repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
XiaoZheng-YY/EEG-DL | [
"cafe35070b811045018d009aedf0ae164c52054b"
] | [
"Models/Network/BiRNN_with_Attention.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n# Import useful packages\nimport tensorflow as tf\n\n\ndef attention(inputs, attention_size, time_major=False, return_alphas=False):\n \"\"\"\n\n Attention mechanism layer which reduces RNN/Bi-RNN outputs with Attention vector.\n The idea was proposed in t... | [
[
"tensorflow.matmul",
"tensorflow.nn.softmax",
"tensorflow.layers.batch_normalization",
"tensorflow.concat",
"tensorflow.contrib.rnn.DropoutWrapper",
"tensorflow.reshape",
"tensorflow.expand_dims",
"tensorflow.contrib.rnn.BasicRNNCell",
"tensorflow.random_normal",
"tensorflo... |
HarrieO/RankingComplexLayouts | [
"53e8fdca3b2d4efffc2506423997e257f01ba094"
] | [
"mdprank/main.py"
] | [
"import os, sys\nsys.path.insert(1, os.path.join(sys.path[0], '..'))\nimport argparse\nimport letorinput as letorin\nimport losses\nimport models\nimport numpy as np\nimport rewards\nimport tensorflow as tf\nimport gru.gru as gru\nimport mdprank as mdprank\n\nfrom tensorflow.contrib.training import wait_for_new_che... | [
[
"tensorflow.clip_by_value",
"tensorflow.summary.FileWriter",
"tensorflow.local_variables_initializer",
"tensorflow.Variable",
"tensorflow.reduce_mean",
"tensorflow.train.latest_checkpoint",
"tensorflow.train.start_queue_runners",
"tensorflow.train.Coordinator",
"tensorflow.glob... |
jiangwenj02/MLC | [
"3cecdc669a9027f230d29e1565d16bab958809a2"
] | [
"CIFAR/data_helper_cifar.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.backends.cudnn as cudnn\nimport torch.nn.functional as F\nimport torchvision.datasets as dset\nimport torchvision.transforms as transforms\nimport numpy as np\nfrom PIL import Image\nfrom utils import DataIterator\n\ndef prepare_data(gold_fraction, corruption_prob,... | [
[
"torch.utils.data.DataLoader"
]
] |
themilkyreygalaxy/astr-119-session_4 | [
"0933cfd60149b748a66797732c4476d4ee5dac42"
] | [
"demo_numpy.py"
] | [
"import numpy as np\n\nx = 1.0\t\t\t#define a float\ny = 2.0\t\t\t#define another float\n\n#trigonometry\nprint(np.sin(x))\t\t#sin(x)\nprint(np.cos(x))\t\t#cos(x)\nprint(np.tan(x))\t\t#tan(x)\nprint(np.arcsin(x))\t\t#arcsin(x)\nprint(np.arccos(x))\t\t#arccos(x)\nprint(np.arctan(x))\t\t#arctan(x)\nprint(np.arctan2(x... | [
[
"numpy.arctanh",
"numpy.cosh",
"numpy.arctan",
"numpy.arcsin",
"numpy.arccosh",
"numpy.arccos",
"numpy.cos",
"numpy.sin",
"numpy.tan",
"numpy.arctan2",
"numpy.rad2deg",
"numpy.sinh",
"numpy.tanh",
"numpy.arcsinh"
]
] |
mihailupu/classifier | [
"8f3e9017d4650c2927beebd6855426d00532cf8a"
] | [
"eval.py"
] | [
"#! /usr/bin/env python\n\nimport tensorflow as tf\nimport numpy as np\nimport os\nimport data_helpers\nfrom tensorflow.contrib import learn\nimport csv\n\n# Parameters\n# ==================================================\n\n# Data Parameters\ntf.flags.DEFINE_string(\"positive_data_file\", \"/home/mlupu/wipoAbstra... | [
[
"tensorflow.flags.DEFINE_boolean",
"tensorflow.Graph",
"tensorflow.train.latest_checkpoint",
"tensorflow.flags.DEFINE_string",
"tensorflow.ConfigProto",
"numpy.concatenate",
"numpy.max",
"tensorflow.Session",
"numpy.array",
"tensorflow.contrib.learn.preprocessing.Vocabulary... |
pawel-ta/ranmath | [
"f52a15b10bdb5830a50c43da11fed5f182026587"
] | [
"Ranmath/MatrixGenerators/MultivariateGaussianGenerator.py"
] | [
"\nfrom .AbstractGenerator import AbstractGenerator\nimport numpy as np\nimport scipy.linalg as la\n\n\nclass MultivariateGaussianGenerator(AbstractGenerator):\n\n def __init__(self, C: np.ndarray, A: np.ndarray, number_of_iterations):\n super().__init__()\n self.__number_of_iterations = number_of_... | [
[
"scipy.linalg.sqrtm",
"numpy.random.normal",
"numpy.array"
]
] |
paxtonfitzpatrick/timecorr | [
"fd6b797304c1c002a31f99f858cb7e51ed4a5de3"
] | [
"timecorr/timecorr.py"
] | [
"# coding: utf-8\n\nimport numpy as np\nfrom .helpers import isfc, gaussian_weights, format_data, null_combine, reduce, smooth\n\ndef timecorr(data, weights_function=gaussian_weights,\n weights_params=None, include_timepoints='all', exclude_timepoints=None,\n combine=null_combine, cfun=isfc,... | [
[
"numpy.abs",
"numpy.eye",
"numpy.round",
"numpy.triu",
"numpy.tril"
]
] |
forgi86/RNN-adaptation | [
"d32e8185c6a746060dd726a0f5080231e0c9439b"
] | [
"examples/WH/01_WH2009_train.py"
] | [
"import os\nimport torch\nimport pandas as pd\nimport numpy as np\nfrom models import WHNet3\nimport matplotlib.pyplot as plt\nimport time\nimport torchid.metrics\n\n\n# In[Main]\nif __name__ == '__main__':\n\n # In[Set seed for reproducibility]\n np.random.seed(0)\n torch.manual_seed(0)\n\n # In[Settin... | [
[
"matplotlib.pyplot.legend",
"torch.mean",
"numpy.random.seed",
"torch.sqrt",
"torch.manual_seed",
"numpy.arange",
"torch.tensor",
"matplotlib.pyplot.plot",
"torch.no_grad",
"matplotlib.pyplot.grid",
"numpy.array",
"matplotlib.pyplot.figure"
]
] |
Peltarion/scaling_fl | [
"011f845a6472e9a3df338351b8970b0fc70cf242"
] | [
"scripts/spooky_author/split_data.py"
] | [
"import argparse\n\nimport pandas\nfrom sklearn.model_selection import train_test_split\n\n\ndef main():\n parser = argparse.ArgumentParser(\n description='Split the spooky author dataset into two files, train and test.')\n parser.add_argument(\n '--full-path', type=str, help='Path of full datas... | [
[
"pandas.read_csv",
"sklearn.model_selection.train_test_split"
]
] |
msobrevillac/Multilingual-RDF-Verbalizer | [
"ba396693f65eaf74d1f60eb9aed3e78ab9593b22"
] | [
"hierarchical-decoding/utils/loss_new.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\ndef linear_combination(x, y, epsilon): \n return epsilon*x + (1-epsilon)*y\n\ndef reduce_loss(loss, reduction='mean'):\n return loss.mean() if reduction=='mean' else loss.sum() if reduction=='sum' else loss\n\n# Implementation found at \... | [
[
"torch.nn.functional.nll_loss"
]
] |
pps-lab/fl-analysis | [
"798fc0292d0611ec8900ebdb090b9e282d0df457"
] | [
"src/subspace/keras_ext/rproj_layers.py"
] | [
"# Copyright (c) 2018 Uber Technologies, Inc.\n# \n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"), to deal\n# in the Software without restriction, including without limitation the rights\n# to use, copy, modify... | [
[
"tensorflow.keras.backend.floatx",
"tensorflow.keras.constraints.serialize",
"tensorflow.keras.regularizers.serialize",
"tensorflow.keras.backend.moving_average_update",
"tensorflow.keras.backend.batch_normalization",
"tensorflow.python.keras.utils.conv_utils.conv_output_length",
"tens... |
esztermarton/tf-quant-finance | [
"18afe2e56e657b4eaca72bd67ee1428891ebea46"
