repo_name stringlengths 8 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
alirkaya/card-fraud-detection | [
"90e4639c55a8502e03c35660a7b86a847c069cfb"
] | [
"Documentation/my_module.py"
] | [
"\"\"\"Prepared by [Ali Rifat Kaya](https://www.linkedin.com/in/alirifatkaya/)\n\"\"\"\n\n\ndef pr_auc_score(y_test, predicted_probabilities):\n \"\"\"Return AUCPR (Area Under Curve Precision-Recall) score\n\n Parameters\n ----------\n\n y_test : Test set target values\n Example:\n # df is... | [
[
"sklearn.base.clone",
"numpy.array",
"numpy.interp",
"sklearn.metrics.roc_curve",
"sklearn.metrics.auc",
"pandas.DataFrame",
"numpy.std",
"matplotlib.pyplot.gca",
"sklearn.preprocessing.scale",
"sklearn.metrics.confusion_matrix",
"sklearn.metrics.roc_auc_score",
"nu... |
onnela-lab/mech-mle | [
"8a36c1a75dbbc665feb642f527aeb09e7462e90b"
] | [
"drosa.py"
] | [
"# JP Onnela\r\n# April 20, 2021\r\n\r\n# Edited May 17, 2021 by Jonathan Larson\r\n\r\nimport networkx as nx\r\nimport random\r\nimport scipy.stats as ss\r\nimport time\r\n\r\ndef generate_DMC(q_mod, q_con, n):\r\n \"\"\"Generate DMC model realization given parameters.\"\"\"\r\n G = nx.Graph()\r\n G.add_e... | [
[
"scipy.stats.bernoulli.rvs"
]
] |
jasonfan1997/threeML | [
"21b1c76ad3423f745b9f56413d93ee01d1d5855f"
] | [
"threeML/test/test_fits_file.py"
] | [
"from threeML.io.fits_file import FITSExtension, FITSFile\nimport numpy as np\nimport astropy.io.fits as fits\n\nimport pytest\n\n\nclass DUMMYEXT(FITSExtension):\n def __init__(self, test_value):\n\n data_list = [(\"TEST_VALUE\", test_value)]\n\n super(DUMMYEXT, self).__init__(\n tuple(... | [
[
"numpy.alltrue",
"numpy.ones"
]
] |
benneely/lungmap-pipeline | [
"a38a6d1331468834280ce1ac41f30c76ee553ed4"
] | [
"examples/run_pipeline_60x.py"
] | [
"import os\nimport numpy as np\nfrom micap import pipeline\nfrom glob import glob\nfrom PIL import Image\nimport cv2_extras as cv2x\n\n# weird import style to un-confuse PyCharm\ntry:\n from cv2 import cv2\nexcept ImportError:\n import cv2\n\ncell_radius = 17 * 3\ncell_size = np.pi * (cell_radius ** 2)\n\nseg... | [
[
"numpy.asarray"
]
] |
salvacarrion/autonlp | [
"5cc462901e451b9259219f44225034fc8eedf6d3"
] | [
"examples/3_plot_results.py"
] | [
"import pandas as pd\nfrom tokenizers import normalizers\nfrom tokenizers.normalizers import NFKC, Strip, Lowercase\n\nfrom autonmt.bundle import utils\nfrom autonmt.bundle.report import generate_multivariable_report\nfrom autonmt.preprocessing import DatasetBuilder\n\n\ndef main():\n\n # Create preprocessing f... | [
[
"pandas.DataFrame"
]
] |
hbaspecto-com/tmip-emat | [
"e1c936e88f36f9b3e4379d814ecb7a3c255e16b1"
] | [
"emat/model/core_model.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\" core_model.py - define coure model API\"\"\"\nimport os\nimport abc\nimport yaml\nimport pandas as pd\nimport numpy as np\nimport logging\nimport subprocess\nimport warnings\nfrom contextlib import contextmanager\nfrom typing import Union, Mapping\nfrom ..workbench.em_framework.mode... | [
[
"numpy.std",
"pandas.DataFrame",
"pandas.concat",
"pandas.DataFrame.from_dict"
]
] |
YoungSkKim/CenterTrack-RideFlux | [
"36c0e4ddc608bddd203c12feb8a5f562c990eacb"
] | [
"src/lib/dataset/datasets/mot.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport pycocotools.coco as coco\nfrom pycocotools.cocoeval import COCOeval\nimport numpy as np\nimport json\nimport os\nfrom collections import defaultdict\nfrom ..generic_dataset import GenericDataset... | [
[
"numpy.random.randint"
]
] |
snji-khjuria/RelationClassificationFewShotModels | [
"a5047f44a57a81ab3281bf1290fa149a4c456486"
] | [
"models/metagan_queryattentive.py"
] | [
"#creating the metagan model\nimport torch\nimport torch.nn as nn\n\nimport sys\n\nsys.path.append('..')\nimport fewshot_re_kit\nimport torch\nfrom torch import autograd, optim, nn\nfrom torch.autograd import Variable\nfrom torch.nn import functional as F\n\n\n\n\n\n\n\nclass MetaGenerator(fewshot_re_kit.adversaria... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.BatchNorm1d",
"torch.tanh",
"torch.nn.ReLU",
"torch.cat",
"torch.pow"
]
] |
samysweb/dnnv | [
"58fb95b7300914d9da28eed86c39eca473b1aaef"
] | [
"dnnv/verifiers/marabou/__init__.py"
] | [
"import numpy as np\nimport tempfile\n\nfrom dnnv.verifiers.common.base import Parameter, Verifier\nfrom dnnv.verifiers.common.reductions import IOPolytopeReduction, HalfspacePolytope\nfrom dnnv.verifiers.common.results import SAT, UNSAT, UNKNOWN\nfrom functools import partial\n\nfrom .errors import MarabouError, M... | [
[
"numpy.load",
"numpy.save"
]
] |
gstoica27/ENAS-pytorch | [
"f8b9acbd101ab15c158066d2e4e9012ad11061a7"
] | [
"main.py"
] | [
"\"\"\"Entry point.\"\"\"\nimport os\n\nimport torch\n\nimport data\nimport config\nimport utils\nimport trainer\nimport re_trainer\n\nfrom data.loader import DataLoader\nfrom tacred_utils import scorer, constant, helper\nfrom tacred_utils.vocab import Vocab\nimport numpy as np\n\nlogger = utils.get_logger()\n\n\nd... | [
[
"torch.cuda.manual_seed",
"numpy.load",
"torch.manual_seed"
]
] |
bsavelev/medipy | [
"f0da3750a6979750d5f4c96aedc89ad5ae74545f"
] | [
"lib/medipy/gui/image/spectro_dialog.py"
] | [
"##########################################################################\n# MediPy - Copyright (C) Universite de Strasbourg\n# Distributed under the terms of the CeCILL-B license, as published by\n# the CEA-CNRS-INRIA. Refer to the LICENSE file or to\n# http://www.cecill.info/licences/Licence_CeCILL-B_V1-en.html... | [
[
"numpy.fromfile"
]
] |
Xingbaji/pytorch-template | [
"2246bf32a0605f2e8527f296274550a88b1e8fc9"
] | [
"model/attentionPDE_model.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\nfrom base import BaseModel\nimport pdb\nimport torch\nimport math\n\nclass AttentionPDEModel(nn.Module):\n def __init__(self,ndim,T,device_num = 0):\n super(AttentionPDEModel, self).__init__()\n # W_x = torch.randn(ndim, ndim, requires_grad=T... | [
[
"torch.ones_like",
"torch.ones",
"torch.load",
"torch.cos",
"torch.tensor",
"torch.diag",
"torch.sin",
"torch.diag_embed",
"torch.bmm",
"torch.cat",
"torch.matmul",
"torch.transpose"
]
] |
tianhm/rqalpha | [
"a2df4cb85fc86a20429c66a5a6d4f1a48520f173"
] | [
"rqalpha/data/data_source.py"
] | [
"import pytz\nimport six\n\nimport pandas as pd\nfrom ..instruments import Instrument\n\n\nclass LocalDataSource:\n DAILY = 'daily.bcolz'\n INSTRUMENTS = 'instruments.pk'\n DIVIDEND = 'dividend.bcolz'\n TRADING_DATES = 'trading_dates.bcolz'\n YIELD_CURVE = 'yield_curve.bcolz'\n\n YIELD_CURVE_TENOR... | [
[
"pandas.DataFrame"
]
] |
Giselle-Liu/PyTorch-Tutorial | [
"52b7a8c8fc8fa23b2fafb6d539b3b8aff13af45c"
] | [
"tutorial-contents/502_GPU.py"
] | [
