repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
henrique/jigsaw20 | [
"5d12de807667810ea9b9bdb9cbccebabea7ed21d"
] | [
"one_cycle_scheduler.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nimport tensorflow as tf\nfrom tensorflow.keras.callbacks import Callback\n\n\nclass CosineAnnealer:\n def __init__(self, start, end, steps):\n self.start = start\n self.end = end\n self.steps = steps\n self.n = 0\n \n d... | [
[
"tensorflow.keras.backend.get_value",
"matplotlib.pyplot.subplot",
"numpy.cos",
"tensorflow.keras.backend.set_value"
]
] |
sudo-prakhar/touri_ros-1 | [
"38ffc7f2f7d3484c7073af248f470f135e11dca6"
] | [
"src/touri_perception/scripts/hands_pose_detector.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\nTouRI Robot Base Code\n\"\"\"\n__author__ = \"Jigar Patel\"\n__mail__ = \"jkpatel@andrew.cmu.edu\"\n__copyright__ = \"NONE\"\n\n# -----------------------------------------------------------------------------\n\nfrom csv import excel_tab\nimport cv2\nimport numpy as np\nimpor... | [
[
"numpy.frombuffer"
]
] |
monadyn/fedlearn-algo | [
"63d9ceb64d331ff2b5103ae49e54229cad7e2095",
"63d9ceb64d331ff2b5103ae49e54229cad7e2095"
] | [
"demos/HFL/app/run_client.py",
"demos/HFL/example/communicator/tornado_communicator.py"
] | [
"# Copyright 2021 Fedlearn authors.\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 agre... | [
[
"numpy.ones"
],
[
"numpy.zeros"
]
] |
hexiang-hu/UNITER | [
"f2582bc2532b58f95a07973f3112b4876ed3de3e"
] | [
"data/loader.py"
] | [
"\"\"\"\nCopyright (c) Microsoft Corporation.\nLicensed under the MIT license.\n\nA prefetch loader to speedup data loading\nModified from Nvidia Deep Learning Examples\n(https://github.com/NVIDIA/DeepLearningExamples/tree/master/PyTorch).\n\"\"\"\nimport torch\n\n\ndef move_to_cuda(batch):\n if isinstance(batch... | [
[
"torch.cuda.current_stream",
"torch.cuda.Stream",
"torch.cuda.stream"
]
] |
udaynbausj/Machine_Learning | [
"ddcdb59a3c6786a7acff2dfd55e09765e8afa30a"
] | [
"Decision_Tree.py"
] | [
"from sklearn.datasets import load_iris\nfrom sklearn import tree\nfrom sklearn.naive_bayes import GaussianNB\n\niris = load_iris()\n\nclf = tree.DecisionTreeClassifier()\n\nnb_clf = GaussianNB()\n\n#loading and training the dataset\n\nclf.fit(iris.data,iris.target)\n\nnb_clf.fit(iris.data,iris.target)\n\n#lets tes... | [
[
"sklearn.tree.DecisionTreeClassifier",
"sklearn.datasets.load_iris",
"sklearn.naive_bayes.GaussianNB"
]
] |
deanrp2/neorl | [
"14734988e3034c9b3bbc8f33678bae67fd082a9f",
"14734988e3034c9b3bbc8f33678bae67fd082a9f"
] | [
"neorl/hybrid/epso.py",
"neorl/evolu/gwo.py"
] | [
"# This file is part of NEORL.\n\n# Copyright (c) 2021 Exelon Corporation and MIT Nuclear Science and Engineering\n# NEORL is free software: you can redistribute it and/or modify\n# it under the terms of the MIT LICENSE\n\n# THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR... | [
[
"numpy.linspace",
"numpy.cumsum",
"pandas.DataFrame",
"numpy.round",
"numpy.max",
"numpy.argmin",
"numpy.exp",
"numpy.where",
"numpy.arange",
"numpy.argmax",
"numpy.zeros",
"numpy.multiply",
"numpy.min",
"numpy.argsort",
"numpy.logical_and",
"numpy.a... |
wenjunsun/FacialDebiasing | [
"d894e1354fc0391f5be74e86ccb9503553f71aef"
] | [
"code/download.py"
] | [
"# Dependencies\nimport os\nimport urllib.request\nimport tarfile\nimport pandas as pd\n\n# Set path to current directory\nabspath = os.path.abspath(__file__)\ndname = os.path.dirname(abspath)\nos.chdir(dname)\n\ndef ensure_path(path):\n \"\"\"Makes sure a path exists and otherwise creates one.\"\"\"\n if not... | [
[
"pandas.read_csv"
]
] |
phetdam/bac-advanced-ml | [
"26de8661c3c5f00c13353e2d695ebf316545a037"
] | [
"bacaml/supervised/_linear.py"
] | [
"\"\"\"Linear regression and classification models.\n\n.. codeauthor:: Derek Huang <djh458@stern.nyu.edu>\n\"\"\"\n\nimport math\nimport numpy as np\nimport scipy.sparse.linalg\nimport scipy.special\nimport scipy.optimize\nfrom sklearn.base import BaseEstimator\nfrom sklearn.utils import check_array, check_X_y\n\n\... | [
[
"sklearn.utils.check_X_y",
"numpy.unique",
"numpy.power",
"sklearn.utils.check_array",
"numpy.eye",
"numpy.zeros",
"numpy.exp",
"numpy.where",
"numpy.empty"
]
] |
Wentaobi/Vehicle-Detection | [
"0d6842224832e03692cbad36012bfd61129c1c7d"
] | [
"utils/utils.py"
] | [
"# code based on:\n#YAD2K https://github.com/allanzelener/YAD2K\n#darkflow https://github.com/thtrieu/darkflow\n#Darknet.keras https://github.com/sunshineatnoon/Darknet.keras\n\nimport numpy as np\nimport cv2\n\ndef load_weights(model,yolo_weight_file):\n \n data = np.fromfile(yolo_weight_file,np.... | [
[
"numpy.fromfile",
"numpy.prod"
]
] |
3kwa/ipython | [
"70362b811aced1ceb429433875ac0861c4d0729d"
] | [
"IPython/extensions/rmagic.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n======\nRmagic\n======\n\nMagic command interface for interactive work with R via rpy2\n\nUsage\n=====\n\n``%R``\n\n{R_DOC}\n\n``%Rpush``\n\n{RPUSH_DOC}\n\n``%Rpull``\n\n{RPULL_DOC}\n\n``%Rget``\n\n{RGET_DOC}\n\n\"\"\"\n\n#-----------------------------------------------------------... | [
[
"numpy.asarray",
"numpy.array",
"pandas.rpy.common.convert_to_r_dataframe",
"numpy.rec.fromarrays"
]
] |
lynex/nnfusion | [
"99ada47c50f355ca278001f11bc752d1c7abcee2"
] | [
"models/tensorflow/deep_speech_model.py"
] | [
"# Copyright 2018 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.layers.batch_normalization",
"tensorflow.concat",
"tensorflow.nn.static_rnn",
"tensorflow.shape",
"tensorflow.reshape",
"tensorflow.layers.dense",
"tensorflow.squeeze",
"tensorflow.pad",
"tensorflow.split"
]
] |
cortext/patstat | [
"ae02ee130ecfe21cef3096a73e0a167fdee22481"
] | [
"Actors/applicants classification/fuzzy string matching/fuzzy.py"
] | [
"import pymysql\nimport pandas as pd\nfrom sshtunnel import SSHTunnelForwarder\nfrom os.path import expanduser\nimport configparser\nfrom fuzzywuzzy import fuzz\nfrom progress.bar import Bar\n\nconfig = configparser.ConfigParser()\nconfig.read('config.ini')\nhome = expanduser('~')\n\n# remote database auth\nsql_hos... | [
[
"pandas.read_sql_query"
]
] |
brain-good/determined | [
"4a80514f514b1cc2aa5dcd604e17c18876b3b76e"
] | [
"harness/tests/experiment/tensorflow/test_estimator_trial.py"
] | [
"import os\nimport pathlib\nimport tempfile\nfrom pathlib import Path\nfrom typing import Any, Callable, Dict, Optional\n\nimport pytest\nimport tensorflow as tf\n\nimport determined as det\nfrom determined import workload\nfrom determined.exec import harness\nfrom tests.experiment import utils # noqa: I100\nfrom ... | [
[
"tensorflow.Graph",
"tensorflow.compat.v1.saved_model.loader.load"
]
] |
BillyTang/CIL | [
"26f863aea98b339cc4f8f53f0d33f61a44742d5c"
] | [
"Wrappers/Python/cil/optimisation/operators/Operator.py"
] | [
"# -*- coding: utf-8 -*-\r\n# This work is part of the Core Imaging Library (CIL) developed by CCPi \r\n# (Collaborative Computational Project in Tomographic Imaging), with \r\n# substantial contributions by UKRI-STFC and University of Manchester.\r\n\r\n# Licensed under the Apache License, Version 2.0 (the... | [
