repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
jackhidaryG/TensorNetwork | [
"6911556ab66e0413cd06180fec3db96f854d7d05"
] | [
"tensornetwork/tensornetwork_test.py"
] | [
"# Copyright 2019 The TensorNetwork 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 required by applicable... | [
[
"numpy.random.rand",
"tensorflow.ones",
"numpy.tensordot",
"numpy.random.normal",
"numpy.eye",
"numpy.transpose",
"numpy.arange",
"numpy.array",
"tensorflow.zeros",
"numpy.matmul",
"numpy.zeros",
"tensorflow.eye",
"tensorflow.map_fn",
"tensorflow.test.main",... |
chrsmlls333/stylegan2-ada | [
"c8594e2bbe5cf4141989489717328e02aa83a658"
] | [
"generate.py"
] | [
"# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.\n#\n# NVIDIA CORPORATION and its licensors retain all intellectual property\n# and proprietary rights in and to this software, related documentation\n# and any modifications thereto. Any use, reproduction, disclosure or\n# distribution of this softwa... | [
[
"numpy.rint",
"numpy.load",
"numpy.multiply",
"numpy.cos",
"numpy.sin",
"numpy.linalg.norm",
"numpy.save",
"numpy.prod",
"numpy.sqrt",
"numpy.square",
"numpy.array",
"numpy.zeros",
"numpy.round",
"numpy.random.randn",
"numpy.clip",
"numpy.log2",
... |
sdarkhovsky/audio | [
"c388ec2b5e6b4d0b99f9c5274d597858e90f5789"
] | [
"torchaudio/compliance/kaldi.py"
] | [
"from typing import Tuple\n\nimport math\nimport torch\nimport torchaudio\nfrom torch import Tensor\n\n__all__ = [\n 'get_mel_banks',\n 'inverse_mel_scale',\n 'inverse_mel_scale_scalar',\n 'mel_scale',\n 'mel_scale_scalar',\n 'spectrogram',\n 'fbank',\n 'mfcc',\n 'vtln_warp_freq',\n 'v... | [
[
"torch.rfft",
"torch.cat",
"torch.gt",
"torch.finfo",
"torch.le",
"torch.ones",
"torch.eye",
"torch.lt",
"torch.nn.functional.pad",
"torch.flip",
"torch.ceil",
"torch.hamming_window",
"torch.zeros_like",
"torch.nn.functional.conv_transpose1d",
"torch.emp... |
Ardor-Wu/gym_fishing | [
"db8b9e52c603cab94669e6922855a62c6521f19d"
] | [
"tests/const_escapement-v1-test.py"
] | [
"import pandas as pd\nimport gym\nimport gym_fishing\nimport math\n\nr = 0.3\nK = 1\nenv = gym.make('fishing-v1', r=r, K=K, sigma=0.)\n\n## inits\nrow = []\nrep = 0\n## Simulate under MSY\nenv.reset()\nobs = env.state\n\n## Rewrite this as a custom `model` class that has a `predict` method for an obs\n\nfor t in ra... | [
[
"pandas.DataFrame"
]
] |
adalke/FPSim2 | [
"23ddf388dd00657e595cf8244360e5c60dc11661"
] | [
"FPSim2/base.py"
] | [
"from abc import ABC, abstractmethod\nfrom .io.chem import load_molecule, rdmol_to_efp\nfrom .io.backends import PyTablesStorageBackend\nfrom .FPSim2lib import py_popcount\nimport numpy as np\n\nSEARCH_TYPES = {\"tanimoto\": 0, \"tversky\": 1, \"substructure\": 2}\n\n\nclass BaseEngine(ABC):\n\n fp_filename = No... | [
[
"numpy.array"
]
] |
Polydynamical/morfeus | [
"b50d35477faed6ed40a1f769d27e6ac68c874525"
] | [
"morfeus/sasa.py"
] | [
"\"\"\"Solvent accessible surface area code.\"\"\"\n\nimport functools\nimport typing\nfrom typing import Any, Dict, Iterable, List, Optional, Union\n\nimport numpy as np\nimport scipy.spatial\n\nfrom morfeus.data import atomic_symbols, jmol_colors\nfrom morfeus.geometry import Atom, Sphere\nfrom morfeus.io import ... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.dot",
"numpy.zeros",
"matplotlib.colors.hex2color",
"numpy.sum",
"numpy.min",
"numpy.vstack"
]
] |
heerokbanerjee/contiki-ng | [
"3b7cd4aef22ac7ac16c48bddfe3176114144a5e6"
] | [
"LSN/assignment_1/question_2/mean_joining_time.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Nov 10 19:40:12 2019\n\n@author: heerokbanerjee\n\"\"\"\n\nimport pandas as pd\nimport re\nimport sys,os,subprocess\n\n \ndef get_join_times(inFile):\n pattern2=r'TIME NEEDED TO JOIN:[ ]*(\\d+)'\n file=open(inFile,'r').read()\n join_... | [
[
"pandas.DataFrame"
]
] |
muziyongshixin/pytorch_SSRP | [
"e54b3098927ba2ff16bdc8f64f3a2bf46d1f72c5"
] | [
"src/lxrt/relation_prob.py"
] | [
"\"\"\"Classes for specifying probe pytorch modules.\"\"\"\r\n\r\nimport torch.nn as nn\r\nimport torch\r\n\r\n\r\nclass Probe(nn.Module):\r\n pass\r\n\r\n\r\nclass TwoWordPSDProbe(Probe):\r\n \"\"\" Computes squared L2 distance after projection by a matrix.\r\n For a batch of sentences, computes all n^2 p... | [
[
"torch.zeros",
"torch.nn.init.uniform_",
"torch.matmul",
"torch.sum"
]
] |
bledem/yolotest | [
"69206260969938b4e318726ff589a122d8c0a5e7"
] | [
"yolov2_predict.py"
] | [
"import time\nimport cv2\nimport glob\nimport numpy as np\nfrom chainer import serializers, Variable\nimport chainer.functions as F\nimport argparse\nfrom yolov2 import *\n\nclass drinkPredictor:\n def __init__(self):\n # hyper parameters\n weight_file = \"/home/ubuntu/sdcard/YOLOv2-master/backup/1... | [
[
"numpy.asarray"
]
] |
daphnei/google-research | [
"26a130831ee903cb97b7d04e71f227bbe24960b2"
] | [
"grouptesting/colab/spreadsheet.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",
"numpy.zeros"
]
] |
bala-codes/Chatbot_With_Machine_Learning_Based-Intent_Classification | [
"2ad503b52d73bb91fd0941acf3c9080b7c4ae182"
] | [
"codes/2. CHAT_HERE.py"
] | [
"import pickle, json, random\nimport numpy as np\nimport smtplib\n\nwith open('intents.json', 'r') as json_data:\n intents = json.load(json_data)\n \nwith open(\"pac_chatbot_classifier.pkl\",\"rb\") as fin:\n vectorizer, PA_classifier = pickle.load(fin)\n\nwith open(\"sgd_chatbot_classifier.pkl\",\"rb\") a... | [
[
"numpy.argmax",
"numpy.mean"
]
] |
eikevons/pandas-seleector | [
"8c54b54ad0e2feb74e9e63435053eb28c8ea073b"
] | [
"tests/test_pickleable.py"
] | [
"from pickle import dumps, loads\nimport pandas as pd\n\nfrom pandas_selector import DF, S\n\n\ndef test_can_be_pickled():\n # This should not raise an error.\n dumps(DF)\n\ndef test_unpickled_instance_works_again():\n df = pd.DataFrame({'x': range(5, 10)})\n sel1 = DF['x'] < 7\n a = df.loc[sel1]\n ... | [
[
"pandas.testing.assert_frame_equal"
]
] |
TongXinNSSC/my_galaxyclassification | [
"43aa55540916d0f2c37fa955cb9f5b19c23b1399"
] | [
"input_data.py"
] | [
"from torchvision import transforms\r\nfrom PIL import Image\r\nimport torch\r\nimport numpy as np\r\nimport math\r\nimport random\r\nimport cv2\r\nfrom model import *\r\ncv2.ocl.setUseOpenCL(False)\r\nfrom torch.utils.data import Dataset\r\n# from MLP import *\r\n\r\nclass ResizeCV2(object):\r\n def __init__(se... | [
[
"numpy.array",
"torch.max",
"torch.std",
"torch.ones",
"torch.load",
"torch.mean"
]
] |
sidsrini12/FURL_Sim | [
"55b420a771858c06f1aef58f48bb68302be36621",
"55b420a771858c06f1aef58f48bb68302be36621"
] | [
"LBGM/src/train_distributed.py",
"LBGM/src/data/distributor.py"
] | [
"import os\nimport pickle as pkl\nimport shutil\nimport sys\n\nimport functools\nimport syft as sy\nimport torch\nfrom torch.utils.tensorboard import SummaryWriter\n\nfrom common.argparser import argparser\nfrom common.arguments import Arguments\nfrom common.utils import get_device, get_paths, init_logger\nfrom dat... | [
