHEIGHT = 600\n\nWHITE = \"white\"\nTEXT = \"white\"\n# B... | [
[
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg"
]
] |
mrbermell/ffai | [
"8b70faf615fc70eb40aa8b3519a7d2339872ea15"
] | [
"tests/performance/run_env.py"
] | [
"#!/usr/bin/env python3\n\nimport gym\nimport numpy as np\nimport botbowl\nfrom botbowl.core.game import Game\nfrom botbowl.core.model import Agent\n\nimport cProfile\nimport io\nimport pstats\n\n\ndef profile_and_print_result(function, sortkey=\"tottime\"):\n \"\"\"\n Choose sortkey from: 'ncalls', 'tottime'... | [
[
"numpy.random.RandomState"
]
] |
nesl/DeepCEP_DAIS | [
"04dbfefe3c42d74836035a73bfbcd51eebc7992d"
] | [
"detection.py"
] | [
"import os\nimport time\nimport cv2\nimport numpy as np\nfrom yolo.yolo_model import YOLO\n\ndef process_image(img):\n \"\"\"Resize, reduce and expand image.\n\n # Argument:\n img: original image.\n\n # Returns\n image: ndarray(64, 64, 3), processed image.\n \"\"\"\n image = cv2.resize(... | [
[
"numpy.array",
"numpy.expand_dims",
"numpy.floor"
]
] |
thompson318/arucochristmas | [
"0cf6e2f646ae4d0380aa1330b155418db2449ad1"
] | [
"arucochristmas/aruco.py"
] | [
"\"\"\" Module to provide the aruco tracking logic \"\"\"\n#pylint:disable=import-error\nimport numpy as np\nfrom picamera import PiCamera\nfrom picamera.array import PiRGBArray\nfrom sksurgeryarucotracker.arucotracker import ArUcoTracker\n\n\ndef init_camera_and_tracker():\n \"\"\"\n Initialises an sksurgery... | [
[
"numpy.array"
]
] |
alfa-th/lang-modeler-pytorch | [
"a13e94841df9fc3996b33a93d0a58a99c0596359"
] | [
"transformer/main.py"
] | [
"import time\nimport math\nimport copy\n\nfrom torchtext.datasets import WikiText2\nimport torch.nn as nn\nimport torch\n\nfrom functions import evaluate, train\nfrom dataset import get_vocab, get_processed_data, get_tokenizer\nfrom classes.transformer_model import TransformerModel\n\ntokenizer = get_tokenizer(\"ba... | [
[
"torch.device",
"torch.nn.CrossEntropyLoss",
"torch.optim.lr_scheduler.StepLR"
]
] |
mcsorkun/Genetic-Selection-Cheminformatics | [
"6f85cd26ffc0aa00b8c34c6d482a2a5f4de149ae"
] | [
"AqSolDB_example.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue May 26 18:35:38 2020\r\n\r\n@author: Murat Cihan Sorkun\r\n\r\nFeature Selection by Genetic Algorithm: An example on AqSolDB dataset (Aqueous Solubility) \r\n\"\"\"\r\n\r\nfrom sklearn.model_selection import train_test_split\r\nfrom sklearn.neural_network import ... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"sklearn.neural_network.MLPRegressor"
]
] |
neurotechdk/fnirs-bci | [
"fa7d757dad2060b8acc6e64a51968707b45aa120"
] | [
"code/exp_bci_task.py"
] | [
"from sklearn.model_selection import KFold\r\nfrom sklearn.metrics import f1_score\r\nfrom sklearn.metrics import confusion_matrix\r\nfrom helper_functions import *\r\nfrom helper_functions import preprocess, visualize_loss, show_plot\r\nimport warnings\r\nfrom icecream import ic\r\nic(\"Importing packages...\")\r\... | [
[
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.preprocessing.timeseries_dataset_from_array",
"numpy.load",
"numpy.repeat",
"tensorflow.keras.callbacks.EarlyStopping",
"tensorflow.keras.models.Sequential"
]
] |
phillipi/AMT_Real_vs_Fake | [
"4f5f25cdaffc8ee8c0a3ccd186f6ff45beb0c5c9"
] | [
"process_csv.py"
] | [
"\nimport numpy as np\nimport csv\nfrom collections import OrderedDict\nimport argparse\nfrom tqdm import tqdm\n\nfrom IPython import embed\n\ndef collect_csv_results(filename):\n\twith open(filename, newline='') as csvfile:\n\t\treader = csv.DictReader(csvfile)\n\t\tfor rr,row in enumerate(reader):\n\t\t\tif(rr==0... | [
[
"numpy.setdiff1d",
"numpy.max",
"numpy.std",
"numpy.argmax",