[
"numpy.sqrt",
"numpy.abs",
"numpy.finfo"
]
] |
DigitalMediaProfessionals/application | [
"63d5f90a152d62cca2a8daa33158950de463d2c2"
] | [
"YOLOv3TF/YOLOv3TF.py"
] | [
"#!/usr/bin/env python3\n\"\"\"\n Copyright 2019 Digital Media Professionals 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/L... | [
[
"tensorflow.keras.models.load_model",
"numpy.expand_dims",
"numpy.maximum",
"numpy.minimum",
"numpy.concatenate",
"numpy.delete",
"numpy.float32",
"numpy.argsort",
"tensorflow.keras.backend.set_learning_phase",
"numpy.tanh",
"numpy.where",
"numpy.empty"
]
] |
brechmos-stsci/specutils | [
"a3c721d044e890a1b7fc4f94bc0884a45703d323"
] | [
"specutils/manipulation/estimate_uncertainty.py"
] | [
"import numpy as np\n\nfrom astropy import units as u\n\nfrom .. import Spectrum1D, SpectralRegion\nfrom astropy.nddata import StdDevUncertainty\nfrom .extract_spectral_region import extract_region\n\n\n__all__ = ['noise_region_uncertainty']\n\n\ndef noise_region_uncertainty(spectrum, spectral_region, noise_func=np... | [
[
"numpy.concatenate",
"numpy.ones"
]
] |
Bhavya-Hingorani/SimpleHTR | [
"c7548cbfe60e6be29d21c09d1b8e7fe16da7e310"
] | [
"src/model.py"
] | [
"import os\nimport sys\nfrom typing import List, Tuple\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom dataloader_iam import Batch\n\n# Disable eager mode\ntf.compat.v1.disable_eager_execution()\n\n\nclass DecoderType:\n \"\"\"CTC decoder types.\"\"\"\n BestPath = 0\n BeamSearch = 1\n WordBeamSea... | [
[
"tensorflow.concat",
"tensorflow.control_dependencies",
"tensorflow.nn.ctc_beam_search_decoder",
"tensorflow.compat.v1.nn.rnn_cell.LSTMCell",
"tensorflow.compat.v1.train.Saver",
"tensorflow.compat.v1.nn.bidirectional_dynamic_rnn",
"tensorflow.nn.atrous_conv2d",
"numpy.exp",
"te... |
swshon/arabic-dialect-identification | [
"de15d4a574c2057d89e1e2a7411aed0f3c1fabec"
] | [
"scripts/feature_tools.py"
] | [
"from tqdm import tqdm\n\nimport os,sys\nimport numpy as np\nimport librosa\n\n\ndef cmvn_slide(feat,winlen=300,cmvn=False): #feat : (length, dim) 2d matrix\n maxlen = np.shape(feat)[0]\n new_feat = np.empty_like(feat)\n cur = 1\n leftwin = 0\n rightwin = winlen/2\n \n # middle\n for cur in ... | [
[
"numpy.imag",
"numpy.nonzero",
"numpy.empty_like",
"numpy.random.shuffle",
"numpy.std",
"numpy.real",
"numpy.shape",
"numpy.mean",
"numpy.array"
]
] |
egepaksoy/python | [
"093b54eba52d62789f149abf8155fa1b38138eb3"
] | [
"opencv/getColor.py"
] | [
"import cv2\r\nimport numpy as np\r\nfrom random import randint\r\nimport time\r\n\r\nboolean = input('Do you want to use your webcam?\\ny or n\\n')\r\nboolean = upper(boolean)\r\n\r\nif boolean == \"y\": \r\n boolean = True\r\n print(\"webcam will used\")\r\nif boolean == \"n\": \r\n boolean = False\r\n ... | [
[
"numpy.array"
]
] |
josandmann/BSTIM-Covid19 | [
"b31b8f8f8eeb064b86803eabd0c134b54a850c85",
"b31b8f8f8eeb064b86803eabd0c134b54a850c85"
] | [
"src/plot_interaction_kernel_window.py",
"src/plot_curves.py"
] | [
"import matplotlib\n#matplotlib.use('TkAgg')\nfrom sampling_utils import *\nimport numpy as np\nimport pickle as pkl\nimport seaborn as sns\nimport matplotlib.patheffects as PathEffects\nfrom config import *\nfrom plot_utils import *\nfrom shared_utils import *\nimport matplotlib\nfrom matplotlib import pyplot as p... | [
[
"numpy.linspace",
"matplotlib.colors.Normalize",
"matplotlib.pyplot.colorbar",
"matplotlib.cm.ScalarMappable",
"numpy.random.randint",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.style.use",
"numpy.empty",
"matplotlib.pyplot.figure"
],
[
"numpy.reshape",
"m... |
vektorelpython24proje/temelbilgiler | [
"bced2723d247dbb8b10cf86e25ee209635f82921"
] | [
"SAKIR/OPENCV/opencv10.py"
] | [
"import cv2 \nimport numpy as np\n# frame per second\ncap = cv2.VideoCapture(0,cv2.CAP_DSHOW)\nwhile True:\n ret,frame = cap.read()\n ret,frame = cap.read()\n\n # boundaries = [\n\t# ([17, 15, 100], [50, 56, 200]),\n\t# ([86, 31, 4], [220, 88, 50]),\n\t# ([25, 146, 190], [62, 174, 250]),\n\t# ([103, 86, 65... | [
[
"numpy.hstack",
"numpy.array"
]
] |
ravwojdyla/dask | [
"3b92efff2e779f59e95e05af9b8f371d56227d02"
] | [
"dask/dataframe/tests/test_multi.py"
] | [
"import warnings\n\nimport dask.dataframe as dd\nimport numpy as np\nimport pandas as pd\n\nfrom dask.base import compute_as_if_collection\nfrom dask.dataframe._compat import tm\nfrom dask.dataframe.core import _Frame\nfrom dask.dataframe.methods import concat\nfrom dask.dataframe.multi import (\n align_partitio... | [
[
"pandas.merge",
"pandas.concat",
"pandas.to_datetime",
"pandas.Series",
"numpy.arange",
"pandas.Index",
"pandas.DataFrame",
"pandas.Timedelta",
"pandas.DatetimeIndex",
"numpy.dtype",
"numpy.random.randn",
"numpy.random.randint",
"pandas.melt",
"pandas.merge_... |
Impelon/road-network-link-prediction | [
"b259935dd5f8ce7023b4bad14ca1221dcf2f19fe"
] | [
"code/predict_links.py"
] | [
"import sys\nimport os\nimport time\nimport itertools\nimport json\nimport joblib\nimport osmnx as ox\nimport networkx as nx\nimport sklearn as sk\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport __init__ as util\nfrom sklearn.ensemble import RandomForestClassifier\n\n\n# feature-function / similarity-s... | [
[
"numpy.array",
"numpy.math.hypot",
"sklearn.ensemble.RandomForestClassifier"
]
] |
zezhong-zhang/atomate | [
"c31fb58ec82e71be69e5d15ebad31489dff8af5d"
] | [
"atomate/vasp/firetasks/write_inputs.py"
] | [
"\"\"\"\nThis module defines tasks for writing vasp input sets.\n\"\"\"\n\nimport os\nfrom importlib import import_module\n\nimport numpy as np\n\nfrom monty.serialization import dumpfn\n\nfrom fireworks import FiretaskBase, explicit_serialize\nfrom fireworks.utilities.dict_mods import apply_mod\n\nfrom pymatgen.co... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.multiply"
]
] |
skforest/intro_ds | [
"478a6b236c2e33c4baffec8aafa8e0a8ed68dca8",
"478a6b236c2e33c4baffec8aafa8e0a8ed68dca8",
"478a6b236c2e33c4baffec8aafa8e0a8ed68dca8"
] | [
"ch08-supervised/svm/svm_vs_logit.py",
"ch04-linear/simple_example/generate_data.py",
"ch10-unsupervised/clustering/kmeans_choose_k.py"
] | [
"# -*- coding: UTF-8 -*-\n\"\"\"\n此脚本用于展示svm和logit regression的差异\n\"\"\"\n\n\nimport sys\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.svm import SVC\n\n\ndef generate_data(n, centers):\n \"\"\"\n 生成训练模型的数据\n \... | [
[
"matplotlib.pyplot.legend",
"sklearn.linear_model.LogisticRegression",
"numpy.random.seed",
"numpy.linspace",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.random.randn",
"sklearn.svm.SVC",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pypl... |
dgrinko/qiskit-aqua | [
"43a0f5675205f92086560c7171ab1d7917e7c53c"
] | [
"qiskit/aqua/algorithms/many_sample/qsvm/qsvm.py"
] | [
"# -*- coding: utf-8 -*-\n\n# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2018, 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... | [
[
"numpy.triu_indices",
"numpy.asarray",
"numpy.indices",
"numpy.ones",
"numpy.concatenate",
"numpy.all",
"numpy.vdot"
]
] |
rodrigo2019/keras_yolo2 | [
