repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
lsterzinger/advent-of-code-2021 | [
"4b082efd2c9ea3228e84ae42fdec9fb582ef88b9"
] | [
"01/01a.py"
] | [
"import numpy as np\n\ndepths = np.loadtxt('input.txt')\n\ncounter = 0\n\nfor i in range(1, len(depths)):\n if depths[i-1] < depths[i]:\n counter +=1 \n\nprint(counter)\n"
] | [
[
"numpy.loadtxt"
]
] |
Shadric/pandas-profiling | [
"2d304ef8abda4ecdbad82803bd8ba4a7f72a5e1f"
] | [
"src/pandas_profiling/model/summary.py"
] | [
"\"\"\"Compute statistical description of datasets.\"\"\"\n\nimport multiprocessing\nimport multiprocessing.pool\nimport string\nimport warnings\nfrom pathlib import Path\nfrom typing import Callable, Mapping, Optional, Tuple\nfrom urllib.parse import urlsplit\n\nimport numpy as np\nimport pandas as pd\nfrom pandas... | [
[
"scipy.stats.stats.chisquare",
"numpy.isfinite",
"numpy.min",
"numpy.isnan",
"numpy.median",
"numpy.max",
"numpy.std",
"numpy.mean",
"numpy.count_nonzero",
"numpy.var",
"numpy.histogram",
"numpy.sum"
]
] |
jt17383/neural_collaborative_filtering | [
"7db00c59cd2f11f35b09a98f2eaf7f379b2e13a9"
] | [
"MLP.py"
] | [
"'''\nCreated on Aug 9, 2016\nKeras Implementation of Multi-Layer Perceptron (GMF) recommender model in:\nHe Xiangnan et al. Neural Collaborative Filtering. In WWW 2017. \n\n@author: Xiangnan He (xiangnanhe@gmail.com)\n'''\n\nimport argparse\nfrom time import time\nfrom datetime import datetime\n\nimport numpy as ... | [
[
"numpy.array"
]
] |
Hrishi97/All-About-Machine-Learning | [
"e141951bc629cbd8c3068cc9d284cb40478d2d75"
] | [
"Machine Learning Algorithms/Section 3 - Classification/1. Logistic Regression/logistic_regression.py"
] | [
"# Logistic Regression\n\n# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importing the dataset\ndataset = pd.read_csv('Social_Network_Ads.csv')\nX = dataset.iloc[:, :-1].values\ny = dataset.iloc[:, -1].values\n\n# Splitting the dataset into the Training set ... | [
[
"matplotlib.pyplot.legend",
"pandas.read_csv",
"sklearn.linear_model.LogisticRegression",
"matplotlib.pyplot.title",
"numpy.unique",
"sklearn.metrics.confusion_matrix",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.ylabel",
"matplotlib.colors.ListedColormap",
... |
XuankangLin/ART | [
"2a734f960527f7b680cb42b1577f84fc9db68a2f"
] | [
"art/bisecter.py"
] | [
"\"\"\" Apply input bisection for Neural Network verification / certification / falsification. \"\"\"\n\nimport logging\nimport sys\nfrom pathlib import Path\nfrom typing import Tuple, Optional, Union\nfrom timeit import default_timer as timer\n\nimport torch\nfrom torch import Tensor, nn, autograd\nfrom torch.util... | [
[
"torch.enable_grad",
"torch.cat",
"torch.utils.data.DataLoader",
"torch.zeros_like",
"torch.tensor",
"torch.no_grad",
"torch.where",
"torch.autograd.grad"
]
] |
guanjue/vision_project_used_script | [
"6373304432a4938d5768ca42a14008b5b876d4f7"
] | [
"other_analysis/fig6_supple_fig18_step7_get_megatable/get_megatable_eRP.py"
] | [
"import numpy as np\n\n#ccRE0 = open('mouse_allChr_wTAD_022519.bed', 'r')\nccRE0 = open('mouse_allChr_wTAD_022519.repeat.bed', 'r')\nccRE1 = []\n\nfor records in ccRE0:\n\ttmp = [x.strip() for x in records.split('\\t')]\n\tccRE1.append(tmp[3])\n\n\nccRE_eRP0 = open('ccRE_eRP.table.r.txt', 'r')\nccRE_eRP1 = {}\n\nfo... | [
[
"numpy.array"
]
] |
maozezhong/imgaug | [
"18f2fe7d7c9933db52f09bc9f2049066a5eead01"
] | [
"tests/test.py"
] | [
"\"\"\"\nAutomatically run tests for this library.\nSimply execute\n python test.py\nor execute\n nosetests --verbose\nfrom within tests/\nor add @attr(\"now\") in front of a test and then execute\n nosetests --verbose -a now\nto only execute a specific test.\n\"\"\"\nfrom __future__ import print_function,... | [
[
"numpy.sqrt",
"numpy.all",
"numpy.max",
"numpy.zeros_like",
"numpy.mean",
"numpy.var",
"numpy.exp",
"numpy.histogram",
"numpy.random.randint",
"numpy.hstack",
"numpy.allclose",
"numpy.pad",
"numpy.unique",
"numpy.fliplr",
"numpy.uint8",
"numpy.clip",... |
MarcaWitt/Data_hackers | [
"c6fcb185c0bd6ad0ca7057c5323e05c21a8e9224",
"c6fcb185c0bd6ad0ca7057c5323e05c21a8e9224"
] | [
"Tianchi-Taobao-clothes-retrieval-master/bbox_sub/src_infer/layers.py",
"Tianchi-Taobao-clothes-retrieval-master/bbox_sub/src_infer/dataset.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\ndef gem(x, p=3, eps=1e-6):\n return F.avg_pool2d(x.clamp(min=eps).pow(p), (x.size(-2), x.size(-1))).pow(1. / p)\n\nclass GeM(nn.Module):\n\n def __init__(self, p=3.0, eps=1e-6, freeze_p=True):\n super(GeM, self).__init__()\n ... | [
[
"torch.ones"
],
[
"torch.cuda.is_available"
]
] |
tadatoshi/StatisticalClearSky | [
"40a7354f8e8b65c8008a56c655dddff700031558"
] | [
"statistical_clear_sky/algorithm/serialization/serialization_mixin.py"
] | [
"\"\"\"\nThis module defines Mixin for serialization.\n\"\"\"\nimport json\nimport numpy as np\nfrom statistical_clear_sky.algorithm.serialization.state_data import StateData\n\nclass SerializationMixin(object):\n \"\"\"\n Mixin for IterativeClearSky, taking care of serialization.\n \"\"\"\n\n def save_... | [
[
"numpy.array"
]
] |
Ien001/non-random-initialization-for-DFL-CNN | [
"f5982a2f3679970de122ec9d5a2389e11385d0eb"
] | [
"main.py"
] | [
"from model.DFL import DFL_VGG16, DFL_ResNet, DFL_ResNet_for_sample\nfrom utils.util import *\nfrom utils.transform import *\nfrom train import *\nfrom validate import *\nfrom utils.init import *\nimport sys\nimport argparse\nimport os\nimport random\nimport shutil\nimport time\nimport warnings\nimport torch\nimpor... | [
[
"torch.nn.CrossEntropyLoss",
"torch.utils.data.DataLoader",
"torch.load"
]
] |
julffers/pandapower | [
"b227571b4a123b38245932c0acb8e2b818ce6f5a"
] | [
"pandapower/io_utils.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright (c) 2016-2021 by University of Kassel and Fraunhofer Institute for Energy Economics\n# and Energy System Technology (IEE), Kassel. All rights reserved.\nimport copy\nimport importlib\nimport json\nimport numbers\nimport os\nimport pickle\nimport sys\nimport types\nimport weak... | [
[
"pandas.notnull",
"pandas.testing.assert_series_equal",
"numpy.allclose",
"pandas.isnull",
"numpy.isnan",
"pandas.DataFrame",
"pandas.testing.assert_frame_equal",
"numpy.equal",
"pandas.read_json",
"pandas.DataFrame.from_dict",
"pandas.Int64Index",
"numpy.array"
]... |
AminRezaei0x443/SnowFall | [
"daf9c4310f6c8129a65149e563beec52f99b479f"
] | [
"snowfall/generalization/loss_regularizers.py"
] | [
"import torch\n\nfrom snowfall.losses import Loss\n\n\nclass LossRegularizer(Loss):\n def __init__(self, loss, lambda_):\n super().__init__()\n # set loss\n if isinstance(loss, str):\n if Loss.has(loss):\n loss = Loss.get(loss)\n self.loss = loss\n ... | [
[
"torch.norm",
"torch.tensor"
]
] |
Cadair/ginga | [
"5afdd8824f27c7ae7d8d82b5013b0ff0068bd8b8"
] | [
"ginga/AstroImage.py"
] | [