"\"\"\"\nView more, visit my tutorial page: https://mofanpy.com/tutorials/\nMy Youtube Channel: https://www.youtube.com/user/MorvanZhou\n\nDependencies:\ntorch: 0.4\ntorchvision\n\"\"\"\nimport torch\nimport torch.nn as nn\nimport torch.utils.data as Data\nimport torchvision\n\n# torch.manual_seed(1)\n\nEPOCH = 1\n... | [
[
"torch.unsqueeze",
"torch.utils.data.DataLoader",
"torch.nn.MaxPool2d",
"torch.sum",
"torch.nn.Linear",
"torch.nn.CrossEntropyLoss",
"torch.nn.Conv2d",
"torch.max",
"torch.nn.ReLU"
]
] |
Crazy-Jack/SpatialExpGeneCluster | [
"9e57c308d1c577a936a2358d0641c65b8130034f"
] | [
"src/trainDEC.py"
] | [
"import argparse\nimport os, sys\n\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.backends.cudnn as cudnn\nimport torchvision\nfrom torchvision import transforms\nfrom PIL import Image\nimport numpy as np\nfrom tqdm import tqdm\nfrom sklearn.cluster import KMeans\nfrom scipy.stats i... | [
[
"torch.utils.data.DataLoader",
"numpy.save",
"torch.nn.MSELoss",
"torch.load",
"torch.no_grad",
"torch.cuda.device_count",
"sklearn.cluster.KMeans",
"numpy.where",
"scipy.stats.ortho_group.rvs",
"torch.cuda.is_available",
"numpy.random.rand",
"numpy.array",
"tor... |
BeyondTheProof/metrics | [
"8af688daff819a95f4cb3d757ffc919c86072ee9"
] | [
"tests/retrieval/inputs.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.rand",
"torch.randint"
]
] |
mkolod/Vitis-Tutorials | [
"33d6cf9686398ef1179778dc0da163291c68b465"
] | [
"Machine_Learning/Design_Tutorials/03-using_densenetx/files/datadownload.py"
] | [
"'''\n Copyright 2020 Xilinx Inc.\n\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n\n http://www.apache.org/licenses/LICENSE-2.0\n\n Unless required by applicable law or agreed to i... | [
[
"tensorflow.keras.datasets.cifar10.load_data",
"tensorflow.keras.utils.to_categorical"
]
] |
srkc95/kaggle-landmark-2021-1st-place | [
"034a7d8665bb4696981698348c9370f2d4e61e35"
] | [
"configs/cfg_ch_hybrid_swin224_b5_s3x.py"
] | [
"from default_config import basic_cfg\nimport albumentations as A\nimport os\nimport pandas as pd\nimport cv2\n\ncfg = basic_cfg\ncfg.debug = True\n\n# paths\ncfg.name = os.path.basename(__file__).split(\".\")[0]\ncfg.data_dir = \"/raid/landmark-recognition-2019/\"\n\ncfg.train\ncfg.data_folder = cfg.data_dir + \"t... | [
[
"pandas.read_csv"
]
] |
Artur-UF/MetCompA | [
"1198f861f4e5190f7435314bf476c594471e79fa"
] | [
"Ark.MetCompA/Aula-py14/atv_ajuste.py"
] | [
"# Ajuste de funções\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef aj_lin(xi, yi):\n '''\n Realiza o ajuste linear de pontos em uma reta de ajuste no formato \"y = ax + b\"\n :param xi: coordenadas x dos pontos\n :param yi: coordenadas y dos pontos\n :return: coeficiente angular \"a\"... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"numpy.loadtxt",
"numpy.linspace",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.scatter"
]
] |
vophihungvn/h1st | [
"d421995bb0b8de6a5a76788261efef5b26bc7c12"
] | [
"examples/AutoCyber/streamlit_app.py"
] | [
"import streamlit as st\nimport time\nimport numpy as np\nimport pandas as pd\n\nfrom aegis_datagen import build_constant_val_msg_stream\n\n@st.cache\ndef get_data():\n AWS_BUCKET_URL = \"s3://h1st-tutorial-autocyber/attack-samples\"\n df = pd.read_parquet(AWS_BUCKET_URL + \"/20181114_Driver2_Trip1-0.parquet\... | [
[
"matplotlib.pyplot.legend",
"pandas.Series",
"pandas.read_parquet",
"matplotlib.pyplot.figure",
"numpy.argmax",
"pandas.DataFrame.from_records",
"pandas.concat",
"matplotlib.pyplot.plot"
]
] |
srijan-deepsource/dask | [
"0673d9084e02f985f3fdf5ba6ede80e8de5ac15c"
] | [
"dask/array/core.py"
] | [
"import math\nimport operator\nimport os\nimport pickle\nimport re\nimport sys\nimport traceback\nimport uuid\nimport warnings\nfrom bisect import bisect\nfrom collections.abc import Iterable, Iterator, Mapping\nfrom functools import partial, wraps, reduce\nfrom itertools import product, zip_longest\nfrom numbers i... | [
[
"numpy.ones",
"numpy.empty",
"numpy.searchsorted",
"numpy.dtype",
"numpy.asarray",
"numpy.median",
"numpy.errstate",
"numpy.asanyarray",
"numpy.can_cast",
"numpy.prod",
"numpy.max",
"numpy.isnan",
"numpy.array",
"numpy.isscalar"
]
] |
cophus/PhaseContrastTomographySolver | [
"e75cfd5af5cc0fdf363d3754c22d91f4c2dec8e8"
] | [
"transform.py"
] | [
"\"\"\"\nTransform functions for Tomography in Numpy, Scipy, Torch, and Skimage\nEstimates affine transform between measured image and predicted image\nhttps://github.com/scikit-image/scikit-image\n\nDavid Ren david.ren@berkeley.edu\n\nDec 28, 2020\n\"\"\"\n\nimport numpy as np\nimport torch\nfrom skimage.regi... | [
[
"numpy.zeros_like",
"numpy.zeros",
"torch.tensor",
"numpy.cos",
"numpy.arange",
"numpy.array",
"numpy.sin",
"numpy.concatenate"
]
] |
mnassar/deep-learning | [
"b69617993b2e67cfd5635460d1a295e91b6c66d6"
] | [
"tv-script-generation/problem_unittests.py"
] | [
"import numpy as np\nimport tensorflow as tf\nfrom tensorflow.contrib import rnn\n\n\ndef _print_success_message():\n print('Tests Passed')\n\n\ndef test_create_lookup_tables(create_lookup_tables):\n with tf.Graph().as_default():\n test_text = '''\n Moe_Szyslak Moe's Tavern Where the elite meet ... | [
[
"tensorflow.placeholder",
"tensorflow.contrib.rnn.BasicLSTMCell",
"tensorflow.Graph",
"numpy.array_equal",
"numpy.array"
]
] |
otosense/oplot | [
"5b4b4b96ebfa5486501c02e7051d1c11b1c3b86c"
] | [
"oplot/multiplots.py"
] | [
"\"\"\"Drawing multiple plots in a single figure\"\"\"\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom matplotlib import gridspec\n\n\ndef make_space_above(axes, topmargin=1):\n \"\"\" increase figure size to make topmargin (in inches) space for\n titles, without changing the axes sizes\"\"\"... | [
[
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots"
]
] |
ICASSP-2020-Robustness-Tutorial/Robust-Signal-Processing-Toolbox-Python | [
"293f4281fdbd475549aa42eae9fe615976af27a0"
] | [
"robustsp/Regression/enetpath.py"
] | [
"'''\n enethpath computes the elastic net (EN) regularization path (over grid \n of penalty parameter values). Uses pathwise CCD algorithm. \n INPUT: \n y : Numeric 1darray of size N (output, respones)\n X : Nnumeric 2darray of size N x p. Each row represents one \n observation, and each colum... | [
[
"numpy.vstack",
"numpy.zeros",
"numpy.conj",
"numpy.abs",
"numpy.asarray",
"numpy.repeat",
"numpy.arange",
"numpy.log",
"numpy.linalg.norm",
"numpy.mean"
]
] |
neuropoly/ivadomed | [
"e5f14c02a6c73d9360eee130ff39f0a364e0a697"
] | [
"ivadomed/uncertainty.py"
] | [
"import nibabel as nib\nfrom tqdm import tqdm\nfrom scipy.ndimage import label, generate_binary_structure\nfrom pathlib import Path\nimport json\nimport numpy as np\nfrom ivadomed import postprocessing as imed_postpro\nfrom typing import List\n\n\ndef run_uncertainty(image_folder):\n \"\"\"Compute uncertainty fr... | [