"28ed56befa2eb9de6d75d475b3736f33a2464bd9"
] | [
"keras_yolov2/frontend.py"
] | [
"import os\nimport sys\n\nimport cv2\nimport numpy as np\nfrom tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint, TensorBoard\nfrom tensorflow.keras.layers import Reshape, Conv2D, Input\nfrom tensorflow.keras.models import Model\nfrom tensorflow.keras.optimizers import Adam\n\nfrom .cosine_decay impo... | [
[
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.models.Model",
"tensorflow.keras.layers.Conv2D",
"numpy.random.normal",
"tensorflow.keras.optimizers.Adam",
"tensorflow.keras.callbacks.TensorBoard",
"tensorflow.keras.layers.Reshape",
"tensorflow.keras.callbacks.Early... |
raymond-devries/skagit60-scraping | [
"bea9c41c7bb650abe77ae6c1bfa9f755f1e65846"
] | [
"clean_raw_data.py"
] | [
"import pandas as pd\nimport re\n\n\ndef clean_mountain_names(mountain_name: str, remove_spaces=True):\n mountain_name = mountain_name.lower()\n words_to_remove = ['mountain', 'mount', 'mt', 'peak', 'the', ',', '\"']\n for word in words_to_remove:\n mountain_name = mountain_name.replace(word, '')\n\... | [
[
"pandas.read_csv"
]
] |
gilad83/Taboola-Internship | [
"454d566bfe2eef729e9f8bcd6d7941650c0bccf0",
"454d566bfe2eef729e9f8bcd6d7941650c0bccf0"
] | [
"old_files/plot_W_plotly.py",
"LSTM_model.py"
] | [
"import os, glob\nimport time\nfrom functools import reduce\n\n\nimport pandas as pd\nimport plotly.express as px\n\n\n#single server\nfrom sklearn.preprocessing import MinMaxScaler\n\navg_cpu_load = '/avg_cpu_load'\navg_heap = '/avg_heap'\navg_memory = '/avg_memory'\navg_num_cores = '/avg_num_cores'\ncpu_user_util... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.merge",
"pandas.DataFrame",
"sklearn.preprocessing.MinMaxScaler"
],
[
"pandas.concat",
"pandas.to_datetime",
"pandas.read_csv",
"pandas.merge",
"pandas.DataFrame",
"sklearn.preprocessing.MinMaxScaler"
]
] |
stevenkleinegesse/GradBED | [
"1aaba1a7062bcbfb0a328dc243e357153d5b6614"
] | [
"scripts/sde_pe_train_obs.py"
] | [
"import numpy as np\nfrom tqdm import tqdm as tqdm\nimport random\nimport sys, os\n\n# PyTorch stuff\nimport torch\nfrom torch.optim.lr_scheduler import StepLR\n\n# GradBED stuff\nfrom gradbed.networks.fullyconnected import *\nfrom gradbed.bounds.jsd import *\nfrom gradbed.bounds.nwj import *\nfrom gradbed.utils.in... | [
[
"torch.optim.Adam",
"torch.abs",
"numpy.random.seed",
"torch.load",
"torch.cuda.manual_seed",
"torch.manual_seed",
"torch.zeros_like",
"torch.tensor",
"torch.save",
"torch.no_grad",
"torch.cuda.manual_seed_all",
"torch.cuda.is_available",
"torch.where",
"tor... |
faruq2021/ivy | [
"1b24beadbd673d6a9dd504e037c68547e5640627"
] | [
"ivy/functional/backends/numpy/creation.py"
] | [
"# global\nimport numpy as np\nfrom typing import Union, Tuple, Optional, List\n\n# local\nfrom ivy import dtype_from_str, default_dtype\n# noinspection PyProtectedMember\nfrom ivy.functional.backends.numpy.old.general import _to_dev\n\n\ndef zeros(shape: Union[int, Tuple[int], List[int]],\n dtype: Optiona... | [
[
"numpy.ones_like",
"numpy.dtype",
"numpy.ones",
"numpy.full_like",
"numpy.triu",
"numpy.tril"
]
] |
juliandehoog/geo-timeseries-to-image | [
"2a8dda727f8010dfdc02af630e951e6e723e1c05"
] | [
"geots2img/geots2img.py"
] | [
"import warnings\nimport copy\nimport numpy as np\nimport os\nfrom scipy.interpolate import griddata\nimport matplotlib.pyplot as plt\nfrom PIL import Image\nfrom pathlib import Path\nimport pytz\n\n\nclass ImageGenerator:\n \"\"\" Generates an image based on a number of individual data points \"\"\"\n\n def ... | [
[
"numpy.swapaxes",
"numpy.linspace",
"matplotlib.pyplot.get_cmap",
"numpy.append",
"scipy.interpolate.griddata",
"numpy.array",
"numpy.flip"
]
] |
michaelborck/ddmso | [
"9c587a34e46d3aea0b2b401778020f6f9a90ce29"
] | [
"src/mrcnn/utils.py"
] | [
"\"\"\"\nMask R-CNN\nCommon utility functions and classes.\n\nCopyright (c) 2017 Matterport, Inc.\nLicensed under the MIT License (see LICENSE for details)\nWritten by Waleed Abdulla\n\"\"\"\n\nimport sys\nimport os\nimport logging\nimport math\nimport random\nimport numpy as np\nimport tensorflow as tf\nimport sci... | [
[
"numpy.dot",
"numpy.minimum",
"numpy.sqrt",
"tensorflow.stack",
"numpy.around",
"tensorflow.cast",
"numpy.cumsum",
"numpy.concatenate",
"numpy.max",
"numpy.all",
"numpy.any",
"numpy.exp",
"numpy.where",
"numpy.divide",
"numpy.pad",
"numpy.reshape",
... |
VijayAnand-B/OPIXray | [
"73a435ea820584f300cf8e074e459f750d15eec1"
] | [
"DOAM/counting.py"
] | [
"#统计一下数据中每个类别的数量\r\n\r\n\r\nimport sys\r\n\r\nimport numpy as np\r\n\r\nif sys.version_info[0] == 2:\r\n import xml.etree.cElementTree as ET\r\nelse:\r\n import xml.etree.ElementTree as ET\r\n\r\nimport os\r\n\r\n\r\nSIXray_CLASSES = ('gun', 'knife', 'wrench', 'pliers', 'scissors')\r\n\r\n\r\n\r\nclass_to_ind... | [
[
"numpy.zeros"
]
] |
bobelly/torchsupport | [
"5aa0a04f20c193ec99310f5d6a3375d2e95e740d",
"5aa0a04f20c193ec99310f5d6a3375d2e95e740d",
"5aa0a04f20c193ec99310f5d6a3375d2e95e740d"
] | [
"torchsupport/interacting/control.py",
"examples/conditional_mnist_ebm.py",
"examples/set_mnist_gan.py"
] | [
"from copy import copy\nimport torch.multiprocessing as mp\n\nclass ReadControl:\n def __init__(self, ctrl):\n self.ctrl = ctrl\n\n def __enter__(self):\n with self.ctrl.read_lock:\n self.ctrl.read_count.value += 1\n if self.ctrl.read_count.value == 1:\n self.ctrl.write_lock.acquire()\n ... | [
[
"torch.multiprocessing.Lock",
"torch.multiprocessing.Value"
],
[
"torch.cat",
"torch.zeros",
"torch.nn.functional.avg_pool2d",
"torch.nn.Conv2d",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.nn.functional.relu",
"torch.nn.GroupNorm"
],
[
"torch.cat",
"torch... |
shachargluska/centerpose | [
"555d753cd82693476f91f78c53aa4147f5a83015",
"555d753cd82693476f91f78c53aa4147f5a83015"
] | [
"lib/models/decode.py",
"demo/tracking/util.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom .utils import _gather_feat, _transpose_and_gather_feat\n\n\ndef _nms(heat, kernel=3):\n pad = (kernel - 1) // 2\n\n hmax = nn.functional.max_pool2d(\n heat, ... | [
[
"torch.max",
"torch.cat",
"torch.nn.functional.conv2d",
"torch.stack",
"torch.nn.functional.max_pool2d"
],
[
"numpy.arange",
"numpy.array",
"numpy.exp"
]
] |
swang-sjtu/espnet | [
"51ccb3fc140c48f4c11d73787943a2a895252783"
] | [
"espnet/nets/pytorch_backend/e2e_tts_tacotron2.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n# Copyright 2018 Nagoya University (Tomoki Hayashi)\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\n\"\"\"Tacotron 2 related modules.\"\"\"\n\nimport logging\n\nimport numpy as np\nimport torch\nimport torch.nn.functional as F\n\nfrom espnet.nets.p... | [
[
"torch.nn.functional.normalize",
"torch.nn.Module.__init__",
"torch.zeros",
"torch.cat",
"torch.tensor",
"torch.exp",
"torch.no_grad",
"torch.nn.L1Loss",
"torch.arange",
"torch.nn.MSELoss"
]
] |
maksym-del/allennlp | [
"672485fbc130edb9fb5980d0e0156b2f63c129e5"
] | [
"tests/modules/transformer/toolkit_test.py"
] | [