[
"torch.set_printoptions",
"torch.utils.tensorboard.SummaryWriter"
],
[
"torch.cat",
"numpy.random.permutation",
"numpy.unique",
"sklearn.model_selection.train_test_split",
"torch.where"
]
] |
touristCheng/Learning2Regrasp | [
"2823c8da5506bcf7d6328976a1e1e7ede84d90cb"
] | [
"inference.py"
] | [
"import argparse\nimport os\nimport os.path as osp\nimport time\n\nimport numpy as np\nimport open3d as o3d\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.nn as nn\nimport torch.nn.parallel\nfrom tqdm import tqdm\n\nfrom ES import Searcher, Critic, Actor, apply_transform, matrix2vectors\nfrom pos... | [
[
"numpy.concatenate",
"torch.device",
"torch.zeros",
"torch.cat",
"numpy.array",
"numpy.asarray",
"torch.min",
"torch.no_grad",
"torch.from_numpy",
"torch.cuda.empty_cache",
"torch.eye",
"torch.mean",
"torch.nn.DataParallel"
]
] |
jhamrick/plotchecker | [
"04ea362b35b3d18685a816895950dddc68c97d2a"
] | [
"plotchecker/scatterplot.py"
] | [
"import numpy as np\n\nfrom .base import PlotChecker, InvalidPlotError\n\nclass ScatterPlotChecker(PlotChecker):\n \"\"\"A plot checker for scatter plots.\n\n Parameters\n ----------\n axis : ``matplotlib.axes.Axes`` object\n A set of matplotlib axes (e.g. obtained through ``plt.gca()``)\n\n \... | [
[
"numpy.concatenate",
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.testing.assert_equal",
"numpy.sqrt"
]
] |
tetutaro/deeplearning_models_pytorch | [
"d5f9ffb733692b62a4c744a901fdbc5dc3f9a490"
] | [
"models/LightningCycleGAN.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\nfrom __future__ import annotations\nfrom typing import Dict, List, Tuple, Callable\nfrom itertools import chain\nimport torch\nimport torch.optim as optim\nimport torch.optim.lr_scheduler as sched\nfrom torch.utils.data import TensorDataset\nfrom .CycleGAN import Cyc... | [
[
"torch.optim.lr_scheduler.LambdaLR",
"torch.stack"
]
] |
Linardos/torchio | [
"b0555fc939960128d37e56c27edcfc74a3a967e3",
"b0555fc939960128d37e56c27edcfc74a3a967e3"
] | [
"tests/transforms/augmentation/test_random_anisotropy.py",
"torchio/transforms/augmentation/intensity/random_spike.py"
] | [
"import torch\nfrom torchio import ScalarImage, RandomAnisotropy\nfrom ...utils import TorchioTestCase\n\n\nclass TestRandomAnisotropy(TorchioTestCase):\n \"\"\"Tests for `RandomAnisotropy`.\"\"\"\n\n def test_downsample(self):\n transform = RandomAnisotropy(\n axes=1,\n downsampl... | [
[
"torch.rand"
],
[
"torch.rand",
"numpy.array",
"torch.stack",
"numpy.asarray",
"torch.randint",
"numpy.floor"
]
] |
aashen12/rule-vetting | [
"b1a91675f838aee45eb8d989e299664151d02c11"
] | [
"rulevetting/api/validation.py"
] | [
"import warnings\nfrom os.path import join as oj\n\nimport sys\n\nsys.path.insert(1, oj(sys.path[0], '..')) # insert parent path\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom tqdm import tqdm\nfrom sklearn import metrics\n\n\ndef all_stats_curve(y_test, preds_proba, plot=False, thresholds=None):\n ... | [
[
"sklearn.metrics.confusion_matrix",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"numpy.unique"
]
] |
Yuki-Tanaka-33937424/Kaggle-SIIM-FISABIO-RSNA | [
"c7714bdf5190b4408392b899deadc3f54a548312"
] | [
"code/003/ver09/siim-003-train-eff-2class-ver09.py"
] | [
"# ====================================================\n# Library #\n# ====================================================\nimport os\nimport gc\nimport sys\nimport math\nimport time\nimport random\nimport shutil\nfrom requests import get\nfrom pathlib import Path\nfrom contextlib import contextmanager\nfrom coll... | [
[
"torch.nn.Linear",
"torch.cuda.manual_seed",
"torch.cuda.amp.autocast",
"numpy.where",
"torch.squeeze",
"torch.cuda.is_available",
"numpy.finfo",
"pandas.concat",
"numpy.cumsum",
"numpy.concatenate",
"sklearn.model_selection.__getattribute__",
"pandas.DataFrame",
... |
pramitchoudhary/Experiments | [
"71c251dbb2a7af801d9afab2bfb93d6a55caa7da"
] | [
"natural_language_processing/tensorflow/utils.py"
] | [
"import string\nimport os\nimport urllib.request\nimport io\nimport tarfile\nimport collections\nimport numpy as np\nimport requests\nimport gzip\n\n# Normalize text\ndef normalize_text(texts, stops):\n # Lower case\n texts = [x.lower() for x in texts]\n\n # Remove punctuation\n texts = [''.join(c for c... | [
[
"numpy.array"
]
] |
mili-li/zvt | [
"7a538d3ad813bec8f13ff514ea0889819a16beb0"
] | [
"examples/trader/ma250_trader.py"
] | [
"# -*- coding: utf-8 -*-\nimport datetime\nfrom typing import List\n\nimport numpy as np\n\nfrom zvt import init_log\nfrom zvt.api import get_kdata\nfrom zvt.contract import IntervalLevel\nfrom zvt.contract.api import get_entities\nfrom zvt.domain import Stock\nfrom zvt.factors import TargetSelector, VolumeUpMaFact... | [
[
"numpy.all",
"numpy.logical_and.reduce"
]
] |
EllianCarlos/preparing-siicusp-presentation | [
"cdd429a7f13f850051c62fb676e2179e4e60aa39"
] | [
".reference/3b1b/zeta.py"
] | [
"\"\"\"\n This code was in the 3b1b videos repository: https://github.com/3b1b/videos\n\"\"\"\n\nimport numpy as np\nimport mpmath\n\ninf = np.inf\n\ndef zeta_v(z):\n return np.vectorize(zeta)(z)\n\ndef zeta(z):\n max_norm = inf\n try:\n return np.complex(mpmath.zeta(z))\n except:\n pri... | [
[
"numpy.complex",
"numpy.vectorize"
]
] |
StevenCyb/Segnet_Ar_Marker | [
"02b910558ba95de7b37d736a1a3d89d4c194ceed"
] | [
"utils/sample_generator.py"
] | [
"import os\nimport random\nimport numpy as np\nimport cv2\nimport cv2.aruco as aruco\n\n# Get dictionary by name\ndef get_dictionary(DICT_4X4_50=False, DICT_4X4_100=False, DICT_4X4_250=False, DICT_4X4_1000=False, DICT_5X5_50=False, DICT_5X5_100=False, DICT_5X5_250=False, DICT_5X5_1000=False, DICT_6X6_50=False, DICT... | [
[
"numpy.zeros",
"numpy.ones",
"numpy.float32",
"numpy.random.uniform",
"numpy.random.randint"
]
] |
Shujun-He/3rd_Solution_Feedback_Prize_Evaluating_Student_Writing | [
"1a3d1041978ab27f7158505b3d1438676d15b7ca"
] | [
"SW_Deberta/make_oofs.py"
] | [
"from sklearn.model_selection import StratifiedKFold\n\nimport os, sys\n# DECLARE HOW MANY GPUS YOU WISH TO USE.\n# KAGGLE ONLY HAS 1, BUT OFFLINE, YOU CAN USE MORE\n\nimport argparse\ndef get_args():\n parser = argparse.ArgumentParser()\n #parser.add_argument('--disc_type', type=int, default=0, help='disc_t... | [
[
"torch.nn.Linear",
"scipy.stats.mode",
"torch.cat",
"torch.stack",
"torch.nn.GRU",
"torch.nn.LSTM",
"torch.cuda.amp.autocast",
"numpy.mean",
"torch.cuda.is_available",
"torch.load",
"torch.nn.functional.pad",
"pandas.read_csv",
"torch.nn.LayerNorm",
"sklearn... |
imRushabhShah/aima-python | [
"77066d1afd0bc432a7c8611ef78e6f351906a663"
] | [
"utils4e.py"
] | [
"\"\"\"Provides some utilities widely used by other modules\"\"\"\n\nimport bisect\nimport collections\nimport collections.abc\nimport functools\nimport heapq\nimport math\nimport os.path\nimport random\nfrom itertools import chain, combinations\nfrom statistics import mean\n\nimport numpy as np\n\n\n# part1. Gener... | [