"numpy.mean",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.random.randint"
]
] |
jalilm/SDN-Monitoring | [
"4ba8dd0f0ed5e44c0e803713d6c82ee2c815c7e4"
] | [
"util/get_percentage_plots.py"
] | [
"#!/usr/bin/env python\n\nimport glob\nimport os\n\nimport matplotlib.pyplot as plt\n\n\ndef main():\n res_per_k = {}\n for fn in glob.glob(os.path.expanduser('~/logs/') + '*-Topk-*'):\n if os.path.isfile(fn):\n # bfn = os.path.basename(fn)\n # mechanism, topk, rate, directory, ti... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
pavanchhatpar/AttnGAN | [
"9a4ac53aee9890ad488f11aeb913623d2c93a6b2"
] | [
"code/trainer.py"
] | [
"from __future__ import print_function\nfrom six.moves import range\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.autograd import Variable\nimport torch.backends.cudnn as cudnn\n\nfrom PIL import Image\n\nfrom miscc.config import cfg\nfrom miscc.utils import mkdir_p\nfrom miscc.uti... | [
[
"torch.cuda.set_device",
"torch.load",
"torch.from_numpy",
"torch.FloatTensor",
"numpy.transpose",
"numpy.repeat"
]
] |
vibhoothi/awcy | [
"172edeeca8c331d63ee72f6a3928fc6b2965d845"
] | [
"dump_convex_hull.py"
] | [
"#!/usr/bin/env python3\n\nfrom __future__ import print_function\n\nfrom numpy import *\nimport numpy as np\nfrom scipy import *\nfrom scipy.interpolate import interp1d\nfrom scipy.interpolate import pchip\nfrom scipy.interpolate import BPoly\nfrom scipy._lib._util import _asarray_validated\nimport sys\nimport os\n... | [
[
"numpy.flipud"
]
] |
RichardJ112/nebula_dynamic_2021 | [
"6e120f4562e46cd02d981e75aa4238d16ee0e9c8"
] | [
"nebula_test_files/vox_tri_pri/gen_pri_wall.py"
] | [
"import numpy as np\nimport os\n\n# Point exposure for Wall Depositions\n\n#Automation Additions\nHPC_toggle = False\nmulti_run_folder_toggle = False# single or multi folder (True is multi,False is single)\ndesktop_toggle = True\n\ndate = \"/20_8_2021/\"\n\n# Parameters Geom\nvoxel_size = 0.3; # voxel size in nanom... | [
[
"numpy.linspace",
"numpy.dtype",
"numpy.random.normal",
"numpy.zeros",
"numpy.empty"
]
] |
mcx/tensorflow | [
"d7e521a1ad21681855b439b9c2a05837c804e488"
] | [
"tensorflow/python/distribute/sharded_variable_test.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.python.compat.v2_compat.enable_v2_behavior",
"tensorflow.python.framework.tensor_shape.TensorShape",
"tensorflow.python.distribute.distribution_strategy_context._get_default_strategy",
"tensorflow.python.distribute.test_util.TestClusterParams",
"tensorflow.python.ops.variables.Vari... |
tonyw/antares | [
"6c2c505ab73d25b2f40831898a10bbf09602a4a0"
] | [
"platforms/c-rocm/schedule/standard/batch_matmul_v1.py"
] | [
"# Copyright (c) Microsoft Corporation.\n# Licensed under the MIT license.\n\nimport numpy as np\nfrom tvm import te\nimport logging\nimport sys, time, subprocess\n\n\nimport json\nimport os\n\n\ndef schedule(attrs):\n cfg, s, output = attrs.auto_config, attrs.scheduler, attrs.outputs[0]\n th_vals, rd_vals = ... | [
[
"numpy.product"
]
] |
hogikyan/xarrayutils | [
"a0c583113665882e70fce8590a90a5b2fff176c3"
] | [
"xarrayutils/plotting.py"
] | [
"import numpy as np\nimport xarray as xr\nimport matplotlib.pyplot as plt\nimport gsw\n\n\ndef center_lim(ax, which='y'):\n if which == 'y':\n lim = np.array(ax.get_ylim())\n ax.set_ylim(np.array([-1, 1]) * abs(lim).max())\n elif which == 'x':\n lim = np.array(ax.get_xlim())\n ax.s... | [
[
"matplotlib.pyplot.gca",
"numpy.linspace",
"numpy.meshgrid",
"matplotlib.pyplot.gcf",
"numpy.diff",
"matplotlib.pyplot.text",
"numpy.array"
]
] |
rluver/ocr_attention_tensorflow | [
"448876d809bd6f80d7fae00ebdbbc9222046ddb4"
] | [