"import torch\nfrom torch.testing import assert_allclose\nfrom overrides import overrides\nfrom transformers import AutoModel\nfrom transformers.models.albert.modeling_albert import AlbertEmbeddings\n\nfrom allennlp.common import cached_transformers\nfrom allennlp.data.vocabulary import Vocabulary\nfrom allennlp.mo... | [
[
"torch.LongTensor",
"torch.testing.assert_allclose"
]
] |
ktfm2/Kai_updates | [
"f731922d3e140c1f16ea9b4b45f39232fe19a1ba"
] | [
"chemevo/Paint_comparison.py"
] | [
"#Compare painted data with observed data - for three different sets of ages\n#Works but could do with some tidying up of the code\nimport numpy as np\nimport h5py\nimport pandas as pd\nimport math\nfrom astropy.io import fits\nfrom astropy.table import Table, join\nimport matplotlib.pyplot as plt\nfrom matplotlib.... | [
[
"matplotlib.colors.LogNorm",
"matplotlib.pyplot.title",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.sca",
"numpy.random.normal",
"matplotlib.pyplot.xlim",
"numpy.tanh",
"pandas.isna... |
jie311/MutualGuide | [
"4671e1c46c156d84ac4f52acdd9e9ff3fed94252"
] | [
"utils/loss/focal_loss.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\nclass FocalLoss(nn.Module):\n\n def __init__(\n self,\n alpha: float = 0.25,\n gamma: float = 1.0,\n loss_weight: float = 1.0,\n ) -> None:\n super(FocalL... | [
[
"torch.nn.functional.binary_cross_entropy_with_logits"
]
] |
WoojuLee24/APR | [
"8bfafcfa5c7b1747d555362b84a1ebe0bb3fbdbd"
] | [
"autoattacks/eval.py"
] | [
"import os\nimport argparse\nimport torch\nimport torch.nn as nn\nimport torchvision.datasets as datasets\nimport torch.utils.data as data\nimport torchvision.transforms as transforms\n\nimport sys\nsys.path.insert(0,'..')\n\n\nif __name__ == '__main__':\n parser = argparse.ArgumentParser()\n parser.add_argum... | [
[
"torch.nn.Sequential",
"torch.cat",
"torch.load",
"torch.utils.data.DataLoader",
"torch.no_grad",
"torch.nn.DataParallel"
]
] |
macedo22/spectre | [
"9350d61830b360e2d5b273fdd176dcc841dbefb0",
"9350d61830b360e2d5b273fdd176dcc841dbefb0"
] | [
"tests/Unit/Evolution/Systems/Cce/NewmanPenrose.py",
"tests/Unit/NumericalAlgorithms/Interpolation/Python/Test_RegularGridInterpolant.py"
] | [
"# Distributed under the MIT License.\n# See LICENSE.txt for details.\n\nimport numpy as np\n\n\ndef psi0(bondi_j, dy_j, dy_dy_j, bondi_k, bondi_r, one_minus_y):\n dy_beta = 0.125 * one_minus_y * (\n dy_j * np.conj(dy_j) - 0.25 *\n (bondi_j * np.conj(dy_j) + np.conj(bondi_j) * dy_j)**2 / bondi_k**2... | [
[
"numpy.conj"
],
[
"numpy.allclose",
"numpy.stack",
"numpy.concatenate",
"numpy.polynomial.legendre.Legendre.basis",
"numpy.meshgrid"
]
] |
winnerineast/TGS-Salt-Identification-Challenge | [
"0c7246035ba6ba42cdb40592d65998ca9a56c742"
] | [
"src/4.train.py"
] | [
"import os\nimport numpy as np\nimport tensorflow as tf\n\nfrom tqdm import tqdm_notebook\nfrom skimage.transform import resize\nfrom keras.models import Model, load_model\nfrom keras.layers import Input\nfrom keras.layers.core import Lambda\nfrom keras.layers.convolutional import Conv2D, Conv2DTranspose\nfrom kera... | [
[
"tensorflow.metrics.mean_iou",
"tensorflow.local_variables_initializer",
"tensorflow.control_dependencies",
"numpy.arange",
"tensorflow.identity",
"tensorflow.to_int32",
"numpy.zeros"
]
] |
soumitri2001/Py_FS | [
"172c861d8a5783435d3f8582ad8a1bebf641ee4c"
] | [
"build/lib/Py_FS/wrapper/nature_inspired/MA.py"
] | [
"\"\"\"\n\nProgrammer: Trinav Bhattacharyya\nDate of Development: 13/10/2020\nThis code has been developed according to the procedures mentioned in the following research article:\nZervoudakis, K., Tsafarakis, S., A mayfly optimization algorithm, Computers &\nIndustrial Engineering (2020)\n\n\"\"\"\n\nimport numpy ... | [
[
"numpy.minimum",
"numpy.sqrt",
"numpy.maximum",
"numpy.random.random",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.savefig",
"numpy.random.normal",
"numpy.mean",
"sklearn.datasets.load_digits",
"numpy.floor",
"numpy.exp",
"numpy.random.uniform",
... |
lunayach/pytorch-custom-dataset-examples | [
"530187bc3342870231ce0937a32bf16ef035f220"
] | [
"src/custom_datasets.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom PIL import Image\n\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Variable\nfrom torchvision import transforms\nfrom torch.utils.data.dataset import Dataset # For custom datasets\n\nfrom cnn_model import MnistCNNModel\n\n\nclass CustomDatasetFromImag... | [
[
"torch.nn.CrossEntropyLoss",
"pandas.read_csv",
"numpy.asarray",
"torch.utils.data.DataLoader",
"torch.autograd.Variable"
]
] |
Danigore25/python2 | [
"de6d582fcc35107aa21a1bd73fdf04a0d4209d31"
] | [
"class/numpy_aps_class.py"
] | [
"import numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport networkx as nx\r\nfrom Bio.Seq import Seq\r\nfrom Bio import SeqIO\r\nimport csv\r\nimport re\r\n\r\n\r\ncount_matrix = np.array([[3, 3, 0], [0, 0, 1], [1, 1, 0], [0, 0, 1], [1, 0, 4], [1, 2, 0]])\r\n\r\ncount_matrix = np.where(count_matrix > 0, 1, 0)... | [
[
"matplotlib.pyplot.imshow",
"numpy.random.seed",
"numpy.random.choice",
"numpy.matmul",
"numpy.empty",
"matplotlib.pyplot.colorbar",
"numpy.loadtxt",
"numpy.append",
"numpy.array",
"numpy.where",
"numpy.sum",
"matplotlib.pyplot.show"
]
] |
nimrodkre/IML.HUJI | [
"4f794041dde142e820889dfe40dbb5509f417aad"
] | [
"exercises/adaboost_scenario.py"
] | [
"import numpy as np\nfrom typing import Tuple\nfrom IMLearn.metalearners.adaboost import AdaBoost\nfrom IMLearn.learners.classifiers import DecisionStump\nfrom utils import *\nimport plotly.graph_objects as go\nfrom plotly.subplots import make_subplots\n\n\ndef generate_data(n: int, noise_ratio: float) -> Tuple[np.... | [
[
"numpy.random.seed",
"numpy.ones",
"numpy.random.rand",
"numpy.array",
"numpy.sum"
]
] |
pequode/QR-Code-Signing-Cyber-Security-Final-Proj | [
"6224b6620542c87888acedebe27b05119e4d5348"
] | [
"website/readSurveyData.py"
] | [
"import json\nimport matplotlib.pyplot as plt\nimport numpy as np\n# this reads the output json from firebase.\n# this is a work around because firebase doesnt allow downloads of data without paid subscription\n#used if you need an absolute path \npath = \"./\"\nf = open(path+'website/resultServey.json', 'r')\ndata... | [
[
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.bar",
"matplotlib.pyplot.title"
]
] |
vipermu/taming-transformers | [
"d64977b4a0c3639798e997b2eaed057be0dee9e6"
] | [
"taming/models/vqgan.py"
] | [
"import torch\nimport torch.nn.functional as F\nimport pytorch_lightning as pl\n\nfrom forks.taming_transformers.main import instantiate_from_config\n\nfrom forks.taming_transformers.taming.modules.diffusionmodules.model import Encoder, Decoder\nfrom forks.taming_transformers.taming.modules.vqvae.quantize import Ve... | [
[
"torch.load",
"torch.randn",
"torch.nn.functional.conv2d",
"torch.nn.Conv2d",
"torch.no_grad",
"torch.nn.functional.one_hot",
"torch.argmax"
]
] |
anacalhau/query_by_humming | [
"b3ff5e5e4f79cd8349d57a0e916cff8e71eb99e9"
] | [