] | [
"tf_quant_finance/black_scholes/__init__.py"
] | [
"# Lint as: python3\n# Copyright 2019 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# https://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by appli... | [
[
"tensorflow.python.util.all_util.remove_undocumented"
]
] |
psli01/DISTRE | [
"ba5115c1c2bea96ecccd91be781a6fcdaa3df6fb"
] | [
"experiments/utils/pr_curve_and_predictions.py"
] | [
"from typing import Optional\n\nimport sys\nsys.path.append('./')\n\nimport logging\nimport json\nimport pickle\nimport pathlib\nimport random\nfrom os.path import join\nfrom itertools import groupby\nfrom collections import namedtuple\nfrom operator import attrgetter\n\nimport fire\nimport numpy as np\nimport tre\... | [
[
"sklearn.metrics.auc"
]
] |
team1236/Tensorflow-2.0-Computer-Vision-Cookbook | [
"92ea6713f664cff9eccaaccea8ac756f808e2066"
] | [
"ch2/recipe7/data_aug_keras.py"
] | [
"import os\nimport pathlib\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport tensorflow_docs as tfdocs\nimport tensorflow_docs.plots\nfrom glob import glob\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import LabelBinarizer\nfrom tensorflow.keras.layers import *\nfro... | [
[
"numpy.random.seed",
"tensorflow.keras.models.Model",
"matplotlib.pyplot.ylim",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"sklearn.preprocessing.LabelBinarizer",
"numpy.array",
"matplotlib.pyplot.style.use"
]
] |
akssri/rlax | [
"dce52b43c57be7b56d7632b39c0446164526a668"
] | [
"rlax/_src/distributions_test.py"
] | [
"# Copyright 2019 DeepMind Technologies Limited. 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# Unle... | [
[
"numpy.log",
"numpy.asarray",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.sum"
]
] |
ptelang/opencv_contrib | [
"dd68e396c76f1db4d82e5aa7a6545580939f9b9d"
] | [
"modules/rgbd/misc/python/test/test_rgbd.py"
] | [
"#!/usr/bin/env python\n\n# Python 2/3 compatibility\nfrom __future__ import print_function\n\nimport os, numpy\n\nimport cv2 as cv\n\nfrom tests_common import NewOpenCVTests\n\nclass rgbd_test(NewOpenCVTests):\n\n def test_computeRgbdPlane(self):\n\n depth_image = self.get_sample('/cv/rgbd/depth.png', cv... | [
[
"numpy.asarray",
"numpy.array"
]
] |
bagustris/ravdess_song_speech | [
"05cf32d2530bc26f309c2e068817afcb6847edfc"
] | [
"code/song_gemaps_hsf_cv.py"
] | [
"#!/usr/bin/env python3 \n\n# load needed modules\nimport numpy as np\nimport pandas as pd \nimport matplotlib.pyplot as plt\n\nfrom keras.models import Sequential \nfrom keras.layers import Dense, Activation, Flatten, CuDNNLSTM, Flatten \nfrom keras.layers import Dropout, BatchNormalization, Bidirectional\nfrom ... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.model_selection.train_test_split",
"numpy.argmax",
"numpy.load",
"sklearn.preprocessing.LabelEncoder"
]
] |
vikramborana/face_recognition | [
"6afb54ca3fcea2e37dcebcb627d116c271ff21d4"
] | [
"Hritik/labelface.py"
] | [
"import face_recognition\nfrom PIL import Image, ImageDraw\nimport numpy as np\n\n# This is an example of running face recognition on a single image\n# and drawing a box around each person that was identified.\n\n# Load a sample picture and learn how to recognize it.\nhritik_image = face_recognition.load_image_file... | [
[
"numpy.argmin"
]
] |
pints-team/performance-testing | [
"30ee6e5ab7eff48e47bea505e52e20a9d3c537f7"
] | [
"pmatrix/_tasks.py"
] | [
"import numpy as np\nimport multiprocessing\nfrom itertools import repeat\nfrom GPyOpt.methods import BayesianOptimization\nimport pickle\nimport numpy as np\nimport matplotlib as mpl\nmpl.use('Agg')\nimport matplotlib.pyplot as plt\nimport os\n\nimport pmatrix\nimport pints\n\n\ndef to_filename(noise_level, model,... | [
[
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.tight_layout",
"numpy.min",
"numpy.asarray",
"matplotlib.use",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.colorbar",
"numpy.max",
"matplotlib.pyplot.clf",
"numpy.mean",
"matplotlib.pyplot.xticks",
"numpy.array",
... |
Bertinus/IRM-games | [
"e8a94e9647d1ea7211236bbd3f4ed16b1e8207b6"
] | [
"IRM_methods.py"
] | [
"import tensorflow as tf\nimport torch\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom sklearn.utils import shuffle\nfrom tqdm import tqdm_notebook as tqdm\n\ntf.compat.v1.enable_eager_execution()\n\n\nclass AbstractIrmGame:\n \"\"\" Abstract class for IRM games. \"\"\"\n\n def __init__(self, model... | [
[
"matplotlib.pyplot.legend",
"tensorflow.zeros",
"torch.zeros",
"tensorflow.reduce_sum",
"tensorflow.compat.v1.enable_eager_execution",
"matplotlib.pyplot.plot",
"numpy.concatenate",
"numpy.mean",
"torch.no_grad",
"tensorflow.where",
"numpy.where",
"torch.nn.CrossEnt... |
gilangsamudra/Data_Mining_HousePrices | [
"41355631db1ce680e3cc7f85cbe888cca915c5ab"
] | [
"houseprice-regresion.py"
] | [
"# Bismillah\n# Import all necessary libraries\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom statsmodels.formula.api import ols\n\n# Load dataset\ndf = pd.read_csv('D:/Phyton Code/Data_Mining_HousePrices/kc_house_data.csv')\n\n# # Check data quality\n# df.info()\n# df.head()\n# ... | [
[
"pandas.read_csv",
"matplotlib.pyplot.figure"
]
] |
aliddell/spiketag | [
"f5600126c2c6c9be319e8b808d51ea33be843909"
] | [
"spiketag/view/raster_view.py"
] | [
"import numpy as np\r\nfrom ..base.CLU import CLU\r\nfrom .color_scheme import palette\r\nfrom .scatter_2d_view import scatter_2d_view\r\nfrom vispy import scene, app, visuals\r\nfrom numba import njit, prange\r\n\r\n\r\n@njit(cache=True, parallel=True, fastmath=True)\r\ndef get_population_firing_count(spike_times,... | [
[
"numpy.hstack",
"numpy.logical_and",
"numpy.unique",
"numpy.arange",
"numpy.memmap",
"numpy.full",
"numpy.concatenate",
"numpy.zeros_like",
"numpy.column_stack",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] |
dburkhardt/neurips2021_multimodal_viash | [
"e3449af07749bac6faf32613f91fd149a23250a6",
"e3449af07749bac6faf32613f91fd149a23250a6"
] | [
"src/predict_modality/starter_kit/starter_kit_python/script.py",
"src/match_modality/methods/dummy_random/script.py"
] | [
"# Dependencies:\n# pip: scikit-learn, anndata, scanpy\n#\n# Python starter kit for the NeurIPS 2021 Single-Cell Competition.\n# Parts with `TODO` are supposed to be changed by you.\n#\n# More documentation:\n#\n# https://viash.io/docs/creating_components/python/\n\nimport logging\nimport anndata as ad\n\nfrom scip... | [
[
"sklearn.decomposition.TruncatedSVD",
"scipy.sparse.csc_matrix",
"sklearn.linear_model.LinearRegression"
],
[
"sklearn.preprocessing.normalize",
"numpy.random.rand",
"numpy.random.randint"
]
] |
posterrieri/mllib | [
"809265573eb5af5c68f92537ed90390795008e40"