"inference.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Jul 31 23:13:26 2021\n\n@author: MJH\n\"\"\"\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\nfrom model import OCR_Attention\nfrom auxiliary import decode_batch_predictions, encode_single_sample\nfrom tensorflow.keras.models import Mode... | [
[
"tensorflow.data.Dataset.from_tensor_slices",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
MLO-lab/MuVI | [
"98796ab6deab225adc3add75e20c4b51f842f529"
] | [
"muvi/core/index.py"
] | [
"import numpy as np\n\n\ndef _normalize_index(indexer, index, as_idx=True):\n # work with ints, convert at the end\n # if single str, get idx and put to list\n # TODO: can be an issue if any of the indices is named 'all'..\n if isinstance(indexer, str):\n if indexer == \"all\":\n index... | [
[
"numpy.array",
"numpy.where"
]
] |
czlwang/groundedSCAN | [
"3d03ac6de37dde8d22d487dc3cc5a53af188fa2e"
] | [
"GroundedScan/gym_minigrid/minigrid.py"
] | [
"import math\nimport gym\nfrom enum import IntEnum\nimport numpy as np\nfrom gym import spaces\nfrom gym.utils import seeding\n\n# Size in pixels of a cell in the full-scale human view\nCELL_PIXELS = 60\n\n# Map of color names to RGB values\nCOLORS = {\n 'red': np.array([128, 0, 0]),\n 'green': np.array([46, ... | [
[
"numpy.array",
"numpy.zeros",
"numpy.array_equal"
]
] |
blakeNaccarato/boilerdaq | [
"bc39074237c42d94c5402327495f05ff662e7a35"
] | [
"src/boilerdaq.py"
] | [
"\"\"\"Data acquisition and control of a boiler.\"\"\"\n\nfrom __future__ import annotations\n\nimport os\nfrom collections import OrderedDict, deque\nfrom csv import DictReader, DictWriter\nfrom datetime import datetime, timedelta\nfrom os.path import splitext\nfrom threading import Thread\nfrom time import sleep\... | [
[
"numpy.random.normal",
"numpy.exp"
]
] |
KiroSummer/AMR | [
"49f4edc9e738ba3409d2d5e45e5e1881d8b338cc"
] | [
"parser/decoder.py"
] | [
"import torch\nfrom torch import nn\nimport torch.nn.functional as F\nfrom torch.nn import Parameter\nfrom parser.data import NIL, PAD\nfrom parser.utils import compute_f_by_tensor\nfrom parser.transformer import MultiheadAttention, Transformer, TiedTransformer\n\nfrom parser.utils import label_smoothed_nll_loss\n\... | [
[
"torch.ge",
"torch.max",
"torch.nn.functional.log_softmax",
"torch.nn.functional.dropout",
"torch.nn.init.constant_",
"torch.cat",
"torch.eq",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.init.normal_",
"torch.log",
"torch.scatter_add",
"torch.ne"
]
] |
sugarchain-dev/electrum-sugar | [
"5c70bfa883950bb501625916a888618792cd635b"
] | [
"electrum/plot.py"
] | [
"import datetime\nfrom collections import defaultdict\n\nimport matplotlib\nmatplotlib.use('Qt5Agg')\nimport matplotlib.pyplot as plt\nimport matplotlib.dates as md\n\nfrom .i18n import _\nfrom .bitcoin import COIN\n\n\nclass NothingToPlotException(Exception):\n def __str__(self):\n return _(\"Nothing to ... | [
[
"matplotlib.pyplot.gca",
"matplotlib.dates.DateFormatter",
"matplotlib.use",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.ylabel"
]
] |
tchayintr/thwcc-attn | [
"4ee38365eb338e82bf455f46ff5fe7c59fb7a975"
] | [
"src/models/rnn_with_chunk_sw_tagger.py"
] | [
"from allennlp.modules.conditional_random_field import ConditionalRandomField\nfrom allennlp.nn.util import get_mask_from_sequence_lengths\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.nn.utils.rnn import pad_sequence\n\nimport sys\n\nimport constants\nimport ... | [
[
"torch.div",
"torch.nn.CrossEntropyLoss",
"torch.nn.functional.softmax",
"torch.ones",
"torch.transpose",
"torch.nn.Module.__init__",
"torch.cat",
"torch.nn.functional.dropout",
"torch.zeros",
"torch.nn.utils.rnn.pad_sequence",
"torch.sum",
"torch.unsqueeze",
"t... |
ietheredge/VisionEngine | [
"271c8dcaef6eb574e9047fca436d7b13cab75d3b"