"#\n# AstroImage.py -- Abstraction of an astronomical data image.\n#\n# Eric Jeschke (eric@naoj.org)\n#\n# Copyright (c) Eric R. Jeschke. All rights reserved.\n# This is open-source software licensed under a BSD license.\n# Please see the file LICENSE.txt for details.\n#\nimport sys, os\nimport re\nimport math\ni... | [
[
"numpy.nanmax",
"numpy.nanmin",
"numpy.fromstring",
"numpy.zeros",
"numpy.isclose"
]
] |
lavoiems/SADt | [
"26cce9d0dbc58f1a57de617d9eb49efe55d9ac59"
] | [
"src/models/sg_sem_blank/evaluate/fetch_results_sr.py"
] | [
"import torch\nfrom ..model import Generator, MappingNetwork, semantics\nimport torchvision.utils as vutils\nfrom common.loaders.images import dataset_single\nfrom common.util import get_args\n\n\ndef save_image(x, ncol, filename):\n x = (x + 1) / 2\n x.clamp_(0, 1)\n vutils.save_image(x.cpu(), filename, n... | [
[
"torch.cat",
"torch.load",
"torch.randn",
"torch.tensor",
"torch.no_grad",
"torch.stack"
]
] |
thetianshuhuang/l2o | [
"7497956aec42d8e8d43a641b2eb5a03ebf42f674"
] | [
"policies/choice_large.py"
] | [
"\"\"\"L2O that chooses either Adam or RMSProp at each iteration.\"\"\"\n\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.keras.layers import LSTMCell, Dense\n\nfrom .architectures import BaseCoordinateWisePolicy\nfrom .moments import rms_momentum\nfrom .softmax import softmax\n\n\nclass ChoiceLargeOp... | [
[
"tensorflow.cond",
"tensorflow.keras.layers.LSTMCell",
"tensorflow.zeros",
"tensorflow.shape",
"tensorflow.keras.layers.Dense",
"tensorflow.reduce_sum",
"tensorflow.cast",
"tensorflow.reshape",
"numpy.stack",
"tensorflow.sqrt",
"tensorflow.math.tanh",
"tensorflow.si... |
lamylio/federated | [
"6a709f5598450232b918c046cfeba849f479d5cb",
"6a709f5598450232b918c046cfeba849f479d5cb"
] | [
"rcc_dp/frequency_estimation/rhr.py",
"compressed_communication/aggregators/group_test.py"
] | [
"# Copyright 2021, Google LLC.\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 applicable law or agree... | [
[
"numpy.random.random_sample",
"numpy.concatenate",
"numpy.copy",
"numpy.array",
"numpy.zeros"
],
[
"tensorflow.ones"
]
] |
tzaremba5/Cross-Subject-BCI-Motor-Imagery-Classification | [
"be4e786db39696da992b36d5186b908e98398969"
] | [
"src/Experiments/tuner.py"
] | [
"################################################################################\n#\n# keras_tuner.py\n#\n# Tunes the model testing across 5 folds for the single-trial experiments\n\nimport kerastuner as kt\n\nimport os\nimport pickle\nimport random\nimport argparse\nfrom dataset_descriptions import *\nfrom create... | [
[
"sklearn.model_selection.KFold"
]
] |
FelixTheoret/Ergocycle | [
"0656e6cb43b535dd2f845420ad71742b1b85e412"
] | [
"source/StartWindow.py"
] | [
"\"\"\"\nCreated on Wed March 24 11:15:00 2022\n\n@author: Frédérique Leclerc\n\"\"\"\nfrom PyQt5 import QtWidgets\nfrom PyQt5.QtWidgets import *\nfrom PyQt5.QtGui import QFont, QPixmap\nimport numpy\nimport datetime\n#from Ergocycle.source.TestingWindow import TestingWindow\nfrom TestingWindow import TestingWindow... | [
[
"numpy.array"
]
] |
nataliavelez/teaching_fmri | [
"8f59642248aa1e548c5042929bb3c4f7a7f1f37b"
] | [
"7_multivariate/1_roi_rsa.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # Representational similarity analysis in mentalizing regions\n# Natalia Vélez, April 2022\n\nimport matplotlib\nmatplotlib.use('Agg')\n\n# general utils\nimport os,sys,pickle\nimport numpy as np\nimport pandas as pd\nfrom os.path import join as opj\nfrom scipy.io import... | [
[
"pandas.concat",
"pandas.read_csv",
"numpy.expand_dims",
"numpy.unravel_index",
"numpy.abs",
"matplotlib.use",
"numpy.arange",
"scipy.spatial.distance.cosine",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"numpy.floor",
"numpy.mod",
"numpy.zeros"
]
] |
steysie/morra | [
"556371dbc6f96bb2735aaa556dd6fd5653655644"
] | [
"morra/base_parser.py"
] | [
"# -*- coding: utf-8 -*-\n# Morra project: Base parser\n#\n# Copyright (C) 2020-present by Sergei Ternovykh\n# License: BSD, see LICENSE for details\n\"\"\"\nBase classes for the project.\n\"\"\"\nfrom collections import OrderedDict, defaultdict\nfrom copy import deepcopy\nfrom math import isclose\nimport pickle\ni... | [
[
"scipy.special.softmax"
]
] |
HyOsori/Osori-SelfDrivingWithGTA5 | [
"b88bffeaeef199a5f84c0fd0ecb5475424b618f6"
] | [
"grabscreen.py"
] | [
"import cv2\nimport numpy as np\nimport win32gui, win32ui, win32con, win32api\n\n\ndef grab_screen(region=None):\n hwin = win32gui.GetDesktopWindow()\n\n if region:\n left, top, x2, y2 = region\n width = x2 - left + 1\n height = y2 - top + 1\n else:\n width = win32api.GetSystemM... | [
[
"numpy.fromstring"
]
] |
msfasha/Arabic-Deep-Learning-OCR | [
"10cd02937eb4aa7f3e40265ec6a4d50f4ef5ef29"
] | [
"src/SamplePreprocessor.py"
] | [
"from __future__ import division\r\nfrom __future__ import print_function\r\n\r\nimport random\r\nimport numpy as np\r\nimport cv2\r\nimport Config as config\r\n\r\n\r\ndef preprocess(img):\r\n \"scale image into the desired imgSize, transpose it for TF and normalize gray-values\"\r\n\r\n # increase dataset s... | [
[
"numpy.ones"
]
] |
fedepal450/ROAR-RL_FullControl | [
"99c86b5d2f9da626098c0c13c63cbaf63d78792f"
] | [
"ROAR_Jetson/camera_d_t.py"
] | [
"import logging\nimport cv2\nfrom cv2 import aruco\nimport pyrealsense2 as rs\nimport math as m\nimport numpy as np\nimport sys\nimport time\nfrom typing import Optional, Tuple, List\ntry:\n from ROAR_Jetson.part import Part\nexcept:\n from part import Part\nCAM_CONFIG = {\n \"image_w\": 640, # image widt... | [
[
"numpy.radians",
"numpy.sqrt",
"numpy.linalg.inv",
"numpy.arctan2",
"numpy.identity",
"numpy.array"
]
] |
xxchenxx/DLDR | [
"22159199c54a0a2e902e17bcbf2a2fe7e2e4ff69",
"22159199c54a0a2e902e17bcbf2a2fe7e2e4ff69"
] | [
"models/inceptionv4.py",
"train_pbfgs_imagenet.py"
] | [
"# -*- coding: UTF-8 -*-\n\"\"\" inceptionv4 in pytorch\n\n\n[1] Christian Szegedy, Sergey Ioffe, Vincent Vanhoucke, Alex Alemi\n\n Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning\n https://arxiv.org/abs/1602.07261\n\"\"\"\n\nimport torch\nimport torch.nn as nn\n\nclass Basic... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout2d",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.MaxPool2d",
"torch.nn.AvgPool2d",
"torch.nn.Linear",
"torch.nn.AdaptiveAvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU"
],
[
"torch.nn.CrossEntropyLoss",
"torch.mm",
"t... |
manthangandhi/analyzing-weather-dataset | [
"52583e6471a02ecac8b9e064528f25b6ecbcddeb"
] | [
"code.py"
] | [
"# --------------\n# --------------\r\n#Importing the modules\r\nimport pandas as pd\r\nimport numpy as np\r\nfrom scipy.stats import mode \r\n\r\n\r\n#Code for categorical variable\r\ndef categorical(df):\r\n \"\"\" Extract names of categorical column\r\n \r\n This function accepts a dataframe and returns... | [
[
"pandas.read_csv",
"pandas.to_datetime",
"pandas.pivot_table"
]
] |
chriskjou/opennmt-inspection | [
