repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list | possible_versions list |
|---|---|---|---|---|---|
cxy1997/Transferable-Active-Grasping | [
"a826889bcdc466a59696e7d65f024a6c8237f6ed"
] | [
"viewpoint_optim/RL_pointnet/evaluate.py"
] | [
"from __future__ import print_function\n\nimport numpy as np\nimport argparse\nimport os\nimport sys\nsys.path.append('..')\nimport time\n\nimport torch\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.autograd import Variable\nfrom torch.utils.cpp_extension import load\n\nfrom environment ... | [
[
"torch.nn.functional.softmax",
"numpy.random.seed",
"torch.load",
"torch.zeros",
"torch.manual_seed",
"torch.from_numpy",
"torch.no_grad",
"torch.cuda.is_available"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mkarthick271/oid_fasterrcnn | [
"9b07d6ba9a9e0f83f0d4f68df9c29a811408c75f"
] | [
"valprepoid.py"
] | [
"import pandas as pd\nfrom imageio import imread\nimport psycopg2\nimport numpy as np\nimport csv \nimport pickle\nimport os\nfrom imageio import imread \nimport pdb\nimport copy\nimport json\nimport csv\n\ndef init_data():\n root_dir = os.path.abspath(os.path.dirname(__file__))\n labdata = pd.read_csv(root_d... | [
[
"numpy.argsort",
"numpy.array",
"pandas.read_csv",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
sssssdzxc/CMU10703_Assignments | [
"ddb5c41db6e5632cbc088cb0f4c1b9214110f6f2"
] | [
"HW2/deeprl_hw2/preprocessors.py"
] | [
"\n\"\"\"Suggested Preprocessors.\"\"\"\n\nimport numpy as np\nfrom PIL import Image\nfrom collections import deque\nimport time\n\nfrom deeprl_hw2 import utils\nfrom deeprl_hw2.core import Preprocessor\n\n\nclass HistoryPreprocessor(Preprocessor):\n \"\"\"Keeps the last k states.\n\n Useful for domains where... | [
[
"numpy.random.randint",
"numpy.array",
"numpy.zeros",
"numpy.clip"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
shaun95/LPCNet | [
"117214c3a63d4f43cf5741b299c497e85c983327"
] | [
"dump_lpcnet.py"
] | [
"#!/usr/bin/python3\n'''Copyright (c) 2017-2018 Mozilla\n\n Redistribution and use in source and binary forms, with or without\n modification, are permitted provided that the following conditions\n are met:\n\n - Redistributions of source code must retain the above copyright\n notice, this list of conditi... | [
[
"numpy.diag",
"numpy.dot",
"numpy.abs",
"numpy.reshape",
"numpy.concatenate",
"numpy.append",
"numpy.transpose",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
fornaxai/Mars-Express-Challenge | [
"4e0dff9909df0d10e507083af59326b3342d67fe"
] | [
"preprocessing/prepare_evtf.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n@author: fornax\n\"\"\"\nfrom __future__ import print_function, division\nimport os\nimport numpy as np\nimport pandas as pd\n\nos.chdir(os.path.dirname(os.path.abspath(__file__)))\nos.sys.path.append(os.path.dirname(os.getcwd()))\nimport prepare_data1 as prep\nDATA_PATH = os.path.... | [
[
"numpy.unique"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
PuchatekwSzortach/printed_characters_net | [
"9478d4ecffeca040cc353676382d0ec775558458"
] | [
"net/vision.py"
] | [
"\"\"\"\nModule with computer vision related code.\nDetecting card candidates in images, handling image contours and like.\n\"\"\"\nimport cv2\nimport numpy as np\n\n\nclass CardCandidate:\n \"\"\"\n A very simple container for a card candidate\n \"\"\"\n\n def __init__(self, coordinates, image):\n\n ... | [
[
"numpy.squeeze",
"numpy.linalg.norm",
"numpy.arccos",
"numpy.tile",
"numpy.max",
"numpy.argmax",
"numpy.zeros_like",
"numpy.diff",
"numpy.argmin",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
manipopopo/pytorch-lightning | [
"ef7d41692ca04bb9877da5c743f80fceecc6a100"
] | [