] | [
"VisionEngine/utils/eval.py"
] | [
"import tensorflow as tf\nimport math\n\n\ndef embed_images(x, model):\n outputs = [\n model.model.get_layer(\"variational_layer\").output,\n model.model.get_layer(\"variational_layer_1\").output,\n model.model.get_layer(\"variational_layer_2\").output,\n model.model.get_layer(\"varia... | [
[
"tensorflow.losses.mean_squared_error",
"tensorflow.exp",
"tensorflow.keras.Model",
"tensorflow.sqrt",
"tensorflow.keras.layers.Flatten"
]
] |
mengzaiqiao/MultiObjectiveOptimization | [
"7085638b3918506836118f88fed8bb2f8994a499"
] | [
"multi_task/metrics.py"
] | [
"# Adapted from: https://github.com/meetshah1995/pytorch-semseg/blob/master/ptsemseg/metrics.py\n\nfrom losses import l1_loss_instance\nimport numpy as np\n\nclass RunningMetric(object):\n def __init__(self, metric_type, n_classes =None):\n self._metric_type = metric_type\n if metric_type == 'ACC':... | [
[
"numpy.diag",
"numpy.zeros",
"numpy.sum",
"numpy.nanmean"
]
] |
wasiahmad/community_question_answering | [
"73d13bc1cdf2ea66d13209c007dcc2767cf2155c"
] | [
"senteval/examples/all.py"
] | [
"# Copyright (c) 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n#\n\n\"\"\"\nInferSent models. See https://github.com/facebookresearch/InferSent.\n\"\"\"\n\nfrom __future__ import abso... | [
[
"numpy.concatenate"
]
] |
gan3sh500/keras-YOLOv3-model-set | [
"1a1108c52073c01c130618dc68607f455adadf28"
] | [
"common/utils.py"
] | [
"#!/usr/bin/python3\n# -*- coding=utf-8 -*-\n\"\"\"Miscellaneous utility functions.\"\"\"\n\nfrom PIL import Image\nimport numpy as np\nimport os, cv2, colorsys\nfrom matplotlib.colors import rgb_to_hsv, hsv_to_rgb\nfrom common.backbones.efficientnet import swish\nfrom common.backbones.mobilenet_v3 import hard_sigm... | [
[
"numpy.random.seed",
"numpy.around",
"tensorflow.config.experimental.list_physical_devices",
"numpy.random.shuffle",
"tensorflow.config.experimental.VirtualDeviceConfiguration",
"tensorflow.ConfigProto",
"tensorflow.Session",
"numpy.array",
"tensorflow.__version__.startswith"
... |
werlang/Gas-Station-BinanceSmartChain | [
"4462dfcae2407d4785e333bdc88b0486e1095896"
] | [
"gasPriceApi.py"
] | [
"import time\nimport sys\nimport json\nimport math\nimport traceback\nimport os\nimport pandas as pd\nimport numpy as np\nfrom web3 import Web3, HTTPProvider\nfrom web3.middleware import geth_poa_middleware\n## newly added packages for api\nimport click\nimport logging\nfrom threading import Thread\nfrom sanic impo... | [
[
"numpy.isnan",
"numpy.ma.masked_array",
"pandas.DataFrame",
"pandas.DataFrame.from_dict"
]
] |
Storiesbyharshit/Deep-Learning | [
"2464e3354c8c2c99237d76b47264d509cc1a7cef"
] | [
"Deep Learning using Tensorflow Keras/Churn-Model-using-ANN/ANN - Churn Modelling.py"
] | [
"\r\n\r\n# Importing the libraries \r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport pandas as pd\r\n\r\nimport warnings\r\nwarnings.filterwarnings('ignore')\r\nwarnings.filterwarnings(\"ignore\", category=DeprecationWarning)\r\n\r\n\r\n\r\n\r\n\r\n# Importing the datasetm\r\ndataset = pd.read_csv... | [
[
"pandas.read_csv",
"sklearn.preprocessing.OneHotEncoder",
"sklearn.metrics.confusion_matrix",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.StandardScaler",
"sklearn.preprocessing.LabelEncoder"
]
] |
mariaborbones/AIF360 | [
"05b3d155aa89a1b173ac3f1ec42110a899710cf8"
] | [
"aif360/datasets/standard_dataset.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nfrom logging import warn\n\nimport numpy as np\nimport pandas as pd\n\nfrom aif360.datasets import BinaryLabelDataset\n\n\nclass StandardDataset(BinaryLabelData... | [
[
"numpy.issubdtype",
"numpy.array",
"numpy.equal.outer",
"pandas.get_dummies"