"c70e1f3665ed29b20abcf464e4c73aa7e228a046",
"c70e1f3665ed29b20abcf464e4c73aa7e228a046"
] | [
"flair_embeddings.py",
"find_best_likelihood.py"
] | [
"from flair.embeddings import TransformerWordEmbeddings\nfrom flair.embeddings import BertEmbeddings, RoBERTaEmbeddings, XLMEmbeddings\nfrom flair.data import Sentence\nimport numpy as np\nimport os\nimport pickle\nimport argparse\nfrom tqdm import tqdm\n\ndef process_sentence(vocab, typ):\n\tnsentences = len(vocab... | [
[
"numpy.array",
"numpy.mean"
],
[
"numpy.maximum",
"numpy.minimum",
"numpy.nonzero",
"numpy.stack",
"numpy.equal",
"numpy.array",
"numpy.sum"
]
] |
bihui9968/SummaRuNNer | [
"4b5d7ac943debe982ef28b42bb5605a09a95bd13"
] | [
"src/test.py"
] | [
"#!/usr/bin/env python\n#coding:utf8\nimport argparse\nimport logging\nimport torch\nimport sys\nimport cPickle as pkl\nimport torch.nn as nn\nfrom helper import Config\nfrom helper import Dataset\nfrom helper import DataLoader\nfrom helper import prepare_data\nfrom helper import test\nfrom model import SummaRuNNer... | [
[
"torch.from_numpy",
"torch.cuda.set_device",
"torch.load"
]
] |
TmsRC/RubioTomas_Ejercicio17 | [
"27453477d27d677f66d7c73d872ac1f717fcc7f8"
] | [
"forest_quiebra.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport sklearn.ensemble\nimport sklearn.model_selection\nimport sklearn.metrics\nfrom scipy.io import arff\n\n\ndata = arff.loadarff('1year.arff')\ndf = pd.DataFrame(data[0])\n\ndata = arff.loadarff('2year.arff')\ndf2 = pd.DataFrame(data[0])... | [
[
"pandas.Series",
"numpy.isnan",
"numpy.arange",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"numpy.argmax",
"scipy.io.arff.loadarff",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.figure"
]
] |
buildOMG/kb | [
"c6465637b3e12d4869aec8e574d00cfdd80bf60c"
] | [
"redditbot/mainbot.py"
] | [
"# pip install -r requirements.txt\n\nimport praw\nimport time\nfrom datetime import datetime\nimport os\nimport csv\nfrom random import randint\nfrom logzero import logger\nimport json\nimport pandas as pd\nfrom pandasql import sqldf\nfrom tabulate import tabulate\nimport configparser\nfrom progress.bar import Bar... | [
[
"pandas.DataFrame.from_dict"
]
] |
naomi-choy/Mask_RCNN | [
"d06ee96b7d2ce2ded1f1d63af21a0a3ef5ffdb4b"
] | [
"mrcnn/config.py"
] | [
"\"\"\"\nMask R-CNN\nBase Configurations class.\n\nCopyright (c) 2017 Matterport, Inc.\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\"\"\"\n\nimport numpy as np\n\n\n# Base Configuration Class\n# Don't use this class directly. Instead, sub-class it and override\n# the config... | [
[
"numpy.array"
]
] |
metrizable/sagemaker-python-sdk | [
"8006fc4fda6572ba97fc5386739040792224eefb"
] | [
"tests/integ/test_tf.py"
] | [
"# Copyright 2017-2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"). You\n# may not use this file except in compliance with the License. A copy of\n# the License is located at\n#\n# http://aws.amazon.com/apache2.0/\n#\n# or in th... | [
[
"numpy.zeros"
]
] |
DOsinga/reverse_image_search | [
"8e129d6bc8bc5196f621150e9764ce9264f31e7d"
] | [
"image_server.py"
] | [
"#!/usr/bin/env python\nimport argparse\nimport pickle\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.python.platform import gfile\nimport os\nfrom flask import Flask, request, redirect, flash, jsonify\n\nBOTTLENECK_TENSOR_NAME = 'pool_3/_reshape:0'\nJPEG_DATA_TENSOR_NAME = 'DecodeJpeg/contents:0'\nI... | [
[
"tensorflow.import_graph_def",
"numpy.squeeze",
"tensorflow.Session",
"tensorflow.python.platform.gfile.FastGFile",
"tensorflow.GraphDef"
]
] |
pekasen/DBoeS-Automatization | [
"7888013868bb99cff324dbf374d4931231da065d"
] | [
"scraper/twitter_fetcher.py"
] | [
"from __future__ import unicode_literals\n\nimport csv\nimport os\nimport webbrowser\n\nimport pandas as pd\nimport tweepy as tp\n\nfrom credentials import twitter_api_key, twitter_api_secret_key\nfrom entities import Account, Entity, EntityGroup\n\ntokens_cache_file = os.path.join(\n os.path.dirname(__file__), ... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
Quanfita/ImageProcessing | [
"2a7c1d093a003c43d6d259f6e8db3b4e6163839b"
] | [
"styletransfer/animation/filter.py"
] | [
"import imp\nimport cv2\nimport numpy as np\nfrom math import tanh\n\ns = 9\nsigmacolor = 17\nsigmaspace = 17\n\nphieq = 20\n\nsigma = 1\nphie = 5\ntau = 0.981\n\ndef qnearest(f):\n f = f / 255 * 100\n if f >= 0 and f < 100.0/16:\n q=0\n elif f >= 100.0/16 and f < 12.5 + 100.0/16:\n q = 1... | [
[
"numpy.zeros"
]
] |
raviqqe/tensorflow-word2sent2doc | [
"0b6c7b6bf76e6353862730292ebd25397a330893"
] | [
"font2char2word2sent2doc/font2char2word2sent2doc_test.py"
] | [
"import sys\n\nimport tensorflow as tf\n\nfrom .font2char2word2sent2doc import def_font2char2word2sent2doc\n\n\ndef test_def_font2char2word2sent2doc():\n sys.argv = [\"command\",\n \"--num_classes\", \"7\",\n \"--font_file\", \"data/font.ttf\",\n \"--char_file\", \"da... | [
[
"tensorflow.variable_scope",
"tensorflow.zeros"
]
] |
7cm-diameter/bnet | [
"37e97266e81a966c579d9dd7601f68fde1993e67",
"37e97266e81a966c579d9dd7601f68fde1993e67"
] | [
"hbtfmt/sims/sarsa_variable_ratio.py",
"hbtfmt/sims/hqnet.py"
] | [
"import numpy as np\nfrom bnet.env import ConcurrentSchedule\nfrom hbtfmt.model import SarsaAgent\nfrom hbtfmt.util import to_onehot\n\n\ndef train_under_varibale_ratio(agent: SarsaAgent, env: ConcurrentSchedule):\n n, _ = agent.weights.shape\n pseudo_rewards = np.ones(n)\n prev_response = agent.choose_act... | [
[
"numpy.median",
"numpy.ones"
],
[
"numpy.savetxt"
]
] |
chunfuchen/aqua | [
"fde435203a2799433a4e50897554fa226c8ff1dc",
"fde435203a2799433a4e50897554fa226c8ff1dc",
"fde435203a2799433a4e50897554fa226c8ff1dc"
] | [
"test/aqua/test_data_providers.py",
"test/chemistry/test_end2end_with_iqpe.py",
"qiskit/chemistry/bksf.py"
] | [
"# -*- coding: utf-8 -*-\n\n# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2019.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE-2.0.\... | [
[
"numpy.array"
],
[
"numpy.testing.assert_approx_equal"
],
[
"numpy.diag",
"numpy.sqrt",
"numpy.einsum",
"numpy.asarray",
"numpy.size",
"numpy.triu",
"numpy.zeros",
"numpy.where"
]
] |
lukelbd/analysis | [
"b583e6c02d23602e05a3dc668abc7a0537393212"
] | [
"climopy/var.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nAnalyses of variance and trends. Many of these are adapted\nfrom examples and course notes provided by Professors `Elizabeth Barnes \\\n<http://barnes.atmos.colostate.edu/COURSES/AT655_S15/lecture_slides.html>`__\nand `Dennis Hartmann \\\n<https://atmos.washington.edu/~dennis/552_No... | [
[
"numpy.diag",
"numpy.polyfit",
"numpy.sqrt",
"numpy.asarray",
"numpy.round",
"numpy.any",
"numpy.moveaxis",
"numpy.exp",
"scipy.optimize.curve_fit",
"numpy.histogram",
"numpy.trace",
"numpy.fliplr",
"numpy.arange",
"numpy.atleast_1d",
"scipy.linalg.eigh"... |
majercakdavid/Mask_RCNN | [
"b398f68bd563e84d63c3b23af1cad9727b66bf74"