"tests/untitled0.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Nov 18 21:30:52 2020\n\n@author: Ana Calhau\n\"\"\"\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom IPython import get_ipython\nget_ipython().run_line_magic('matplotlib', 'qt')\n\nx =np.arange(0.5, 10, 0.001)\n\ny1=np.log(x)\ny2=5*np.sin(x)/x\n\nplt.plot... | [
[
"matplotlib.pyplot.legend",
"numpy.log",
"numpy.arange",
"numpy.sin",
"matplotlib.pyplot.plot"
]
] |
akaszynski/sunpy | [
"d300d5015b2b37f8c75bdaf05c6df7865760eadc"
] | [
"sunpy/image/tests/test_coalignment.py"
] | [
"import os\n\nimport numpy as np\nimport pytest\nfrom numpy.testing import assert_allclose, assert_array_almost_equal\nfrom scipy.ndimage import shift as sp_shift\n\nimport astropy.units as u\n\nimport sunpy.data.test\nfrom sunpy.image.coalignment import (\n _default_fmap_function,\n _lower_clip,\n _upper_... | [
[
"numpy.abs",
"numpy.isfinite",
"scipy.ndimage.shift",
"numpy.asarray",
"numpy.ones",
"numpy.all",
"numpy.max",
"numpy.float64",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.zeros",
"numpy.testing.assert_array_almost_equal"
]
] |
tugrabatin/Pandas | [
"d6330ae97aa9f1755cdcbcd7f8e33a7dc59118df"
] | [
"filter.py"
] | [
"# -*- coding: utf-8 -*-\r\n\r\nimport pandas as pd\r\n\r\nfilms = pd.read_csv(\"imdb_1000.csv\")\r\n\r\nprint(films)\r\nprint(films.columns)\r\nprint(films.head())\r\nprint(films.tail())\r\nprint(films['title'].head())\r\nprint(films.title.head())\r\nprint(films[['title','star_rating']].head())\r\nprint(films[:9][... | [
[
"pandas.read_csv"
]
] |
BrunoFant/mhcnuggets | [
"eb9e95c9f6ebd73719e43341199a54ca152f1e6f"
] | [
"mhcnuggets/src/calculate_mhc_relations.py"
] | [
"'''\nCalculate MHC relations for\ntransfer learning\n\nRohit Bhattacharya\nrohit.bhattachar@gmail.com\n'''\n\nfrom __future__ import print_function\nfrom mhcnuggets.src.dataset import Dataset\nimport numpy as np\nimport os\nfrom mhcnuggets.src.models import get_predictions\nimport mhcnuggets.src.models\nfrom sklea... | [
[
"sklearn.metrics.roc_auc_score",
"sklearn.metrics.precision_score",
"pandas.DataFrame",
"sklearn.metrics.f1_score",
"numpy.array"
]
] |
mahmoudyusof/pycaret | [
"4ec4ff5868a55282e0986690fc64bebf650b970f"
] | [
"pycaret/classification.py"
] | [
"# Module: Classification\n# Author: Moez Ali <moez.ali@queensu.ca>\n# License: MIT\n# Release: PyCaret 2.1x\n# Last modified : 07/08/2020\n\ndef setup(data, \n target, \n train_size = 0.7, \n sampling = True, \n sample_estimator = None,\n categorical_features = None,... | [
[
"sklearn.neural_network.MLPClassifier",
"sklearn.metrics.roc_auc_score",
"numpy.linspace",
"numpy.around",
"sklearn.metrics.matthews_corrcoef",
"pandas.DataFrame",
"numpy.round",
"sklearn.base.clone",
"sklearn.tree.DecisionTreeClassifier",
"matplotlib.pyplot.plot",
"num... |
flashlin/pycore | [
"6055821df05f0343fcf8d281fa610d9aea875936"
] | [
"ptf/data_utils.py"
] | [
"import tensorflow as tf\r\nimport numpy as np\r\n\r\n\r\ndef _bytes_feature(value):\r\n \"\"\"Returns a bytes_list from a string / byte.\"\"\"\r\n if isinstance(value, type(tf.constant(0))):\r\n # BytesList won't unpack a string from an EagerTensor.\r\n value = value.numpy()\r\n return tf.tr... | [
[
"tensorflow.constant",
"tensorflow.decode_raw",
"tensorflow.train.FloatList",
"tensorflow.train.BytesList",
"tensorflow.train.Int64List"
]
] |
b-rousse/HF_and_MP2 | [
"7b39c66a4290f9e7df7e0c226fa74c24a4816253"
] | [
"quentem_mechenex/hartree_fock.py"
] | [
"import numpy as np\nimport quentem_mechenex.fock_fast as fock_fast\n#from noble_gas_model import NobleGasModel\nclass HartreeFock:\n def __init__(self, NobleGasModel, atomic_coordinates, quick_fock = False):\n self.atomic_coordinates = atomic_coordinates\n #self.gas_model = NobleGasModel...\n ... | [
[
"numpy.dot",
"numpy.einsum",
"numpy.linalg.norm",
"numpy.size",
"numpy.linalg.eigh",
"numpy.exp",
"numpy.zeros"
]
] |
m-serra/action-inference-for-video-prediction-benchmarking | [
"4ff6b35de5abe7bdc431ccf3cb4b25a32562c950"
] | [
"video_prediction/savp/models/networks.py"
] | [
"import tensorflow as tf\nfrom tensorflow.python.util import nest\n\nfrom video_prediction.savp import ops\nfrom video_prediction.savp.ops import conv2d\nfrom video_prediction.savp.ops import dense\nfrom video_prediction.savp.ops import lrelu\nfrom video_prediction.savp.ops import pool2d\nfrom video_prediction.savp... | [
[
"tensorflow.reshape",
"tensorflow.squeeze",
"tensorflow.pad",
"tensorflow.variable_scope",
"tensorflow.python.util.nest.map_structure"
]
] |
Anonymous633671/STABILIZER | [
"5a1ab8099a2d75ace7e053afc78055f1f4d359c0",
"5a1ab8099a2d75ace7e053afc78055f1f4d359c0"
] | [
"Project_Health/src/predictor_advance.py",
"Project_Health/src/Find_bellwethers.py"
] | [
"from utils import *\nfrom sklearn.tree import DecisionTreeRegressor\nfrom optimizer import *\nfrom predictor_baseline import *\nimport pandas as pd\n\n\ndef DECART(dataset, metrics, month):\n\n dataset = normalize(dataset)\n\n for trainset, testset in df_split(dataset, month):\n train_input = trainset... | [
[
"pandas.concat",
"sklearn.tree.DecisionTreeRegressor"
],
[
"pandas.read_pickle",
"pandas.DataFrame",
"pandas.DataFrame.from_dict"
]
] |
errornonamer/maplestory_dpm_calc | [
"2e53b12fe6e7fed33efb660b85b902872ea8e088"
] | [
"statistics/graph_compare_line.py"
] | [
"import argparse\n\nimport pandas as pd\nfrom matplotlib import pyplot as plt\nfrom matplotlib import ticker\nimport seaborn as sns\n\nplt.style.use([\"bmh\"])\nsns.set_palette(sns.color_palette(\"Paired\", 6))\n\n\ndef get_args():\n parser = argparse.ArgumentParser(\"graph argument\")\n parser.add_argument(\... | [
[
"matplotlib.pyplot.legend",
"pandas.read_pickle",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.plot",
"matplotlib.ticker.FuncFormatter",
"matplotlib.pyplot.show",
"matplotlib.pyplot.style.use"
]
] |
aasensio/pyiacsun | [
"56bdaca98461be7b927f8d5fbbc9e64517c889fb"
] | [
"pyiacsun/tests/test_radtran.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport numpy.testing as npt\nimport pyiacsun\nimport time\nimport os\n\ndef test_voigt():\n\tvoigt = pyiacsun.radtran.voigt(1.0, 0.1)\n\tnpt.assert_equal(voigt, 0.37317014831126744)\n\ndef todo_milne():\n\tlambda0 = 6301.5080\n\tJUp = 2.0\n\tJLow = 2.0\n... | [
[
"numpy.testing.assert_equal",
"numpy.linspace",
"numpy.asarray",
"numpy.zeros",
"numpy.loadtxt"
]
] |
qorrect/auditorium | [
"9f9ad5d72d4f70761e91186a8a9226b7fd608764"
] | [
"auditorium/demo.py"
] | [
"# coding: utf8\n\n\"\"\"\nA simple demo script for `auditorium`.\n\"\"\"\n\nfrom auditorium import Show\n\nshow = Show(\"Auditorium Demo\", autoslide=10000)\napp = show.app\n\n\n@show.slide(autoslide=4000)\ndef intro(ctx):\n \"\"\"\n # Auditorium\n ## A Python-powered slideshow generator with steroids\n ... | [
[
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.xlim",
"numpy.random.RandomState",
"matplotlib.pyplot.scatter"
]
] |
AkshayJaitly/NLPDisasterResponsePipeline | [
"d0b85ce9289f538342fe86d3a8190e6c07caf6fb"
] | [
"models/train_classifier.py"
] | [
"import re\nimport sys\nimport pandas as pd\nimport numpy as np\nimport pickle\nimport nltk\n\nfrom sqlalchemy import create_engine\nfrom nltk.tokenize import word_tokenize\nfrom nltk.corpus import stopwords\nfrom nltk.stem.wordnet import WordNetLemmatizer\nnltk.download(['punkt', 'stopwords', 'wordnet', 'averaged_... | [