[
"numpy.logical_or",
"numpy.sum",
"numpy.zeros",
"scipy.ndimage.label",
"numpy.logical_and",
"numpy.argmax",
"numpy.expand_dims",
"numpy.array",
"numpy.std",
"numpy.where",
"numpy.unique",
"numpy.mean",
"scipy.ndimage.generate_binary_structure"
]
] |
AghilasSini/AT-Annotator | [
"532c6de0fe143e2b6ace0d382cc79f1f0f2cf941"
] | [
"cnn-for-sentence-classification/train_keras.py"
] | [
"import numpy as np\nimport codecs\nimport os\nimport random\n\nfrom keras import backend as K\nfrom keras.models import Model\nfrom keras.layers.embeddings import Embedding\nfrom keras.layers import Input, Dense, Lambda, Permute, Dropout\nfrom keras.layers import Conv2D, MaxPooling1D\n\ndef load_data(fpath, label)... | [
[
"numpy.array",
"numpy.asarray",
"numpy.zeros"
]
] |
ostap-viniavskyi/acme | [
"8fbae90217557a35e1d773aa63ab80890e799765"
] | [
"acme/agents/tf/svg0_prior/networks.py"
] | [
"# python3\n# Copyright 2018 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... | [
[
"numpy.prod"
]
] |
chappers/multiagent-particle-envs | [
"5c56a0cc4241fb2e5a6f4dc62bf1735862d6e30c"
] | [
"examples/ppo_agent.py"
] | [
"\"\"\"\nExample using this environment with stable_baseline library\n\nfrom stable_baselines.common.vec_env import DummyVecEnv\nenv = DummyVecEnv([lambda: env])\n\nmodel = PPO2(MlpPolicy, env, verbose=1)\nmodel.learn(total_timesteps=25000)\nmodel.save(\"ppo2_cartpole\")\n\n# Enjoy trained agent\nmodel = PPO2.load(... | [
[
"numpy.zeros_like",
"numpy.asarray",
"numpy.zeros",
"numpy.copy"
]
] |
YerongLi2/LTVRR | [
"ec3be058da9c4f2f68d7c4dfb759209748732b93"
] | [
"lib/roi_data/fast_rcnn_rel.py"
] | [
"# Copyright (c) 2017-present, Facebook, Inc.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicabl... | [
[
"numpy.append",
"numpy.zeros",
"numpy.concatenate",
"numpy.random.choice",
"numpy.hstack",
"numpy.array",
"numpy.where",
"numpy.minimum"
]
] |
Cryaaa/Master-Thesis-Repository | [
"a887fd9dd95c32ce9275d14ec6583bd19cd8bc15"
] | [
"Code/Generating video data/embryo serosa kmeans finsterwalde making the pictures.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Tue Sep 28 15:24:40 2021\n\n@author: ryans\n\"\"\"\nimport tribolium_clustering as tc\nimport pyclesperanto_prototype as cle\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport umap\nimport hdbscan\nimport napari\n\n\ndef nice_screenshots_of... | [
[
"numpy.load",
"pandas.DataFrame"
]
] |
jmaberk/RGPUCB | [
"a14cc524fa10bc90166ba0955c611a1c46d0f779"
] | [
"RGP-UCB/prada_bayes_opt/bayesian_optimization_function.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue Mar 29 11:49:58 2016\r\n\r\n\"\"\"\r\n\r\nfrom __future__ import division\r\nimport numpy as np\r\n#from sklearn.gaussian_process import GaussianProcess\r\nfrom scipy.optimize import minimize\r\nfrom prada_bayes_opt.acquisition_functions import AcquisitionFunctio... | [
[
"numpy.vstack",
"numpy.ones",
"numpy.random.uniform",
"numpy.append",
"numpy.zeros",
"numpy.reshape",
"numpy.random.seed",
"numpy.asarray",
"numpy.hstack",
"numpy.std",
"numpy.mean"
]
] |
zoeimogen/AoC2019 | [
"44ffc08a38cb07273d7c4fd49200fb7912d4a1cb"
] | [
"tests/day09_test.py"
] | [
"#!/usr/bin/python3\n'''Advent of Code 2019 Day 5 tests'''\nimport unittest\nimport os\nimport sys\nimport numpy\nsys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))\nfrom aoc2019 import intcode # pylint: disable=wrong-import-position\n\nclass TestUM(unittest.TestCase):\n '''Tests ... | [
[
"numpy.zeros"
]
] |
timsque/deep-histopath | [
"a91619cc5b20c5a760d72d89124e558306ef5fc3"
] | [
"resnet.py"
] | [
"\"\"\"Custom ResNet model with pre-activation residual blocks.\n\nHe K, Zhang X, Ren S, Sun J. Identity Mappings in Deep Residual\nNetworks. arXiv.org. 2016.\n\nAuthor: Mike Dusenberry\n\"\"\"\nimport tensorflow as tf\n\n\ndef res_block(xin, dbottle, dout, k, stride):\n \"\"\"A residual block.\n\n This implement... | [
[
"tensorflow.keras.layers.AvgPool2D",
"tensorflow.keras.layers.Flatten",
"tensorflow.shape",
"tensorflow.keras.Model",
"tensorflow.keras.layers.Activation",
"tensorflow.variable_scope",
"tensorflow.keras.initializers.VarianceScaling",
"tensorflow.keras.layers.BatchNormalization",
... |
hqucms/onnxruntime | [
"6e4e76414639f50836a64546603c8957227857b0"
] | [
"docs/python/examples/plot_backend.py"
] | [
"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License.\n\n\"\"\"\n\n.. _l-example-backend-api:\n\nONNX Runtime Backend for ONNX\n=============================\n\n*ONNX Runtime* extends the \n`onnx backend API <https://github.com/onnx/onnx/blob/master/docs/ImplementingAnOnnxB... | [
[
"numpy.array"
]
] |
qdpham/machine-learning-engineering-for-production-public | [
"e02961fa72cd5d009bfb699c2e76594b9dbad1bf"
] | [
"course4/week3-ungraded-labs/C4_W3_Lab_4_Github_Actions/app/main.py"
] | [
"# added by QDP to run the test using the CI/CD pipeline\nimport pickle\nimport numpy as np\nfrom typing import List\nfrom fastapi import FastAPI\nfrom pydantic import BaseModel, conlist\n\n\n\napp = FastAPI(title=\"Predicting Wine Class with batching\")\n\n# Open classifier in global scope\nwith open(\"models/wine... | [
[
"numpy.array"
]
] |
world2vec/coref | [
"a314773215f7f59e3dc1cb14034460a23734b291"
] | [
"coref_ops.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nimport os\n\nimport tensorflow as tf\nfrom tensorflow.python import pywrap_tensorflow\n\ncur_dir = os.path.dirname(os.path.realpath(__file__))\n\ncoref_op_library = tf.load_op_library(os.path.join(cur_di... | [
[
"tensorflow.NotDifferentiable"
]
] |
graphcore/poprithms | [
"9975a6a343891e3c5f8968a9507261c1185029ed"
] | [
"poprithms/tests/regression/schedule/shift/summarize.py"
] | [
"# Copyright (c) 2020 Graphcore Ltd. All rights reserved.\nimport matplotlib.pyplot as mpl\nimport matplotlib.gridspec as gridspec\nimport numpy as np\nimport sys\nimport os\n\n\ndef run(logsDir, plotsDir=\".\"):\n \"\"\"\n logsDir : \n -- where to read all log files from (.txt and .log extensions). \n ... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.gca",
"matplotlib.pyplot.title",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.plot",
"matplotlib.gridspec.GridSpec",
"matplotlib.pyplot.xlabel"
]
] |
IanYeung/ReCp | [
"1a7ace0e1ca3c262e24a222f3f0ab0d5674e9410"
] | [
"basicsr/archs/iconvsr_arch.py"
] | [
"import torch\nfrom torch import nn as nn\nfrom torch.nn import functional as F\n\nfrom basicsr.utils.registry import ARCH_REGISTRY\nfrom .spynet_arch import SpyNet\nfrom .basicvsr_arch import ConvResBlock, PSUpsample\nfrom .edvr_arch import PredeblurModule, PCDAlignment, TSAFusion\nfrom .arch_util import ResidualB... | [
[