[
"numpy.tanh",
"numpy.exp",
"numpy.convolve"
]
] |
bsmitty5000/andrewNgML-In-Python | [
"5064040adfc6795bed4c32c0b2730a6aabd8a6a0"
] | [
"machine-learning-ex4/ex4.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Jan 22 07:09:41 2018\n\n@author: Batman\n\"\"\"\nimport sys\nsys.path.insert(0, '../shared')\n\nimport pandas as pd\nimport numpy as np\nimport scipy.optimize as opt\nimport matplotlib.pyplot as plt\nimport os\n\nimport neuralNetworks as nn\n\nfrom scipy.io import lo... | [
[
"numpy.array",
"scipy.io.loadmat",
"scipy.optimize.minimize",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.OneHotEncoder"
]
] |
f0k/dcase_task2 | [
"e7246e2e2ffdd59efde3b571556eef4c3bcffe22"
] | [
"dcase_task2/eval.py"
] | [
"\nfrom __future__ import print_function\n\nimport os\nimport sys\nimport pickle\nimport argparse\nimport numpy as np\nimport matplotlib.pyplot as plt\nfrom collections import Counter\nfrom sklearn.metrics import accuracy_score, precision_recall_fscore_support\n\nfrom dcase_task2.lasagne_wrapper.network import Netw... | [
[
"matplotlib.pyplot.xlim",
"numpy.mean",
"matplotlib.pyplot.bar",
"numpy.concatenate",
"numpy.histogram",
"matplotlib.pyplot.savefig",
"sklearn.metrics.accuracy_score",
"numpy.argmax",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.subplot",
"numpy.zeros",
"... |
nsryan2/pyne | [
"f65ad55c7eaba5ee26108960cf33f524ce43a1a7"
] | [
"pyne/dbgen/ndsfpy.py"
] | [
"\"\"\"This module provides a way to grab and store raw data for fission product yeilds\nfrom the NDS library at the IAEA. For more information, please visit their website:\nhttps://www-nds.iaea.org/sgnucdat/index.htm or\nhttps://www-nds.iaea.org/sgnucdat/c2.htm. Please contact the NDS at\nonline@iaeand.iaea.org wi... | [
[
"numpy.dtype"
]
] |
acobo/tf2-eager-yolo3 | [
"7f3195657b6e10fb154c422e1122421a9bcf1340"
] | [
"yolo/loss/utils.py"
] | [
"# -*- coding: utf-8 -*-\r\nimport numpy as np\r\nimport tensorflow as tf\r\n\r\n\r\ndef adjust_pred_tensor(y_pred):\r\n\r\n grid_offset = _create_mesh_xy(*y_pred.shape[:4])\r\n \r\n pred_xy = grid_offset + tf.sigmoid(y_pred[..., :2]) # sigma(t_xy) + c_xy\r\n pred_wh = y_pred[..., 2:4] ... | [
[
"tensorflow.exp",
"tensorflow.range",
"tensorflow.minimum",
"tensorflow.concat",
"tensorflow.sigmoid",
"tensorflow.expand_dims",
"tensorflow.argmax",
"tensorflow.truediv",
"tensorflow.transpose",
"tensorflow.reshape",
"tensorflow.constant",
"tensorflow.squeeze",
... |
e-zolotarevskaya/oemof-solph | [
"750163efdbbb8851c5c8f9ffd340d07a63178b92"
] | [
"tests/test_scripts/test_solph/test_connect_invest/test_connect_invest.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"Connecting different investment variables.\n\nThis file is part of project oemof (github.com/oemof/oemof). It's copyrighted\nby the contributors recorded in the version control history of the file,\navailable from its original location\noemof/tests/test_scripts/test_solph/test_conn... | [
[
"pandas.date_range",
"pandas.read_csv"
]
] |
abecker99/ProjectileMotion1 | [
"b93905511fdd080fb9bbad2612beaf3b6e40807f"
] | [
"ProjectileXYplot.py"
] | [
"import matplotlib.pyplot as plt\n\nX = []\nY = []\n\ninFile = open(\"projectileDragData.txt\", \"r\")\nfor line in inFile:\n t, x, y, z, v_x, v_y, v_z, a_x, a_y, a_z = line.split(\" \")\n X.append(float(x))\n Y.append(float(y))\ninFile.close()\n\nplt.xlabel(\"$x$ (m)\")\nplt.ylabel(\"$y$ (m)\")\nplt.plot(... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
Casper-Smet/ct_assist | [
"5dbbd291562c52f56625e044b8bdd9732501d1d3"
] | [
"ct_assist/tests/test_reference_detection.py"
] | [
"import pytest\n\nimport torch\nimport numpy as np\nfrom ct_assist import reference_detection as rd\nfrom ct_assist.exceptions import SkipFieldWarning\n\nfrom detectron2.config.config import CfgNode\nfrom detectron2.engine import DefaultPredictor\nfrom detectron2.structures import Instances\n\n\ndef test_load_model... | [
[
"torch.zeros",
"numpy.array"
]
] |
CSP197/biopython | [
"3b08f8c7ca387ce628165db3abae8c5e622983cc"
] | [
"Bio/PDB/mmtf/DefaultParser.py"
] | [
"# Copyright 2016 Anthony Bradley. All rights reserved.\n#\n# This file is part of the Biopython distribution and governed by your\n# choice of the \"Biopython License Agreement\" or the \"BSD 3-Clause License\".\n# Please see the LICENSE file that should have been included as part of this\n# package.\n\"\"\"Code ... | [
[
"numpy.array"
]
] |
pjhaest/flopy | [
"369893b6e58cf37bd09c95c6e7cb129c74359214"
] | [
"flopy/export/utils.py"
] | [
"from __future__ import print_function\r\nimport json\r\nimport os\r\nimport numpy as np\r\nfrom ..utils import Util2d, Util3d, Transient2d, MfList, \\\r\n HeadFile, CellBudgetFile, UcnFile, FormattedHeadFile\r\nfrom ..mbase import BaseModel\r\nfrom ..pakbase import Package\r\nfrom . import NetCdf, netcdf\r\nfro... | [
[
"numpy.array",
"numpy.isnan",
"numpy.empty",
"numpy.errstate",
"numpy.nanmin",
"numpy.where",
"numpy.abs",
"numpy.nanmax"
]
] |
DavidMeda/gym-donkeycar | [
"d162fd58d0369282e54dd2ee1ae4538d049c2575"
] | [
"examples/reinforcement_learning/PPO_model_evaluation.py"
] | [
"import os\nimport pandas as pd\nfrom torch.utils.data import Dataset, DataLoader\nimport torch\nfrom torch.nn import L1Loss, MSELoss\nfrom torchvision import transforms\nfrom PIL import Image\nimport numpy as np\nimport glob\nimport json\nfrom sklearn.model_selection import train_test_split\nimport shutil\nimport ... | [
[
"pandas.cut",
"numpy.asarray",
"torch.nn.MSELoss",
"pandas.DataFrame",
"torch.no_grad",
"numpy.mean",
"torch.nn.L1Loss",
"torch.abs",
"torch.tensor"
]
] |
sejunssi/edited_benchmarking_gnn | [
"643fc5a96aae9ba77fd97a5176617d3e9bfff26b",
"643fc5a96aae9ba77fd97a5176617d3e9bfff26b"
] | [
"nets/molecules_graph_regression/mlp_net.py",
"nets/molecules_graph_regression/gcn_net.py"
] | [
"import torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\n\r\nimport dgl\r\n\r\nfrom layers.mlp_readout_layer import MLPReadout\r\n\r\nclass MLPNet(nn.Module):\r\n def __init__(self, net_params):\r\n super().__init__()\r\n num_atom_type = net_params['num_atom_type']\r\n nu... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.Sequential",
"torch.nn.L1Loss",
"torch.nn.ReLU",
"torch.nn.Embedding"
],
[
"torch.nn.Dropout",
"torch.nn.Embedding",
"torch.nn.L1Loss"
]
] |
oddgr8/QCGym | [
"66bebe0b4bd5f56e59a161dca3a3121e74b96751"
] | [
"QCGym/hamiltonians/cross_resonance.py"
] | [
"from QCGym.hamiltonians.generic_hamiltonian import GenericHamiltonian\nfrom QCGym.interpolators.identity import IdentityInterpolator\nimport numpy as np\nfrom gym import spaces\nimport logging\nlogger = logging.getLogger(__name__)\n\n\nclass CrossResonance(GenericHamiltonian):\n \"\"\"\n Hamiltonian for Cros... | [
[
"numpy.array",
"numpy.eye",
"numpy.cos",
"numpy.conjugate",
"numpy.kron"
]
] |
mauriliosalg/Seis_Shift-Net_pytorch | [
"26f777d5e3be9d0828972202a61f0e01e2c04a1a"
] | [