"pytorch_lightning/plugins/training_type/ddp_spawn.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.distributed.init_process_group",
"torch.multiprocessing.spawn",
"torch.cuda.set_device",
"torch.distributed.is_initialized",
"torch.distributed.barrier",
"torch.multiprocessing.get_context",
"torch.distributed.get_backend"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
liuzhongling/Image-Captioning-Project-CVND | [
"85a6ae87bd3994e42c411ee748cc16fab7300dd6"
] | [
"data_loader.py"
] | [
"import nltk\nimport os\nimport torch\nimport torch.utils.data as data\nfrom vocabulary import Vocabulary\nfrom PIL import Image\nfrom pycocotools.coco import COCO\nimport numpy as np\nfrom tqdm import tqdm\nimport random\nimport json\n\ndef get_loader(transform,\n mode='train',\n batch_... | [
[
"torch.Tensor",
"numpy.random.choice",
"torch.utils.data.DataLoader",
"torch.utils.data.sampler.SubsetRandomSampler",
"numpy.array",
"torch.utils.data.sampler.BatchSampler"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
goofyweng/mavros_multi_uav_control | [
"60a17e59bd54b491521ac4fb173c9bca74490718"
] | [
"scripts/ru_s mTSP/f.py"
] | [
"#!/usr/bin/env python\n#coding=utf-8\n\n# calculate the individual ant's fitness\ndef longest_len(colony,edges,antNo,gp,n):\n # 回傳本次旅行團所需的最長距離\n import numpy as np\n\n indi_max=np.zeros((antNo,1))\n\n\n for i in range(antNo):\n length=np.zeros((gp,1))\n\n for k in range(gp):\n ... | [
[
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Anonymous-ICML2022/Multi-Agent-Constrained-Policy-Optimisation | [
"0bfe52024e4d07600a39d3228de36fd75a3cd65d"
] | [
"MACPO/macpo/envs/safety_ma_mujoco/safety_multiagent_mujoco/coupled_half_cheetah.py"
] | [
"import numpy as np\nfrom gym import utils\nfrom gym.envs.mujoco import mujoco_env\nfrom macpo.envs.safety_ma_mujoco.safety_multiagent_mujoco import mujoco_env\nimport os\nimport mujoco_py as mjp\nfrom gym import error, spaces\n\nclass CoupledHalfCheetah(mujoco_env.MujocoEnv, utils.EzPickle):\n def __init__(self... | [
[
"numpy.squeeze",
"numpy.sin",
"numpy.abs",
"numpy.clip"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
CityU-AIM-Group/GFBS | [
"d71361243f1bcf699e1a20b312b05fe0be4dfd6d"
] | [
"gfbs.py"
] | [
"'''Train CIFAR10 with PyTorch.'''\nimport torch\nimport logging\nimport datasets\nimport numpy as np\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.nn.functional as F\nimport torchvision\nfrom torch.optim.lr_scheduler import MultiStepLR\nfrom torch.utils.tensorboard import SummaryWriter\nfrom to... | [
[
"torch.optim.lr_scheduler.MultiStepLR",
"torch.norm",
"torch.cuda.manual_seed",
"torch.load",
"torch.manual_seed",
"torch.nn.functional.cross_entropy",
"torch.utils.data.DataLoader",
"torch.sum",
"torch.no_grad",
"torch.cuda.is_available",
"torch.nn.DataParallel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Leputa/MANN-meta-learning | [
"c2f32ca6db9bf545ffb9c0da0bc9fb0d93074055"
] | [
"mann/mann_cell.py"
] | [
"import tensorflow as tf\nimport numpy as np\nfrom mann.utils.tf_utils import variable_one_hot\n\n\nclass MANNCell():\n def __init__(self, lstm_size, memory_size, memory_dim, nb_reads,\n gamma=0.95, reuse=False):\n self.lstm_size = lstm_size\n self.memory_size = memory_size\n ... | [
[
"tensorflow.nn.rnn_cell.BasicLSTMCell",
"tensorflow.matmul",
"tensorflow.concat",
"tensorflow.nn.softmax",
"tensorflow.transpose",
"tensorflow.zeros",
"tensorflow.random_uniform_initializer",
"tensorflow.reduce_sum",
"tensorflow.sigmoid",
"tensorflow.expand_dims",
"nump... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
fabiofumarola/pytorch-toolbelt | [
"bf2915c4c4ac602b9e177a8d8ff796e8268b5def"
] | [
"pytorch_toolbelt/inference/tta.py"
] | [