"torch.stack",
"torch.randn",
"torch.nn.functional.pad",
"torch.zeros_like",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.cat",
"torch.nn.LeakyReLU"
]
] |
JulianoLagana/MT3 | [
"c1270e1de5b8d68eab50a797d16061310fa95d97"
] | [
"src/modules/position_encoder.py"
] | [
"import torch\nfrom torch import nn, Tensor\nimport math\n\nclass LearnedPositionEncoder(nn.Module):\n \"\"\"\n Learned Position Encoder. Takes tensor of positional indicies and converts to learned embeddings \n \"\"\"\n\n def __init__(self, n_timesteps, d_model):\n super().__init__()\n ... | [
[
"torch.arange",
"torch.nn.init.uniform_",
"torch.nn.Embedding"
]
] |
bfabiandev/atom3d | [
"b2499ff743be2e851c286cabf64696682abffa44"
] | [
"atom3d/util/graph.py"
] | [
"import numpy as np\nimport scipy.spatial as ss\nimport torch\n\nimport atom3d.util.formats as fo\n\n# PDB atom names -- these include co-crystallized metals\nprot_atoms = ['C', 'H', 'O', 'N', 'S', 'P', 'ZN', 'NA', 'FE', 'CA', 'MN', 'NI', 'CO', 'MG', 'CU', 'CL', 'SE', 'F']\n# RDKit molecule atom names\nmol_atoms = ... | [
[
"torch.FloatTensor",
"numpy.linalg.norm",
"scipy.spatial.KDTree",
"numpy.argwhere",
"torch.zeros",
"torch.LongTensor",
"torch.cat"
]
] |
Darel13712/rs_metrics | [
"bf1c2f6e02537508255bbf675c48a14f512e51de"
] | [
"tests/test_metrics.py"
] | [
"import numpy as np\nimport pandas as pd\nimport pytest\n\nfrom rs_metrics.metrics import _ndcg_score\nfrom rs_metrics import *\nfrom rs_metrics.statistics import item_pop\n\n\ndef test_dcg_score_1():\n assert _ndcg_score([1], [1], 1) == 1\n\n\ndef test_dcg_score_0():\n assert _ndcg_score([1], [0], 1) == 0\n\... | [
[
"numpy.log2",
"pandas.DataFrame"
]
] |
aytackanaci/deep-vehicle-reid | [
"9f951288a38f8b295b5c77cc6c9b26f0632ecea3"
] | [
"train_imgreid_dpfl_large_batch.py"
] | [
"from __future__ import print_function\nfrom __future__ import division\n\nimport os\nimport sys\nimport time\nimport datetime\nimport os.path as osp\nimport numpy as np\n\nimport torch\nimport torch.nn as nn\nimport torch.backends.cudnn as cudnn\nfrom torch.nn import functional as F\nfrom torch.optim import lr_sch... | [
[
"torch.load",
"torch.nn.functional.softmax",
"torch.no_grad",
"numpy.asarray",
"torch.cuda.is_available",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.nn.DataParallel",
"torch.cat",
"torch.pow"
]
] |
dhruv9vats/stingray | [
"e952762ebc098de42d8decf2d0df34f9e9b0c200"
] | [
"stingray/crossspectrum.py"
] | [
"import copy\nimport warnings\nfrom collections.abc import Iterable, Iterator\n\nimport numpy as np\nimport scipy\nimport scipy.optimize\nimport scipy.stats\n\nfrom stingray.exceptions import StingrayError\nfrom stingray.gti import bin_intervals_from_gtis, check_gtis, cross_two_gtis\nfrom stingray.largememory impor... | [
[
"numpy.sum",
"scipy.special.factorial",
"numpy.diff",
"numpy.any",
"numpy.isclose",
"numpy.size",
"scipy.special.gamma",
"numpy.log",
"matplotlib.pyplot.ylabel",
"numpy.isfinite",
"numpy.vstack",
"numpy.allclose",
"matplotlib.pyplot.figure",
"matplotlib.pypl... |
SanjibSarkarU/EDRC | [
"c2408fad8b007b4709ee91caf173f98612afadb1"
] | [
"iver.py"
] | [
"import datetime\nimport re\nimport threading\nimport time\nimport tkinter as tk\nfrom collections import deque\nfrom queue import Queue\nfrom time import monotonic\n\nimport pandas as pd\nimport rasterio\nimport serial\nfrom geographiclib.geodesic import Geodesic\nfrom matplotlib import pyplot as plt, animation\nf... | [
[
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg",
"pandas.DataFrame",
"matplotlib.pyplot.Figure"
]
] |
jiye-ML/CoCosNet | [
"c4b3f44393462c8353c6c6952d7b05496298df1c"
] | [
"models/networks/base_network.py"
] | [
"\"\"\"\nCopyright (C) 2019 NVIDIA Corporation. All rights reserved.\nLicensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).\n\"\"\"\n\nimport torch.nn as nn\nfrom torch.nn import init\n\n\nclass BaseNetwork(nn.Module):\n def __init__(self):\n super(Base... | [
[
"torch.nn.init.kaiming_normal_",
"torch.nn.init.xavier_uniform_",
"torch.nn.init.constant_",
"torch.nn.init.xavier_normal_",
"torch.nn.init.normal_",
"torch.nn.init.orthogonal_"
]
] |
am-ivanov/dace | [
"4d65e0951c112160fe783766404a806b6043b521"
] | [
"tests/state_transition_array_test.py"
] | [
"import dace as dp\nimport numpy as np\n\nsdfg = dp.SDFG('sta_test')\ns0 = sdfg.add_state()\ns1 = sdfg.add_state()\ns2 = sdfg.add_state()\n\n# Arrays\ninp = s0.add_array('inp', [1], dp.float32)\nA = s0.add_array('A', [1], dp.float32)\nt = s0.add_tasklet('seta', {'a'}, {'b'}, 'b = a')\ns0.add_edge(inp, None, t, 'a',... | [
[
"numpy.ndarray"
]
] |
sixin-zh/kymatio_wph | [
"237c0d2009766cf83b2145420a14d3c6e90dc983"
] | [
"kymatio/phaseexp1d/pyscatwave/scatwave/scattering1d/examples/real_signal.py"
] | [
"import torch\nfrom torch.autograd import Variable\nfrom scatwave import Scattering1D\nfrom scatwave import fetch_fsdd\nimport matplotlib.pyplot as plt\nfrom scipy.io import wavfile\nimport numpy as np\nimport os\n\n\ndef loadfile(path_file):\n sr, x = wavfile.read(path_file)\n x = np.asarray(x, dtype='float'... | [
[
"numpy.argmin",
"numpy.abs",
"numpy.asarray",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show",
"torch.from_numpy",
"scipy.io.wavfile.read",
"torch.LongTensor"
]
] |
Fdl1989/TimingofOneShotInterventions | [
"cfd7a5238c06baf77ee465b22392367197969a27"
] | [
"Fig4.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Feb 29 15:19:36 2020\n@author: Francesco Di Lauro\n@mail: F.Di-Lauro@sussex.ac.uk\nCopyright 2020 Francesco Di Lauro. All Rights Reserved.\nSee LICENSE file for details\n\"\"\"\nfrom Eulerclasssir import SIR_model\nimport numpy as np\nimport m... | [
[
"numpy.sum",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"matplotlib.rc",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.close",
"numpy.linspace",
"numpy.loadtxt"
]
] |
shelleyHLX/bilm_EMLo | [
"7e3f94c80716665a16bfbc2efc2b8f2f32aad553"
] | [
"usage_token.py"
] | [
"'''\nELMo usage example with pre-computed and cached context independent\ntoken representations\n\nBelow, we show usage for SQuAD where each input example consists of both\na question and a paragraph of context.\n'''\n\nimport tensorflow as tf\nimport os\nfrom bilm_model import TokenBatcher, BidirectionalLanguageM... | [
[
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.variable_scope",
"tensorflow.Session",
"tensorflow.reset_default_graph"
]
] |
laurent90git/scipy | [
"bc111c2f56e854b1bf95b208078da525d267ceff"
] | [
"scipy/integrate/_ivp/tests/test_ivp.py"
] | [
"from itertools import product\nfrom numpy.testing import (assert_, assert_allclose,\n assert_equal, assert_no_warnings, suppress_warnings)\nimport pytest\nfrom pytest import raises as assert_raises\nimport numpy as np\nfrom scipy.optimize._numdiff import group_columns\nfrom scipy.integrat... | [