"models/face_shift_net/InnerFaceShiftTripleFunction.py"
] | [
"import numpy as np\nfrom util.NonparametricShift import Modified_NonparametricShift\nimport torch\nimport util.util as util\nimport time\n\n# This script offers a version of shift from multi-references.\nclass InnerFaceShiftTripleFunction(torch.autograd.Function):\n ctx = None\n\n @staticmethod\n def forw... | [
[
"torch.zeros",
"torch.cat",
"torch.max",
"torch.mm",
"torch.Tensor"
]
] |
huangkaiyikatherine/nexperia_new | [
"b9b5c35d989883f8b29280726bfbb0fc84e62b10"
] | [
"main_huber_lasso.py"
] | [
"import argparse\nimport os\nimport shutil\nimport time\nimport copy\nimport PIL.Image as Image\nimport numpy as np\nimport pandas as pd\n\nimport torch\nimport torch.nn as nn\nfrom torch.nn import functional as F\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\n\nfrom datasets import get_loader\nfr... | [
[
"torch.cuda.manual_seed",
"numpy.zeros",
"pandas.DataFrame",
"torch.no_grad",
"torch.norm",
"torch.cuda.device_count",
"torch.nn.functional.cross_entropy",
"torch.load",
"torch.nn.functional.softmax",
"torch.nn.CrossEntropyLoss",
"torch.nn.DataParallel"
]
] |
dschien/eam-table-data-reader | [
"9cc0867496c3b04d781ce3b0a324eb86881c1dad"
] | [
"src/table_data_reader/__init__.py"
] | [
"__version__ = '1.0.0'\n\nimport csv\nimport datetime\nimport importlib\n\nfrom abc import abstractmethod\nfrom collections import defaultdict\nfrom typing import Dict, List, Set\n\nimport numpy as np\nimport pandas as pd\nfrom dateutil import relativedelta as rdelta\n\nimport logging\nfrom functools import partial... | [
[
"scipy.interpolate.interp1d",
"numpy.array",
"numpy.flipud",
"numpy.multiply",
"pandas.MultiIndex.from_product",
"numpy.abs",
"pandas.Series",
"numpy.vstack"
]
] |
fraunhofer-iais/UoC-ml-school-2019 | [
"e651bc9d6245c2d48229dd8ba18022f3abba25b6"
] | [
"audioset/vggish_input.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 requi... | [
[
"scipy.io.wavfile.read",
"numpy.mean"
]
] |
Sikerdebaard/lifelines | [
"220dcb9ad9c38ecceaa536f7cff3886d4e73a817"
] | [
"perf_tests/cp_perf_test.py"
] | [
"# -*- coding: utf-8 -*-\n# cox regression\n\n\nif __name__ == \"__main__\":\n import pandas as pd\n import time\n import numpy as np\n\n from lifelines import CoxPHFitter\n from lifelines.datasets import load_rossi\n\n df = load_rossi()\n df = pd.concat([df] * 16)\n # df = df.reset_index()\... | [
[
"pandas.concat"
]
] |
NunoEdgarGFlowHub/shap | [
"6992883fb3470163fcbe2bfacae0bd5f724ed1f8",
"6992883fb3470163fcbe2bfacae0bd5f724ed1f8"
] | [
"setup.py",
"shap/explainers/tree.py"
] | [
"from setuptools import setup, Extension\nfrom setuptools.command.build_ext import build_ext as _build_ext\nimport os\nimport re\nimport codecs\nimport platform\nfrom distutils.sysconfig import get_config_var\nfrom distutils.version import LooseVersion\nimport sys\n\n# to publish use:\n# > python setup.py sdist bdi... | [
[
"numpy.get_include"
],
[
"numpy.max",
"numpy.nextafter",
"numpy.isnan",
"numpy.empty",
"numpy.asarray",
"numpy.zeros",
"numpy.uint32",
"numpy.ones",
"numpy.min",
"numpy.multiply",
"numpy.unique"
]
] |
muelljoh/gsee | [
"cb63a0645d24d80db4f77494f5f7256820ae6321"
] | [
"gsee/climatedata_interface/test_interface.py"
] | [
"import pytest\n\nimport numpy as np\nimport pandas as pd\nimport xarray as xr\n\nimport gsee.climatedata_interface.interface as interface\n\n\ndef test_run_interface_from_dataset():\n for freq in ['A', 'S', 'M', 'D', 'H']:\n\n freq_string = freq if freq != 'S' else 'QS-DEC'\n ds = xr.Dataset(\n ... | [
[
"numpy.random.rand",
"pandas.date_range",
"numpy.array_equal",
"pandas.DatetimeIndex"
]
] |
royqh1979/python_libs_usage | [
"57546d5648d8a6b7aca7d7ff9481aa7cd4d8f511"
] | [
"References/tools/毕设答辩分配.py"
] | [
"from typing import Set, Dict\n\nimport pandas as pd\nfrom dataclasses import dataclass\nimport random\n\n\n@dataclass\nclass Teacher:\n name: str\n students: Set[str]\n group: int\n\nteachers : Dict[str,Teacher] = {}\nreviews = {}\nstudents = {}\ngroups = {}\nwith open(\"导师分配.csv\",\"r\",encoding=\"GBK\")... | [
[
"pandas.read_csv"
]
] |
elmajdma/seismic-deeplearning | [
"bc084abe153509c40b45f8bf0f80dfda1049d7dc"
] | [
"cv_lib/tests/test_metrics.py"
] | [
"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License.\n\nimport torch\nimport numpy as np\nfrom pytest import approx\n\nfrom ignite.metrics import ConfusionMatrix, MetricsLambda\n\nfrom cv_lib.segmentation.metrics import class_accuracy, mean_class_accuracy\n\n\n# source rep... | [
[
"numpy.max",
"torch.min",
"numpy.zeros",
"torch.max",
"numpy.ones",
"torch.from_numpy",
"numpy.all"
]
] |
rosomaxa/coremltools | [
"f7c2c32e2fa4f3d988dc07c44774c701e32c5cc8"
] | [
"coremltools/test/sklearn/test_random_forest_regression_numeric.py"
] | [
"# Copyright (c) 2017, Apple Inc. All rights reserved.\n#\n# Use of this source code is governed by a BSD-3-clause license that can be\n# found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause\n\nimport unittest\nimport numpy as np\nimport pandas as pd\nimport os\nfrom coremltools._deps im... | [
[
"pandas.DataFrame",
"sklearn.ensemble.RandomForestRegressor",
"sklearn.datasets.load_boston"
]
] |
antolikjan/topographica-recovered | [
"dfd06574f13400de7d634d13bc72ce25a6e4eec5"
] | [
"topo/base/projection.py"
] | [
"\"\"\"\nProjection and related classes.\n\"\"\"\n\nimport numpy\nfrom numpy import array,asarray,ones,sometrue, logical_and, logical_or\n\nimport param\nfrom param.parameterized import overridable_property\n\nfrom topo.misc.keyedlist import KeyedList # CEBALERT: not in base\n\nfrom sheet import Sheet\nfrom simulat... | [
[
"numpy.array",
"numpy.ones",
"numpy.sometrue"
]
] |
svigeland/enterprise_extensions | [
"52993aadec9f821c2883a81160c9af1c0e5b3eca"
] | [
"enterprise_extensions/sampler.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import (absolute_import, division,\n print_function)\nimport numpy as np\nimport os\nfrom enterprise import constants as const\nimport pickle\nimport healpy as hp\nimport glob\n\nfrom enterprise import constants as const\nfrom PTMCMCSampler.PTMCMCSamp... | [
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.arccos",
"numpy.random.choice",
"numpy.log",
"numpy.ones",
"numpy.load",
"numpy.any",
"numpy.random.uniform",
"numpy.atleast_1d",
"numpy.random.randint",
"numpy.arange",
"numpy.cos",
"numpy.hstack",... |
qvandenberg/plant-disease-experiments | [
"fc79197a34acc3f03f6562e510255de28461b49d",
"fc79197a34acc3f03f6562e510255de28461b49d"
] | [
"Plant_Disease_Detection_Benchmark_models/tests/test_shared_utils.py",
"Plant_Disease_Detection_gan_experiments/infoDCGAN/main.py"
] | [
"import argparse\nimport unittest\nimport os\nimport shutil\nimport tempfile\nfrom unittest import mock\n\nfrom tensorflow.python.keras.applications.inception_v3 import preprocess_input, InceptionV3\nfrom tensorflow.python.keras import Model, Input\n\nimport shared.utils as utils\nfrom shared.utils import IM_WIDTH,... | [