] | [
"deepfashion2_to_coco.py"
] | [
"import json\nfrom PIL import Image\nimport numpy as np\nfrom tqdm import tqdm\nimport os\nfrom mrcnn import utils\n\n\ndef get_dataset_categories():\n return [{\n 'id': 1,\n 'name': \"short_sleeved_shirt\",\n 'supercategory': \"clothes\",\n 'keypoints': ['1', '2', '3', '4', '5', '6',... | [
[
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] |
rickyHong/ClariNet-WaveNet-repl | [
"b03f99a64087e6eaf7682536b04379f1fe71b38a"
] | [
"synthesize.py"
] | [
"import time\nimport torch\nfrom torch.utils.data import Dataset, DataLoader\nfrom data import LJspeechDataset, collate_fn, collate_fn_synthesize\nfrom wavenet import Wavenet\nimport librosa\nimport os\nimport argparse\n\n\nparser = argparse.ArgumentParser(description='Train WaveNet of LJSpeech',\n ... | [
[
"torch.cuda.synchronize",
"torch.load",
"torch.utils.data.DataLoader",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device"
]
] |
sooftware/char-rnnlm | [
"fc6573bde13b151f373fc081f63e3f563debf56c"
] | [
"model.py"
] | [
"import random\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass LanguageModel(nn.Module):\n def __init__(self, n_class, n_layers, rnn_cell, hidden_size, dropout_p, max_length, sos_id, eos_id, device):\n\n super(LanguageModel, self).__init__()\n assert rnn_cell.lower(... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.Embedding",
"torch.zeros"
]
] |
plant99/MetPy | [
"b1e68bca9c7c0edf7f64e8ab963173fb9e0f1410"
] | [
"metpy/calc/tests/test_calc_tools.py"
] | [
"# Copyright (c) 2016,2017,2018 MetPy Developers.\n# Distributed under the terms of the BSD 3-Clause License.\n# SPDX-License-Identifier: BSD-3-Clause\n\"\"\"Test the `tools` module.\"\"\"\n\nfrom collections import namedtuple\n\nimport numpy as np\nimport numpy.ma as ma\nimport pytest\nimport xarray as xr\n\n\nfro... | [
[
"numpy.log",
"numpy.ones_like",
"numpy.linspace",
"numpy.meshgrid",
"numpy.asarray",
"numpy.arange",
"numpy.tile",
"numpy.datetime64",
"numpy.ma.arange",
"numpy.zeros_like",
"numpy.ma.array",
"numpy.array",
"numpy.zeros"
]
] |
stober/gridworld | [
"58762295687f890a66f1bfff0a22b05d62044d80"
] | [
"src/chainwalk.py"
] | [
"#! /usr/bin/env python\n\"\"\"\nAuthor: Jeremy M. Stober\nProgram: CHAINWALK.PY\nDate: Monday, January 11 2010\nDescription: Chainwalk from LSPI paper (2003).\n\"\"\"\n\nimport os, sys, getopt, pdb, string\nimport random as pr\nimport numpy as np\nimport scipy as sp\nimport scipy.io as sio\n\nfrom markovdp import ... | [
[
"numpy.array",
"numpy.zeros"
]
] |
ystoto/shelter_ml | [
"a961a6cd6c8771a3a8ee8e807bbe61c5c42ef857"
] | [
"code/utils.py"
] | [
"\"\"\" This file contains different utility functions that are not connected\nin anyway to the networks presented in the tutorials, but rather help in\nprocessing the outputs into a more understandable way.\n\nFor example ``tile_raster_images`` helps in generating a easy to grasp\nimage from a set of samples or we... | [
[
"numpy.zeros"
]
] |
NadezhdaBzhilyanskaya/pymatgen | [
"fae11a8142d457a649fa84ff9781eb2b39334bdc",
"fae11a8142d457a649fa84ff9781eb2b39334bdc"
] | [
"pymatgen/symmetry/bandstructure.py",
"pymatgen/io/abinitio/abitimer.py"
] | [
"\"\"\"\nCreated on March 25, 2013\n\n@author: geoffroy\n\"\"\"\nfrom __future__ import division\n\nimport numpy as np\n\nfrom math import ceil\nfrom math import cos\nfrom math import sin\nfrom math import tan\nfrom math import pi\nfrom warnings import warn\nfrom pymatgen.symmetry.finder import SymmetryFinder\n\ncl... | [
[
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"numpy.asarray",
"numpy.arange",
"matplotlib.pyplot.figure",
"numpy.fabs",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.draw",
"matplot... |
Mv77/Notebooks | [
"4eaac0ae20516acd835f5af0a87fd471ac56d725"
] | [
"notebooks/Durables-vs-Nondurables-At-Low-And-High-Frequencies.py"
] | [
"# ---\n# jupyter:\n# jupytext:\n# formats: ipynb,py:percent\n# text_representation:\n# extension: .py\n# format_name: percent\n# format_version: '1.1'\n# jupytext_version: 0.8.3\n# kernelspec:\n# display_name: Python 3\n# language: python\n# name: python3\n# langua... | [
[
"matplotlib.pyplot.legend",
"pandas.concat",
"matplotlib.pyplot.title",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.show",
"matplotlib.pyplot.style.use",
... |
mortenlj/advent_of_code | [
"738c1f3116f6a817a67183f076e1fe93680ea407"
] | [
"ibidem/advent_of_code/y2021/dec03.py"
] | [
"#!/usr/bin/env python\nimport numpy as np\n\nfrom ibidem.advent_of_code.board import Board\nfrom ibidem.advent_of_code.util import get_input_name\n\n\ndef load():\n with open(get_input_name(3, 2021)) as fobj:\n return Board.from_string(fobj.read(), fill_value=0, dtype=np.int_)\n\n\ndef to_decimal(grid):\... | [
[
"numpy.delete",
"numpy.sum",
"numpy.int_"
]
] |
kimbring2/MOBA_RL | [
"f3a02142e9125ee959eedd792b52d64545f5a3a5"
] | [
"dr-derks-mutant-battlegrounds/agent/oldbot.py"
] | [
"import os\nimport random\nimport timeit\nimport yaml\nfrom collections import deque\nimport numpy as np\nimport tensorflow as tf\nimport abc\nimport collections\n\nfrom discretization import SmartDiscrete, get_dtype_dict\nfrom utils import get_entity, get_action\nfrom model import get_network_builder\n\nimport grp... | [
[
"numpy.reshape",
"numpy.concatenate",
"numpy.iinfo",
"numpy.array",
"tensorflow.summary.scalar",
"tensorflow.summary.create_file_writer"
]
] |
bmalezieux/plipy | [
"35d17cad908219013fa43d81c4aeb6bb46ce9384"
] | [
"experiments/figures_from_results/inpainting_patch_rho.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport os\n\nfrom pathlib import Path\n\n\ntry:\n os.mkdir(\"../figures\")\nexcept OSError:\n pass\n\n\ndef compute_scores(df, name):\n\n value = df.loc[(data[\"name\"] == name)]\n\n patches = value.m_patch.unique()\n rhos = v... | [
[
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"matplotlib.pyplot.subplots",
"numpy.max",
"numpy.meshgrid",
"numpy.zeros"
]
] |
PeterouZh/PVT | [
"8edf436ac8f090882c1fdaf6392f439017dbcd52"
] | [
"losses.py"
] | [
"# Copyright (c) 2015-present, Facebook, Inc.\n# All rights reserved.\n\"\"\"\nImplements the knowledge distillation loss\n\"\"\"\nimport torch\nfrom torch.nn import functional as F\n\n\nclass DistillationLoss(torch.nn.Module):\n \"\"\"\n This module wraps a standard criterion and adds an extra knowledge dist... | [
[
"torch.no_grad",
"torch.nn.functional.log_softmax"
]
] |
MaybeS/Classifier | [
"b39ae3d775ad2ffe7c1fa59dfda15d4d4a906af3"
] | [
"test.py"
] | [
"import json\nfrom pathlib import Path\n\nfrom tqdm import tqdm\nimport torch\nimport torch.nn as nn\nfrom torch.utils import data\n\nfrom utils.arguments import Arguments\n\n\ndef init(model: nn.Module, device: torch.device,\n args: Arguments.parse.Namespace = None) \\\n -> nn.Module:\n model = m... | [
[
"torch.max",
"torch.load",
"torch.sum",
"torch.utils.data.DataLoader",
"torch.set_grad_enabled"