]
] |
shfshf/ner_s2s | [
"a04311310bddf396b551969fd1e63fdb3fc2ca0b"
] | [
"ner_s2s/ner_estimator/algorithms/model.py"
] | [
"from pathlib import Path\n\nimport tensorflow as tf\nimport numpy as np\nfrom ner_s2s.metrics import precision, recall, f1, correct_rate\n\n\nclass Model(object):\n @classmethod\n def default_params(cls):\n return {}\n\n @classmethod\n def get_model_name(cls):\n return cls.__name__\n\n ... | [
[
"tensorflow.get_variable",
"tensorflow.contrib.lookup.index_table_from_tensor",
"tensorflow.metrics.accuracy",
"tensorflow.layers.dropout",
"numpy.vstack",
"tensorflow.train.AdamOptimizer",
"tensorflow.contrib.crf.crf_decode",
"tensorflow.contrib.crf.crf_log_likelihood",
"tenso... |
pfriesch/neural-pipeline | [
"2df4f7467a721b1fbd93f4439086c6dcee5dac2c",
"2df4f7467a721b1fbd93f4439086c6dcee5dac2c"
] | [
"examples/files/img_classification.py",
"neural_pipeline/builtin/monitors/mpl.py"
] | [
"from neural_pipeline.builtin.monitors.tensorboard import TensorboardMonitor\nfrom neural_pipeline import DataProducer, AbstractDataset, TrainConfig, TrainStage,\\\n ValidationStage, Trainer, FileStructManager\n\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\nfrom torchvision import dataset... | [
[
"torch.nn.NLLLoss",
"torch.nn.functional.log_softmax",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.device",
"torch.nn.functional.max_pool2d"
],
[
"matplotlib.pyplot.cm.get_cmap",
"matplotlib.pyplot.subplot",
"numpy.mean",
"matplotlib.ticker.MaxNLocator",
"matplotli... |
jyf588/SimGAN | [
"23283d7b5629f1653567b2437bb28aac1cc17169",
"23283d7b5629f1653567b2437bb28aac1cc17169"
] | [
"third_party/a2c_ppo_acktr/model_split.py",
"third_party/a2c_ppo_acktr/algo/ppo.py"
] | [
"# MIT License\n#\n# Copyright (c) 2017 Ilya Kostrikov and (c) 2020 Google LLC\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 without restriction, including without limitati... | [
[
"numpy.sqrt",
"torch.cat",
"torch.nn.init.constant_",
"torch.nn.Tanh",
"torch.nn.Linear"
],
[
"torch.exp",
"torch.clamp",
"torch.max",
"torch.min"
]
] |
PilmautBotics/Tracking_SSD_ReID | [
"5fa2f83ac48c64dc1be24cc1a156d19ba5908dff"
] | [
"data_management/VOC2012ManagerObjDetection.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n\"\"\"\nPascal VOC2012 dataset manager\n\"\"\"\n\nimport os\nimport xml.etree.ElementTree as ET\n\nimport numpy as np\nimport tensorflow as tf\n\n\nclass VOC2012ManagerObjDetection:\n def __init__(self, path=\"\", trainRatio=0.7, batch_size=32, floatType=32):\n... | [
[
"tensorflow.clip_by_value",
"tensorflow.convert_to_tensor",
"tensorflow.concat",
"tensorflow.Variable",
"tensorflow.math.minimum",
"tensorflow.keras.preprocessing.image.load_img",
"tensorflow.expand_dims",
"tensorflow.repeat",
"numpy.array",
"tensorflow.keras.preprocessing.... |
alopezgit/project-adapt | [
"e93ab350344a5504f76f4e460002e0163996f88a"
] | [
"Models/model.py"
] | [
"\"\"\"\nAuthor: Wouter Van Gansbeke\nLicensed under the CC BY-NC 4.0 license (https://creativecommons.org/licenses/by-nc/4.0/)\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nimport torch.utils.data\nimport torch.nn.functional as F\nimport numpy as np\nfrom .ERFNet import Net\nimport copy\nimport Utils.utils as ut... | [
[
"torch.nn.Softmax",
"torch.nn.ConvTranspose2d",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.Sigmoid",
"torch.nn.functional.relu",
"torch.nn.functional.interpolate",
"torch.nn.BatchNorm2d",
"torch.chunk",
"torch.nn.ReLU",
"torch.nn.functional.max_pool2d"
]
] |
sameh999/kalam | [
"7a867c71daa4d230356d0b85fde2e36397ce608a"
] | [
"utils.py"
] | [