[
"tensorflow.python.keras.Input"
],
[
"tensorflow.app.run",
"tensorflow.Session"
]
] |
lucaspbastos/mirdata | [
"e591c5411c41591e8606812df869dca1ad52ee0f"
] | [
"tests/datasets/test_otmm_makam.py"
] | [
"import numpy as np\nfrom mirdata import annotations\nfrom mirdata.datasets import compmusic_otmm_makam\nfrom tests.test_utils import run_track_tests\n\n\ndef test_track():\n data_home = \"tests/resources/mir_datasets/compmusic_otmm_makam\"\n track_id = \"cafcdeaf-e966-4ff0-84fb-f660d2b68365\"\n\n dataset ... | [
[
"numpy.array"
]
] |
shellerbrand/arbitrary-neural-style-transfer | [
"c211fb2d2951b8f56d50d33c148f2ddc9e8da1bc",
"c211fb2d2951b8f56d50d33c148f2ddc9e8da1bc"
] | [
"lib/vgg.py",
"lib/learning.py"
] | [
"# Copyright 2016 Google Inc. All Rights Reserved.\n# Modifications copyright 2018 Stephan Hellerbrand\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... | [
[
"tensorflow.contrib.slim.repeat",
"tensorflow.contrib.slim.softmax",
"tensorflow.constant",
"tensorflow.variable_scope",
"tensorflow.contrib.slim.arg_scope",
"tensorflow.contrib.slim.conv2d",
"tensorflow.contrib.slim.dropout"
],
[
"tensorflow.shape",
"tensorflow.Session",
... |
jqueguiner/HighRes-net | [
"4d24b80b7b9b601a3bc01ada793fe4fe1c2e3b40"
] | [
"src/Evaluator.py"
] | [
"\"\"\" Python script to evaluate super resolved images against ground truth high resolution images \"\"\"\n\nimport itertools\n\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom DataLoader import get_patch\n\n\ndef cPSNR(sr, hr, hr_map):\n \"\"\"\n Clear Peak Signal-to-Noise Ratio. The PSNR score, adjusted ... | [
[
"numpy.max",
"numpy.square",
"numpy.sum",
"numpy.log10",
"numpy.iinfo"
]
] |
fralc/folium | [
"4c0c8535f748db05c91d8256bf02b6b8cff6c00f"
] | [
"folium/features.py"
] | [
"# -*- coding: utf-8 -*-\n\n\"\"\"\nLeaflet GeoJson and miscellaneous features.\n\n\"\"\"\n\nimport json\nimport warnings\nimport functools\nimport operator\n\nfrom branca.colormap import LinearColormap, StepColormap\nfrom branca.element import (Element, Figure, JavascriptLink, MacroElement)\nfrom branca.utilities ... | [
[
"numpy.histogram",
"numpy.nextafter",
"numpy.isnan",
"numpy.digitize",
"numpy.any"
]
] |
Mikma03/High-performance-Python | [
"b7720377bc967e856e16678ae91b37c2503b49e0"
] | [
"06. Chapter_6/diffusion_2d/diffusion_numpy_memory.py"
] | [
"#!/usr/bin/env python3\n\nimport time\n\nimport numpy as np\n\ntry:\n profile\nexcept NameError:\n profile = lambda x: x\n\ngrid_shape = (640, 640)\n\n\ndef laplacian(grid, out):\n np.copyto(out, grid)\n out *= -4\n out += np.roll(grid, +1, 0)\n out += np.roll(grid, -1, 0)\n out += np.roll(gri... | [
[
"numpy.copyto",
"numpy.roll",
"numpy.zeros"
]
] |
riciche/SimpleCVReproduction | [
"4075de39f9c61f1359668a413f6a5d98903fcf97",
"4075de39f9c61f1359668a413f6a5d98903fcf97"
] | [
"tensorflow2/class4/tensorflow2_mnist_subclassing.py",
"nni/test/ut/sdk/test_pruners.py"
] | [
"import math\nimport numpy as np\nfrom sklearn import preprocessing, model_selection, svm\nfrom sklearn.linear_model import LinearRegression\nimport matplotlib.pyplot as plt\nfrom matplotlib import style\nimport pandas as pd\nimport datetime\nimport tensorflow as tf\n\nmnist = tf.keras.datasets.mnist\n\n(x_train, y... | [
[
"tensorflow.keras.callbacks.TensorBoard",
"tensorflow.keras.utils.to_categorical",
"tensorflow.keras.optimizers.SGD",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.layers.MaxPooling2D"
],
[
"torch.nn.Line... |
dongminlee94/Samsung-DRL-Code | [
"c72408ca29c25230687d81b7ca3a85bab40956a9"
] | [
"4_TRPO_PPO/trpo/test.py"
] | [
"import os\nimport gym\nimport argparse\nimport numpy as np\n\nimport torch\nfrom utils import *\nfrom model import Actor\n\nparser = argparse.ArgumentParser()\nparser.add_argument('--env_name', type=str, default=\"Pendulum-v0\")\nparser.add_argument(\"--load_model\", type=str, default='model.pth.tar')\nparser.add_... | [
[
"torch.manual_seed",
"torch.Tensor",
"numpy.reshape",
"torch.load"
]
] |
kirknorth/pytmatrix | [
"08070e5a63eceea04535a8ae6db99a4d4f91ce05"
] | [
"pytmatrix/orientation.py"
] | [
"\"\"\"\nCopyright (C) 2009-2013 Jussi Leinonen\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of\nthis software and associated documentation files (the \"Software\"), to deal in\nthe Software without restriction, including without limitation the rights to\nuse, copy, modify, merge,... | [
[
"numpy.sin",
"numpy.zeros",
"numpy.exp",
"scipy.integrate.dblquad",
"numpy.linspace",
"scipy.integrate.quad"
]
] |
shiningsurya/gwa_final | [
"9cb77202c5e5b5eec9941845f1e79da52dc90c59"
] | [
"create_ccsn.py"
] | [
"# coding: utf-8\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport scipy.signal as ssg\nimport glob\nplt.ion ()\n############ PARAMETERS\nfs=2048\nT=1\nt = np.arange (0, int(T*fs)) / fs\ntsize = t.size\n############ ccsn\nprint (\"ccsn\")\nFF = glob.glob (\"ccsn_signals/*.dat\")\nFL = len(FF)\nNITER = 15... | [
[
"matplotlib.pyplot.ion",
"scipy.signal.spectrogram",
"numpy.random.rand",
"numpy.zeros",
"numpy.genfromtxt",
"numpy.random.randn",
"numpy.save"
]
] |
mChataign/smileCompletion | [
"1bde2dd9fada2194c79cb3599bc9e9139cde6ee5"
] | [
"Code/regression.py"
] | [
"import numpy as np\r\nimport pandas as pd\r\nimport tensorflow as tf\r\nimport dask\r\nimport scipy\r\nimport time\r\n\r\nfrom functools import partial\r\nfrom abc import ABCMeta, abstractmethod\r\n\r\nfrom sklearn.decomposition import PCA\r\nfrom sklearn.preprocessing import scale\r\nfrom sklearn.linear_model imp... | [
[
"sklearn.linear_model.LinearRegression",
"numpy.argmin",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.global_variables_initializer",
"tensorflow.contrib.layers.variance_scaling_initializer",
"pandas.DataFrame",
"tensorflow.train.Saver",
"tensorflow.Variable",
"num... |
cseveriano/spatio-temporal-forecasting | [
"8391f3de72b840edb2b35148537502ec5d2ac888"
] | [
"src/spatiotemporal/models/benchmarks/fbem/graph_utils.py"
] | [
"import matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d.art3d import Poly3DCollection\n\n\ndef plot_singular_output(fbem_instance, expected_output):\n \"\"\"\n Plot singular output of predicted values from FBeM\n to be compared to the expected output\n :param fbem_instance: FBeM instance\n :param... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure"
]
] |
Whity25/MC_LJ_NVT | [
"d2cc9a0c4117d2a84514a70f6635933b1e603033"
] | [
"main.py"
] | [
"import MC_LIB\nfrom mpi4py import MPI\nimport sys\nimport os\nimport glob\nimport time\nimport numpy as np\n\ncomm = MPI.COMM_WORLD\nmy_rank = comm.Get_rank()\np = comm.Get_size()\n\n#simulation parameters\nnr_of_atoms = 100\nbox_len = 125.\nmax_stepsize = 2.\n\nendpoint = 250000 #Amount of attempted steps before ... | [
[
"numpy.random.rand"
]
] |
mo-jan/google-files-backup | [
"f6bc724b5d6de17d550a4c713b626f3d85bfb25c"
] | [
"src/queries.py"
] | [