[
"sklearn.externals.joblib.dump",
"sklearn.model_selection.GridSearchCV",
"sklearn.ensemble.RandomForestClassifier",
"pandas.read_sql_table",
"sklearn.model_selection.train_test_split",
"sklearn.feature_extraction.text.CountVectorizer",
"sklearn.feature_extraction.text.TfidfTransformer"... |
alclol/modin | [
"91e89eafc71f6ef03eb44456d646a6c5971b1c4c"
] | [
"stress_tests/kaggle/kaggle8.py"
] | [
"import modin.pandas as pd\nfrom sklearn.ensemble import RandomForestRegressor\n\ntrain = pd.read_csv(\"train.csv\")\ntrain_y = train.SalePrice\npredictor_cols = [\"LotArea\", \"OverallQual\", \"YearBuilt\", \"TotRmsAbvGrd\"]\ntrain_X = train[predictor_cols]\nmy_model = RandomForestRegressor()\nmy_model.fit(train_X... | [
[
"sklearn.ensemble.RandomForestRegressor"
]
] |
javiermesonero/streamlit | [
"c35fb867ef40bcfbd77b833da02f49d3919e91b9"
] | [
"streamlit_app.py"
] | [
"import pandas as pd\r\nimport streamlit as st\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sns\r\nimport numpy as np\r\nfrom scipy.stats import iqr\r\n\r\n\r\n\r\n\r\n\r\n\r\ndef configuracion():\r\n st.set_page_config(\r\n page_title=\"VITA Data Analysis\",\r\n page_icon=\":pizza:\")\r\n\r\n... | [
[
"matplotlib.pyplot.legend",
"pandas.read_csv",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"scipy.stats.iqr",
"pandas.cut",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.figure"
]
] |
KarlaMendoza75/bert-sklearn | [
"bc6adea6cd9d5242dba340044136a9d8b8a70276"
] | [
"bert_sklearn/sklearn.py"
] | [
"\"\"\"sklearn interface to finetuning BERT.\n\nOverall flow:\n-------------\n\n # define model\n model = BertClassifier() # text/text pair classification\n model = BertRegressor() # text/text pair regression\n model = BertTokenClassifier() # token sequence classification\n\n # fit mode... | [
[
"torch.nn.functional.softmax",
"sklearn.utils.validation.check_is_fitted",
"torch.max",
"torch.load",
"numpy.unique",
"torch.sum",
"numpy.tile",
"pandas.DataFrame",
"numpy.max",
"torch.no_grad",
"sklearn.base.is_classifier",
"numpy.zeros_like",
"pandas.set_optio... |
w86763777/pytorch-simple-yolov3 | [
"fb08b7c83493bdad3c0d60f8446a2018827b53a1"
] | [
"yolov3/dataset.py"
] | [
"import os\n\nimport torch\nimport torch.nn.functional as F\nimport torch.distributed as dist\nfrom torch.utils.data import Dataset, Sampler\nfrom PIL import Image\n\n\nfrom .transforms import ToTensor\n\n\nclass DetectionDataset(Dataset):\n def __init__(self,\n coco,\n img_root,\... | [
[
"torch.Generator",
"torch.randint",
"torch.empty",
"torch.cat",
"torch.tensor",
"torch.repeat_interleave",
"torch.split",
"torch.stack",
"torch.distributed.get_rank",
"torch.distributed.get_world_size",
"torch.nn.functional.pad"
]
] |
bl4ck5un/proof-of-useful-work | [
"73aba24be375914f7cf2efef85d50aa15badc795"
] | [
"scripts/brokenCpuSimulation.py"
] | [
"import bisect\n\nimport numpy as np\nfrom scipy.stats import poisson\n\n\ndef rejectPolicy(n, rate_max, time, alpha):\n plambda = rate_max * time\n threshold = poisson.ppf(1-alpha, plambda)\n\n return n > threshold\n\n\ndef simulation(alpha, tmax, nround=5):\n fBest = 10 ** 9 # guess per sec.\n p =... | [
[
"numpy.linspace",
"numpy.random.exponential",
"scipy.stats.poisson.ppf",
"numpy.mean",
"numpy.savetxt",
"numpy.array"
]
] |
themaoci/Tarkov-Wireless-Exploit | [
"a75dae42fefe88e18a46da5d1777acb5eb6f1ff6"
] | [
"server/agent/agent_callbacks.py"
] | [
"import tensorflow as tf\nimport matplotlib\nmatplotlib.use('TkAgg')\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport os\nimport cv2\nimport scipy.misc\nfrom random import randint\ncwd = os.getcwd()\n\n\nclass Autoencoder_Callbacks(tf.keras.callbacks.Callback):\n\n def __init__(self, val_data):\n ... | [
[
"matplotlib.use"
]
] |
WadhwaniAI/covid-modelling | [
"db9f89bfbec392ad4de6b4583cfab7c3d823c1c9"
] | [
"data/dataloader/athena.py"
] | [
"from pyathena import connect\nimport copy\nimport pandas as pd\nimport numpy as np\nfrom pyathena.pandas_cursor import PandasCursor\n\nfrom data.dataloader.base import BaseLoader\n\n\nclass AthenaLoader(BaseLoader):\n \"\"\"Dataloader that gets casecount data from the AWS Athena DB\n\n We use AWS Athena DB t... | [
[
"pandas.to_datetime",
"numpy.where",
"numpy.logical_and",
"pandas.Timedelta"
]
] |
alai-arpas/pydsstools | [
"1de47f6822e6b57528757920009591e21ecf5ba2"
] | [
"pydsstools/heclib/utils.py"
] | [
"import logging\nimport numpy as np\nimport numpy.ma as ma\nimport math\nfrom .._lib import BoundingBox\nfrom ..core import (HecTime, DssStatusException, GranularityException,ArgumentException,DssLastError,setMessageLevel,squeeze_file) \nfrom ..core import (GRID_TYPE, GRID_DATA_TYPE, GRID_COMPRESSION_METHODS,gridIn... | [
[
"numpy.isnan",
"numpy.linspace"
]
] |
tailofcat/SOGNN | [
"73ef1ea7696a48dae7d245ff5e23632fda98f314"
] | [
"Net.py"
] | [
"\"\"\"\n\n\"\"\"\n\nimport math\nimport torch \nimport torch.nn.functional as F\nfrom torch_geometric.data import DataLoader\nfrom torch_geometric.nn import GCNConv, ChebConv, SAGEConv, GraphConv, DenseSAGEConv, dense_diff_pool, DenseGCNConv\nfrom torch_geometric.nn import TopKPooling, SAGPooling, EdgePooling\nfro... | [
[
"torch.softmax",
"torch.nn.Dropout",
"torch.nn.functional.softmax",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.Linear",
"torch.nn.MaxPool2d",
"torch.device"
]
] |
anggelomos/Whatsapp-Wordcloud-Generator | [
"5c481c0f111a4f761f9cca73c28f0174405fcc8c"
] | [
"whatsapp_wordcloud.py"
] | [
"#!/usr/bin/env python3\n\nimport subprocess\n\n# Install automatically external modules in case it isn't possible print an error message\ntry:\n import wordcloud\n from PIL import Image\n from matplotlib import pyplot as plt\n import matplotlib.patches as mpatches\n import numpy as np\n from bs4 ... | [
[
"matplotlib.pyplot.legend",
"matplotlib.patches.Patch",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
nikola3794/edge-evaluation-PASCAL-MT-tmp | [
"d3bc7164608a20eb6351c1d41219213927ae6239"
] | [
"Multi-Task-Learning-PyTorch-master/main.py"
] | [
"#\n# Authors: Simon Vandenhende\n# Licensed under the CC BY-NC 4.0 license (https://creativecommons.org/licenses/by-nc/4.0/)\n\nimport argparse\nimport cv2\nimport os\nimport numpy as np\nimport sys\nimport torch\n\nfrom utils.config import create_config\nfrom utils.common_config import get_train_dataset, get_tran... | [
[
"torch.nn.DataParallel",
"torch.load"
]
] |
jb1361/memelon | [
"98c42f63bbf6447110eb1d6a73da53e5c318ab69"
] | [
"doge-training/doge-classification-trainer.py"
] | [
"from imageai.Classification.Custom import ClassificationModelTrainer\nimport tensorflow as tf\nimport os\n# This will disable the gpu\n# os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"-1\"\nprint(\"Num GPUs Available: \", len(tf.config.experimental.list_physical_devices('GPU')))\nmodel_trainer = ClassificationModelTrain... | [
[
"tensorflow.config.experimental.list_physical_devices"
]
] |