[
"numpy.ones",
"numpy.diff",
"numpy.testing.assert_equal",
"numpy.random.seed",
"numpy.asarray",
"numpy.ones_like",
"numpy.testing.assert_no_warnings",
"scipy.integrate._ivp.common.num_jac",
"scipy.integrate.OdeSolution",
"numpy.vstack",
"scipy.sparse.csc_matrix",
"n... |
mseeger/autogluon-1 | [
"e8d82363ce07fd8e3087bcdd2d71c6f6bd8fd7a0"
] | [
"core/tests/unittests/bayesopt/gpmxnet/test_warping.py"
] | [
"import numpy as np\nimport mxnet as mx\n\nfrom autogluon.core.searcher import OneDimensionalWarping, \\\n Warping, WarpedKernel\nfrom autogluon.core.searcher.bayesopt.gpmxnet.constants import DATA_TYPE, \\\n NUMERICAL_JITTER\nfrom autogluon.core.searcher import Matern52\nfrom autogluon.core.searcher import \... | [
[
"numpy.testing.assert_almost_equal",
"numpy.ones",
"numpy.sqrt",
"numpy.random.uniform",
"numpy.random.seed",
"numpy.abs",
"numpy.hstack",
"numpy.log",
"numpy.array"
]
] |
labscript-suite-bitbucket-archive/shjohnst-runviewer--forked-from--labscript_suite-runviewer | [
"78d7be530bbfd005744b3a6b1cd3f1beb5fd7fe9"
] | [
"__main__.py"
] | [
"#####################################################################\n# #\n# /main.pyw #\n# #\n# Copyright 2014, Monash Univer... | [
[
"scipy.interpolate.interp1d",
"numpy.abs",
"numpy.float",
"numpy.array",
"numpy.sin",
"numpy.where",
"numpy.linspace",
"numpy.float64"
]
] |
maniospas/pygrank | [
"a92f6bb6d13553dd960f2e6bda4c041a8027a9d1"
] | [
"pygrank/measures/unsupervised.py"
] | [
"import warnings\nimport numpy as np\nfrom pygrank.measures.utils import Measure\nfrom pygrank.core.signals import to_signal\nfrom pygrank.core import backend, GraphSignalGraph, GraphSignalData, BackendPrimitive\n\n\nclass Unsupervised(Measure):\n pass\n\n\nclass Conductance(Unsupervised):\n \"\"\" Graph cond... | [
[
"numpy.random.seed",
"numpy.random.choice"
]
] |
SummaLabs/DLS | [
"2adba47430b456ad0f324e4c8883a896a23b3fbf"
] | [
"data-test/test_data_serialization/step2_h5py_test_perf/run02_s1_write_image_blob.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n__author__ = 'ar'\n\nimport skimage.io as skio\nimport numpy as np\nimport h5py\nimport time\n\nfrom run00_common import ImageDirParser\n\n############################\ndef buidImageDataset(imageDirParser=None, datasetName='test-dataset.h5', numberOfSamples=1000, isRawBl... | [
[
"numpy.array"
]
] |
Heng-Z/mwr | [
"28e42a3a64f46dc627333b2c6ae4b317803648ba"
] | [
"training/data_sequence.py"
] | [
"from tensorflow.keras.utils import Sequence\nimport numpy as np\nimport mrcfile\nimport os\n# Here, `x_set` is list of path to the images\n# and `y_set` are the associated classes.\n\nclass dataSequence(Sequence):\n\n def __init__(self, x_set, y_set, batch_size):\n self.x, self.y = x_set, y_set\n ... | [
[
"numpy.random.shuffle"
]
] |
dwkim565/laygo2 | [
"fea1263638fa5641ad27f2000d7562cdf910c67f"
] | [
"examples/demo/7_thshin_test.py"
] | [
"#!/usr/bin/python\n########################################################################################################################\n#\n# Copyright (c) 2014, Regents of the University of California\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without modification... | [
[
"numpy.array"
]
] |
jihyunbak/spyglass | [
"780fe2c101db60d42a1b73ad8fd729db42620ba6"
] | [
"src/nwb_datajoint/spikesorting/spikesorting_artifact.py"
] | [
"import warnings\nfrom functools import reduce\n\nimport datajoint as dj\nimport numpy as np\nimport scipy.stats as stats\nimport spikeinterface as si\nfrom spikeinterface.core.segmentutils import AppendSegmentRecording\n\nfrom ..common.common_interval import IntervalList\nfrom ..common.nwb_helper_fn import get_val... | [
[
"scipy.stats.zscore",
"numpy.sum",
"numpy.logical_or",
"numpy.argwhere",
"numpy.abs",
"numpy.asarray",
"numpy.copy",
"numpy.all",
"numpy.sort"
]
] |
taylorguo/model-optimization | [
"ddd9a67c7599214a4061ae04b28387171d29d96a"
] | [
"CPD/CPDtorch/quant/quant_function.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport numpy as np\nfrom torch.utils.cpp_extension import load\nimport os\ncurrent_path = os.path.dirname(os.path.realpath(__file__))\n\nif torch.cuda.is_available():\n quant_cuda = load(\n name='quant_cuda',\n sources=[\n ... | [
[
"torch.zeros",
"torch.cuda.is_available"
]
] |
JiachenMao/TransfornerPrune | [
"084956e00807af5ce3f363d964f327405862e51b"
] | [
"tensor2tensor/models/resnet.py"
] | [
"# coding=utf-8\n# Copyright 2019 The Tensor2Tensor Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requir... | [
[
"tensorflow.pad",
"tensorflow.summary.histogram",
"tensorflow.variance_scaling_initializer",
"tensorflow.reshape",
"tensorflow.zeros_initializer",
"tensorflow.to_float",
"tensorflow.reduce_mean",
"tensorflow.ones_initializer",
"tensorflow.squeeze",
"tensorflow.identity",
... |
IvanaEscobar/oceanAcouPy | [
"9ea11792dfe1cc0ba7004d23521fd222b4e949eb"
] | [
"oceanAcouPy/soundSpeed.py"
] | [
"# EE348N: Ocean Acoustics \n# Sound speed profiles used in class\n\nfrom numpy import exp, sin\n\n### FUNCTIONS ###\ndef cSTD (t,s,z, lat=0, eqn='mackenzie81'):\n# Inputs:\n# t : tempurature [degC]\n# s : salinity [ppt]\n# z : column depth [m]\n# lat : latitude [deg]\n# eqn : mackenzie81, leroy08\n# Retu... | [
[
"numpy.exp"
]
] |
omyllymaki/shifting-peaks | [
"0dd67662daac29ce1c2db257553c3355202a46f1"
] | [
"solvers/tests/test_grid_solver.py"
] | [
"import itertools\n\nimport numpy as np\n\nfrom solvers.grid_solver import GridSolver\nfrom solvers.math import interpolate_signal, ls_fit\nfrom solvers.tests.base_test_case import BaseTestCase\nfrom solvers.tests.correction_models import linear_correction\n\n\nclass TestGridSolver(BaseTestCase):\n offset_candid... | [
[
"numpy.arange"
]
] |
imaginary-person/pipeline_experiments | [
"32d20f1b9a4192e75ed6ba709c9acd2e0cf23e06"
] | [
"BERT/bert_local_pipeline.py"
] | [
"import argparse\nimport math\nimport sys\nimport time\nimport os\nimport socket\nimport statistics\n\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\n\nfrom model import MLMTask, MLMTask2, MLMTaskEmbedding, MLMTaskEncoder, MLMTaskHead\nfrom cuda_local_pipeline import LocalSequential, ... | [
[
"torch.ones",
"torch.load",
"torch.manual_seed",
"torch.save",
"torch.tensor",
"torch.nn.CrossEntropyLoss",
"torch.cuda.Event",
"torch.randperm",
"torch.zeros"
]
] |
dchenam/AnimeGAN | [
"15707a99dde000a6d7f283f4f82d5176b8313e0a"
] | [
"logger.py"
] | [
"# Code referenced from https://gist.github.com/gyglim/1f8dfb1b5c82627ae3efcfbbadb9f514\nimport tensorflow as tf\nimport numpy as np\nimport scipy.misc\nimport logging\n\ntry:\n from StringIO import StringIO # Python 2.7\nexcept ImportError:\n from io import BytesIO # Python 3.5+\n\n\nclass Logger(object):\... | [