"#! /usr/bin/env python\nimport datetime\nimport io\nfrom pathlib import Path\n\nimport pandas as pd\nfrom googleapiclient.http import MediaFileUpload, MediaIoBaseDownload\n\n\ndef search_file(drive_service, num_of_responses, query):\n \"\"\"\n Search for files and store results of query in pd.DataFrame\n ... | [
[
"pandas.DataFrame"
]
] |
Saman689/Weed-sensing-basics | [
"25355b20af94432fbe43969cc21fcbf402d01972"
] | [
"Nets on Jetson TX1 board/PDU_Designed_simplenet.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# ### In this notebook we tried to investigate simple network on PDU data\n\n# ### Importing the libraries\n\n# In[1]:\n\n\nimport torch \n\nimport torch.nn as nn\nimport torch.utils.data as Data\nfrom torch.autograd import Function, Variable\nfrom torch.optim import lr_s... | [
[
"torch.nn.Linear",
"torch.stack",
"torch.max",
"torch.nn.MaxPool2d",
"torch.autograd.Variable",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.cuda.is_available",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.utils.data.DataLoader",
"torch.nn.Dropout2d",
"to... |
LUMII-Syslab/Switchblade | [
"f398589d23d973836b78cf7dd5cf0872bff42f9c"
] | [
"layers/quaternary_shuffle.py"
] | [
"from enum import Enum\n\nimport numpy as np\nimport tensorflow as tf\n\nimport utils.data as data_utils\nimport utils.shuffle as shuffle_utils\nfrom layers.shuffle import LinearTransform, QuaternarySwitchUnit\n\n\nclass ShuffleType(Enum):\n LEFT = shuffle_utils.qrol\n RIGHT = shuffle_utils.qror\n\n def __... | [
[
"numpy.array",
"tensorflow.reshape",
"numpy.arange",
"tensorflow.name_scope",
"tensorflow.gather"
]
] |
dantecomedia/IMAGE-to-TEXT | [
"bddfd69643f7000721e48171f2f447c7d8eeacd3"
] | [
"image_to_text.py"
] | [
"import cv2\nimport numpy as np\nfrom PIL import Image\nimport tempfile\nimport pytesseract\nimport os\nfrom tqdm import tqdm\nimg_size = 1800\nthreshold = 215\n\n\ndef process_image(file):\n temp = image_dpi(file)\n im_new = remove_noise_and_smooth(temp)\n return im_new\n\n\ndef image_dpi(file):\n im =... | [
[
"numpy.ones"
]
] |
apsdehal/nli-batch-optimizations | [
"946dbeae58edd39dcda948d03765f7b1070b4eab"
] | [
"parikh-et-al-and-bilstm-max-pool/modules/BiRNNEncoder.py"
] | [
"from torch import nn\n\nfrom modules.TimeDistributed import TimeDistributed\nfrom modules.Utils import utils\n\n\nclass BiRNNEncoder(nn.Module):\n def __init__(self, max_length, nr_hidden, dropout=0.0):\n super(BiRNNEncoder, self).__init__()\n\n self.nr_hidden = nr_hidden\n\n self.fully_con... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.LSTM",
"torch.nn.ReLU"
]
] |
cn007b/stash | [
"bae604d3056f09b9b6c6b3e0282f02c829801f5c"
] | [
"ed/ai/ml/tensorflow/examples/one.py"
] | [
"import tensorflow as tf\nimport tensorflow.compat.v1 as tf1\n\n\ndef p(v):\n print(\"\\n==========\\n\", v, \"\\n==========\\n\")\n\n\ndef f1():\n c = tf.constant('100')\n p(c)\n tf.print(c)\n\n\ndef f2():\n a = tf.Variable(2.0, name='a')\n p(a)\n\n\ndef f3():\n x1 = tf.constant([1,2,3,4])\n x2 = tf.consta... | [
[
"tensorflow.compat.v1.placeholder",
"tensorflow.multiply",
"tensorflow.compat.v1.disable_v2_behavior",
"tensorflow.Variable",
"tensorflow.print",
"tensorflow.constant"
]
] |
JS00000/trading_simulation | [
"10f216182bd4eed8ec7af45ca0dd0c48af9b3ec2"
] | [
"helper/test.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\n\nx = np.linspace(0, 1, 10)\nnumber = 10\ncmap = plt.get_cmap('gnuplot')\n\n# colors = [cmap(i) for i in np.linspace(0, 1, number)]\n\ncolors = [(i/number, 0, 0, 1) for i in range(number)]\n\nfor i, color in enumerate(colors, start=1):\n plt.plot(x, i * x + i... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.show",
"numpy.linspace",
"matplotlib.pyplot.get_cmap"
]
] |
phlong3105/onevision | [
"90552b64df7213e7fbe23c80ffd8a89583289433",
"90552b64df7213e7fbe23c80ffd8a89583289433"
] | [
"src/onevision/nn/layer/weight_init.py",
"src/onevision/cv/imgproc/filtering/filter.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Weight Initialization.\n\"\"\"\n\nfrom __future__ import annotations\n\nimport math\n\nimport torch\nimport torch.nn as nn\nfrom torch import Tensor\nfrom torch.nn.init import _calculate_fan_in_and_fan_out\n\nfrom onevision import error_console\n\n__all__ = [... | [
[
"torch.nn.init._calculate_fan_in_and_fan_out",
"torch.no_grad"
],
[
"torch.nn.functional.pad"
]
] |
zarzen/Megatron-LM | [
"d898a8991d1a08d29074f87819d1bf41517e35f5"
] | [
"tasks/finetune_utils.py"
] | [
"# coding=utf-8\n# Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0... | [
[
"torch.distributed.barrier",
"torch.nn.CrossEntropyLoss",
"torch.utils.data.distributed.DistributedSampler",
"torch.utils.data.DataLoader"
]
] |
jlmaurer/tsfresh | [
"4efea9abf4cd4953712b577c56a05b83a5986eb0"
] | [
"tests/test_feature_significance.py"
] | [
"# -*- coding: utf-8 -*-\n# This file as well as the whole tsfresh package are licenced under the MIT licence (see the LICENCE.txt)\n# Maximilian Christ (maximilianchrist.com), Blue Yonder Gmbh, 2016\n\nimport numpy as np\nimport pandas as pd\nfrom unittest import TestCase\nimport tsfresh.feature_selection.feature_... | [
[
"numpy.random.normal",
"numpy.random.binomial",
"numpy.random.seed",
"numpy.random.poisson",
"numpy.sqrt"
]
] |
michaelaye/xarray | [
"52043bc57f20438e8923790bca90b646c82442ad"
] | [
"xarray/tests/test_dataarray.py"
] | [
"import pickle\nimport sys\nimport warnings\nfrom copy import deepcopy\nfrom textwrap import dedent\n\nimport numpy as np\nimport pandas as pd\nimport pytest\n\nimport xarray as xr\nfrom xarray import DataArray, Dataset, IndexVariable, Variable, align, broadcast\nfrom xarray.coding.times import CFDatetimeCoder\nfro... | [
[
"numpy.testing.assert_allclose",
"numpy.random.rand",
"numpy.tile",
"numpy.mean",
"numpy.tensordot",
"numpy.random.random",
"numpy.full",
"numpy.sin",
"pandas.DataFrame",
"numpy.flipud",
"pandas.Panel",
"numpy.arange",
"pandas.testing.assert_index_equal",
"n... |
luzvazgal/web-scraping-challenge | [
"8b74aba4e0813ec2b365b985ea19ec0b52772524"
] | [
"scrape_mars.py"
] | [
"\n\n# Knowing more about Mars\n#This function returns a dictionary containing all relevant data from Mars\n\n#Importing required libraries\nfrom splinter import Browser\nfrom bs4 import BeautifulSoup\nfrom webdriver_manager.chrome import ChromeDriverManager\n#To use Regular expressions in parsing HTML, the 're' li... | [
[
"pandas.read_html"
]
] |
pinkw/fastNLP | [
"ff8b9a37a71e9b7f7787df8a230446d483b5dfdf"
] | [
"fastNLP/core/metrics.py"
] | [
"r\"\"\"\nmetrics 模块实现了 fastNLP 所需的各种常用衡量指标，一般做为 :class:`~fastNLP.Trainer` 的参数使用。\n\n\"\"\"\n__all__ = [\n \"MetricBase\",\n \"AccuracyMetric\",\n \"SpanFPreRecMetric\",\n \"CMRC2018Metric\",\n \"ClassifyFPreRecMetric\",\n \"ConfusionMatrixMetric\"\n]\n\nimport inspect\nimport warnings\nfrom abc i... | [
[
"torch.eq",
"numpy.sum",
"numpy.any",
"numpy.argsort",
"torch.ones_like",
"numpy.expand_dims",
"torch.sum"
]
] |
GioCurnis/DeepGlobalRegistration | [
"c2a08c87d28b784c3e34fdcf5aed5b98e3ad2a73"
] | [
"util/pointcloud.py"