"\"\"\"Implementation of GPU-friendly test-time augmentation for image segmentation and classification tasks.\n\nDespite this is called test-time augmentation, these method can be used at training time as well since all\ntransformation written in PyTorch and respect gradients flow.\n\"\"\"\nfrom functools import pa... | [
[
"torch.chunk",
"torch.nn.functional.interpolate",
"torch.stack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
eneelo/chaospy | [
"da31792fa5d58c231a77e04234b32cb90df6c6d8"
] | [
"chaospy/quadrature/sparse_grid.py"
] | [
"\"\"\"Smolyak sparse grid constructor.\"\"\"\nfrom collections import defaultdict\nfrom itertools import product\n\nimport numpy\nfrom scipy.special import comb\n\nimport numpoly\nimport chaospy\n\n\ndef construct_sparse_grid(\n order,\n dist,\n growth=None,\n recurrence_algorithm=\"sti... | [
[
"numpy.array",
"numpy.sum",
"numpy.prod",
"numpy.min"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
HekpoMaH/algorithmic-concepts-reasoning | [
"17c87faad2fbe8481455de34a145a4753a2fe4d0"
] | [
"algos/models/algorithm_coloring.py"
] | [
"import torch\r\nfrom overrides import overrides\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\nfrom algos.models import AlgorithmBase\r\n\r\nclass AlgorithmColoring(AlgorithmBase):\r\n '''\r\n The overriding in this class comes from the fact that (only) the parallel\r\n coloring ouptuts ar... | [
[
"torch.cat",
"torch.sum",
"torch.nn.Linear",
"torch.nn.LeakyReLU",
"torch.arange",
"torch.nn.functional.one_hot"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Juanjoglvz/DataMining | [
"9dfdb9b973ce7ff724784299862db5cb19cc1284"
] | [
"src/data/make_dataset.py"
] | [
"import pandas as pd\n\n\n\n# We read the csv\ndf118 = pd.read_csv(\"../../data/raw/0118.csv\")\ndf218 = pd.read_csv(\"../../data/raw/0218.csv\")\ndf318 = pd.read_csv(\"../../data/raw/0318.csv\")\ndf418 = pd.read_csv(\"../../data/raw/0418.csv\")\ndf417 = pd.read_csv(\"../../data/raw/0417.csv\")\ndf518 = pd.read_csv... | [
[
"pandas.read_csv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
ashavish/tensorflow-yolov3 | [
"a4940cdc918a2b2e6fe518231e0704fa70f0e5ea"
] | [
"predict_image_rotated.py"
] | [
"import cv2\nimport os\nimport shutil\nimport numpy as np\nimport tensorflow as tf\nimport core.utils as utils\nfrom core.config import cfg\nfrom core.yolov3 import YOLOV3\nimport core.utils as utils\nfrom PIL import Image\n\nclass YoloTest(object):\n def __init__(self):\n self.input_size = cfg.TEST... | [
[
"numpy.reshape",
"tensorflow.placeholder",
"tensorflow.ConfigProto",
"numpy.copy",
"tensorflow.train.ExponentialMovingAverage",
"tensorflow.name_scope",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
floresdwm/thesis | [
"8780455c27a9f96e3c4e49c629ef1e31c8849604"
] | [
"Classes/Plots.py"
] | [
"import os\nimport seaborn as sns; sns.set()\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport numpy as np\nfrom matplotlib.patches import Ellipse\nimport matplotlib.transforms as transforms\nimport Classes.RegressionAnalysis as pls\nimport Classes.Configurations as cfg\nfrom sklearn.model_selection imp... | [
[
"matplotlib.pyplot.legend",
"matplotlib.patches.Ellipse",
"numpy.sqrt",
"matplotlib.pyplot.title",
"matplotlib.pyplot.scatter",
"matplotlib.transforms.Affine2D",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.pyplot.... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
footprint-network/footprint-analytics | [
"5de4932ce1c21860785edcce90ffdf097b6f9921"
] | [
"footprint_airflow/dags/dex/etl_dex_pair_basic.py"
] | [
"from basic.etl_basic import ETLBasic\nfrom config import project_config\nimport os.path\nimport pandas as pd\nimport moment\nfrom models import BigQueryCheckPoint\nfrom datetime import timedelta, datetime\nfrom gql import Client, gql\nfrom gql.transport.aiohttp import AIOHTTPTransport\nfrom utils.upload_csv_to_gsc... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.3",