"import torch\r\nimport librosa \r\nfrom FastSpeech2.buckwalter import ar2bw, bw2ar\r\n\r\ndevice = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\r\n\r\ndef load_file_to_data(file, srate = 16_000):\r\n batch = {} \r\n speech, sampling_rate = librosa.load(file, sr=srate)\r\n batch[\"sp... | [
[
"torch.nn.Softmax",
"torch.no_grad",
"torch.cuda.is_available",
"torch.topk",
"torch.argmax"
]
] |
va9abund/GAN-traffic-sign | [
"a9e7cc1c6839cdb0f29f68a951040fb27c64f738"
] | [
"classifier/train.py"
] | [
"# Python Standard Library\nfrom datetime import datetime\nimport json\nimport os\nimport time\n\n# Public Libraries\nfrom keras.utils import np_utils\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Conv2D, Flatten, Lambda, Dropout, MaxPooling2D\nfrom keras.optimizers import Adam\nfrom keras.u... | [
[
"sklearn.model_selection.train_test_split"
]
] |
songhaoyu/RCDG | [
"962c3b5803b766bd25577460aa90c2741d500d99"
] | [
"reinforcement_train/onmt/io/TextDataset.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom collections import Counter\nfrom itertools import chain\nimport io\nimport codecs\nimport sys\n\nimport torch\nimport torchtext\n\nfrom onmt.Utils import aeq\nfrom onmt.io.DatasetBase import ONMTDatasetBase, PAD_WORD, BOS_WORD, EOS_WORD\n\nfrom torch.nn.functional import Variable\nf... | [
[
"torch.LongTensor",
"torch.nn.functional.Variable"
]
] |
MCZhi/SMARTS | [
"3ef5650b04ac6fb7145cf4e23d5534d73e0929fc"
] | [
"zoo/policies/cross-rl-agent/cross_rl_agent/train/run_test.py"
] | [
"# Copyright (C) 2020. Huawei Technologies Co., Ltd. All rights reserved.\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 without restriction, including without limitation the rig... | [
[
"tensorflow.compat.v1.ConfigProto",
"tensorflow.compat.v1.train.import_meta_graph",
"tensorflow.compat.v1.Session",
"tensorflow.compat.v1.reset_default_graph",
"numpy.mean",
"tensorflow.compat.v1.train.Saver",
"numpy.sum"
]
] |
pesavent/SMC | [
"8e53f73b81798761ef3aad3dc94e550eb83a3d9b"
] | [
"SMC_V3_11302020.py"
] | [
"# This python script was written by a simple biochemist with little formal programming training. Is the code great?\n# Nope, but it is indeed functional. The program was designed to accomplish a few quick\n# tasks, namely: how many ms2 events occur for a given precursors mass, summing ms2 ions for a given precurso... | [
[
"numpy.amax",
"numpy.unique",
"matplotlib.style.use",
"matplotlib.use",
"matplotlib.figure.Figure",
"numpy.amin",
"numpy.delete",
"numpy.append",
"numpy.loadtxt",
"matplotlib.backends.backend_tkagg.NavigationToolbar2Tk",
"numpy.array",
"matplotlib.rc",
"matplotl... |
muyuuuu/PyQt-learn | [
"a9134566505c88ae9d46ae23480b140c8c911c33"
] | [
"GUI/Basic-train/QtPandas/qtpandas/models/DataFrameModel.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nEasy integration of DataFrame into pyqt framework\n\n@author: Jev Kuznetsov, Matthias Ludwig - Datalyze Solutions\n\"\"\"\nfrom __future__ import unicode_literals\nfrom __future__ import print_function\nfrom __future__ import division\nfrom __future__ import absolute_import\n\nfrom... | [
[
"pandas.Series",
"numpy.dtype",
"numpy.finfo",
"pandas.DataFrame",
"numpy.iinfo",
"numpy.float64",
"pandas.Timestamp",
"numpy.bool_",
"pandas.read_sql"
]
] |
tomerwei/Fusion360GalleryDataset | [
"3e1d58920ac56d271c01a7ba05749c5a05097152"
] | [
"tools/regraphnet/src/inference.py"
] | [
"from __future__ import division\nfrom __future__ import print_function\n\nimport os\nimport json\nimport time\nimport argparse\nimport numpy as np\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom train import *\n\ndef load_graph_pair(path_tar,path_cur,bbox):\n action_type_dict={'C... | [
[
"torch.nn.functional.softmax",
"torch.zeros",
"torch.load",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"numpy.array",