] | [
"# Copyright (c) Chris Choy (chrischoy@ai.stanford.edu) and Wei Dong (weidong@andrew.cmu.edu)\n#\n# Please cite the following papers if you use any part of the code.\n# - Christopher Choy, Wei Dong, Vladlen Koltun, Deep Global Registration, CVPR 2020\n# - Christopher Choy, Jaesik Park, Vladlen Koltun, Fully Convolu... | [
[
"numpy.array",
"numpy.dot",
"numpy.asarray",
"numpy.zeros",
"numpy.mean",
"numpy.identity",
"numpy.random.uniform",
"numpy.power",
"numpy.linalg.inv"
]
] |
JuliousHurtado/Meta-Iteration | [
"8edf09510c9c8c300c8ca42472e7e04bfd790938"
] | [
"method/maml.py"
] | [
"import traceback\nfrom torch.autograd import grad\n\nfrom learn2learn.algorithms.base_learner import BaseLearner\nfrom learn2learn.utils import clone_module\n\n\ndef maml_update(model, lr, grads=None):\n \"\"\"\n [[Source]](https://github.com/learnables/learn2learn/blob/master/learn2learn/algorithms/maml.py)... | [
[
"torch.autograd.grad"
]
] |
mmonfils/solar-eclipses | [
"061de4f20192e180e2777fa6d576f199d0fb6f32"
] | [
"solar_eclipses.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Wed Oct 6 17:22:43 2021\n\n@author: mmonf\n\"\"\"\n\nimport pandas as pd\nimport requests\n\n# Writing a script to retrieve and locally save the data\n# from the Wikipedia website\n\nurl = \"https://en.wikipedia.org/wiki/\" \\\n \"List_of_solar_eclipses_in_the_21st_c... | [
[
"pandas.read_html"
]
] |
vnittur/asl-ml-immersion | [
"c39cbada51951b79c0c93173ba55411bd1504010"
] | [
"notebooks/kubeflow_pipelines/pipelines/solutions/trainer_image_vertex/train.py"
] | [
"# Copyright 2021 Google Inc. 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 required ... | [
[
"sklearn.preprocessing.StandardScaler",
"sklearn.linear_model.SGDClassifier",
"pandas.concat",
"pandas.read_csv",
"sklearn.preprocessing.OneHotEncoder"
]
] |
midsdsy/LOD-Net | [
"2669fc70533c3fe7d74c5a819d1f642a007bfda4"
] | [
"projects/LOD-Net/seman_mask_evaluate.py"
] | [
"# import mmcv\nimport numpy as np\nimport argparse\nimport numpy as np\nimport os\nimport cv2\nfrom tqdm import tqdm\nfrom detectron2.config import get_cfg\nfrom detectron2.data.datasets import register_coco_instances\nfrom detectron2.data import (\n build_detection_test_loader,\n)\nfrom lod_net import add_lod_... | [
[
"numpy.nan_to_num",
"numpy.arange",
"numpy.load",
"numpy.zeros"
]
] |
roshansh-cmu/espnet | [
"5fa6dcc4e649dc66397c629d0030d09ecef36b80",
"5fa6dcc4e649dc66397c629d0030d09ecef36b80",
"5fa6dcc4e649dc66397c629d0030d09ecef36b80",
"5fa6dcc4e649dc66397c629d0030d09ecef36b80"
] | [
"test/test_e2e_compatibility.py",
"espnet/nets/pytorch_backend/e2e_st.py",
"espnet/asr/pytorch_backend/recog.py",
"espnet2/torch_utils/initialize.py"
] | [
"#!/usr/bin/env python3\n# coding: utf-8\n\n# Copyright 2019 Tomoki Hayashi\n# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)\n\nfrom __future__ import print_function\n\nimport importlib\nimport os\nimport re\nimport shutil\nimport subprocess\nimport tempfile\nfrom os.path import join\n\nimport chainer\n... | [
[
"torch.no_grad",
"numpy.random.randn"
],
[
"torch.nn.Dropout",
"numpy.array",
"torch.no_grad",
"numpy.fromiter",
"numpy.ones",
"torch.nn.Module.__init__",
"numpy.prod",
"torch.tensor",
"torch.as_tensor",
"torch.nn.Embedding",
"torch.sum"
],
[
"torch.... |
WMD-group/TrapLimitedConversion | [
"cf652e7aa0ea5e8b2162c2e5ffedec037c1ff705"
] | [
"wannier90-absorption/wannier_alpha.py"
] | [
"#!/usr/bin/env python3\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\neV2Icm = 8.065E3 \nhbar = 6.582119569E-16\t# [eV*s]\n# sigma_si2cgs = 9E11 # [S/cm] -> [1/sec] # 1/(4pi * 8.8541878128E-12) [F/m] \nvac_permittivity = 8.8541878128E-12 \nc = 29979245800\n\n\ndef read_kubo(filename... | [
[
"numpy.array",
"scipy.integrate.simps",
"pandas.DataFrame",
"numpy.sum",
"numpy.real",
"numpy.where",
"numpy.sqrt",
"numpy.abs",
"numpy.log10",
"matplotlib.pyplot.show",
"pandas.read_csv",
"matplotlib.pyplot.subplot"
]
] |
Ze-Yang/Context-Transformer | [
"493fb6b3eb9f546dc172601de787fe89a1489065",
"493fb6b3eb9f546dc172601de787fe89a1489065"
] | [
"test.py",
"data/voc_eval.py"
] | [
"from __future__ import print_function\nimport os\nimport pickle\nimport argparse\nimport torch\nimport torch.backends.cudnn as cudnn\nimport numpy as np\nfrom data import AnnotationTransform, COCODetection, VOCDetection, BaseTransform, \\\n VOC_300, VOC_512, COCO_300, COCO_512, VOCroot, COCOroot\nfrom layers.fu... | [
[
"numpy.empty",
"torch.no_grad",
"numpy.where",
"torch.cuda.is_available",
"numpy.sort",
"numpy.hstack",
"torch.Tensor"
],
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.minimum",
"numpy.sum",
"numpy.where",
"numpy.finfo",
... |
Mythologos/data-science-project | [
"8cddd73f97617f8a3b8cb74d6df096e411b1c1ed"
] | [
"classifiers/prototypical.py"
] | [
"\"\"\"\nThis file contains the prototypical network.\n\nCurrently, it takes three optional arguments:\n * learning-rate: a floating point value indicating the learning rate of the neural network.\n * max-epochs: an integer indicating the maximum number of epochs for which the network will be trained.\n * ... | [
[
"numpy.concatenate",
"numpy.array",
"torch.optim.lr_scheduler.StepLR",
"scipy.ndimage.rotate",
"torch.arange",
"torch.nn.MaxPool2d",
"torch.autograd.Variable",
"numpy.random.permutation",
"torch.nn.BatchNorm2d",
"torch.from_numpy",
"torch.nn.ReLU",
"torch.nn.functio... |
huunghia160799/simsg | [
"225632f496695d3964e59af372048c97b9bc0fb8"
] | [
"PerceptualSimilarity/models/networks_basic.py"
] | [
"\nfrom __future__ import absolute_import\n\nimport sys\nimport torch\nimport torch.nn as nn\nimport torch.nn.init as init\nfrom torch.autograd import Variable\nimport numpy as np\nfrom pdb import set_trace as st\nfrom skimage import color\nfrom IPython import embed\nfrom . import pretrained_networks as pn\n\nfrom ... | [
[
"torch.cat",
"torch.nn.Dropout",
"torch.nn.Sigmoid",
"torch.nn.Sequential",
"torch.nn.LeakyReLU",
"torch.nn.Upsample",
"torch.nn.Conv2d",
"torch.nn.BCELoss",
"torch.Tensor",
"torch.mean"
]
] |
sungyubkim/GBML | [
"1577e172dc5852267ad0b94cdb9c175a5ca7018e"
] | [
"gbml/reptile.py"
] | [
"import numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport higher\n\nfrom gbml.gbml import GBML\nfrom utils import get_accuracy, apply_grad, mix_grad, grad_to_cos, loss_to_ent\n\nclass Reptile(GBML):\n\n def __init__(self, args):\n super().__init__(args)\n sel... | [
[
"torch.enable_grad",
"torch.nn.functional.cross_entropy",
"torch.no_grad"
]
] |
austiezr/DS-12-Web-App | [
"1e2d8d9f3fc3d03e242b07fc25bc0377bfc289ec"
] | [
"web_app/routes/stats_routes.py"
] | [
"from flask import Blueprint, request, jsonify, render_template\nfrom sklearn.linear_model import LogisticRegression\nfrom web_app.models import User, Tweet\nimport basilica\nimport os\n\nAPI_KEY = os.getenv('BASILICA_API_KEY')\n\nconnection = basilica.Connection(API_KEY)\n\nstats_routes = Blueprint('stats_routes',... | [
[