"1.1",
"1.5",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
Lamanova/Python | [
"deec41917cd96b32834e65de8071f50544d6564d"
] | [
"Module-3/assignment6.py"
] | [
"'''\nauthor: Lama Hamadeh\n'''\n\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n\n#\n# TODO: Load up the Seeds Dataset into a Dataframe\n# It's located at 'Datasets/wheat.data'\n# \n# .. your code here ..\n\nwheat_dataset=pd.read_csv('/Users/ADB3HAMADL/Desktop/Anaconda_Packages/DAT210x-master/Module3/Dat... | [
[
"matplotlib.pyplot.yticks",
"pandas.read_csv",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.xticks",
"matplotlib.pyplot.show"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
uwescience/new_xstate | [
"f7563db624258f43c9547e974a0fd5929fc2fa5b"
] | [
"xstate/python/tests/common/test_data_provider.py"
] | [
"from common import data_provider\nfrom common.trinary_data import TrinaryData\nimport common.constants as cn\nfrom common_python.testing import helpers\nfrom common_python.util.persister import Persister\nimport common_python.util.dataframe as dataframe\n\nimport copy\nimport numpy as np\nimport os\nimport pandas ... | [
[
"numpy.dtype"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
enliktjioe/nn2020 | [
"930ef4168ffbddbb5e81a782ba1328077a4f2525"
] | [
"practice3/neural_net.py"
] | [
"from __future__ import print_function\r\n\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nfrom past.builtins import xrange\r\n\r\nclass TwoLayerNet(object):\r\n \"\"\"\r\n A two-layer fully-connected neural network. The net has an input dimension of\r\n N, a hidden layer dimension of H, and performs... | [
[
"numpy.maximum",
"numpy.random.choice",
"numpy.arange",
"numpy.argmax",
"numpy.random.randn",
"numpy.exp",
"numpy.zeros",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
gzdx-chenghui/qlib-lihua | [
"d5a0ccca059509007b3ea8d734fdbbc77ea915f8"
] | [
"qlib1/data/ops.py"
] | [
"# Copyright (c) Microsoft Corporation.\n# Licensed under the MIT License.\n\n\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport sys\nimport numpy as np\nimport pandas as pd\n\nfrom scipy.stats import percentileofscore\n\nfrom .base import Expression, ExpressionOps\nfrom ..log import... | [
[
"numpy.log",
"pandas.Series",
"numpy.isnan",
"scipy.stats.percentileofscore",
"numpy.seterr",
"numpy.nansum",
"numpy.nanmean",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [
"0.13",
"1.6",
"0.14",
"1.10",
"0... |
sourcery-ai-bot/hpc-in-a-day | [
"51f5fafb04ed3cc0fa681055fba38593fc891f53"
] | [
"_episodes/code/03_parallel_jobs/generate_scrambled_data.py"
] | [
"#!/usr/bin/env python3\nimport sys\nimport numpy as np\n\nnp.random.seed(2017)\n\ndef inside_circle(total_count):\n\n x = np.float32(np.random.uniform(size=total_count))\n y = np.float32(np.random.uniform(size=total_count))\n\n radii = np.sqrt(x*x + y*y)\n\n count = len(radii[np.where(radii<=1.0)])\n\n... | [
[
"numpy.sqrt",
"numpy.random.seed",
"numpy.dtype",
"numpy.random.uniform",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
salesforce/CASPI | [
"3e4cd23f4f3d1fa7132ba89805366472c9fe5983"
] | [
"RewardLearning.py"
] | [
"from gensim.models.keyedvectors import KeyedVectors\nimport json\nfrom tensorflow.keras.callbacks import ReduceLROnPlateau, TensorBoard, ModelCheckpoint, EarlyStopping\nfrom tensorflow.keras.layers import *\nfrom tensorflow.keras.metrics import *\nfrom tensorflow.keras.models import Sequential, Model\nfrom tensorf... | [
[
"tensorflow.keras.backend.repeat_elements",
"pandas.read_csv",
"tensorflow.keras.models.Model",
"numpy.random.choice",