] | [
"mllib/supervised/parametric.py"
] | [
"#!/usr/bin/env python3\nimport numpy as np\n\n\nclass LinearRegression:\n \"\"\"Linear regression algorithm\"\"\"\n def fit(self, X, y, lamb=0, add_intercept=True, iters=1000, lr=0.006):\n \"\"\"Fits the training data using normal equation\"\"\"\n if add_intercept:\n X = np.column_st... | [
[
"numpy.exp",
"numpy.random.randn",
"numpy.ones"
]
] |
hyounghk/ArraMon | [
"c8366b01420ac1a32871b898129ccf1e9c0fe6de"
] | [
"src/main_nosim.py"
] | [
"import random\nimport numpy as np\n\nimport torch\nfrom torch import nn, optim\nimport torchvision.transforms as transforms\nfrom data import NADataset, TorchDataset\nimport argparse\nfrom tqdm import tqdm\nfrom decoders_nosim import ActionDecoder\nfrom metric_dtw import DTW\nfrom sim_mul import simulator\nimport ... | [
[
"torch.nn.CrossEntropyLoss",
"numpy.random.seed",
"torch.load",
"torch.cuda.manual_seed",
"matplotlib.use",
"torch.manual_seed",
"torch.zeros",
"torch.utils.data.DataLoader",
"torch.sum",
"torch.sqrt",
"torch.no_grad",
"torch.nn.DataParallel"
]
] |
bantnd/pytorch-vsumm-reinforce | [
"d042203d5dd03086d53ef2ff7dde9999cb81e22f"
] | [
"utils/generate_dataset.py"
] | [
"\"\"\"\n Generate Dataset\n\n 1. Converting video to frames\n 2. Extracting features\n 3. Getting change points\n 4. User Summary ( for evaluation )\n\n\"\"\"\nimport sys\nsys.path.append('.')\nsys.path.append('../networks')\nfrom networks.CNN import ResNet\nfrom utils.KTS.cpd_auto import cpd_auto\n... | [
[
"numpy.concatenate",
"numpy.dot",
"numpy.vstack"
]
] |
saobangmath/CZ4034-Aspect-Classification-Model | [
"2a5e1d1e26bb6ec524bd13f3adc03bcc57ab74b9"
] | [
"utils/utils.py"
] | [
"import time\nimport inspect\n\nimport torch\nfrom loguru import logger\n\n\ndef to_device(x, device):\n if not isinstance(x, dict):\n return x\n\n new_x = {}\n\n for k, v in x.items():\n if isinstance(v, torch.Tensor):\n new_v = v.to(device)\n elif isinstance(v, (tuple, lis... | [
[
"torch.cat"
]
] |
Loliver1224/Creative-Experiment | [
"14857078995afca729c9f2935c7e741a8be42edc"
] | [
"main.py"
] | [
"import pandas as pd\nimport numpy as np\nimport pyper\nfrom graphviz import Source\nimport webbrowser\nimport tempfile\nfrom os import getcwd\nfrom shutil import copy2 as copyfile\nimport sys\n\nfrom SAM import SAM\nfrom testdata import make_test_data\n\nnp.set_printoptions(precision=2, floatmode='fixed', suppress... | [
[
"numpy.set_printoptions",
"numpy.where",
"numpy.random.seed",
"pandas.DataFrame"
]
] |
j20232/moco_image_pipeline | [
"997ae76e795548e75f95e862284c1fc0a3c7541a"
] | [
"mcp/augmentation/album.py"
] | [
"import numpy as np\nfrom PIL import Image, ImageOps, ImageEnhance\nimport albumentations as A\n\n# ndarray: H x W x C\n\n\ndef apply_aug(aug, image):\n return aug(image=image)[\"image\"]\n\n\n# ----------------------------------- Blur -------------------------------------------\nclass RandomBlur():\n def __i... | [
[
"numpy.random.random",
"numpy.random.beta",
"numpy.clip",
"numpy.asarray",
"numpy.random.choice",
"numpy.median",
"numpy.zeros_like",
"numpy.random.uniform",
"numpy.random.dirichlet",
"numpy.random.randint"
]
] |
mokadyr/structural-analogy | [
"70bbfa183b00a9bf103e493019486a17285e105a"
] | [
"train.py"
] | [
"\nimport models\nimport os\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.utils.data\nimport math\n\nimport sys\nfrom PIL import Image\nimport torchvision\nimport argparse\nimport random\nfrom utils import adjust_scales2image, generate_noise2, calc_gradient_penalty\nfrom imresize import imresize... | [
[
"torch.nn.MSELoss"
]
] |
grahamdelafield/DeepRTplus | [
"e4fe740e28af7ba427266fc039a7b5c3845671fd"
] | [
"prediction_emb_cpu.py"
] | [
"import torch\nimport numpy as np\nfrom torch.autograd import Variable\nfrom capsule_network_emb_cpu import *\nimport pickle\nfrom sys import argv\n\ndef pred_from_model(conv1_kernel,\n conv2_kernel,\n param_path, \n RTdata,\n ... | [
[
"torch.autograd.Variable",
"numpy.array",
"torch.load"
]
] |
prjemian/pnx | [
"75477ab63518d8c134ebc02bf839c60042a0461e"
] | [
"punx/ignore_now/validate.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n#-----------------------------------------------------------------------------\n# :author: Pete R. Jemian\n# :email: prjemian@gmail.com\n# :copyright: (c) 2016, Pete R. Jemian\n#\n# Distributed under the terms of the Creative Commons Attribution 4.0 Internat... | [
[
"numpy.ndarray"
]
] |
557mp/pk_story | [
"adcee7cfcc3b5d95601565066a6e8e7587974059"
] | [
"3_conditional_seqgan/sequence_gan_load_test.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport random\nfrom dataloader import Gen_Data_loader, Dis_dataloader\nfrom generator import Generator\nfrom discriminator_ import Discriminator\nfrom rollout import ROLLOUT\nimport pickle\n\n##############################################################################... | [
[
"numpy.random.seed",
"tensorflow.ConfigProto",
"tensorflow.global_variables_initializer",
"tensorflow.reset_default_graph",
"numpy.mean",
"tensorflow.Session",
"tensorflow.train.Saver",
"numpy.random.randint"
]
] |
fusion-flap/flap_nstx_gpi | [
"cf7d4bdecea8fd7434f8f7eb64e1a7b13fc0f759"
] | [
"publications/plot_results_for_rsi_2021.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed May 6 14:35:54 2020\n\n@author: mlampert\n\"\"\"\nimport os\nimport copy\nimport pickle\n\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib.backends.backend_pdf import PdfPages\nfrom matplotlib.gridspec import GridSpec\n\n... | [
[
"matplotlib.backends.backend_pdf.PdfPages",
"matplotlib.pyplot.title",
"matplotlib.style.use",
"numpy.min",
"numpy.arange",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.subplots",
"numpy.max",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.subplot",
"matplotlib.gridspec.G... |
vkuznet/CMSMonitoring | [
"af85d41846a19f68ed2fa1a1761a536fcbd16eb7"
] | [
"src/python/CMSMonitoring/eos_path_size.py"
] | [
"# !/usr/bin/env python\n# -*- coding: utf-8 -*-\n# Author: Ceyhun Uzunoglu <ceyhunuzngl AT gmail [DOT] com>\n# Create html table for EOS paths' size as a result of xrdcp command\n#\n# acronjob:\n# - $HOME/CMSMonitoring/scripts/eos_path_size.sh\n# How it works:\n# - Gets only paths from XRDCP command\n#... | [
[
"numpy.isnan",
"pandas.set_option",
"numpy.isinf"
]
] |
HyeonwooNoh/tensorflow_hw | [
"5828e285209ff8c3d1bef2e4bd7c55ca611080d5",
"b794611c9b90763ffbe2cb01f91b3a9e33c9b892"
] | [
"tensorflow/contrib/tpu/python/tpu/tpu_feed.py",
"tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.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.ops.array_ops.split",
"tensorflow.python.framework.ops.colocate_with",