]
] |
sushseqi/disaster_response_pipeline | [
"b9ada88d52e1ac5a7916aa590fe44430c3b9edd4"
] | [
"app/run.py"
] | [
"import json\nimport plotly\nimport pandas as pd\n\nfrom nltk.stem import WordNetLemmatizer\nfrom nltk.tokenize import word_tokenize\n\nfrom flask import Flask\nfrom flask import render_template, request, jsonify\nfrom plotly.graph_objs import Bar, Line, Scatter\nfrom sklearn.externals import joblib\nfrom sqlalchem... | [
[
"pandas.read_sql_table",
"sklearn.externals.joblib.load"
]
] |
kymotsujason/sweeperbot2 | [
"136ce7dabce9ded7badfa1f8aeabc9f920865942"
] | [
"main.py"
] | [
"import cv2\nfrom PIL import ImageGrab\nimport numpy as np\n\n\ndef main():\n while True:\n # bbox specifies specific region (bbox= x,y,width,height)\n img = ImageGrab.grab(bbox=(0, 0, 2560, 1440))\n vanilla = img_np = np.array(img)\n img_np = np.array(img)\n gray = cv2.cvtColo... | [
[
"numpy.array"
]
] |
mfredriksz/semanticGAN_code | [
"c6e7b490086afd8a7593e2892452295555910494",
"c6e7b490086afd8a7593e2892452295555910494"
] | [
"models/lpips/__init__.py",
"semanticGAN/ranger.py"
] | [
"\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nfrom skimage.measure import compare_ssim\nimport torch\n\nfrom models.lpips import dist_model\n\n\nclass PerceptualLoss(torch.nn.Module):\n def __init__(self, model='net-lin', ... | [
[
"numpy.maximum",
"numpy.arange",
"torch.sum",
"numpy.concatenate",
"numpy.max",
"numpy.mean",
"numpy.prod",
"numpy.transpose",
"numpy.where",
"numpy.sum",
"numpy.isclose"
],
[
"torch.empty_like",
"torch.zeros_like"
]
] |
asvskartheek/transformers | [
"2d443d39bffe4f10dd01cbbf40897084366fb5ab",
"2d443d39bffe4f10dd01cbbf40897084366fb5ab"
] | [
"src/transformers/modeling_fx_utils.py",
"examples/pytorch/token-classification/run_ner.py"
] | [
"import copy\nimport functools\nimport inspect\nfrom typing import Any, Dict, List, Optional, Union\n\nimport torch\nfrom torch import nn\nfrom torch.fx import Graph, GraphModule, Node, Proxy, Tracer\nfrom torch.fx.node import Argument\n\nfrom . import (\n MODEL_FOR_CAUSAL_LM_MAPPING,\n MODEL_FOR_IMAGE_CLASSI... | [
[
"torch.fx.GraphModule",
"torch.ones",
"torch.zeros"
],
[
"numpy.argmax"
]
] |
CavalcanteLucas/devito | [
"f52cfd7d55b91f83245f33af4424adbdb03075d8"
] | [
"tests/test_symbolic_coefficients.py"
] | [
"import numpy as np\nimport pytest\n\nfrom conftest import skipif\nfrom devito import (Grid, Function, TimeFunction, Eq, Coefficient, Substitutions,\n Dimension, solve, Operator)\nfrom devito.finite_differences import Differentiable\nfrom devito.tools import as_tuple\n\n_PRECISION = 9\n\npytestma... | [
[
"numpy.array",
"numpy.isclose"
]
] |
ssinister/mfti-1784 | [
"9096f124761c986b03f5401d0642c74b0b2f57f3"
] | [
"knn.py"
] | [
"import numpy as np\n\n\nclass KNN:\n \"\"\"K-neariest-neighbor классификатор с L1 нормой.\"\"\"\n\n def __init__(self, k=1):\n self.k = k\n self.train_X = None\n self.train_y = None\n\n def fit(self, X, y):\n self.train_X = X\n self.train_y = y\n\n def predict(self, X... | [
[
"numpy.abs",
"numpy.linalg.norm",
"numpy.bincount",
"numpy.argsort",
"numpy.zeros"
]
] |
sanmitraghosh/pymc3 | [
"284e31c0dcc9bf60523f5d2f30328b29ab751f4d"
] | [
"pymc3/distributions/distribution.py"
] | [
"import numbers\n\nimport numpy as np\nimport theano.tensor as tt\nfrom theano import function\nimport theano\nfrom ..memoize import memoize\nfrom ..model import (\n Model, get_named_nodes_and_relations, FreeRV,\n ObservedRV, MultiObservedRV, Context, InitContextMeta\n)\nfrom ..vartypes import string_types\nf... | [
[
"numpy.hstack",
"numpy.asarray",
"numpy.atleast_1d",
"numpy.broadcast",
"numpy.floor",
"numpy.broadcast_arrays",
"numpy.prod",
"numpy.array",
"numpy.empty"
]
] |
Provincie-Zuid-Holland/satellite-images-datascience | [
"a6d26ef9f89389d14700b7e790416c90146e8ea3"
] | [
"nso_ds_classes/nso_ds_models.py"
] | [
"from locale import normalize\nimport numpy as np\nimport pandas as pd\nimport geopandas as gpd\nimport os\nfrom sklearn.preprocessing import LabelEncoder\nfrom sqlalchemy import false\nimport joblib\n\n\n\nclass euclidean_distance_model:\n\n \"\"\"\n A model that simply predicts a pixel kernel based on the e... | [
[
"tensorflow.keras.layers.Dropout",
"pandas.read_csv",
"numpy.abs",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.MaxPooling2D",
"numpy.concatenate",
"tensorflow.keras.layers.Convolution2D",
"numpy.load",
"numpy.array",
"sklearn.preprocessing.LabelEncoder",
"... |
KMarino/hrl-ep3 | [
"f1ad0c936d271955f4899a3a830023e1a2cffda3"
] | [
"hierarchical_main.py"
] | [
"# Modified by Kenneth Marino \n# This file trains the baseline actor critic methods\n# Modified from https://github.com/ikostrikov/pytorch-a2c-ppo-acktr \n\nimport argparse\nimport yaml\nimport json\nimport csv\nfrom pprint import pprint\nimport click\nimport shutil\nimport copy\nimport glob\nimport os\nimport tim... | [
[
"torch.cuda.manual_seed",
"torch.zeros",
"torch.load",
"torch.manual_seed",
"torch.from_numpy",
"numpy.stack",
"numpy.ones",
"numpy.concatenate",
"torch.set_num_threads",
"torch.no_grad",
"torch.cuda.is_available",
"torch.FloatTensor",
"numpy.array",
"torch.... |
gadde5300/sign_language_flask | [
"2a5859132b0dcd5dd4fc0c075a81289b39336909"
] | [
"app.py"
] | [
"import flask\nfrom PIL.Image import core as _imaging\nfrom flask import Flask, request, jsonify\nfrom PIL import Image\nimport numpy as np\nimport base64\nimport io\nimport os\n\nfrom backend.tf_inference import load_model, inference\n\nos.environ['CUDA_VISIBLE_DEVICES'] = '0'\n\nsess, detection_graph = load_model... | [
[
"numpy.array"
]
] |
denis-torre/biojupies-plugins | [
"8f59b407ffa8a463544d2296bd7c250d4edb351e"
] | [
"library/analysis_tools/l1000fwd/l1000fwd.py"
] | [
"#################################################################\n#################################################################\n############### DE \n#################################################################\n#################################################################\n\n########################... | [
[
"pandas.set_option",
"pandas.DataFrame"
]
] |
Zepyhrus/tf2 | [
"807f93a5cc81dc424ef76be3103b68fb3d2dded9"
] | [
"src/4-8.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\nfrom utils import get_one\n\ntf.compat.v1.disable_v2_behavior()\n\n\n\ndef generate_data(data_size=100):\n train_X = np.linspace(-data_size/100, data_size/100, data_size)\n train_Y = 2 * train_X + np.random.randn(*train_X.shape) * 0.3\n\n return train_X, train_Y\n\... | [
[
"tensorflow.compat.v1.data.make_one_shot_iterator",
"numpy.linspace",
"tensorflow.compat.v1.disable_v2_behavior",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.cast",
"tensorflow.compat.v1.Session",
"numpy.random.randn"
]
] |
johnson7788/EasyTransfer | [
"7e59935ab663fbdb9be56e7e081e59a2154b5489",
"7e59935ab663fbdb9be56e7e081e59a2154b5489",
"7e59935ab663fbdb9be56e7e081e59a2154b5489",