"tensorflow.keras.callbacks.ReduceLROnPlateau",
"tensorflow.keras.backend.sum",
"tensorflow.keras.callbacks.EarlyStopping",
"tensorflow.keras.backend.squeeze",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": [
"2.7",
"2.6",
"2.4",
"2.3",
"2.5",
"2.2"
]
}
] |
ChangminWu/ExpanderGNN | [
"a88bea8ee15d902be2881ec59ec37a8b092a0cd8"
] | [
"nets/citation_node_classification/gin_net.py"
] | [
"import torch.nn as nn\n\nfrom dgl.nn.pytorch.glob import SumPooling, AvgPooling, MaxPooling\n\nfrom layers.gin_layer import GINLayer\nfrom layers.expander.expander_layer import LinearLayer, MultiLinearLayer\nfrom utils import activations\n\n\nclass GINNet(nn.Module):\n def __init__(self, net_params):\n s... | [
[
"torch.nn.CrossEntropyLoss",
"torch.nn.ModuleList"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
raafatzahran/Udacity-DataScience | [
"3e875838cb602865d8b9786fbe940d0704771fca"
] | [
"Lesson7-ensemble_methods/ensemnle-methods/venv/lib/python3.6/site-packages/imblearn/utils/tests/test_validation.py"
] | [
"\"\"\"Test for the validation helper\"\"\"\n# Authors: Guillaume Lemaitre <g.lemaitre58@gmail.com>\n# Christos Aridas\n# License: MIT\n\nfrom collections import Counter\n\nfrom pytest import raises\nimport numpy as np\n\nfrom sklearn.neighbors.base import KNeighborsMixin\nfrom sklearn.neighbors import Nea... | [
[
"numpy.array",
"sklearn.neighbors.NearestNeighbors",
"numpy.ones"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
AndreeaDRacovita/face-recognition | [
"cd1ae58b785034d4e1fdf2c01bc4e32086f099e4"
] | [
"face-recognition.py"
] | [
"import numpy as np\nimport cv2 as cv\nimport face_recognition\n\nvideo_capture = cv.VideoCapture(0, cv.CAP_DSHOW)\n\n# Haar cascade face recognition\nhaar_cascade = cv.CascadeClassifier('haarcascade_frontalface_default.xml')\nface_recognizer = cv.face.LBPHFaceRecognizer_create()\nface_recognizer.read('face_trained... | [
[
"numpy.argmin"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
EvelynYihuiYang/MCMOT | [
"8ea20b57d836cc8f8efe1b13dead3e5d8511c16d"
] | [
"src/lib/utils/image.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft\n# Licensed under the MIT License.\n# Written by Bin Xiao (Bin.Xiao@microsoft.com)\n# Modified by Xingyi Zhou\n# ------------------------------------------------------------------------------\n\nfrom __futur... | [
[
"numpy.dot",
"numpy.maximum",
"numpy.sqrt",
"numpy.arange",
"numpy.cos",
"numpy.sin",
"numpy.ones",
"numpy.finfo",
"numpy.float32",
"numpy.array",
"numpy.exp",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
denred0/mediapipe | [
"e9f4c7b54e68ccd8ea3bca100420d21b2ae6bbe1"
] | [
"denred0_src/inference.py"
] | [
"import os\nimport cv2\nimport sys\nimport time\nimport torch\n\nimport numpy as np\n\nimport albumentations as A\n\nfrom pathlib import Path\n\nfrom hand_detection import get_hands_rects\nfrom face_detection import get_face_rect\n\nfrom model import Model\nfrom albumentations.pytorch import ToTensorV2\n\ntransform... | [
[
"numpy.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
pixelink-support/PixelinkPythonWrapper | [
"ad7ba24c550825eb12f16e1eaf9c66f35db52a8f"
] | [
"samples/Linux/callbackUsingNumPy.py"
] | [
"\"\"\"\r\ncallbackUsingNumPy.py\r\n\r\nDemonstrates how to use callbacks with Callback.PREVIEW, using a NumPy image\r\nThe callback function will modify the preview buffer supplied by the API.\r\n\"\"\"\r\n\r\nfrom pixelinkWrapper import*\r\nfrom ctypes import*\r\nimport time\r\nimport threading\r\nimport numpy as... | [
[
"numpy.frombuffer"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
emosy/scarphase | [
"98734fe149dacccd28b00232deeb15ed43af1031",
"98734fe149dacccd28b00232deeb15ed43af1031"
] | [
"pyscarphase/plot/perfctrs.py",