[
"numpy.sum",
"tensorflow.Summary.Value",
"numpy.histogram",
"numpy.max",
"tensorflow.HistogramProto",
"numpy.min",
"numpy.prod",
"tensorflow.summary.FileWriter",
"tensorflow.Summary"
]
] |
Hardly-Human/Instance-Segmentation-of-Images | [
"45b048a2eb7fa31d5007f3fcd70b03fcb57abad4"
] | [
"app.py"
] | [
"import streamlit as st\nfrom PIL import Image\nimport matplotlib.pyplot as plt\nfrom gluoncv import model_zoo, data, utils\n\n\n@st.cache\ndef load_image(image_file):\n img = Image.open(image_file)\n return img\n\n@st.cache(allow_output_mutation=True)\ndef load_model(model_name):\n\tmodel = model_zoo.get_mod... | [
[
"matplotlib.pyplot.figure",
"matplotlib.pyplot.show"
]
] |
luh0907/nn_breaking_detection | [
"6e810a5296bea3c6ef975b4e62caa2d94e992b81"
] | [
"density_estimation.py"
] | [
"# Copyright (C) 2017, Nicholas Carlini <nicholas@carlini.com>\n# All rights reserved.\n\nimport sys\nimport time\nimport tensorflow as tf\nimport numpy as np\nimport random\n\nfrom setup_cifar import CIFARModel, CIFAR\nfrom setup_mnist import MNISTModel, MNIST\n\nsys.path.append(\"../..\")\nfrom nn_robust_attacks.... | [
[
"numpy.ones",
"numpy.sum",
"tensorflow.reduce_max",
"tensorflow.reshape",
"numpy.arctanh",
"numpy.copy",
"numpy.log",
"tensorflow.reduce_sum",
"tensorflow.constant",
"numpy.linspace",
"numpy.mean",
"tensorflow.variables_initializer",
"numpy.zeros",
"tensorfl... |
coldfix/probnum | [
"9b93d822c8d6501f9a12a783da84867ea54e6f6c"
] | [
"src/probnum/prob/distributions/dirac.py"
] | [
"\"\"\"\nDirac delta distribution.\n\"\"\"\nimport operator\n\nimport numpy as np\n\nfrom probnum.prob.distributions.distribution import Distribution\n\n\nclass Dirac(Distribution):\n \"\"\"\n The Dirac delta distribution.\n\n This distribution models a point mass and can be useful to represent\n number... | [
[
"numpy.any",
"numpy.tile",
"numpy.isscalar",
"numpy.repeat"
]
] |
SJTU-Det/R3Det | [
"3e092fa65dee2b9f7722b0985b3791811a1de5ae"
] | [
"libs/configs/DOTA1.0/r3det_plusplus/cfgs_res50_dota_r3det_plusplus_v8.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import division, print_function, absolute_import\nimport os\nimport tensorflow as tf\nimport math\n\n\"\"\"\nv3 + weight\n\nThis is your result for task 1:\n\n mAP: 0.694278910759864\n ap of each class:\n plane:0.88866159706304,\n baseball-diamond:0.786035227623... | [
[
"tensorflow.random_normal_initializer",
"tensorflow.constant_initializer"
]
] |
bbrzycki/setigen | [
"3106c32a629c76c71768ea02b7661474e1cf7ff6"
] | [
"setigen/distributions.py"
] | [
"import numpy as np\n\nfwhm_m = 2 * np.sqrt(2 * np.log(2))\n\ndef fwhm(sigma):\n \"\"\"\n Get full width at half maximum (FWHM) for a provided sigma / \n standard deviation, assuming a Gaussian distribution.\n \"\"\"\n return fwhm_m * sigma\n \n\ndef gaussian(x_mean, x_std, shape):\n return np.... | [
[
"numpy.random.normal",
"numpy.random.chisquare",
"numpy.log"
]
] |
mdblackledge/SimpleITK-Image-Symmetry | [
"b18343394852a1514bf45ddb9078e27c4d6f6718"
] | [
"image_symmetry.py"
] | [
"import SimpleITK as sitk\nimport numpy as np\nfrom scipy.optimize import minimize\nfrom pywt import wavedecn\n\nclass ImageSymmetry(object):\n\n def plane_normalised(self, plane):\n if not type(plane) is np.ndarray:\n plane = np.array(plane)\n if not np.abs(np.sum(plane[0:-1]**2) - 1.0)... | [
[
"numpy.sum",
"matplotlib.pyplot.legend",
"numpy.arcsin",
"numpy.sin",
"numpy.einsum",
"matplotlib.pyplot.figure",
"scipy.misc.face",
"scipy.optimize.minimize",
"numpy.cos",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylim",
"numpy.arra... |
shbe-aau/multi-pose-estimation | [
"22cea6cd09684fe655fb2214bc14856f589048e1"
] | [
"multi-pose/utils/sundermeyer/pysixd/view_sampler.py"
] | [
"# Author: Tomas Hodan (hodantom@cmp.felk.cvut.cz)\n# Center for Machine Perception, Czech Technical University in Prague\n\n# Samples views from a sphere.\n\nimport math\nimport numpy as np\n#import transform\nfrom utils.sundermeyer.pysixd import transform\n\ndef calc_2d_bbox(xs, ys, im_size):\n bbTL = (max(xs.... | [
[
"numpy.zeros",
"numpy.cross",
"numpy.argmax",
"numpy.count_nonzero",
"numpy.arange",
"numpy.array",
"numpy.linalg.norm"
]
] |
burcgokden/SDPA-Transformer-Wrapper | [
"81371d1bd7d9ae26a70a549740539242f1a76199"
] | [
"nmt_data_prep.py"
] | [
"\nimport logging\n\nimport tensorflow_datasets as tfds\nimport tensorflow as tf\nimport tensorflow_text as text\n\nlogging.getLogger('tensorflow').setLevel(logging.ERROR)\n\n\nclass src_tgt_data_prep:\n '''\n Prepares data for encoder-decoder architecture for machine translation task\n default inputs are ... | [
[
"tensorflow.saved_model.load",
"tensorflow.keras.utils.get_file",
"tensorflow.size"
]
] |
rostyboost/scipy | [
"2f5aa264724099c03772ed784e7a947d2bea8398"
] | [
"scipy/sparse/linalg/tests/test_matfuncs.py"
] | [
"#\n# Created by: Pearu Peterson, March 2002\n#\n\"\"\" Test functions for scipy.linalg.matfuncs module\n\n\"\"\"\nfrom __future__ import division, print_function, absolute_import\n\nimport math\n\nimport numpy as np\nfrom numpy import array, eye, exp, random\nfrom numpy.linalg import matrix_power\nfrom numpy.testi... | [
[
"scipy.special.factorial",
"numpy.spacing",
"numpy.linalg.matrix_power",
"numpy.diag",
"numpy.random.seed",
"numpy.allclose",
"scipy.sparse.csc_matrix",
"scipy._lib._numpy_compat.suppress_warnings",
"numpy.random.rand",
"scipy.sparse.linalg.matfuncs.ProductOperator",
"n... |
Oriolac/data-utils | [
"87423d7f7f408c26ea31cbeb7a55a77a55a9ee27"
] | [
"src/dataut/visual.py"
] | [
"\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport seaborn as sns\n\ndef show_corr(X, mask=True, figsize=(7,7)):\n fig, ax = plt.subplots(figsize=figsize)\n corr = X.corr()\n mask = np.triu(np.ones_like(corr, dtype=bool)) if mask else np.ones_like(corr, dtype=bool)\n sns.heatmap(corr, mask=m... | [
[
"matplotlib.pyplot.show",
"numpy.ones_like",
"matplotlib.pyplot.subplots"
]
] |
wingkitlee0/lifelines | [
"46a225ab1d8845f0366921d2b61151fb9a69d398"
] | [
"lifelines/fitters/kaplan_meier_fitter.py"
] | [
"# -*- coding: utf-8 -*-\nimport functools\nimport warnings\nimport numpy as np\nimport pandas as pd\n\nfrom lifelines.fitters import UnivariateFitter\nfrom lifelines.utils import (\n _preprocess_inputs,\n _additive_estimate,\n _to_1d_array,\n StatError,\n inv_normal_cdf,\n median_survival_times,\... | [
[
"pandas.DataFrame",
"numpy.ones_like",
"numpy.asarray",
"numpy.exp",
"numpy.seterr",
"numpy.log",
"numpy.sqrt"
]
] |
whfh3900/Tacotron-2-korea-example | [
"2799394f14e5d52bed2e5f7495bbd89e020a350a"
] | [
"wavenet_vocoder/feeder.py"
] | [