"tensorflow.contrib.tpu.python.ops.tpu_ops.infeed_dequeue_tuple",
"tensorflow.contrib.tpu.python.ops.tpu_ops.infeed_enqueue_tuple",
"tensorflow.python.framework.dtypes.as_dtype",
"tensorflow.python.fr... |
falimoradi/E2E-MLT | [
"f14111238cc941a0d3411b00c72e58347229ba8d"
] | [
"fps.py"
] | [
"'''\nCreated on Aug 25, 2017\n\n@author: busta\n'''\n\nimport cv2, glob, os, codecs\nimport numpy as np\n\nfrom nms import get_boxes\n\nfrom models import ModelMLTRCTW\nimport net_utils\n\nfrom ocr_utils import ocr_image\nfrom data_gen import draw_box_points\nimport torch\n\nimport argparse\n\nfrom PIL import Imag... | [
[
"numpy.asarray",
"torch.no_grad"
]
] |
haozaijie/news_scraper | [
"494b8c8db1f452d900fbb4e06e757733fddccf23"
] | [
"src/postgresql_script/load_data.py"
] | [
"from sqlalchemy import create_engine\nimport pandas as pd\n\nengine = create_engine('postgresql://haozaijie:password@localhost:5432/sample_db')\n\ndf = pd.read_csv('files/combined_coronavirus.csv')\ndf.to_sql('news_scraper.raw', engine, if_exists='replace', index=False)\n"
] | [
[
"pandas.read_csv"
]
] |
mahmoud-al-najar/morphcast | [
"75c6eac775be1e54c7893d6fe64b88347d14aa3b"
] | [
"init_scripts/create_dataset.py"
] | [
"import os\nimport copy\nimport netCDF4\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom scipy import interpolate\nfrom itertools import groupby\nfrom utilities.wrappers import Topo\nfrom utilities.common import get_datetime_from_ymd_string, datetime_to_timestamp\n\n\ns_start_ymd = '1... | [
[
"numpy.timedelta64"
]
] |
jbak920/pixelcanvas | [
"c66c6678f22e3616da28a5aa920bd8436e7ea968"
] | [
"conway/conway.py"
] | [
"import time\r\nimport sys\r\nimport random\r\nsys.path.insert(0,'/home/pi/pixelcanvas')\r\n\r\nimport numpy as np\r\n\r\nfrom utils import multiply\r\n\r\ndef num_neighbors(row, col, array):\r\n neighbors = 0\r\n try:\r\n neighbors += array[row][col+1]\r\n except:\r\n pass\r\n try:\r\n ... | [
[
"numpy.full_like",
"numpy.array"
]
] |
pshivam97/Bachelors-Thesis | [
"e55aa943e6f2bf541febb3b63a1e427b56326f33"
] | [
"Research-Work/My-Work/MOEAs/NSGA-II Other Implementation/Implementation-1/NSGA2.py"
] | [
"## TAKEN FROM : https://pythonhealthcare.org/2019/01/17/117-code-only-genetic-algorithms-2-a-multiple-objective-genetic-algorithm-nsga-ii/\n\nimport random as rn\nimport numpy as np\nimport matplotlib.pyplot as plt\n# For use in Jupyter notebooks only:\n\n# Create reference solutions\n# --------------------------\... | [
[
"numpy.asarray",
"numpy.hstack",
"numpy.unique",
"numpy.arange",
"numpy.zeros",
"numpy.logical_not",
"matplotlib.pyplot.savefig",
"numpy.delete",
"numpy.argsort",
"numpy.array",
"matplotlib.pyplot.show",
"numpy.sum",
"matplotlib.pyplot.ylabel",
"numpy.random... |
leelabcnbc/tang_jcompneuro_revision | [
"58e9dbcbef7ca3f0c3976b24a4e4aa9c5efcdd3a"
] | [
"tang_jcompneuro/stimulus_classification.py"
] | [
"\"\"\"similar to misc.py in the previous tang-paper-2017 repo\"\"\"\nimport os.path\nfrom collections import OrderedDict\n# from itertools import product\n\nimport numpy as np\n\nfrom . import dir_dictionary\n\nrange_constructor = np.arange\n\n\ndef _shape_mapping_add_sublevels(prefix, result_dict, global_start_id... | [
[
"numpy.unique",
"numpy.arange",
"numpy.in1d",
"numpy.all",
"numpy.bincount",
"numpy.empty"
]
] |
PolarizedLightFieldMicroscopy/LFMNet2 | [
"c9b064d7625e018ef54b8dd8a0e53801c4565397"
] | [
"mainTrain.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.utils.tensorboard import SummaryWriter\nfrom torch.utils import data\nfrom torch import optim\nimport torchvision.models as models\nfrom torch.autograd import Variable\nimport torchvision as tv\nimport random\nimport math\nimport time... | [
[
"torch.cuda.get_device_properties",
"torch.load",
"torch.randperm",
"torch.utils.data.DataLoader",
"torch.set_grad_enabled",
"torch.set_num_threads",
"torch.utils.tensorboard.SummaryWriter",
"torch.cuda.is_available",
"torch.nn.functional.interpolate",
"torch.no_grad",
... |
reddit-conflicting-viewpoints/Reddit | [
"7d531f8cb826cf2d8196cf126d1e11dacc144155"
] | [
"pages/sas_key.py"
] | [
"import pandas as pd\nimport numpy as np\nfrom pandas.errors import ParserError\n\nAZURE_URL = \"https://redditconflict.blob.core.windows.net/redditconflict/results/\"\nSAS_KEY = \"?sp=r&st=2022-03-06T23:29:32Z&se=2023-01-01T07:29:32Z&sv=2020-08-04&sr=c&sig=%2FGHaPmXaEBpc36JBlYfMJLPE8dYr5cFcAsbPpjV16NA%3D\"\n\ndef ... | [
[
"pandas.Int64Dtype",
"pandas.BooleanDtype"
]
] |
mogwai/torch-audiomentations | [
"7d36c4b5970ca3c16482703fa8e8164ff63c20d0"
] | [
"scripts/demo.py"
] | [
"import os\nimport random\nfrom pathlib import Path\n\nimport librosa\nimport numpy as np\nimport time\nimport torch\nfrom scipy.io import wavfile\n\nfrom torch_audiomentations import (\n PolarityInversion,\n Gain,\n PeakNormalization,\n Compose,\n Shift,\n)\n\nSAMPLE_RATE = 44100\n\nBASE_DIR = Path(... | [
[
"numpy.random.seed",
"torch.from_numpy",
"numpy.stack",
"numpy.std",
"numpy.mean"
]
] |
ashishd/OpenSfM | [
"f66e51df7200fac676d8487499ebaf40e3de3e88"
] | [
"opensfm/test/test_datastructures.py"
] | [
"import copy\nimport random\n\nimport numpy as np\nimport pytest\nfrom opensfm import pygeometry\nfrom opensfm import pymap\nfrom opensfm import types\nfrom opensfm.test.utils import (\n assert_metadata_equal,\n assert_cameras_equal,\n assert_shots_equal,\n)\n\n\ndef _create_reconstruction(\n n_cameras:... | [
[
"numpy.diag",
"numpy.allclose",
"numpy.random.choice",
"numpy.shape",
"numpy.random.rand",
"numpy.array",
"numpy.random.randint"
]
] |
basiralab/Fed-CBT | [
"c85520ebd536153af1005454b48ca5fdb2cff3af"
] | [
"model.py"
] | [
"import torch\nimport torch.nn.functional as F\nfrom torch.nn import Sequential, Linear, ReLU\nfrom torch_geometric.nn import NNConv\n\n\nclass DGN(torch.nn.Module):\n def __init__(self, MODEL_PARAMS):\n super(DGN, self).__init__()\n self.model_params = MODEL_PARAMS\n \n nn = Sequenti... | [
[
"torch.abs",
"torch.transpose",
"torch.sum",
"torch.nn.Linear",
"torch.nn.ReLU"
]
] |
correlllab/nn4mc_cpp | [
"74a2a923dfdf07b65ffe30d92ea8a686b6dbb1f1"
] | [
"data/simpleRNNexample.py"
] | [
"#!/usr/bin/env python\nfrom __future__ import absolute_import, division, print_function, unicode_literals\nimport pandas as pd\nimport collections\nimport numpy as np\nimport matplotlib.pyplot as plt\n\nimport tensorflow as tf\nfrom tensorflow.keras import layers\n\nN = 1000\nTp = 800\n\nt = np.arange(0,N)\nx = np... | [
[
"tensorflow.keras.layers.MaxPool1D",
"numpy.reshape",
"numpy.arange",
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.layers.Dense",
"pandas.DataFrame",
"numpy.sin",
"numpy.concatenate",
"numpy.random.rand",
"numpy.repeat",
"numpy.array"