"pyscarphase/plot/signature.py"
] | [
"# Copyright (c) 2011-2013 Andreas Sembrant\n# All rights reserved.\n#\n# Redistribution and use in source and binary forms, with or without\n# modification, are permitted provided that the following conditions are\n# met:\n#\n# - Redistributions of source code must retain the above copyright\n# notice, this li... | [
[
"matplotlib.pyplot.axes",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pyplot.axes",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
TRex22/picamerax | [
"2e7b05c92331b315533835596862a643ba55b021"
] | [
"docs/examples/yuv_capture4.py"
] | [
"import time\nimport picamerax\nimport picamerax.array\nimport numpy as np\n\nwith picamerax.PiCamera() as camera:\n camera.resolution = (100, 100)\n time.sleep(2)\n y_data = np.empty((112, 128), dtype=np.uint8)\n try:\n camera.capture(y_data, 'yuv')\n except IOError:\n pass\n y_data... | [
[
"numpy.empty"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
smtnkc/bert4epi | [
"e45198916eba6e716be3e1e02c8c2a51de8c9891"
] | [
"combine_results.py"
] | [
"import os\nimport pandas as pd\n\n\nfiles = []\ntrain_cell_lines = []\ntest_cell_lines = []\nf1_scores = []\ntest_times = []\nconfusions = []\n\nfor file in os.listdir(\"results\"):\n if file.endswith(\".txt\") and not file.startswith('training'):\n files.append(file)\n\nfiles = sorted(files)\n\nfor file... | [
[
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
rghosh8/capstone-2 | [
"b7e16642a1f16123f3059db32497ba1c3c815f6f",
"b7e16642a1f16123f3059db32497ba1c3c815f6f"
] | [
"notebooks/preprocessing.py",
"notebooks/NLP_emb_lstm.py"
] | [
"import pandas as pd \n\n\nclass Preprocessing(object):\n def __init__(self, train_datefile, test_datafile):\n self.train_df, self.test_df = pd.read_csv('../data/train.csv'), pd.read_csv('../data/test.csv')\n self.train_df_dis = self.train_df[(self.train_df['target']==1)]\n self.train_df_nod... | [
[
"pandas.read_csv"
],
[
"pandas.read_csv",
"tensorflow.metrics.BinaryAccuracy",
"tensorflow.keras.losses.BinaryCrossentropy",
"tensorflow.keras.optimizers.Adam",
"tensorflow.keras.callbacks.TensorBoard"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1... |
somhathai/Bringing-Old-Photos-Back-to-Life-master | [
"2a2e79af1fdd1b6dc66c4dc91197f757cd3ebfd1"
] | [
"Global/detection.py"
] | [
"# Copyright (c) Microsoft Corporation.\n# Licensed under the MIT License.\n\nimport os\nimport numpy as np\nimport argparse\nimport time\n\nimport torch\nimport torchvision as tv\nimport torch.nn.functional as F\nfrom detection_util.util import *\nfrom detection_models import networks\nfrom PIL import Image, Image... | [
[
"numpy.array",
"torch.unsqueeze",
"torch.load"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
SgtMilk/stock-prediction | [
"2fa9cf851b536ea1cd4fbcf9f767581b36ee38ad"
] | [
"src/predict.py"
] | [
"# Copyright (c) 2021 Alix Routhier-Lalonde. Licence included in root of package.\n\nfrom src.hyperparameters import Train\nfrom src.data import Dataset\nfrom src.model import Net\nfrom src.utils import get_base_path\nimport numpy as np\nimport datetime\nimport os\nimport torch\n\n\ndef predict_stock(code, mode: in... | [
[
"numpy.array",
"torch.cuda.is_available",
"torch.load"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
stancld/adapter-transformers | [
"9a6bf1757b684a4c627c5a35a56e61ea706dccee"
] | [
"src/transformers/adapters/model_mixin.py"
] | [
"import logging\nimport os\nimport warnings\nfrom abc import ABC, abstractmethod\nfrom os.path import join\nfrom typing import List, Optional, Union\n\nimport torch\nfrom torch import nn\n\nfrom .composition import AdapterCompositionBlock, Fuse, Stack, parse_composition\nfrom .configuration import AdapterConfig, Ad... | [