"import os\nimport threading\nimport time\n\nimport numpy as np\nimport tensorflow as tf\nfrom datasets import audio\nfrom infolog import log\nfrom keras.utils import np_utils\nfrom sklearn.model_selection import train_test_split\n\nfrom .util import is_mulaw_quantize, is_scalar_input\n\n\n\n_batches_per_group = 64... | [
[
"tensorflow.placeholder",
"numpy.random.shuffle",
"numpy.transpose",
"tensorflow.device",
"tensorflow.FIFOQueue",
"numpy.expand_dims",
"numpy.clip",
"numpy.array",
"numpy.concatenate",
"sklearn.model_selection.train_test_split"
]
] |
Juanlu001/numpy | [
"1e494f1e283340d545b1c7c15dded04a4aaae939"
] | [
"numpy/core/tests/test_regression.py"
] | [
"from __future__ import division, absolute_import, print_function\n\nimport copy\nimport pickle\nimport sys\nimport platform\nimport gc\nimport warnings\nimport tempfile\nfrom os import path\nfrom io import BytesIO\nfrom itertools import chain\n\nimport numpy as np\nfrom numpy.testing import (\n run_module_s... | [
[
"numpy.ones",
"numpy.testing.assert_equal",
"numpy.any",
"numpy.asarray",
"numpy.testing.assert_warns",
"numpy.transpose",
"numpy.abs",
"numpy.bool_",
"numpy.testing.dec.skipif",
"numpy.bytes_",
"numpy.unique",
"numpy.typeDict.values",
"numpy.string_",
"nump... |
Talendar/qdeep | [
"7228edc9cc7d7e6c6bc59e93a3eb726fda15704d"
] | [
"qdeep/dqn/agent.py"
] | [
"\"\"\" DQN agent implementation.\n\nHeavily based on: https://github.com/deepmind/acme/blob/master/acme/agents/tf/dqn/agent.py\n\"\"\"\n\nimport copy\nfrom typing import Optional, List, Dict\n\nimport numpy as np\nimport reverb\nimport sonnet as snt\nimport tensorflow as tf\nimport trfl\nfrom acme import datasets\... | [
[
"numpy.int32",
"tensorflow.Variable"
]
] |
sflender/autogluon | [
"058398b61d1b2011f56a9dce149b0989adbbb04a"
] | [
"core/src/autogluon/core/models/ensemble/bagged_ensemble_model.py"
] | [
"import copy\nimport logging\nimport os\nimport time\nfrom collections import Counter\nfrom statistics import mean\nfrom functools import reduce\n\nimport numpy as np\nimport pandas as pd\n\nfrom ...constants import MULTICLASS, REGRESSION, SOFTCLASS, REFIT_FULL_SUFFIX\nfrom ...utils.exceptions import TimeLimitExcee... | [
[
"numpy.where",
"numpy.zeros"
]
] |
baidut/PatchVQ | [
"040486b6342dfd36695f1daea0b5c4d77d728a23"
] | [
"fastiqa/browser.py"
] | [
"\"\"\"\nWhat you should know about browser:\n\n* (Browser() << KonIQ) + (Browser() << CLIVE) -- close the first one will close all\n* sync mode: show results of different methods. (qmap comparison, or one showing qmap, one showing the results, very flexible)\n\n# Browser(methods=['PaQ2PiQ-BM', 'PaQ2PiQ-RM']) << Ko... | [
[
"numpy.array",
"numpy.roll"
]
] |
SamPaskewitz/statsrat | [
"3f970f1731b7ec2e22c36a49375619e6afb802a8"
] | [
"statsrat/exemplar/atn_update.py"
] | [
"import numpy as np\n\ndef null(sim, x, y, y_psb, rtrv, y_hat, y_lrn, x_ex, y_ex, n_x, n_y, ex_seen_yet, ex_counts, n_ex, sim_pars):\n '''\n Don't update attention (it remains constant).\n '''\n return 0\nnull.par_names = []\n\ndef gradient_ngsec(sim, x, y, y_psb, rtrv, y_hat, y_lrn, x_ex, y_ex, n_x, n_... | [
[
"numpy.ones",
"numpy.sum",
"numpy.abs",
"numpy.zeros"
]
] |
MohitChaudhari7/Machine-Learning-Using-Python | [
"ff368791133a54df098490d283daf30547b10e8e"
] | [
"Classification/logistic_regression.py"
] | [
"# Logistic Regression\n\n# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importing the dataset\ndataset = pd.read_csv('../Datasets/advertising.csv')\nind = dataset.iloc[:, [0, 2]].values #independent variables(daily time spent on the site and income)\ndep =... | [
[
"matplotlib.pyplot.legend",
"matplotlib.colors.ListedColormap",
"pandas.read_csv",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"sklearn.metrics.confusion_matrix",
"matplotlib.pyplot.show",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.ylabel",
"s... |
vmarcin/FIT-projects | [
"69e3e0f1f271aefd3135f92a681738a4f1a24395"
] | [
"sui/dicewars/ai/dt/wpm_c.py"
] | [
"import numpy\nimport logging\n\nfrom ..utils import probability_of_successful_attack, sigmoid\nfrom ..utils import possible_attacks\n\nfrom dicewars.client.ai_driver import BattleCommand, EndTurnCommand\n\n\nclass AI:\n \"\"\"Agent using Win Probability Maximization (WPM) using logarithms\n of player scores ... | [
[
"numpy.log",
"numpy.warnings.filterwarnings",
"numpy.array"
]
] |
XYHC-MMDA/Multi-modal-Multi-task-DA | [
"ed8297eb489d50c580795713cccb72bc958f406f"
] | [
"nuscenes/eval/common/loaders.py"
] | [
"# nuScenes dev-kit.\n# Code written by Oscar Beijbom, 2019.\n\nimport json\nfrom typing import Dict, Tuple\n\nimport numpy as np\nimport tqdm\nfrom pyquaternion import Quaternion\n\nfrom nuscenes import NuScenes\nfrom nuscenes.eval.common.data_classes import EvalBoxes\nfrom nuscenes.eval.detection.data_classes imp... | [
[
"numpy.array"
]
] |
wesleygas/urban-piriquito | [
"a07dacb8ecf1da40e15d7085ef4502a87e6894bf"
] | [
"interface.py"
] | [
"try:\n # Python2\n import Tkinter as tk\nexcept ImportError:\n # Python3\n import tkinter\n# needs Python25 or higher\n\nfrom functools import partial\nfrom signalTeste import *\nimport matplotlib.pyplot as plt\n#matplotlib.use('TkAgg')\n\nnum ='12'\nsig = signalMeu()\ndef numero():\n global num, si... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.close"
]
] |
fatiando-bot/verde | [
"5d008b0866c1792183ccd02e7ddc0e917f7ed6e1"
] | [
"tutorials/model_evaluation.py"
] | [
"\"\"\"\n.. _model_evaluation:\n\nEvaluating Performance\n======================\n\nThe Green's functions based interpolations in Verde are all linear regressions under the\nhood. This means that we can use some of the same tactics from\n:mod:`sklearn.model_selection` to evaluate our interpolator's performance. Onc... | [
[
"sklearn.model_selection.ShuffleSplit",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.axes",
"matplotlib.pyplot.show",
"matplotlib.pyplot.colorbar",
"numpy.mean"
]
] |
liangfok/oh-distro | [
"eeee1d832164adce667e56667dafc64a8d7b8cee"
] | [
"software/config/terrain/drc_rehearsal_F.py"
] | [
"import numpy as np\n\nblockName = 'cinderblock'\nblockSize = np.array([15 + 5/8.0, 15 + 3/8.0, 5 + 5/8.0]) * 0.0254 # meters\nblockTiltAngle = 15 # degrees\n\n\n# F=sloping up forward (+x), B=sloping up backward (-x),\n# R=sloping up rightward (-y), L=sloping up leftward (+y)\n# last row is closest to robot (robot... | [
[
"numpy.array"
]
] |
andrewsris/preProcessing | [
"70ec54e3f254faacea737f4cbb36a1294ce59417"
] | [
"stainNorm_Macenko.py"
] | [
"\"\"\"\nStain normalization based on the method of:\n\nM. Macenko et al., ‘A method for normalizing histology slides for quantitative analysis’, in 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2009, pp. 1107–1110.\n\nUses the spams package:\n\nhttp://spams-devel.gforge.inria.fr/inde... | [