skailasa/numba | [
"38ab89dd369a14b8826d3fa30d080aa083aed00b",
"38ab89dd369a14b8826d3fa30d080aa083aed00b"
] | [
"numba/core/utils.py",
"numba/tests/test_target_extension.py"
] | [
"import atexit\nimport builtins\nimport functools\nimport inspect\nimport os\nimport operator\nimport timeit\nimport math\nimport sys\nimport traceback\nimport weakref\nimport warnings\nimport threading\nimport contextlib\n\nfrom types import ModuleType\nfrom importlib import import_module\nfrom collections.abc imp... | [
[
"numpy.array",
"numpy.min"
],
[
"numpy.cos",
"numpy.empty",
"numpy.sin"
]
] |
paztronomer/structure_timedomain | [
"6548bd2a9402cf07dd211417cba42945e858cb24"
] | [
"getSectionMask_ccdx.py"
] | [
"''' Code to get basic statistics for a section of a list of exposures \n'''\n\nimport os\nimport sys\nimport uuid\nimport time\nimport numpy as np\nimport pandas as pd\nimport fitsio\nimport pickle\nimport logging\nimport argparse\ntry:\n import partial\nexcept:\n pass\nimport multiprocessing as mp\n\n# Setu... | [
[
"numpy.unique",
"numpy.save",
"numpy.genfromtxt",
"numpy.copy",
"numpy.where"
]
] |
hfhfn/db_recommend | [
"3a9f03157bb81e295f8cff30fbc7ad2a8cfdf963"
] | [
"online_recommend/test/test2.py"
] | [
"# from movie_recall.cal_similar import load_movie_vector, similar_model_path\n# from movie_recall.word2vec import channel_id, channel\n# from utils import channelInfo\nfrom utils.spark_app import MovieDataApp\nfrom utils.save_tohive import RetToHive\n\n\nspark = MovieDataApp().spark\n# tmp = add_topic_field()\nimp... | [
[
"numpy.log"
]
] |
NagisaZj/maesn_baseline | [
"bfcc761dacbc602390d063d8b4770d10655ec7ff"
] | [
"sandbox/rocky/tf/samplers/vectorized_sampler.py"
] | [
"import pickle\n\nimport tensorflow as tf\nfrom rllab.sampler.base import BaseSampler\nfrom sandbox.rocky.tf.envs.parallel_vec_env_executor import ParallelVecEnvExecutor\nfrom sandbox.rocky.tf.envs.vec_env_executor import VecEnvExecutor\nfrom rllab.misc import tensor_utils\nimport numpy as np\nfrom rllab.sampler.st... | [
[
"numpy.asarray",
"numpy.random.normal"
]
] |
davidripsen/dtu_mlops | [
"e63b6e05ac9d87feb063de5ed46908a8921d26bb"
] | [
"example_mlops_/src/tests/test_model.py"
] | [
"#test_model\nimport torch\nfrom src.models.model import MyAwesomeModel\nfrom src.data.make_dataset import CorruptMnist\n\ndevice = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n\nmodel = MyAwesomeModel()\nmodel.load_state_dict(torch.load('./models/trained_model.pt'))\nmodel = model.to(device)\n\nprint(model)... | [
[
"torch.utils.data.DataLoader",
"torch.cuda.is_available",
"torch.load"
]
] |
lucasiqueira86/Data-Science---Python | [
"572f044629ab91be20b485cdc6e0002dc11224df"
] | [
"CODE/Depressed.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[60]:\n\n\nimport pandas as pd\nimport numpy as np\nimport plotly.express as px\nimport seaborn as sb\n\ndepressed = pd.read_csv(r'C:/Users/Master/Desktop/Jupyter/depressed.csv')\n\n#depressed: [ Zero: No depressed] or [One: depressed] \n#married zero : No married or ... | [
[
"pandas.read_csv",
"numpy.unique"
]
] |
ngmaclaren/interruption-networks | [
"553fc68deba9025480c1b87848834017ea3950c6"
] | [
"tst-iss-rate-fig.py"
] | [
"import numpy as np\nimport pandas as pd\nimport networkx as nx\nimport matplotlib.pyplot as plt\nimport matplotlib.colors as Color\nimport InterruptionAnalysis as ia\n\ndata = pd.read_csv('./data/timeseries.csv', index_col = 0)\nnumericcols = ['begin', 'end', 'dur', 'lat']\ndata[numericcols] /= 1000 # cannot be do... | [
[
"pandas.concat",
"pandas.read_csv",
"matplotlib.colors.to_rgba",
"matplotlib.pyplot.subplots",
"pandas.DataFrame",
"pandas.unique"
]
] |
Rahul-Dwivedi-07/Autonomous-Vehicle-self-Driving-Car-Complete | [
"5c62f4a4c0bdddbb6b0a6f058e86f3547b2f3d7b",
"5c62f4a4c0bdddbb6b0a6f058e86f3547b2f3d7b"
] | [
"lanes_basic_understanding.py",
"lanes_coordinates_print.py"
] | [
"import cv2\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\ndef canny(image):\r\n gray = cv2.cvtColor(image,cv2.COLOR_RGB2GRAY)\r\n blur = cv2.GaussianBlur(gray,(5,5),0)\r\n #canny = cv2.Canny(blur,low_threshold,high_threshold)\r\n canny = cv2.Canny(blur,50,150)\r\n return canny\r\n\r... | [
[
"numpy.copy",
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show"
],
[
"numpy.polyfit",
"numpy.copy",
"numpy.zeros_like",
"numpy.average",
"numpy.array"
]
] |
sksmslhy/InstanceShadowDetection | [
"1bcf911ba5dfdefbd22397409cd56e169040abe5",
"1bcf911ba5dfdefbd22397409cd56e169040abe5"
] | [
"PythonAPI/setup.py",
"detectron2/modeling/meta_arch/LISA_meta_arch.py"
] | [
"from setuptools import setup, Extension\nimport numpy as np\n\n# To compile and install locally run \"python setup.py build_ext --inplace\"\n# To install library to Python site-packages run \"python setup.py build_ext install\"\n\next_modules = [\n Extension(\n 'pysobatools._mask',\n sources=['./c... | [
[
"numpy.get_include"
],
[
"torch.device"
]
] |
kuku929/ga-learner-dsmpu-repo | [
"ae7e9a34faf46a01895f2800c241d569c2d72815"
] | [
"Superhero_Statistics/code.py"
] | [
"# --------------\n#Header files\r\nimport pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\n\r\n\r\n#Reading of the file\r\ndata=pd.read_csv(path)\r\ndata['Gender'].replace({\r\n '-':'Agender'\r\n}, inplace=True)\r\ndata.Gender.unique()\r\n\r\ndata['Gender'].value_counts().plot(kind='bar'... | [
[
"pandas.read_csv",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
cloudwiser/tensorflow | [
"f4085f237563b75a2c358aba8507ba8c167d8bd8",
"f4085f237563b75a2c358aba8507ba8c167d8bd8"
] | [
"tensorflow/python/eager/function.py",
"tensorflow/lite/micro/examples/object_detection/models/research/slim/datasets/build_visualwakewords_data.py"
] | [
"# Copyright 2017 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.framework.c_api_util.ScopedTFFunction",
"tensorflow.python.eager.tape.record_operation",
"tensorflow.python.framework.tensor_shape.TensorShape",
"tensorflow.python.util.tf_inspect.ismethod",
"tensorflow.python.pywrap_tfe.TFE_Py_EncodeArg",
"tensorflow.python.framework.co... |
flatberg/scanpy-scripts | [
"e956b6ab060d4ebc06b7654cde36c5dbd868519c"
] | [
"scanpy_scripts/scanpy_run_pca.py"
] | [
"#!/usr/bin/env python3\n\nimport logging\nimport matplotlib\nmatplotlib.use('Agg')\nimport numpy as np\nimport scanpy.api as sc\n\nfrom scanpy_scripts.wrapper_utils import (\n ScanpyArgParser,\n read_input_object, write_output_object, save_output_plot,\n)\n\n\ndef main(argv=None):\n argparser = ScanpyArgP... | [
[
"numpy.savetxt",
"matplotlib.use",
"numpy.sqrt"
]
] |
AhmetHamzaEmra/Something | [
"3b061ad01501c3eff2bafada64b2c20bf7ed7b37"
] | [
"something/data.py"
] | [
"\"\"\"\nWe'll feed inputs into our network in batches.\nSo here are some tools for iterating over data in batches.\n\"\"\"\nimport numpy as np\nfrom typing import Iterator, NamedTuple\nfrom something.tensor import Tensor\n\n\nBatch = NamedTuple(\"Batch\", [(\"inputs\", Tensor), (\"targets\", Tensor)])\n\nclass Dat... | [
[
"numpy.random.shuffle"
]
] |
pyj2001/Sudoku-Solver | [
"0119ee05133fd11449ea73ec2af7867cbd4cfe56"
] | [