]
] |
AdityaKane2001/ACL_WASSA | [
"3912f61807cb08ff55fde36c433230720084b57a"
] | [
"models/essaytoemotionempathydistressbert.py"
] | [
"from transformers import BertTokenizer, BertModel\nimport torch\nfrom torch import nn\n\nimport numpy as np\nfrom tqdm.auto import tqdm\nimport wandb\n\nimport os\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import mean_squared_error as mse\nfrom dataloader import get_dataset\nfrom... | [
[
"torch.nn.Softmax",
"torch.nn.CrossEntropyLoss",
"torch.nn.Linear",
"matplotlib.pyplot.clf",
"numpy.mean",
"torch.no_grad",
"torch.cuda.is_available",
"torch.device",
"torch.nn.MSELoss"
]
] |
davendw49/gakg | [
"9b1cde1c702cbc87edfcb45687815653372665cd"
] | [
"code/baselines/simplE/SimplE.py"
] | [
"import torch\nimport torch.nn as nn\nimport math\n\nclass SimplE(nn.Module):\n def __init__(self, num_ent, num_rel, emb_dim, device):\n super(SimplE, self).__init__()\n self.num_ent = num_ent\n self.num_rel = num_rel\n self.emb_dim = emb_dim\n self.device = device\n\n s... | [
[
"torch.nn.init.uniform_",
"torch.norm",
"torch.sum",
"torch.nn.Embedding",
"torch.clamp"
]
] |
dennissergeev/cloudsat_example | [
"c8abd77466e39a493dd4a7429d50e26fc8cb6713"
] | [
"utils.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Auxiliary functions for sattools module.\"\"\"\nimport numpy as np\n\n\ndef cc_interp2d(data, X, Z, x1, x2, nx, z1, z2, nz, use_numba=True):\n if use_numba:\n try:\n import numba as nb\n except ImportError:\n print(\"Unsuccessful numba import, u... | [
[
"numpy.isnan",
"numpy.zeros"
]
] |
chdoig/blaze | [
"caa5a497e1ca1ceb1cf585483312ff4cd74d0bda"
] | [
"blaze/api/into.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nfrom dynd import nd\nimport datashape\nimport sys\nfrom datashape import DataShape, dshape, Record, to_numpy_dtype\nimport toolz\nfrom toolz import concat, partition_all, valmap\nfrom cytoolz import pluck\nimport copy\nfrom datetime import datetim... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.Series",
"numpy.asarray",
"numpy.issubdtype",
"numpy.ndarray",
"pandas.DataFrame",
"numpy.dtype",
"numpy.vstack"
]
] |
LandAndLand/Deep-Model-Watermarking | [
"9add23a588903f7e6879527b1347bbd628bd6279"
] | [
"SR/testSREmb.py"
] | [
"\nimport os\nimport torch\nfrom tqdm.std import tqdm\n\nfrom SRDataset import SRDataset\nfrom SR_parser import parameter_parser\nfrom tqdm import tqdm\nfrom utils import save_result_pic\nfrom models.HidingRes import HidingRes\n\nopt = parameter_parser()\nstage = \"IniStage\"\ndataset_dir = \"/home/ay3/houls/waterm... | [
[
"torch.cat",
"torch.load"
]
] |
tienduccao/clearml | [
"e182c188e0ceca939fa7ba8f5657228136f3ab1f"
] | [
"clearml/storage/helper.py"
] | [
"from __future__ import with_statement\n\nimport errno\nimport getpass\nimport itertools\nimport json\nimport os\nimport shutil\nimport sys\nimport threading\nfrom abc import ABCMeta, abstractmethod\nfrom collections import namedtuple\nfrom concurrent.futures import ThreadPoolExecutor\nfrom copy import copy\nfrom d... | [
[
"numpy.frombuffer"
]
] |
jsosulski/toeplitz | [
"9d6e6e08af566227e6777067993c17dc39a75971"
] | [
"setup.py"
] | [
"#!/usr/bin/env python\nfrom numpy.distutils.core import Extension, setup\n\nVERSION = '0.3.2-dev'\n\nwith open('README.rst') as f:\n README = f.read()\nDESCRIPTION = README.split('\\n')[2]\nLONG_DESCRIPTION = '\\n'.join(README.split('\\n')[17:])\n\nEXT = Extension(name='toeplitz',\n sources=['src... | [
[
"numpy.distutils.core.Extension",
"numpy.distutils.core.setup"
]
] |
jjtan/unintended-ml-bias-analysis | [
"8172643f6224df09323c2be227bc2ca0f218f03a"
] | [
"unintended_ml_bias/model_tool.py"
] | [
"\"\"\"Train a Toxicity model using Keras.\"\"\"\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nimport cPickle\nimport json\nimport os\nfrom keras.callbacks import EarlyStopping\nfrom keras.callbacks import ModelCheckpoint\nfrom keras.layers import... | [
[
"numpy.asarray",
"sklearn.metrics.roc_auc_score",
"pandas.read_csv"
]
] |
yangcht/radex_emcee | [
"03d948b378773bf1d20a006cdab6143c57072cd0"
] | [
"emcee/emcee_radex_2comp.py"
] | [
"#!/usr/bin/env python\n# To run it on the cluster, login and use\n#\n# > srun -N 1 -c 16 --exclusive emcee_radex_2comp.py\n#\n# to launch it on a node with 16 core, or use\n#\n# > sbatch emcee_radex_2comp.py\n#\n#\n#SBATCH --nodes=1\n#SBATCH --ntasks=32\n#SBATCH --partition=cpu_only\n#SBATCH --account=cyang\n#SBAT... | [
[
"numpy.hstack",
"numpy.amax",
"matplotlib.ticker.MultipleLocator",
"numpy.log",
"numpy.sqrt",
"numpy.isfinite",
"numpy.isnan",
"matplotlib.use",
"numpy.percentile",
"numpy.int_",
"numpy.log10",
"scipy.optimize.minimize",
"numpy.any",
"numpy.random.randn",
... |
Akssi/spin-pommerman | [
"8d74e00fdc95610a8dcc9acd59b3bfebfe2078b3"
] | [
"train_singleAgent.py"
] | [
"import pommerman\nfrom pommerman import agents\nimport SPINAgents\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport torch\nfrom torch import nn\nimport torch.nn.functional as F\nimport gym\nfrom torch.autograd import Variable\nimport random\nfrom collections import namedtuple\n\ni... | [
[
"torch.LongTensor",
"torch.Tensor",
"torch.load",
"numpy.zeros",
"torch.save"
]
] |
sepehrgdr/Mode_Imputation | [
"bd7c17d05beacdbdf2f4c9fdefa3062a253607c8"
] | [
"Codes/Attribute_Extraction/calc_dist.py"
] | [
"import fiona\r\nimport shapely.geometry as sg\r\nfrom shapely.geometry import asMultiLineString\r\nimport time\r\nimport pandas as pd\r\nimport geopandas\r\nimport csv\r\nimport os\r\nimport numpy as np\r\n\r\n\r\ndef calc_dist(in_pts_file, in_net_file, out_path, out_name):\r\n \r\n # Create shapefile from c... | [
[
"pandas.read_csv"
]
] |
alichaudry/pandas | [
"ce3e57b44932e7131968b9bcca97c1391cb6b532"
] | [
"pandas/core/resample.py"
] | [
"from __future__ import annotations\n\nimport copy\nfrom datetime import timedelta\nfrom textwrap import dedent\nfrom typing import Callable, Dict, Optional, Tuple, Union, no_type_check\n\nimport numpy as np\n\nfrom pandas._libs import lib\nfrom pandas._libs.tslibs import (\n IncompatibleFrequency,\n NaT,\n ... | [
[
"pandas.core.indexes.datetimes.DatetimeIndex",
"pandas._libs.tslibs.Timestamp",
"pandas.Series",
"pandas._libs.lib.generate_bins_dt64",
"pandas.DataFrame",
"pandas.core.indexes.datetimes.date_range",
"pandas.core.indexes.timedeltas.timedelta_range",
"pandas.core.indexes.period.Peri... |
rishabhjha708/Pyostie | [
"47091748bc746920f386952c1a6c1002340e3224"
] | [
"pyostie/parsers.py"
] | [
"import os\nimport docx2txt\nimport xlrd\nimport csv\nimport cv2\nimport pytesseract\nfrom PIL import Image\nfrom pkgutil import find_loader\nimport PyPDF2\nimport pdfplumber\nfrom pptx import Presentation\nfrom pdf2image import convert_from_path\nimport speech_recognition as sr\n\nfrom pyostie.convert import *\nfr... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] |