"numpy.zeros"
]
] |
mholts1020/Challenge-5-module | [
"d26eaac00b761bfc625e2e15573e26b256a9e843"
] | [
"MCForecastTools.py"
] | [
"# Import libraries and dependencies\r\nimport numpy as np\r\nimport pandas as pd\r\nimport os\r\nimport alpaca_trade_api as tradeapi\r\nimport datetime as dt\r\nimport pytz\r\n\r\nclass MCSimulation:\r\n \"\"\"\r\n A Python class for runnning Monte Carlo simulation on portfolio price data. \r\n \r\n ..... | [
[
"numpy.random.normal",
"pandas.MultiIndex.from_tuples",
"pandas.DataFrame"
]
] |
jiangyy12/application-tracking-system | [
"6de2d98351df65d43c09a5739c3c3dbdf3bf78d3"
] | [
"backend/app.py"
] | [
"#importing required python libraries\nfrom flask import Flask, jsonify, request\nfrom flask_cors import CORS, cross_origin\nfrom selenium import webdriver\nfrom bs4 import BeautifulSoup\nfrom itertools import islice\nfrom webdriver_manager.chrome import ChromeDriverManager\nfrom data.connection import query, inser... | [
[
"pandas.DataFrame"
]
] |
TuxStory/LCsvGraph | [
"61abca24692a2230597a3736c677322adb262e74"
] | [
"LottoCSVGraph.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport csv, statistics\n\ndef DataList():\n path =\"./LottoGameData.csv\"\n file = open(path,newline='')\n reader = csv.reader(file)\n header = next(reader) #first line is the reader\n data = []\n for row in reader:\n # row = [date, n1,... | [
[
"matplotlib.pyplot.title",
"numpy.unique",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.show"
]
] |
Haichao-Zhang/leap | [
"4d75961ff2ff203d4412633cbeb12889de3c79b6"
] | [
"railrl/torch/pytorch_util.py"
] | [
"import torch\nimport numpy as np\nfrom torch.autograd import Variable as TorchVariable\nfrom torch.nn import functional as F\n\n\ndef soft_update_from_to(source, target, tau):\n for target_param, param in zip(target.parameters(), source.parameters()):\n target_param.data.copy_(\n target_param.... | [
[
"torch.ones",
"torch.floor",
"torch.cuda.set_device",
"torch.zeros",
"numpy.sqrt",
"numpy.eye",
"torch.from_numpy",
"torch.cuda.FloatTensor",
"torch.nn.functional.relu",
"torch.FloatTensor",
"numpy.random.rand",
"numpy.prod",
"numpy.floor",
"torch.clamp",
... |
daniele21/Financial_Sentiment_Analysis | [
"3734733f2d1d291c81a6239de121edcce861b463"
] | [
"tests/network_test.py"
] | [
"import unittest\nimport logging\nimport torch\nfrom torch import nn\n\nfrom constants.config import MOVIE_DATASET, TOKENIZER, MAX_WORD_SENTENCE, SST_DATASET\nfrom scripts.datasets.dataloader import generate_dataloader\nfrom scripts.datasets.dataset import NN_Dataset\nfrom scripts.datasets.sst_dataset import Bert_N... | [
[
"torch.device",
"torch.nn.CrossEntropyLoss",
"torch.nn.BCELoss"
]
] |
HaiNguyen2903/Faster-RCNN | [
"78d249a07dae0c9dad095543dab6385394c8dc0a"
] | [
"data/dataset.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nimport torch as t\nfrom data.voc_dataset import VOCBboxDataset\nfrom skimage import transform as sktsf\n# import skimage.transform as sktsf\nfrom torchvision import transforms as tvtsf\nfrom data import util\nimport numpy as np\nfrom utils.... | [
[
"numpy.array",
"torch.from_numpy"
]
] |
turoger/df_Collate | [
"4c4266fc7074957ca44d5085e915ea6c47123193"
] | [
"dfCollate/dfCollate.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[ ]:\n\n\nimport os\nimport dask.dataframe as ddf\nimport pandas as pd\nimport numpy as np\n\n\n#\ndef big_ddf (directory_to_traits_table,\n directory_to_phenotypes, phenotype_list, filename_type,\n directory_to_MAF,\n gene_name, dir... | [
[
"pandas.read_csv"
]
] |
tomiyee/6.806-Card-Translation | [
"9286b232f60ec53fabbbcbeca23ddd71cd6c3483"
] | [
"code/model.py"
] | [