"Opencv-solver/Sudoku_reader.py"
] | [
"# Create by Packetsss\n# Personal use is allowed\n# Commercial use is prohibited\n\nimport cv2\nimport pytesseract\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom Sudoku_extractor import Extract\n\nimg = Extract().extract_sudoku(\"src/board.jpg\")\nimg = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\ncv2.imshow(... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.show"
]
] |
imhritik/Facial-Recognition | [
"2e0bc81d802d93af9dba7fd0d387ea3932825724"
] | [
"trainer.py"
] | [
"import pandas as pd \r\nimport pickle \r\nfrom sklearn.linear_model import LogisticRegression\r\nclass Trainer:\r\n def __init__(self):\r\n pass\r\n def Dataset(self):\r\n self.dataset = pd.read_csv(r'dataset.csv')\r\n print(self.dataset.head())\r\n def trainModel(self):\r\n se... | [
[
"pandas.read_csv",
"sklearn.linear_model.LogisticRegression"
]
] |
c-boe/Reinforcement-learning | [
"a8cfcf3ff022a31e6f21fe3497c5557443778258"
] | [
"13 Policy Gradient Methods/Short Corridor/main.py"
] | [
"\"\"\"\nSolve short corridor with switched actions (Example 13.1) of Sutton and Barto's\n\"Reinforcement learning\" with REINFORCE with baseline\n\"\"\"\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom shortcorridor import ShortCorridor\nfrom shortcorridor import FeatureVectors... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"numpy.zeros",
"matplotlib.pyplot.ylabel"
]
] |
varder/finplot | [
"d8287e05b4b603b089f1399fc42fa984e22a442f"
] | [
"finplot/__init__.py"
] | [
"# -*- coding: utf-8 -*-\n'''\nFinancial data plotter with better defaults, api, behavior and performance than\nmpl_finance and plotly.\n\nLines up your time-series with a shared X-axis; ideal for volume, RSI, etc.\n\nZoom does something similar to what you'd normally expect for financial data,\nwhere the Y-axis is... | [
[
"numpy.nanmax",
"pandas.merge",
"pandas.to_datetime",
"pandas.Series",
"numpy.nanmin",
"numpy.nan_to_num",
"pandas.DataFrame",
"numpy.nansum",
"numpy.diff",
"pandas.cut",
"pandas.set_option",
"pandas.concat",
"numpy.isnan",
"numpy.log10",
"numpy.errstate... |
ChopinSharp/info-ground | [
"12fba3c478b806f2fe068faac81237fd0f458b80"
] | [
"exp/ground/models/object_encoder.py"
] | [
"import copy\nimport torch\nimport torch.nn as nn\n\nfrom context_layer.transformer import ContextLayerConstants, ContextLayer\nimport utils.io as io\nfrom .info_nce_loss import InfoNCE\n\n\nclass ObjectEncoderConstants(io.JsonSerializableClass):\n def __init__(self):\n super().__init__()\n self.ob... | [
[
"torch.nn.Linear",
"torch.nn.ReLU",
"torch.nn.BatchNorm1d",
"torch.Tensor"
]
] |
eduardomgutierrez/RIAF_radproc | [
"0e4166f04cce27fed2cbd2c7078023c10e0e8d12"
] | [
"src/adaf/python_scripts/plotNeutronInjAGN.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib\n\nfrom matplotlib import rc # TO MANAGE MATPLOTLIB PARAMETERS\"\nrc('font',family='serif')\nrc('text',usetex = True)\n\nfrom matplotlib import cm\nfrom matplotlib.colors import ListedColormap, LinearSegmentedColormap\nviridis = cm.get_c... | [
[
"numpy.power",
"numpy.arange",
"matplotlib.pyplot.subplots",
"matplotlib.rc",
"numpy.log10",
"matplotlib.cm.get_cmap",
"numpy.zeros",
"numpy.loadtxt"
]
] |
petroniocandido/RNA | [
"bdb727cc47baf0d8e04bce5af7e16ea3c07a6a3f"
] | [
"FuncoesAtivacao.py"
] | [
"import numpy as np\n\ndef identidade(x, derivada = False):\n if not derivada:\n return x\n else:\n return 1\n\ndef degrau(x, derivada = False):\n if not derivada:\n return np.where(x > 0, 1, 0)\n else:\n return np.where(x > 0, 1, 0)\n\ndef sigmoide(x, derivada = False):\n if not derivada:\n ret... | [
[
"numpy.maximum",
"numpy.exp",
"numpy.where"
]
] |
mocquin/physipy | [
"a44805dbf4e68544c987e07564dd4a8d50be8b4c",
"a44805dbf4e68544c987e07564dd4a8d50be8b4c"
] | [
"physipy/random.py",
"physipy/quantity/dimension.py"
] | [
"\"\"\"Wrapper of numpy.random distributions\n\nNumpy's random functions cannot be wrapped by array_function/ufunc interface,\nso if we want them to be unit-aware, we have to make our own version.\n\n - https://github.com/numpy/numpy/issues/19382\n\"\"\"\n\nimport numpy as np\nfrom physipy import quantify, Quantity... | [
[
"numpy.random.poisson",
"numpy.random.normal"
],
[
"numpy.isscalar"
]
] |
j0ma/lmm | [
"600a9971d81c1d7eef941ba8dcf30aeac6404c70"
] | [
"build/lib/onmt/ModelConstructor.py"
] | [
"\"\"\"\nThis file is for models creation, which consults options\nand creates each encoder and decoder accordingly.\n\"\"\"\nimport torch\nimport torch.nn as nn\n\nimport onmt\nimport onmt.io\nimport onmt.Models\nimport onmt.modules\nfrom onmt.Models import NMTModel, NMTSourceTrigramModel, NMTTargetCharModel, Char... | [
[
"torch.nn.LogSoftmax",
"torch.load"
]
] |
mixmasteru/CarND-Advanced-Lane-Lines | [
"a111371611fb81cb93a43019613d8cb6eae3d09d"
] | [
"src/advlane/filter.py"
] | [
"import cv2\nimport numpy as np\n\n\nclass Filter:\n\n def __init__(self):\n # Threshold x gradient\n self.grad_thresh_min = 20\n self.grad_thresh_max = 100\n # Threshold color channel\n self.s_thresh_min = 170\n self.s_thresh_max = 255\n # Kernel size\n se... | [
[
"numpy.max",
"numpy.array",
"numpy.absolute",
"numpy.zeros_like"
]
] |
guysoft/WaveCatchers | [
"491a4f94af9987dbda46d09bd863fe03bd1033f1"
] | [
"src/svc/train_svc.py"
] | [
"#!/usr/bin/env python\n# Based on https://www.kaggle.com/alphasis/xgboost-with-context-label-data-acc-99-637\n# Make sure you have dataset/dataset1 and dataset/dataset2 in the right place in the folder above where this file is\n\nfrom __future__ import print_function\nimport sys\nimport numpy as np\nimport os\nimp... | [
[
"numpy.convolve",
"numpy.abs",
"numpy.reshape",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.classification_report",
"numpy.concatenate",
"sklearn.svm.LinearSVC",
"numpy.angle",
"numpy.repeat",
"numpy.zeros"
]
] |
MiguelPax/MUStARD | [
"76e8892470c67c4986260d4a919b932c91826e1a"
] | [
"wandb/run-20210517_115941-1rnyl4zl/files/code/train.py"
] | [
"import argparse\nimport json\nimport os\nimport re\n# import sys\n# from scipy.sparse.construct import random\n# import IPython\n# import ipdb\nimport numpy as np\nfrom sklearn import svm\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.metrics... | [
[
"torch.nn.CrossEntropyLoss",
"sklearn.naive_bayes.GaussianNB",
"sklearn.linear_model.LogisticRegression",
"sklearn.ensemble.RandomForestClassifier",
"numpy.unique",
"sklearn.preprocessing.FunctionTransformer",
"sklearn.metrics.confusion_matrix",
"torch.from_numpy",
"numpy.conca... |
theNewFlesh/aspect-js | [
"ddd71674f07165ad15ca6b77655dcd7d0ffd4280"
] | [
"python/component_parser.py"
] | [
"import os\nimport re\nfrom random import randint\nfrom itertools import takewhile\nfrom collections import defaultdict\nimport pandas as pd\nfrom pandas import DataFrame\nfrom pyparsing import Group, Or, Regex, delimitedList, Optional, Suppress, ZeroOrMore\n# -------------------------------------------------------... | [
[
"pandas.isnull",
"pandas.merge",
"pandas.DataFrame"
]
] |
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