htahir1/ml-metadata | [
"9d76a4ba515a21f68273a3734b1d06572aea9802"
] | [
"ml_metadata/metadata_store/metadata_store.py"
] | [
"# Copyright 2019 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 agreed ... | [
[
"tensorflow.python.framework.errors.exception_type_from_error_code",
"tensorflow.python.framework.errors.UnknownError"
]
] |
Rohit-Kundu/Hybrid_MRFO-OBHSA | [
"3511ead3a2024099fb77e8e19056257c03c8393a"
] | [
"OBHSA.py"
] | [
"import numpy as np\r\nimport pandas as pd\r\nimport sklearn\r\nfrom sklearn import datasets,svm,metrics\r\nfrom sklearn.model_selection import KFold\r\nfrom sklearn.neighbors import KNeighborsClassifier\r\nfrom sklearn.neural_network import MLPClassifier\r\nfrom sklearn.model_selection import train_test_split\r\nf... | [
[
"sklearn.neural_network.MLPClassifier",
"sklearn.model_selection.train_test_split",
"sklearn.model_selection.KFold",
"numpy.ones",
"numpy.concatenate",
"numpy.max",
"sklearn.neighbors.KNeighborsClassifier",
"numpy.argpartition",
"sklearn.svm.SVC",
"numpy.random.rand",
"... |
rogerwxd/Machine-Learning | [
"1fae84725e3d789b709afcfe2b57c40ecbc4af75"
] | [
"sklearn/train/train.py"
] | [
"import pandas as pd\nfrom sklearn import tree\nimport os\nfrom sklearn.ensemble import RandomForestClassifier, BaggingClassifier, AdaBoostClassifier\nfrom sklearn.model_selection import train_test_split\nimport joblib\nfrom sklearn.neural_network import MLPClassifier\n\nsaveModel = 'saveModel/' # PASTA PARA SALVAR... | [
[
"sklearn.neural_network.MLPClassifier",
"sklearn.ensemble.BaggingClassifier",
"pandas.read_csv",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.model_selection.train_test_split",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.ensemble.AdaBoostClassifier"
]
] |
yyuting/FastImageProcessing | [
"c3ac272d3218cc4d30939f8219be70bc4125c4cc"
] | [
"CAN24_AN/read_timeline.py"
] | [
"import os\nimport json\nimport numpy\nimport sys\nimport glob\n\ndef read_time_dur(data_list):\n t_min = numpy.inf\n t_max = -numpy.inf\n\n for item in data_list:\n if 'ts' in item.keys():\n if item['ts'] < t_min:\n t_min = item['ts']\n if 'dur' in item.keys():\... | [
[
"numpy.median",
"numpy.zeros",
"numpy.mean",
"numpy.min"
]
] |
isl-mt/NMTGMinor | [
"573504d0ed2e40240e4186eb4af28275f0e3f422"
] | [
"onmt/EnsembleTranslator.py"
] | [
"import onmt\nimport onmt.modules\nimport torch.nn as nn\nimport torch\nimport math\nfrom torch.autograd import Variable\nfrom onmt.ModelConstructor import build_model\nimport torch.nn.functional as F\n\n\nmodel_list = ['transformer', 'stochastic_transformer']\n\nclass EnsembleTranslator(object):\n def __init__(... | [
[
"torch.norm",
"torch.nn.functional.log_softmax",
"torch.load",
"torch.exp",
"torch.set_grad_enabled",
"torch.log",
"torch.autograd.Variable"
]
] |
seann27/DogBreedDetector | [
"88b76cc6eea869a9d28e775843f5fbf9d9fbc9c1"
] | [
"predict.py"
] | [
"import torchvision.models as models\nimport torch.nn as nn\nimport torch\nimport torchvision.transforms as transforms\nimport sys\nimport os\nimport numpy as np\nimport json\nimport random\nimport matplotlib.pyplot as plt\nfrom glob import glob\nfrom PIL import Image\nfrom torchvision import datasets\n\n# # grab f... | [
[
"torch.nn.Dropout",
"torch.nn.LogSoftmax",
"torch.load",
"torch.exp",
"torch.nn.Linear",
"torch.cuda.is_available",
"torch.nn.ReLU",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] |
rosulucian/handrolled-ml | [
"dc4227039da20a8daaeabc7ec438398b2ff12894"
] | [
"utils/activations.py"
] | [
"import numpy as np\n\n\ndef sigmoid(Z):\n return 1 / (1 + np.exp(-Z))\n\n\ndef relu(Z):\n A = np.maximum(0, Z)\n\n assert(A.shape == Z.shape)\n\n return A\n\n\ndef tanh(Z):\n return np.tanh(Z)\n\n\ndef sigmoid_deriv(dA, Z):\n assert (dA.shape == Z.shape)\n\n s = 1/(1+np.exp(-Z))\n deriv = s... | [
[
"numpy.maximum",
"numpy.power",
"numpy.tanh",
"numpy.array",
"numpy.exp"
]
] |
izhx/hsinkit-learn | [
"94252bed07c5b1bd97985ddcd5ec3e36f115f0cb"
] | [
"hklearn/neighbors.py"
] | [
"import numpy as np\nfrom scipy import stats\n\nfrom .base import BaseEstimator, ClassifierMixin\n\n\nclass KNeighborsClassifier(BaseEstimator, ClassifierMixin):\n def __init__(self, n_neighbors=5, weights=None, metric='L2'):\n super(KNeighborsClassifier, self).__init__()\n self.n_neighbors = n_nei... | [
[
"numpy.abs",
"numpy.arange",
"numpy.sum",
"scipy.stats.mode"
]
] |
Jackson-Kang/VQVC-Pytorch | [
"d2267b5c52253b6ae11a5767963a65320ae335c2"
] | [
"utils/audio/audio_preprocessing.py"
] | [
"\"\"\"\n\tfrom NVIDIA's preprocessing\n\n\treference)\n\t\thttps://github.com/NVIDIA/tacotron2\n\"\"\"\n\nimport torch\nimport numpy as np\nfrom scipy.signal import get_window\nimport librosa.util as librosa_util\nfrom config import Arguments as args\n\ndef window_sumsquare(window, n_frames, hop_length=args.hop_le... | [
[
"scipy.signal.get_window",
"torch.from_numpy",
"torch.exp",
"torch.clamp",
"numpy.zeros"
]
] |
MarcosRBL/ScholarDropout | [
"f35f8c8715bc6eab79e49052098deab549d34144"
] | [
"PredAlunos.py"
] | [
"import pandas as pd\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sns\r\nimport sklearn.metrics as m\r\nimport streamlit as st\r\n\r\nimport inflection\r\nimport pylab\r\nimport random\r\nimport warnings\r\nimport os\r\nimport io\r\n\r\nfrom IPython.display import Image\r\nfrom skle... | [
[
"pandas.read_csv",
"sklearn.model_selection.cross_val_score",
"sklearn.ensemble.RandomForestClassifier",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.LabelEncoder",
"sklearn.metrics.classification_report",
"sklearn.preprocessing.MinMaxScaler",
"sklearn.metrics... |
NagarajSMurthy/Invisibility-cloak | [
"16d02e9ee1d456d5606edf973e85c1dbdb6e5377"
] | [
"Invisibility_cloak.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Fri Jul 17 14:12:32 2020\r\n\r\n@author: nagar\r\n\"\"\"\r\n\r\nimport numpy as np\r\nimport cv2\r\nimport time\r\nimport math\r\n\r\ncam = cv2.VideoCapture(0)\r\n\r\ntime.sleep(1)\r\nnum_frames = 0\r\nbg = None\r\naWeight = 0.8\r\n\r\ndef init_bgnd():\r\n global ... | [
[
"numpy.array",
"numpy.flip",
"numpy.ones"
]
] |
Azeirah/multiplot | [
"5a7b10f0ef5ba480fadfc43fc8e7d9717a6ebac5"
] | [
"multiplot.py"
] | [
"import matplotlib.pyplot as plt\n\n\ndef multiplot(plots, *args, **kwargs):\n \"\"\"A convenient way to lay out matplotlib figures\n The first argument is a multiline string which diagrammatically describes\n the desired layout of your plot\n\n @return (figure, grid)\n\n e.g., a simple single plot l... | [
[
"matplotlib.pyplot.subplot2grid",