[
"torch.save",
"torch.nn.Embedding.from_pretrained",
"torch.nn.Embedding",
"torch.load"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
vishalbelsare/tanda | [
"83ffe22e3ecd4061e9d96e90d8135fd44cddddce"
] | [
"tanda/discriminator/dcnn.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport numpy as np\nimport tensorflow as tf\nimport tensorflow.contrib.rnn as rnn\n\nfrom .discriminator import Discriminator\nfrom functools import partial\n\n... | [
[
"tensorflow.nn.bias_add",
"tensorflow.matmul",
"tensorflow.shape",
"tensorflow.maximum",
"tensorflow.reshape",
"tensorflow.truncated_normal_initializer",
"tensorflow.constant_initializer",
"tensorflow.variable_scope",
"tensorflow.contrib.layers.batch_norm",
"tensorflow.rand... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
nknetsky/ABASliceDownloader | [
"d5dc0623eafd1fbb8437239b4b1877c89709ee27"
] | [
"function.py"
] | [
"# %%\nfrom selenium import webdriver\nfrom selenium.webdriver.common.by import By\nfrom selenium.webdriver.support.ui import WebDriverWait\nfrom selenium.webdriver.support import expected_conditions as EC\n\nimport pandas as pd\nimport sys\n\nfrom allensdk.api.queries.image_download_api import ImageDownloadApi\nfr... | [
[
"pandas.concat",
"pandas.read_csv",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
FeixLiu/abnet | [
"046feafa9280bc77f61f8ef5f76241e8e0f3ecbc"
] | [
"bert/modeling.py"
] | [
" # coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team.\n# Copyright (c) 2018, 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 ma... | [
[
"torch.nn.Softmax",
"torch.cat",
"torch.load",
"torch.zeros",
"torch.nn.Embedding",
"torch.nn.Dropout",
"torch.nn.CrossEntropyLoss",
"torch.ones",
"torch.sqrt",
"torch.from_numpy",
"torch.arange",
"tensorflow.train.list_variables",
"torch.ones_like",
"torch.... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
liangliannie/hht-spectrum | [
"81820901ea1fdf223c69204e26d2a815b92c2b0b"
] | [
"source/hht.py"
] | [
"from netCDF4 import Dataset\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport math\nfrom PyEMD import EEMD\n\n\ndef plot_imfs(signal, imfs, time_samples=None, fig=None):\n \"\"\"\n plot_imfs function for the Hilbert Huang Transform is adopted from pyhht.\n Author: jaidevd https://github.com/jai... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.tick_params",
"numpy.abs",
"numpy.linspace",
"numpy.asarray",
"matplotlib.pyplot.figure",
"numpy.arctan2",
"numpy.ceil",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.subplot",
"numpy.unwrap",
"numpy.diff",
"numpy.m... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
everymind/SurprisingMinds-Analysis | [
"eeb308043f471de3cdb505f82461cf8d6cf40e16"
] | [
"PythonAnalysisScripts/preprocessing/Average_Clip_Per_Day_PupilDetection_MakingFigs.py"
] | [
"import os\nimport glob\nimport cv2\nimport datetime\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport zipfile\nimport shutil\nimport fnmatch\nimport sys\nimport math\nimport csv\n\n### FUNCTIONS ###\ndef unpack_to_temp(path_to_zipped, path_to_temp):\n try:\n # copy zip file to current working ... | [
[
"numpy.uint8",
"numpy.around",
"numpy.genfromtxt",
"numpy.int",
"numpy.copy",
"numpy.std",
"numpy.mean",
"numpy.savetxt",
"numpy.average",
"numpy.zeros",
"numpy.where"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mli0603/PSMNet | [
"52e36b09529225ffd38a1ceef86976087350b987"
] | [
"dataloader/KITTILoader.py"
] | [
"import os\nimport torch\nimport torch.utils.data as data\nimport torch\nimport torchvision.transforms as transforms\nimport random\nfrom PIL import Image, ImageOps\nimport numpy as np\nfrom dataloader import preprocess\n\nIMG_EXTENSIONS = [\n '.jpg', '.JPG', '.jpeg', '.JPEG',\n '.png', '.PNG', '.ppm', '.PPM'... | [