"import torch\nimport torch.nn as nn\n\nclass Card2CodeModel(nn.Module):\n def __init__(self):\n self.linear = nn.Linear(5,5)\n \n def forward(self, inputs=None):\n return self.linear(inputs)\n"
] | [
[
"torch.nn.Linear"
]
] |
seungjooshin/kornia | [
"5bfb8f2f23cc1d99647c36aa982132c5b7adbb6d"
] | [
"test/geometry/calibration/test_undistort.py"
] | [
"import pytest\nimport torch\nfrom torch.autograd import gradcheck\n\nfrom kornia.geometry.calibration.undistort import undistort_points\nfrom kornia.testing import assert_close\n\n\nclass TestUndistortion:\n def test_smoke(self, device, dtype):\n points = torch.rand(1, 2, device=device, dtype=dtype)\n ... | [
[
"torch.autograd.gradcheck",
"torch.rand",
"torch.tensor"
]
] |
ZhaoZhangZZlab/eccDNA_formation_2021 | [
"35bd3db1ab475bd440d7fe20c0856002f2cc73ba"
] | [
"Script/TEinsertion_convert.py"
] | [
"import pandas as pd\nimport os\nimport argparse\nimport re\nfrom Bio import SeqIO\nimport pysam\n\npd.set_option(\"display.max_columns\",40)\n\nparser=argparse.ArgumentParser()\nparser.add_argument(\"-bam\",\"--bamFile\")\nargs=parser.parse_args()\n\nbamFile=args.bamFile\n\n\nfrom TEinsertion_bamConverter import b... | [
[
"pandas.set_option"
]
] |
dbanys/glide-text2im | [
"9cc8e563851bd38f5ddb3e305127192cb0f02f5c",
"5177545ec62f1fddc3075a8a69b63df3eb2256a5"
] | [
"glide_text2im/gaussian_diffusion.py",
"notebooks/run_inpaint.py"
] | [
"\"\"\"\nSimplified from https://github.com/openai/guided-diffusion/blob/main/guided_diffusion/gaussian_diffusion.py.\n\"\"\"\n\nimport math\n\nimport numpy as np\nimport torch as th\n\n\ndef _warmup_beta(beta_start, beta_end, num_diffusion_timesteps, warmup_frac):\n betas = beta_end * np.ones(num_diffusion_time... | [
[
"torch.randn_like",
"numpy.log",
"numpy.sqrt",
"numpy.linspace",
"torch.zeros",
"torch.sqrt",
"torch.randn",
"torch.from_numpy",
"numpy.ones",
"torch.exp",
"torch.tensor",
"numpy.cumprod",
"numpy.append",
"torch.no_grad",
"torch.split",
"numpy.array"... |
codema-dev/seai_deap | [
"52b67582beac8d8a2b46b5991970b6ad6695f7b3"
] | [
"tests/test_fab.py"
] | [
"import numpy as np\nfrom numpy.testing import assert_array_equal\n\nfrom seai_deap import fab\n\n\ndef test_calculate_thermal_bridging() -> None:\n\n expected_output = np.array(0.75)\n\n output = fab.calculate_thermal_bridging(\n wall_area=np.array(1),\n roof_area=np.array(1),\n floor_ar... | [
[
"numpy.testing.assert_array_equal",
"numpy.array"
]
] |
patrick-g-zhang/MPNet | [
"7788b5883c8d3037215d7c0b939b6e9b6e5f4bca"
] | [
"pretraining/setup.py"
] | [
"#!/usr/bin/env python3\n# Copyright (c) Facebook, Inc. and its affiliates.\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\nfrom setuptools import setup, find_packages, Extension\nimport sys\n\n\nif sys.version_info < (3,):\n sys... | [
[
"numpy.get_include"
]
] |
alexacarlson/pggan-pytorch | [
"96600b13dbda732b7c2737ee0e15c47bc239d7ca"
] | [
"dataloader.py"
] | [
"import os\nimport torch as torch\nimport numpy as np\nfrom io import BytesIO\nimport scipy.misc\n#import tensorflow as tf\nimport torchvision\nimport torchvision.transforms as transforms\nfrom torch.utils.data import DataLoader\nfrom torchvision.datasets import ImageFolder\nfrom torch.autograd import Variable\n#fr... | [
[
"torch.utils.data.DataLoader"
]
] |
mcgibbon/marble | [
"801abdf65e112203d2b3c8983b0f73b0a4c821da"
] | [
"examples/initialization.py"
] | [
"import xarray as xr\nimport sympl\nimport numpy as np\nfrom marble import InputHeightToPrincipalComponents, convert_height_to_principal_components\nimport os\n\nheight_to_pc = InputHeightToPrincipalComponents()\n\ndata_path = os.path.join(\n os.path.dirname(\n os.path.realpath(__file__)\n ),\n 'dat... | [
[
"numpy.linspace"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.