"sklearn.linear_model.LogisticRegression"
]
] |
kbrodt/tor4 | [
"d09740b746c534e67a72f492c7c03654f5888a46"
] | [
"tor4/nn/functional.py"
] | [
"import typing as t\n\nimport numpy as np\nfrom scipy import special\n\nimport tor4\n\nfrom ..tensor import Array, Tensor\nfrom .modules.utils import _pair\n\n# Activations\n\n\ndef relu(input: Tensor, inplace: bool = False) -> Tensor:\n mask = input.data > 0\n data = mask * input.data\n\n requires_grad = ... | [
[
"scipy.special.softmax",
"scipy.special.logsumexp",
"numpy.zeros_like",
"numpy.random.binomial",
"numpy.tile",
"scipy.special.expit",
"numpy.put_along_axis",
"numpy.tensordot",
"numpy.take_along_axis",
"numpy.arange",
"numpy.swapaxes",
"numpy.prod",
"numpy.repea... |
kiralpoon/TwinGAN | [
"af067039d4706312c67a9a38ed7f59a3e53831ae"
] | [
"inference/image_translation_infer.py"
] | [
"# Copyright 2018 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 applicable law or agreed ... | [
[
"tensorflow.flags.DEFINE_string",
"tensorflow.expand_dims",
"tensorflow.get_default_graph",
"tensorflow.image.convert_image_dtype",
"tensorflow.Session",
"tensorflow.ConfigProto",
"tensorflow.flags.mark_flags_as_required",
"tensorflow.placeholder",
"tensorflow.flags.DEFINE_inte... |
kemaloksuz/fullgrad-saliency | [
"afa1a55ebf36ac195a90f6e82dc617fcc7c11d72"
] | [
"models/resnet.py"
] | [
"#\n# Copyright (c) 2019 Idiap Research Institute, http://www.idiap.ch/\n# Written by Suraj Srinivas <suraj.srinivas@idiap.ch>\n#\n# Adapted from - https://github.com/pytorch/vision/blob/master/torchvision/models/resnet.py\n\n\"\"\"\n Define ResNet models with getBiases() and getFeatures() methods.\n\n For co... | [
[
"torch.nn.Linear",
"torch.device",
"torch.zeros",
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"torch.hub.load_state_dict_from... |
solarFP/FP | [
"a7c7f318ce162e2ab54d37f2f2231efd051e3280"
] | [
"python/fp.py"
] | [
"class fpoutClass:\n pass\n\ndef readout(outfile,atmfile,fpout):\n import h5py\n import numpy as np\n with h5py.File(outfile, 'r') as h5f:\n fpout.inputparams = dict(h5f['inputparams'].attrs)\n fpout.atm = dict(h5f['atm'].attrs)\n fpout.atm['zin'] = np.array(h5f['atm/zin'])\n fpout.atm['tg'] = n... | [
[
"numpy.array",
"numpy.arccos",
"numpy.sin",
"numpy.ones",
"numpy.diff",
"numpy.einsum",
"numpy.cos",
"numpy.sqrt",
"numpy.outer"
]
] |
BaraaUniKassel/simbench | [
"eca679bbef2b7c61d4a42dd9d9716ad969ff6f77"
] | [
"simbench/test/networks/test_extract_grids_from_csv.py"
] | [
"# Copyright (c) 2019-2021 by University of Kassel, Tu Dortmund, RWTH Aachen University and Fraunhofer\n# Institute for Energy Economics and Energy System Technology (IEE) Kassel and individual\n# contributors (see AUTHORS file for details). All rights reserved.\n\nimport pytest\nimport os\nfrom copy import deepcop... | [
[
"pandas.DataFrame",
"pandas.Series",
"pandas.concat"
]
] |
Phonicavi/pytorch-distributed-example | [
"ee74b94786de988e7f87274fa110214aba27569a"
] | [
"mnist/main.py"
] | [
"from __future__ import division, print_function\n\nimport argparse\nimport sys\nimport time\nimport torch\nimport torch.nn.functional as F\nfrom torch import distributed, nn\nfrom torch.utils import data\nfrom torch.utils.data.distributed import DistributedSampler\nfrom torchvision import datasets, transforms\n\n\... | [
[
"torch.nn.Linear",
"torch.device",
"torch.distributed.get_world_size",
"torch.distributed.init_process_group",
"torch.no_grad",
"torch.nn.functional.cross_entropy",
"torch.cuda.is_available",
"torch.distributed.all_reduce",
"torch.utils.data.distributed.DistributedSampler"
]
... |
ghbrown/taylor | [
"3953b3e06d75292bf811bac41bdedc3b705df4ee"
] | [
"taylor/error.py"
] | [
"\nimport numpy as np\nfrom numpy import ma\n\n\ndef rel_error(measured,exact):\n \"\"\"\n computes the relative error between two scalars or arrays\n in a way robust to division by zero\n\n ---Inputs---\n measured : {scalar, array}\n measured or approximate value(s)\n exact: {scalar, array... | [
[
"numpy.abs"
]
] |
LeviBorodenko/MyAIGuide | [
"3077173e63537522a49d50da5872147460c6469f"
] | [
"scripts/1_createDataFrame.py"
] | [
"import csv\nimport datetime\nimport os\nimport os.path\nimport pickle\nimport re\n\nimport numpy as np\nimport pandas as pd\n\nimport sys\nsys.path.insert(1, '../src/MyAIGuide/data')\n\nfrom storeBasisPeakInDataFrame import storeBasisPeakInDataFrame\nfrom fitbitDataGatheredFromWebExport import fitbitDataGatheredFr... | [
[
"pandas.DataFrame",
"pandas.date_range",
"numpy.full",
"numpy.zeros"
]
] |
oja/qfsumm | [
"dfa3541cfad928df412c86888ef0354ea97e8382"
] | [
"src/models/trainer_ext.py"
] | [
"import os\n\nimport numpy as np\nimport torch\nfrom tensorboardX import SummaryWriter, proto\n\nimport distributed\nfrom models.reporter_ext import ReportMgr, Statistics\nfrom others.logging import logger\nfrom others.utils import test_rouge, rouge_results_to_str\n\nimport json\n\nimport copy\n\nfrom train_abstrac... | [
[
"torch.no_grad",
"torch.save",
"torch.nn.BCELoss",
"numpy.argsort"
]
] |
sunil-at-gh/KerasText | [
"cb678ac3a6c58071bc4a3e20895f6497bef416d6"
] | [
"kerastext/utils.py"
] | [
"\"\"\"\nGeneral Utility and other functions.\nMostly platform dependent code.\n\"\"\"\n\n# noinspection PyPep8Naming\nimport keras.backend as K\n\nif K.backend() == 'tensorflow':\n import tensorflow as tf\n\n\ndef force_masked_to_zero(x, mask, x_ndim=None):\n \"\"\"\n Return a copy of tensor where the mas... | [
[
"tensorflow.rank",
"tensorflow.shape",
"tensorflow.where",
"tensorflow.zeros_like",
"tensorflow.gather"
]
] |
JJSrra/Research-GroupRecommendersForMovies | [
"5ff66865192e648a3f1d280f7fea671e5ea7f09a"
] | [
"optimist.py"
] | [
"import numpy as np\nimport evaluation\nimport baseline\n\ndef predict_individual_rating_for_movie(user, group, movie, movie_ratings, pearson_matrix):\n dim = len(pearson_matrix) # Rembember that User IDs start at 1 but we need a 0 row/column, so this is 1 more\n available_neighbors = [user for user in range(... | [
[
"numpy.sum",
"numpy.delete",
"numpy.apply_along_axis",
"numpy.argsort"
]
] |
cdicle-motional/l5kit | [
"4dc4ee5391479bb71f0b373f39c316f9eef5a961",
"4dc4ee5391479bb71f0b373f39c316f9eef5a961",
"4dc4ee5391479bb71f0b373f39c316f9eef5a961"
] | [
"l5kit/l5kit/vectorization/vectorizer_builder.py",
"l5kit/l5kit/planning/vectorized/closed_loop_model.py",
"l5kit/l5kit/rasterization/render_context.py"
] | [
"import numpy as np\n\nfrom l5kit.configs.config import load_metadata\nfrom l5kit.data.map_api import MapAPI\nfrom l5kit.vectorization.vectorizer import Vectorizer\n\nfrom ..data import DataManager\n\n\ndef build_vectorizer(cfg: dict, data_manager: DataManager) -> Vectorizer:\n \"\"\"Factory function for vectori... | [
[
"numpy.array"
],
[
"torch.cat",
"torch.stack",
"torch.eye",
"torch.ones_like",
"torch.zeros_like",
"torch.tanh",
"torch.flip"
],
[
"numpy.sin",
"numpy.array",
"numpy.linalg.inv",
"numpy.cos"
]
] |
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