[
"numpy.arctan2",
"numpy.cos",
"numpy.exp",
"numpy.array",
"numpy.sin",
"numpy.dot",
"numpy.percentile",
"numpy.cov"
]
] |
fjczx/OpenPCDet-lazurite | [
"e3f17ab17b2c295e1786e34c6feb86adffe84b49"
] | [
"lazurite/h5_merge.py"
] | [
"# -*- coding: utf-8 -*-\r\n# @Time : 4/3/2022 6:28 PM\r\n# @Author : Lazurite\r\n# @Email : lazurite@tom.com\r\n# @File : h5_create.py\r\n# @Software: PyCharm\r\nimport os\r\nimport tqdm\r\nimport h5py\r\nimport numpy as np\r\n\r\nh5_paths = [\"../data/nuscenes/v1.0-trainval/samples.h5\", \"../data/nuscen... | [
[
"numpy.dtype"
]
] |
saroad2/knapsack_solver | [
"7247e464019a1afcaea0b7e5e76bdc729f4b0a51"
] | [
"src/knapsack_solver/__main__.py"
] | [
"from pathlib import Path\n\nimport click\nimport numpy as np\n\nfrom knapsack_solver.knapsack_problem import KnapsackProblem\nfrom knapsack_solver.plots_util import save_plots\nfrom knapsack_solver.weight import Weight\n\n\n@click.command()\n@click.argument(\"output-directory\", type=click.Path(file_okay=False))\n... | [
[
"numpy.arange"
]
] |
kateyose/nrn-7.6.7 | [
"603da174f660370abb425917cc5c64c3db03dcec"
] | [
"share/lib/python/neuron/crxd/rxd.py"
] | [
"from neuron import h, nrn, nrn_dll_sym \nfrom . import species, node, section1d, region\nfrom .nodelist import NodeList\nimport weakref\nimport numpy\nimport ctypes\nimport atexit\nfrom . import options\nfrom .rxdException import RxDException\nfrom . import initializer \nimport collections\nimport os\nfrom distuti... | [
[
"numpy.ctypeslib.ndpointer",
"numpy.zeros",
"numpy.concatenate",
"numpy.ndarray",
"numpy.where",
"numpy.array",
"numpy.ascontiguousarray"
]
] |
alexlee-gk/visual_dynamics | [
"90227bb0d0aebb1989117b5c25ca311655ca7cc7"
] | [
"visual_dynamics/gui/gps_training_gui.py"
] | [
"\"\"\"\nGPS Training GUI\n\nThe GPS Training GUI is used to interact with the GPS algorithm during training.\nIt contains the below seven functionalities:\n\nAction Panel contains buttons for stop, reset, go, fail\nAction Status Textbox displays action status\nAlgorithm Status Textbox displ... | [
[
"numpy.sum",
"numpy.empty",
"matplotlib.pyplot.figure",
"numpy.amin",
"numpy.amax",
"matplotlib.pyplot.ion",
"numpy.diagonal",
"matplotlib.gridspec.GridSpec",
"numpy.mean"
]
] |
milokhl/places-2017 | [
"97d4500aacc35e8e55f31918c3fda081d6345c60"
] | [
"model/tensorflow/vgg_slim.py"
] | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.contrib.layers.python.layers.layers.dropout",
"tensorflow.contrib.layers.python.layers.layers.repeat",
"tensorflow.contrib.layers.python.layers.layers.max_pool2d",
"tensorflow.contrib.layers.conv2d",
"tensorflow.python.ops.variable_scope.variable_scope",
"tensorflow.python.ops.... |
ayueaa/Some-Spiders | [
"4cf085e55eab822c08d06b62099d1c235d1840ae"
] | [
"lianjia_chengjiao(可做模板)/pandans合并数据库表重写入.py"
] | [
"import pymongo\r\nimport pandas as pd\r\n\r\n#连接到数据库\r\n#连接到数据库\r\nclient = pymongo.MongoClient(\"localhost\",27017)\r\nlianjia = client[\"ershoufang\"]\r\ninfo = lianjia[\"lianjia_solded\"]\r\nlocation = lianjia['locations']\r\nnew_info = lianjia['cd_lianjia_solded_total_2']\r\n\r\n#将数据表1（包含原始10w+房源信息）转化为DataFram... | [
[
"pandas.merge"
]
] |
barentsen/photutils | [
"57cbe18c8c1b8b08c93daa3d5c8dd74c10c3daae"
] | [
"photutils/utils/tests/test_cutouts.py"
] | [
"# Licensed under a 3-clause BSD style license - see LICENSE.rst\nfrom __future__ import (absolute_import, division, print_function,\n unicode_literals)\n\nimport numpy as np\nfrom numpy.testing import assert_allclose\nfrom astropy.tests.helper import pytest\n\nfrom ..cutouts import cutout_fo... | [
[
"numpy.ones",
"numpy.zeros_like",
"numpy.zeros",
"numpy.testing.assert_allclose",
"numpy.array"
]
] |
jenniferxsj/CS5001_Project | [
"64e1ecec65a431e66aa83751453bba71fcc33b7c"
] | [
"Monitor_temp_hum.py"
] | [
"#Final Project for CS 5001\n#Brian Meyer\n#Shujun Xiao\n#Xiaoliang Xu\n\nimport Adafruit_DHT as DHT\nimport json\nimport time\nimport psutil\nimport twilio\nfrom twilio.rest import Client\nimport matplotlib.pyplot as plt\nimport csv\nfrom matplotlib import rcParams\nimport http.client\nimport urllib\n\n# Turn on t... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.clf",
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.ion",
"matplotlib.pyplot.xlabel"
]
] |
kimandsharp/bmb510 | [
"5446cd168709dd7f5d6cee66f596e57d3632af3d"
] | [
"SciInf_utilities.py"
] | [
"\"\"\"\nsome useful defs for bayes programs\n\"\"\"\nimport numpy as np\n#-------\n# globals\nCREDIBLE_MIN = 2.5 # lower percentile for credible interval\nCREDIBLE_MAX = 97.5 # upper percentile for credible interval # covers 95%\n#CREDIBLE_MIN = 5. # lower percentile for credible interval\n#CREDIBLE_MAX = 95. # up... | [
[
"numpy.zeros"
]
] |
pavlin-policar/graphml-tutorials | [
"72fb9244e8d392b0222b3cfc94b26eb8463ead75"
] | [
"03-graph-classification/preprocess.py"
] | [
"from rdkit import Chem\nimport numpy as np\nfrom pysmiles import read_smiles\nimport networkx as nx\nfrom molecule import Molecule\nimport pickle\nimport pandas as pd\n\n\n\nclass RegressionData():\n \"\"\"\n \t:param mols: list of nx.Graph molecules describing respective SMILES string\n :param labels... | [
[
"pandas.read_csv",
"numpy.hstack",
"numpy.log10"
]
] |
mohdsherif/mne-python | [
"affc6854168e32e73a075a0104e7af8bddd7eefe"
] | [
"mne/forward/forward.py"
] | [
"# Authors: Alexandre Gramfort <alexandre.gramfort@inria.fr>\n# Matti Hamalainen <msh@nmr.mgh.harvard.edu>\n# Martin Luessi <mluessi@nmr.mgh.harvard.edu>\n#\n# License: BSD (3-clause)\n\nfrom time import time\nfrom copy import deepcopy\nimport re\n\nimport numpy as np\nfrom scipy import linalg, sp... | [
[
"numpy.ones",
"numpy.sum",
"scipy.sparse.block_diag",
"numpy.intersect1d",
"numpy.vstack",
"numpy.append",
"scipy.linalg.norm",
"numpy.concatenate",
"numpy.abs",
"numpy.where",
"numpy.round",
"numpy.unique",
"numpy.minimum",
"numpy.sqrt",
"numpy.tile",
... |
zhangbo2008/facenet | [
"4dfabcb5cf14f99622dbe5f9f12f0539821c169c"
] | [
"etc/tf_tutorial/Tensorflow-101-master/logistic_regression_customdata.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # LOGISTIC REGRESSION WITH CUSTOM DATA\n\n# In[1]:\n\n\nimport os\nimport numpy as np\nimport tensorflow as tf\nimport matplotlib.pyplot as plt\nprint (\"Packages loaded\")\n\n\n# # Load data\n\n# In[2]:\n\n\n# Load them!\ncwd = os.getcwd()\nloadpath = cwd + \"/data/cust... | [
[
"tensorflow.initialize_all_variables",
"numpy.load",
"tensorflow.placeholder",
"tensorflow.zeros",
"tensorflow.nn.l2_loss",
"tensorflow.matmul",
"tensorflow.trainable_variables",
"tensorflow.cast",
"tensorflow.set_random_seed",
"tensorflow.train.GradientDescentOptimizer",
... |
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