"7e59935ab663fbdb9be56e7e081e59a2154b5489"
] | [
"easytransfer/model_zoo/modeling_utils.py",
"easytransfer/losses/labeling_loss.py",
"easytransfer/evaluators/evaluator.py",
"easytransfer/datasets/tfrecord_writer.py"
] | [
"# coding=utf-8\n# Copyright (c) 2019 Alibaba PAI team.\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... | [
[
"tensorflow.constant",
"tensorflow.gfile.Exists",
"tensorflow.python.platform.gfile.GFile",
"tensorflow.train.init_from_checkpoint",
"tensorflow.python.pywrap_tensorflow.NewCheckpointReader",
"tensorflow.trainable_variables"
],
[
"tensorflow.reduce_sum",
"tensorflow.nn.log_soft... |
venturiscm/hcp | [
"74ad18180822301274daa9218d7bd9fbdb7807f7"
] | [
"app/systems/commands/mixins/base.py"
] | [
"from collections import OrderedDict\n\nfrom django.conf import settings\n\nfrom systems.commands import args\nfrom utility import text, data\nfrom .meta import MetaBaseMixin\n\nimport re\nimport copy\nimport pandas\n\n\nclass BaseMixin(object, metaclass = MetaBaseMixin):\n\n @classmethod\n def generate(cls, ... | [
[
"pandas.to_datetime"
]
] |
HotaekHan/classification-pytorch | [
"41185301709280c78ce1e51e3c9bc5c4d23d6443",
"41185301709280c78ce1e51e3c9bc5c4d23d6443"
] | [
"models/efficientnet_builder.py",
"models/layers/split_att_conv2d.py"
] | [
"import logging\nimport math\nimport re\nfrom collections import OrderedDict\nfrom copy import deepcopy\n\nimport torch.nn as nn\n\nfrom .efficientnet_blocks import *\nfrom .layers.cond_conv2d import CondConv2d, get_condconv_initializer\n\n__all__ = [\"EfficientNetBuilder\", \"decode_arch_def\", \"efficientnet_init... | [
[
"torch.nn.Sequential"
],
[
"torch.nn.functional.softmax",
"torch.sigmoid",
"torch.split",
"torch.nn.Conv2d",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.nn.modules.utils._pair",
"torch.nn.ReLU"
]
] |
BuragaIonut/MachineLearning | [
"97ba9eb3faaaf27d35dba435a1bba87ee6a634e9"
] | [
"LinearRegression/Fishes/LinearRegression_Fishes.py"
] | [
"import numpy as np\nimport pandas as pd\nimport sklearn\nimport matplotlib.pyplot as plt\nfrom sklearn.linear_model import LinearRegression\n\ndata = pd.read_csv('Fish.csv')\n# print(data.head())\ndata = data[['Weight','Length1','Length2','Length3','Height','Width']]\n# print(data.head())\n\npredict = 'Weight'\nX ... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.plot",
"sklearn.linear_model.LinearRegression",
"numpy.array",
"matplotlib.pyplot.show"
]
] |
gregschmit/django-pufsim | [
"5578cdbd2ced5b897868ca6a84217f0843c1269b"
] | [
"pufsim/analysis/views.py"
] | [
"from base64 import b64encode\nfrom django.urls import reverse\nfrom django.views import generic, View\nfrom io import BytesIO\nfrom matplotlib import pyplot as plt\nimport numpy as np\nimport puflib as pl\nfrom . import models\n\n\ndef bar_graph(data, top=1, title='', xlabel='', ylabel=''):\n b = BytesIO()\n ... | [
[
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig"
]
] |
MacHu-GWU/wotlkdoc-project | [
"5aaad1351a08d55b88b8a25cbc5c9c667ca576bc"
] | [
"wotlkdoc/localization/__init__.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom loc import LocDict\nimport pandas as pd\nfrom pathlib_mate import PathCls as Path\n\nTAB = \"\\t\"\nDATA_DIR = Path(Path(__file__).change(new_basename=\"data\"))\n\n\ndef read_loc_dict(file):\n df = pd.read_csv(Path(DATA_DIR, file).abspath, sep=TAB)\n ld = LocDict(data=df.to_d... | [
[
"pandas.read_csv"
]
] |
ghost9023/DeepLearningPythonStudy | [
"4d319c8729472cc5f490935854441a2d4b4e8818"
] | [
"DeepLearning/DeepLearning/02_Deep_ChoTH/deep_learning_5.py"
] | [
"## CHAPTER 5 오차역전파법\n# 앞에서는 신경망의 가중치 매개변수의 기울기는 수치미분을 사용해 구했다.\n# 수치미분은 단순하고 구현하기 쉽지만 계산시간이 오래 걸린다는 단점이 있다.\n# 이번장은 가중치 매개변수의 기울기를 효율적으로 계산하는 '오차역전파법'을 배워보자\n\n# 오차역전파법을 제대로 이해하는 방법은 두 가지가 있다.\n# 1. 수식을 통해 - 정확하고 간결함\n# 2. 계산 그래프를 통해 - 시각적으로!! 본질에 다가가기 쉬움\n\n# 계산그래프\n# 노드와 엣지로 표현된다.\n# 계산그래프로 풀다.\n# 1. 계산그래프를 구성한다... | [
[
"numpy.dot",
"numpy.nditer",
"numpy.random.choice",
"numpy.arange",
"numpy.max",
"numpy.argmax",
"numpy.zeros_like",
"numpy.random.rand",
"numpy.random.randn",
"numpy.exp",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
noob-life/GAIL-for-mountain-car-Tensorflow | [
"dd38b3d482ed765487bf0a7ff215fb605f2a1941"
] | [
"model.py"
] | [
"import tensorflow as tf\r\nimport tensorflow.keras as kr\r\nimport collections\r\nimport numpy as np\r\nfrom tensorflow import random\r\n#from tensorflow.python.keras import layers\r\n\r\n\r\nclass gail_gen(kr.Model):\r\n\t\"\"\"docstring for gail_gen\"\"\"\r\n\tdef __init__(self, state_shape,action_shape):\r\n\t\... | [
[
"tensorflow.keras.layers.Dense",
"tensorflow.keras.activations.softmax",
"tensorflow.keras.layers.LeakyReLU"
]
] |
LesterCovax/astrobee | [
"608f6688c6f6088f1357fed9e68b45d68bc9ee2d"
] | [
"tools/graph_bag/scripts/bag_and_parameter_sweep.py"
] | [
"#!/usr/bin/python\n#\n# Copyright (c) 2017, United States Government, as represented by the\n# Administrator of the National Aeronautics and Space Administration.\n#\n# All rights reserved.\n#\n# The Astrobee platform is licensed under the Apache License, Version 2.0\n# (the \"License\"); you may not use this file... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
ymitiku/InstaHide | [
"746405ec0f65c40ff9ba6706cc2eb6fa577474ec"
] | [
"train_cross.py"
] | [
"#!/usr/bin/env python3 -u\n\nfrom __future__ import print_function\n\nimport argparse\nimport csv\nimport os\n\nimport numpy as np\n\nimport torch\nfrom torch.autograd import Variable\nimport torch.backends.cudnn as cudnn\nimport torch.nn as nn\nimport torch.optim as optim\nimport torchvision.transforms as transfo... | [
[
"torch.set_rng_state",
"torch.load",
"torch.randperm",
"torch.utils.data.DataLoader",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"torch.autograd.Variable",
"torch.save",
"torch.nn.CrossEntropyLoss",
"torch.from_numpy",
"torch.distributions.laplace.L... |
SiccarPoint/landlab | [
"4f43055060b544b34e71eba7062c09866ad93640"
] | [
"landlab/components/nonlinear_diffusion/Perron_nl_diffuse.py"
] | [
"from six.moves import range\n\nimport numpy as np\nimport scipy.sparse as sparse\nimport scipy.sparse.linalg as linalg\nfrom landlab.grid.base import BAD_INDEX_VALUE\n\n# these ones only so we can run this module ad-hoc:\n# import pylab\nfrom landlab import ModelParameterDictionary, Component\nfrom landlab.utils.d... | [
[
"scipy.sparse.linalg.spsolve",
"numpy.arange",
"numpy.empty_like",
"numpy.empty",
"numpy.all",
"numpy.tan",
"numpy.concatenate",
"numpy.any",
"numpy.repeat",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"numpy.vstack"
]
] |
vigneshwarajpuresoftware/cpprb | [
"4c0de2fae700b1a198ab8530a9de4f2aea117e57"
] | [
"test/v8.py"
] | [
"import unittest\n\nimport numpy as np\n\nfrom cpprb import ReplayBuffer,PrioritizedReplayBuffer\nfrom cpprb import create_buffer\n\nfrom cpprb.PyReplayBuffer import NstepBuffer\n\nclass TestReplayBuffer(unittest.TestCase):\n def test_buffer(self):\n\n buffer_size = 256\n obs_shape = (15,15)\n ... | [