"matplotlib.pyplot.figure"
]
] |
jakirkham/dask-scheduler-performance | [
"74d4eb7080b351f912a284a9eadb80726858f0e4"
] | [
"nightly-benchmark/nightly-run.py"
] | [
"import os\nimport dask\nimport distributed\nfrom datetime import datetime\nimport numpy as np\nimport time\nfrom dask.distributed import Client, wait, performance_report\nfrom dask.dataframe.shuffle import shuffle\n\nimport xarray as xr\nimport dask.array as dsa\n\nimport pandas as pd\nimport matplotlib.pyplot as ... | [
[
"pandas.read_csv",
"numpy.arange",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.savefig",
"numpy.array"
]
] |
quid256/OpenFermion | [
"562a03abf501885ee5a792ec3d7d10d91581b938"
] | [
"src/openfermion/transforms/_jordan_wigner_test.py"
] | [
"# 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 agreed to in writing, software... | [
[
"numpy.zeros"
]
] |
IvyGao58/Pronoun-Coref | [
"48067a82553bdd25ccf47328cf1f0a3ed5bdc970"
] | [
"elmoForManyLangs/__main__.py"
] | [
"#!/usr/bin/env python\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\nimport os\nimport codecs\nimport argparse\nimport logging\nimport json\nimport sys\n\nimport torch\n\nsys.path.append('../')\nfrom elmoformanylangs.modules.embedding_layer import EmbeddingLayer\nfrom elmoformanyl... | [
[
"torch.cuda.is_available",
"numpy.stack",
"torch.cuda.set_device",
"numpy.average"
]
] |
arpastrana/compas | [
"ed677a162c14dbe562c82d72f370279259faf7da"
] | [
"src/compas/numerical/drx/drx_numba.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom numpy import arccos\nfrom numpy import array\nfrom numpy import isnan\nfrom numpy import mean\nfrom numpy import sin\nfrom numpy import sqrt\nfrom numpy import sum\nfrom numpy import zeros\n\nfrom... | [
[
"numpy.sqrt",
"numpy.isnan",
"numpy.arccos",
"numpy.sin",
"numpy.mean",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] |
sdomanskyi/decneo | [
"c3b78d7cb24fbecde317850ea5068394029a7d03"
] | [
"scripts/demo.py"
] | [
"import pandas as pd\nfrom decneo.analysisPipeline import process\n\ndemoData = '/mnt/home/domansk6/Projects/Endothelial/scripts/demo/VoightChoroid4567RemappedData.h5'\n\nif __name__ == '__main__':\n\n wdir = '/mnt/scratch/domansk6/DECNEOdemo/'\n\n process(pd.read_hdf(demoData, key='dfa'), # Endothelial cel... | [
[
"pandas.read_hdf"
]
] |
lianyfei/bert-utils | [
"5de95a459146482a27deae36464e95a24dfe2bcf"
] | [
"run_classifier_exporter.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unl... | [
[
"tensorflow.contrib.cluster_resolver.TPUClusterResolver",
"tensorflow.metrics.accuracy",
"tensorflow.FixedLenFeature",
"tensorflow.nn.log_softmax",
"tensorflow.estimator.export.build_raw_serving_input_receiver_fn",
"tensorflow.reduce_sum",
"tensorflow.gfile.GFile",
"tensorflow.trai... |
mondrasovic/reid_baseline_syncbn | [
"3d21a786fb1a0519caaa0572c649f750036689b5"
] | [
"dataset/__init__.py"
] | [
"from .transform import RandomErasing\r\nfrom .collate_batch import train_collate_fn\r\nfrom .collate_batch import val_collate_fn\r\nfrom .triplet_sampler import RandomIdentitySampler\r\nfrom .data import ImageDataset, init_dataset\r\nimport torchvision.transforms as T\r\nfrom torch.utils.data.dataloader import Dat... | [
[
"torch.utils.data.dataloader.DataLoader"
]
] |
yun-s-oh/addrmatcher | [
"1d937d1e25d785b170fc967bc6bc21a456bace1b"
] | [
"tests/python/latlon_addrmatching_unfactored_2.py"
] | [
"import os\nimport glob\nimport time\nimport numpy as np\nfrom pyarrow import fs\nimport pyarrow.parquet as pq\nfrom sklearn.neighbors import BallTree\n\nis_index_file_exist = os.path.isfile(\"../../../data/Master/New/index.parquet\")\nfiles = (\n glob.glob(os.path.join(\"../../../\", \"data\", \"Master\", \"New... | [
[
"numpy.deg2rad"
]
] |
guillaume-florent/PyGeM | [
"372682bff82d1cd396de5773b821ae17918eb905"
] | [
"pygem/radial.py"
] | [
"\"\"\"\nModule focused on the implementation of the Radial Basis Functions interpolation\ntechnique. This technique is still based on the use of a set of parameters, the\nso-called control points, as for FFD, but RBF is interpolatory. Another\nimportant key point of RBF strategy relies in the way we can locate th... | [
[
"numpy.dot",
"numpy.log",
"numpy.linalg.solve",
"numpy.sqrt",
"numpy.power",
"scipy.spatial.distance.cdist",
"numpy.ones",
"numpy.bmat",
"numpy.exp",
"numpy.zeros"
]
] |
SoumyajitPal/YinYang | [
"325c5a7846fabf10e601f059d682b5099a351589"
] | [
"CropImage.py"
] | [
"import numpy as np\r\nimport cv2\r\n# from matplotlib import pyplot as plt\r\nimport ImDiffMod\r\nimport math\r\n\r\n\r\ndef cropImage(img1, img2):\r\n\r\n # Initiate SIFT detector\r\n sift = cv2.xfeatures2d.SIFT_create()\r\n\r\n # find the keypoints and descriptors with SIFT\r\n kp1, des1 = sift.detec... | [
[
"numpy.linalg.inv",
"numpy.float32"
]
] |
fidler-lab/efficient-annotation-cookbook | [
"8d02da89c8049c549748761e1762a04f40a64da0"
] | [
"online_label/worker.py"
] | [
"import os\nimport json\nimport uuid\nimport numpy as np\n\nfrom data import REPO_DIR, imagenet100\n\nimport logging\nlogger = logging.getLogger(__name__)\n\n\nclass Worker(object):\n\n def __init__(self, config, known, seed, **kwargs):\n\n self.id = str(uuid.uuid4())\n self.config = config\n ... | [
[
"numpy.diag",
"numpy.clip",
"numpy.eye",
"numpy.ones",
"numpy.array",
"numpy.zeros",
"numpy.random.RandomState"
]
] |
tsumikihuang/ml-agents- | [
"cb0bfa0382650dee2071eb415147d795721297b1"
] | [
"ml-agents/mlagents/trainers/ppo/trainer.py"
] | [
"# # Unity ML-Agents Toolkit\n# ## ML-Agent Learning (PPO)\n# Contains an implementation of PPO as described (https://arxiv.org/abs/1707.06347).\n\nimport logging\nimport os\nfrom collections import deque\n\nimport numpy as np\nimport tensorflow as tf\n\nfrom mlagents.envs import AllBrainInfo, BrainInfo\nfrom mlage... | [
[
"tensorflow.summary.FileWriter",
"numpy.abs",
"numpy.zeros_like",
"numpy.mean",
"numpy.vstack"
]
] |
TSFDlib/TSFEL | [
"a4c30acc93dd3717bf93b19e59c3dc927903caf2"
] | [
"tsfel/feature_extraction/feat_selection.py"
] | [
"import numpy as np\nimport pandas_profiling\nfrom sklearn.metrics import accuracy_score\n\ndef FSE(X_train, X_test, y_train, y_test, features_descrition, classifier):\n \"\"\" Performs a forward feature selection.\n Parameters\n ----------\n X_train: array-like\n train set features\n X_test: ar... | [
[
"numpy.column_stack",
"numpy.array",
"numpy.argmax",
"sklearn.metrics.accuracy_score"
]
] |
dariodsa/pycuda | [
"0fb9477b8b73deb8773ee9007b2ed97720d06552"
] | [
"examples/hello_gpu.py"
] | [
"from __future__ import print_function\nfrom __future__ import absolute_import\nimport pycuda.driver as drv\nimport pycuda.tools\nimport pycuda.autoinit\nimport numpy\nimport numpy.linalg as la\nfrom pycuda.compiler import SourceModule\n\nmod = SourceModule(\"\"\"\n__global__ void multiply_them(float *dest, float *... | [