[
"numpy.random.random",
"numpy.array_equiv",
"numpy.asarray",
"numpy.arange",
"numpy.stack",
"numpy.ones",
"numpy.full",
"numpy.array",
"numpy.zeros",
"numpy.roll"
]
] |
laolaozj/DeepCDR_LCQ | [
"218a14e45fb4ed167f51cd761384dd9d0c48a095"
] | [
"prog/extract_drug_features.py"
] | [
"'''\nmodify from \nhttps://github.com/deepchem/deepchem/blob/master/deepchem/feat/molecule_featurizers/mol_graph_conv_featurizer.py#L1-L233 \n'''\n\nfrom typing import List, Tuple\nimport numpy as np\n\nfrom deepchem.utils.typing import RDKitAtom, RDKitBond, RDKitMol\nfrom deepchem.feat.graph_data import GraphData... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.asarray"
]
] |
dwferrer/tf-poly | [
"28633d630a772cdef8fd477866a58561b5ccd42a"
] | [
"src/tf_polygon/primitives.py"
] | [
"import tensorflow as tf\nimport numpy as np\n\n\ndef signed_point_line_area(lines, points):\n \"\"\"\n Computes the signed (oriented) area of the parallelogram specified by the given directed lines (specified as two\n non-identical points) and each of the given points. A negative value indicates the poin... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.sign",
"tensorflow.constant",
"tensorflow.logical_or",
"tensorflow.roll",
"tensorflow.stack",
"tensorflow.reduce_any",
"tensorflow.cast",
"numpy.exp",
"tensorflow.math.mod",
"tensorflow.logical_not",
"tensorflow.math.reduc... |
allister633/binance-algotrade | [
"fb9de7f770ce9867ed2ffc65c4bf831f09501afd"
] | [
"tests/test_indicators.py"
] | [
"import unittest\nimport pandas as pd\nimport numpy as np\n\nimport indicators\n\nclass TestIndicators(unittest.TestCase):\n \"\"\"Tests indicators against TA-Lib output data.\"\"\"\n\n def setUp(self):\n self.ohlc = pd.read_csv('tests/data/BTCUSDT_15m.csv', index_col='time', parse_dates=True)\n\n d... | [
[
"numpy.all",
"pandas.read_csv",
"numpy.isclose"
]
] |
fuuuyuuu/2048-api | [
"d96aa0bc7099e8ce7b792ec2b1051a44b4325eec"
] | [
"game2048/generate_data.py"
] | [
"import pandas as pd\nfrom game2048.game import Game\nfrom game2048.displays import Display, IPythonDisplay\nfrom game2048.agents import Agent,RandomAgent, ExpectiMaxAgent\nimport numpy as np\nimport csv\n# 0: left, 1: down, 2: right, 3: up\n\nwith open(\"data_random.csv\",\"a\") as csvfile:\n writer = csv.writ... | [
[
"numpy.log2",
"numpy.array",
"numpy.int32",
"numpy.where"
]
] |
davidbrochart/bundle | [
"9e6a14fa48e4d22a2cbc8239b13e600a86c5e5b0"
] | [
"bundle/expression.py"
] | [
"# Author: AxiaCore S.A.S. http://axiacore.com\n#\n# Based on js-expression-eval, by Matthew Crumley (email@matthewcrumley.com, http://silentmatt.com/)\n# https://github.com/silentmatt/js-expression-eval\n#\n# Ported to Python and modified by Vera Mazhuga (ctrl-alt-delete@live.com, http://vero4ka.info/)\n#\n# You a... | [
[
"numpy.add",
"numpy.cos",
"numpy.multiply",
"numpy.sin"
]
] |
sx14/HOI-det | [
"28c302c40b311f38352384f42ea72aeeaa76cb3c"
] | [
"exp/generate_HICO_detection.py"
] | [
"# --------------------------------------------------------\n# Tensorflow TIN\n# Licensed under The MIT License [see LICENSE for details]\n# --------------------------------------------------------\n\n\"\"\"\nChange the HICO-DET detection results to the right format.\ninput arg: python Generate_HICO_detection_nis.p... | [
[
"numpy.argsort",
"numpy.zeros",
"scipy.io.savemat"
]
] |
pvarin/ncortex | [
"e0c1cd1815148649920db100e6c8d006312ea408"
] | [
"ncortex/optimization/test/test_trajopt.py"
] | [
"''' Test the trajectory optimization procedures.\n'''\n\nimport tensorflow as tf\n\nclass TestTrajOpt(tf.test.TestCase):\n ''' Test the trajectory optimization procedures.\n '''\n\n def test_naive_trajopt(self):\n ''' Test the naive_trajopt function.\n '''\n pass\n\nif __name__ == '__... | [
[
"tensorflow.test.main"
]
] |
xiling42/VL-BERT | [
"4573b4e1e82b6c092d4830d0b88821e9ee1a81fb",
"4573b4e1e82b6c092d4830d0b88821e9ee1a81fb"
] | [
"refcoco/data/collate_batch.py",
"common/nlp/input_variational_dropout.py"
] | [
"import torch\nfrom common.utils.clip_pad import *\n\n\nclass BatchCollator(object):\n def __init__(self, dataset, append_ind=False):\n self.dataset = dataset\n self.test_mode = self.dataset.test_mode\n self.data_names = self.dataset.data_names\n self.append_ind = append_ind\n\n de... | [
[
"torch.tensor"
],
[
"torch.nn.functional.dropout"
]
] |
tobywise/multi_agent_mdp | [
"51571d2ed387d1111ddff56c75d58582fb73a471"
] | [
"maMDP/algorithms/policy_learning.py"
] | [
"from abc import abstractmethod\nimport numpy as np\nfrom typing import Union, List\nfrom ..mdp import MDP\nfrom .irl import BaseIRL\nfrom copy import deepcopy\n\ndef degdist(x, y):\n \"\"\"\n Gives (shortest) distance between two angles \n \"\"\"\n return np.abs(((x - y) + 180) % 360 - 180)\n\ndef deg_... | [
[
"numpy.abs",
"numpy.power",
"numpy.arange",
"numpy.argmax",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] |
JanuszBartosz/peds2019 | [
"878a49ec11090df43bdd127ffd655a9b14e65795"
] | [
"model.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Jan 18 15:04:06 2019\n\n@author: Chonghua Xue (Kolachalama's Lab, BU)\n\"\"\"\n\nfrom lstm_bi import LSTM_Bi\nfrom utils_data import ProteinSeqDataset, aa2id_i, aa2id_o, collate_fn\nfrom tqdm import tqdm\nimport numpy as np\nimport torch\nimpo... | [
[
"torch.nn.NLLLoss",
"numpy.split",
"torch.utils.data.DataLoader",
"numpy.cumsum",
"numpy.save",
"torch.tensor",
"torch.set_grad_enabled",
"numpy.load",
"torch.argmax"
]
] |
sanixa/blind_MI | [
"d0fafe56ea998a5b18fd1ace2176d434d7d04ca7",
"d0fafe56ea998a5b18fd1ace2176d434d7d04ca7"
] | [
"Top1_Threshold_Attack.py",
"ModelUtil.py"
] | [
"from dataLoader import *\r\nimport tensorflow as tf\r\nfrom tensorflow.keras.models import load_model\r\nfrom BlindMIUtil import evaluate_attack\r\nimport sys\r\n\r\nos.environ['CUDA_VISIBLE_DEVICES'] = '0'\r\ntf.config.experimental.set_memory_growth(tf.config.experimental.list_physical_devices('GPU')[0], True)\r\... | [
[
"tensorflow.keras.models.load_model",
"tensorflow.config.experimental.list_physical_devices"
],
[
"tensorflow.keras.layers.GlobalAveragePooling2D",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.application... |
vohoaiviet/tag-image-retrieval | [
"0a257560581f702cd394f3f28c9e0f6202827ce8"
] | [
"model_based/tagfeat/concat_tag_visual.py"
] | [
"import sys\nimport os\nimport random\nimport numpy as np\n\nfrom basic.constant import ROOT_PATH\nfrom basic.common import makedirsforfile,niceNumber,checkToSkip,printStatus\nfrom basic.util import readImageSet\nfrom util.simpleknn.bigfile import BigFile\n\nINFO = __file__\n\nif __name__ == '__main__':\n rootpa... | [
[
"numpy.argsort",
"numpy.array"
]
] |
bopopescu/PyRate | [
"f914bf562955ec6d7ab3d4549c3327e20a1b3848",
"f914bf562955ec6d7ab3d4549c3327e20a1b3848"
] | [
"tests/test_mpi_vs_multiprocess_vs_single_process.py",
"tests/test_stackrate.py"
] | [
"import os\nimport shutil\nimport pytest\nfrom pathlib import Path\nfrom subprocess import check_call, check_output, CalledProcessError\nimport numpy as np\nfrom pyrate.core import config as cf\nfrom tests.common import (\n assert_same_files_produced,\n assert_two_dirs_equal,\n manipulate_test_conf,\n T... | [
[
"numpy.random.randint"
],
[
"numpy.eye",
"numpy.ones",
"numpy.testing.assert_array_equal",
"numpy.array",
"numpy.testing.assert_array_almost_equal"
]
] |
yezouagh/Face-Recognition-webapp | [
"78f66ee4dea9b15bd069d6b7e0c4c3c4c50855dc"
] | [
"face_reco.py"
] | [
"from email import encoders\nfrom email.mime.base import MIMEBase\nimport time\nfrom datetime import datetime\nimport ssl\nimport face_recognition\nimport cv2\nimport os\nimport numpy as np\nimport smtplib\nfrom email.mime.multipart import MIMEMultipart\nfrom email.mime.text import MIMEText\n\nos.environ['TF_CPP_MI... | [
[
"numpy.argmin"
]
] |
SvenSerneels/OptimalPortfolio | [
"ebba4dadb06d9b018d1a80ce14a6db18e8f52a3c"
] | [
"portfolioopt/utility_functions.py"
] | [
"\"\"\"\nThe ``utility_functions`` module provides common utility functions, mainly used interally.\nThose wanting to extend must take note of the requirements of scipy.optimize to\nnot run into errors.\n\nCurrently implemented:\n\n- mean, covariance, skew and kurtosis utility function\n\"\"\"\n\nimport numpy as np... | [
[
"numpy.dot",
"numpy.kron",
"numpy.transpose"
]
] |
23jura23/NeMo | [
"6815146775432852feee1bc28ed1a7a2fc94010d",
"6815146775432852feee1bc28ed1a7a2fc94010d"
] | [
"nemo/collections/asr/models/ctc_models.py",
"nemo/collections/asr/models/rnnt_models.py"
] | [
"# Copyright (c) 2020, 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 at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless re... | [
[
"torch.no_grad",
"torch.cuda.is_available"
],
[
"torch.stack",
"torch.no_grad",
"torch.cuda.is_available"
]
] |
kalray/tensorflow-yolo-v3 | [
"efd58246c741ab4c6ef3131fa2c62b9ac19068cc"
] | [
"demo.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport numpy as np\nimport tensorflow as tf\nfrom PIL import Image\nimport time\n\nimport yolo_v3\nimport yolo_v3_tiny\n\nfrom utils import load_coco_names, draw_boxes, get_boxes_and_inputs, get_boxes_and_inputs_pb, non_max_suppression, \\\n load_graph, letter_box_image\... | [
[
"tensorflow.app.flags.DEFINE_bool",
"tensorflow.global_variables",
"tensorflow.app.flags.DEFINE_integer",
"tensorflow.ConfigProto",
"tensorflow.GPUOptions",
"tensorflow.app.flags.DEFINE_string",
"tensorflow.app.flags.DEFINE_float",
"tensorflow.Session",
"tensorflow.app.run"
]... |
dongdongdong666/CPGAN | [
"ef82f2d605a8fb6b0a031d65810fc840d99cc465"
] | [
"evaluation/datasets.py"
] | [
"from __future__ import absolute_import\r\nfrom __future__ import division\r\nfrom __future__ import print_function\r\nfrom __future__ import unicode_literals\r\n\r\n\r\nfrom nltk.tokenize import RegexpTokenizer\r\nfrom collections import defaultdict\r\nfrom config import cfg\r\n\r\nimport torch\r\nimport torch.uti... | [
[
"pandas.read_csv",
"numpy.minimum",
"numpy.maximum",
"numpy.asarray",
"numpy.arange",
"numpy.random.shuffle",
"numpy.sort",
"torch.sort",
"numpy.zeros",
"torch.autograd.Variable"
]
] |
kartikeyshaurya/SDV | [
"e66a3cafe28e2cace2f4cfdb4a71bb002dc7bcb6"
] | [
"venv/1Finding_Lanes/lanes.py"
] | [
"# MOTIVE FIND THE AREA OF INTEREST\nimport cv2\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef canny(lane_image):\n grey = cv2.cvtColor(lane_image, cv2.COLOR_RGB2BGR)\n # blurring the image to reduce the noise\n blur = cv2.GaussianBlur(grey, (5, 5), 0)\n # here it will outline the final b... | [
[
"numpy.copy",
"numpy.array",
"numpy.zeros_like"
]
] |
PerryXDeng/hps | [
"94325b3b4150600baf56a21f72e0aa44fc774f0b",
"94325b3b4150600baf56a21f72e0aa44fc774f0b"
] | [
"losses.py",
"global_vars.py"
] | [
"\"\"\"\nDefines losses used in the optimization\n\"\"\"\nimport torch\n\nimport numpy as np\nfrom scipy.spatial.transform import Rotation as R\n\nimport torchgeometry as tgm\nfrom torch.nn import functional as F\nimport cv2\n\ndef joint_angle_error(pred_mat, gt_mat, rot_max):\n \"\"\"\n Compute the geodesic ... | [
[
"torch.mean",
"torch.norm",
"torch.transpose",
"scipy.spatial.transform.Rotation.from_quat",
"torch.from_numpy",
"torch.tensor",
"torch.nn.functional.relu",
"torch.bmm",
"torch.nn.functional.pad"
],
[
"numpy.dot",
"torch.mean",
"torch.transpose",
"scipy.spat... |
husqvarnagroup/rtl8xxxu-utils | [
"b80d6defc0e132823998c785533be8f37487eb3f"
] | [
"rtl8xxxu_visualize.py"
] | [
"#!/usr/bin/env python3\nimport argparse\nimport logging\nimport os\nimport sys\n\nimport pandas\nfrom matplotlib import pyplot as plt\nfrom tabulate import tabulate\n\nfrom rtl8xxxu.analyze import get_metadata, process_pcap_file\n\nlog = logging.getLogger(\"rtl8xxxu_visualize\")\n\n\ndef pandas_series(file_name, m... | [
[
"matplotlib.pyplot.show",
"pandas.MultiIndex.from_tuples",
"matplotlib.pyplot.subplots_adjust"
]
] |
sanjaradylov/moleculegen-ml | [
"4acb77244909cf8cfe4fb75461d4bed9b77f29f1"
] | [
"moleculegen/callback/callbacks.py"
] | [
"\"\"\"\nThe collection of callbacks.\n\nClasses:\n BatchMetricScorer:\n Calculate and log metrics after batch sampling and forward computation.\n EarlyStopping:\n Stop training when a monitored evaluation function has stopped improving.\n EpochMetricScorer:\n Calculate and log metrics... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure"
]
] |
s-col/cymandel | [
"8f65e79c51073910779e54ab540cb0cd7916b3c4"
] | [
"setup.py"
] | [
"from distutils.core import setup\nfrom distutils.extension import Extension\nfrom Cython.Distutils import build_ext\nimport numpy\n\n\next_modules = [Extension('c_mandel.calc_mandel', ['c_mandel/calc_mandel.pyx'],\n include_dirs=[numpy.get_include()])]\n\nsetup(\n name='c_mandel',\n a... | [
[
"numpy.get_include"
]
] |
lionelkusch/compare_zerlaut | [
"4e22d1fdc5889fb404187bb7a48d7847759443d6"
] | [
"parameter_analyse/create_TF.py"
] | [
"# Copyright 2021 Aix-Marseille Université\n# \"Licensed to the Apache Software Foundation (ASF) under one or more contributor license agreements; and to You under the Apache License, Version 2.0. \"\nfrom parameter_analyse.function_fitting_parameters import engin\nfrom parameters import excitatory_param, inhibito... | [
[
"numpy.set_printoptions"
]
] |
MannyKayy/PlayableVideoGeneration | [
"14133f94e14a40fc17f283e5b01c168bc45990b6"
] | [
"utils/tensor_folder.py"
] | [
"from typing import List\n\nimport torch\nimport torch.nn as nn\n\nclass TensorFolder:\n\n @staticmethod\n def flatten(tensor: torch.Tensor) -> torch.Tensor:\n '''\n Flattens the first two dimensions of the tensor\n\n :param tensor: (dim1, dim2, ...) tensor\n :return: (dim1 * dim2,... | [
[
"torch.reshape"
]
] |
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