[
"numpy.random.randn",
"numpy.zeros_like"
]
] |
saiyalamarty/advent-of-code | [
"e3ef525d06859515451d5ac7125004536d8ef985"
] | [
"src/year_2021/day_7/puzzle.py"
] | [
"import os\n\nimport numpy as np\n\n\ndef main():\n\n # Read contents of input (as a file) with a context manager\n file_path = os.path.abspath(\n os.path.join(os.path.dirname(__file__), 'input.data')\n )\n with open(file_path, \"r\") as input_file:\n for line in input_file:\n p... | [
[
"numpy.absolute"
]
] |
thestephencasper/football | [
"5f10d87961c493712ba22146696088aea891df66"
] | [
"gfootball/make_victim_action_dataset.py"
] | [
"# coding=utf-8\n# Copyright 2019 Google LLC\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 la... | [
[
"numpy.array",
"numpy.vstack"
]
] |
valsworthen/toxic-comment-classification | [
"12ceb4d78410a14fba05e43f6f424cec52e6665d"
] | [
"tools/utils.py"
] | [
"\"\"\"Utilities\"\"\"\nimport pandas as pd\nimport numpy as np\nfrom attrdict import AttrDict\nimport yaml\n\ndef average_predictions(cv_predictions, n_splits, num_samples = 153164, num_labels = 6):\n \"\"\"Average k-fold predictions stored in a dict\"\"\"\n preds = np.zeros((num_samples, num_labels))\n f... | [
[
"pandas.read_csv",
"numpy.zeros",
"pandas.DataFrame",
"numpy.ones"
]
] |
zsy0828/OpenHGNN | [
"7fe0917008c9f50269bbd308e411a1d8199d667d"
] | [
"openhgnn/trainerflow/entity_classification.py"
] | [
"import dgl\nimport torch\nfrom tqdm import tqdm\nfrom ..models import build_model\nfrom ..layers.EmbedLayer import HeteroEmbedLayer\nfrom . import BaseFlow, register_flow\nfrom ..tasks import build_task\nfrom ..utils import extract_embed, EarlyStopping, get_nodes_dict\n\n\n@register_flow(\"entity_classification\")... | [
[
"torch.no_grad",
"torch.cat"
]
] |
RobinAbrahamse/hls4ml | [
"8d68c5262c6c8728502fa88b1a2d2429929e222c"
] | [
"hls4ml/model/profiling.py"
] | [
"from hls4ml.model.hls_model import HLSModel\nfrom hls4ml.model.hls_layers import IntegerPrecisionType, FixedPrecisionType\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas\nimport seaborn as sb\nimport uuid\nimport os\nimport shutil\nimport json\nfrom collections import defaultdict\n\nfrom hls4ml... | [
[
"matplotlib.pyplot.legend",
"numpy.sqrt",
"pandas.DataFrame",
"matplotlib.pyplot.plot",
"numpy.histogram",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.tight_layout",
"numpy.arange",
"matplotlib.pyplot.gcf",
"numpy.zeros",
"matplotlib.pyplot.figure",
"matplotlib.pypl... |
Mostafa-ashraf19/TourchPIP | [
"a5090a0ec9cc81a91fe1fd6af41d77841361cec1"
] | [
"DLFrameWork/dataset/FashionMNIST.py"
] | [
"import os\nimport zipfile, urllib.request, shutil\nimport requests\nimport matplotlib.pyplot as plt\n\n\nMNIST_URL = 'https://drive.google.com/uc?id=1NjvEw9Ob7sJkEQLWPe_M-XhhZLYCx7lE&export=download'\n\n\nclass FashionMNIST:\n def __init__(self,path,download=True,train=True):\n self.path = path\n ... | [
[
"matplotlib.pyplot.show"
]
] |
sandrarum/inqbus.graphdemo | [
"63cbea8118673f755c78f62cab06d9744e7fc61c"
] | [
"src/inqbus/graphdemo/bokeh_extension/helpers_contour.py"
] | [
"import os\nfrom glob import glob\n\nimport dask.array as da\nimport numpy as np\nimport scipy.ndimage as sc\nimport tables as tb\nfrom bokeh.models import ColumnDataSource, Float\nfrom inqbus.graphdemo.bokeh_extension.helpers import \\\n binary_from_data_map\nfrom inqbus.graphdemo.constants import (\n MAX_NU... | [
[
"numpy.meshgrid",
"numpy.linspace",
"scipy.ndimage.zoom",
"numpy.cos",
"numpy.sin",
"numpy.array"
]
] |
reeshogue/OldProjects | [
"e4b105148b8aa44827a7fd2d4b417b66a76218ba"
] | [
"IDontKnowWhatThisIsButTheFolderWasCalledGodel/imaginative_ddpg.py"
] | [
"import tensorflow as tf\nimport tensorflow.keras.layers as L\nfrom collections import deque\nimport random\nimport numpy as np\nimport tensorflow_probability as tfp\n\ndef set_random_seed():\n # tf.random.set_seed(1233)\n np.random.seed(1233)\n random.seed(1233)\n\nset_random_seed()\n\ndef mod_sigmoid(x):... | [
[
"tensorflow.keras.models.load_model",
"numpy.squeeze",
"tensorflow.tanh",
"numpy.mean",
"tensorflow.keras.layers.Concatenate",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.losses.BinaryCrossentropy",
"numpy.argmax",
"numpy.float32",
"tensorflow.keras.layers.Add",
... |
shahaniRG/sinogram_changepoint_detection | [
"17c0193d5628c691172cccde2d3d5d82fc076107"
] | [
"sinogram_functions.py"
] | [
"# -----------------------------------------------------------\r\n# Code free for public use, just acknowledge use\r\n# Paul Chao, pchao@umich.edu\r\n# December 18, 2020\r\n# Data obtained at APS 2ID-BM\r\n# Original data type: hdf (h5) file\r\n#\r\n# -----------------------------------------------------------\r\n\... | [
[
"numpy.linspace",
"numpy.asarray",
"numpy.squeeze",
"pandas.DataFrame",
"numpy.concatenate",
"numpy.round",
"matplotlib.pyplot.plot",
"numpy.max",
"numpy.mean",
"matplotlib.pyplot.rcParams.update",
"numpy.digitize",
"scipy.signal.savgol_filter",
"numpy.unique",
... |
skyssj/graph-learn | [
"7bbffceed2c69a7acf903d80ee5bbc7e3fec6ca1"
] | [
"examples/tf/gat/gat.py"
] | [
"# Copyright 2020 Alibaba Group Holding Limited. 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# Unle... | [
[
"tensorflow.math.argmax",
"tensorflow.math.equal",
"tensorflow.placeholder",
"tensorflow.shape"
]
] |
mchancan/Hierarchical-Localization | [
"e310e311a722405f19a54f9e833834feb5e70a47"
] | [
"hloc/utils/parsers.py"
] | [
"from pathlib import Path\nimport logging\nimport numpy as np\nfrom collections import defaultdict\n\n\ndef parse_image_lists_with_intrinsics(paths):\n results = []\n files = list(Path(paths.parent).glob(paths.name))\n assert len(files) > 0\n\n for lfile in files:\n with open(lfile, 'r') as f:\n ... | [
[
"numpy.array"
]
] |
Derek-TH-Wang/OpenRoboRL | [
"b81333f034acff7252322322b8d499cd2c3c49e9"
] | [
"OpenRoboRL/envs/quadruped_robot/robots/laikago.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Google Research Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.array"
]
] |
cwpeng-cn/deep-person-reid | [
"354df0860c4730df4466869aaf512db93b05303a"
] | [
"torchreid/data/datasets/video/mars.py"
] | [
"from __future__ import division, print_function, absolute_import\nimport os.path as osp\nimport warnings\nfrom scipy.io import loadmat\n\nfrom ..dataset import VideoDataset\n\n\nclass Mars(VideoDataset):\n \"\"\"MARS.\n\n Reference:\n Zheng et al. MARS: A Video Benchmark for Large-Scale Person Re-iden... | [
[
"scipy.io.loadmat"
]
] |
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