[
"numpy.ascontiguousarray"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
margaretkennedy/deephaven-core | [
"d1656f0994a42b5fdf51c41c49a63e8d8a2b4088"
] | [
"Integrations/python/test/testPlot.py"
] | [
"#\n# Copyright (c) 2016-2021 Deephaven Data Labs and Patent Pending\n#\n\n\n##############################################################################\n# NOTE: the jvm should have been initialized, or this test will certainly fail\n##############################################################################\... | [
[
"numpy.arange",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
andrewdoss/algorithms_practice | [
"671ae4a4ec05b6cf87ee44faf092456444ed3cf0"
] | [
"algorithms_illuminated/part_4/chapter_20/hueristic_tsp.py"
] | [
"\"\"\"Two-Opt local search for Traveling Salesman Problem.\n\nThis module introduces efficient and approximately correct alternatives to\nexhaustive search.\n\"\"\"\n\n\nimport numpy as np\nimport itertools\n\n\ndef read_edge_file(filename):\n \"\"\"Constructs an undirected adjacency matrix from an edge list.\n... | [
[
"numpy.random.RandomState",
"numpy.random.shuffle",
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
nashory/rtic-gcn-pytorch | [
"75c3a6d6c05dd69f1260db7b0b4bfaca20c56d5d"
] | [
"model/compose_ae.py"
] | [
"import math\nimport random\nimport string\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision\nimport torchvision.models as M\nfrom einops import rearrange\nfrom torch.autograd import Variable\n\nimport model.resnet as resnet\nfrom model.base import Image... | [
[
"torch.nn.BatchNorm1d",
"torch.nn.AdaptiveMaxPool1d",
"torch.nn.Dropout",
"torch.cat",
"torch.sin",
"torch.nn.ModuleDict",
"torch.tensor",
"torch.cuda.FloatTensor",
"torch.nn.Linear",
"torch.nn.Conv1d",
"torch.nn.ReLU",
"torch.nn.MSELoss",
"torch.cos"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
tbarua1/MachneLearning | [
"b810a64f4af23174f273d5afb8d0ab4dad7796e7"
] | [
"Chapter06/ch06.py"
] | [
"# coding: utf-8\n\n\nimport pandas as pd\nfrom sklearn.preprocessing import LabelEncoder\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.decomposition import PCA\nfrom sklearn.linear_model import LogisticRegression\nfrom sklearn.pipeline import ... | [
[
"matplotlib.pyplot.legend",
"numpy.linspace",
"sklearn.model_selection.validation_curve",
"sklearn.metrics.confusion_matrix",
"matplotlib.pyplot.plot",
"sklearn.tree.DecisionTreeClassifier",
"numpy.mean",
"sklearn.metrics.f1_score",
"sklearn.preprocessing.LabelEncoder",
"nu... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
JohnZ03/Open-L2O | [
"06d3860aa9446be2b61368c6ef357a462982db91"
] | [
"Model_Free_L2O/L2O-Scale/L2O-Scale-Training/optimizer/learning_rate_schedule.py"
] | [
"# Copyright 2017 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 by app... | [
[
"tensorflow.get_variable",
"tensorflow.constant",
"tensorflow.scalar_mul",
"tensorflow.minimum",
"tensorflow.constant_initializer",
"tensorflow.gather",
"tensorflow.variable_scope"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.4",
"1.5",
"1.7",
"0.12",
"1.0",
"1.2"
]
}
] |
ngaro/TB2J | [
"2a8dbec0788abe4201fd7001b29b8dfb2aeead64"
] | [
"TB2J/greentest.py"
] | [
"import numpy as np\nfrom scipy.linalg import eigh, inv\n\n\ndef eigen_to_G(evals, evecs, efermi, energy):\n \"\"\" calculate green's function from eigenvalue/eigenvector for energy(e-ef): G(e-ef).\n :param evals: eigen values\n :param evecs: eigen vectors\n :param efermi: fermi energy\n :param ene... | [
[
"numpy.diag",
"numpy.random.random",
"numpy.eye",
"scipy.linalg.eigh",
"scipy.linalg.inv"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"0.12",
"0.14",
"0.15"
],
"tensorflow": []
}
] |
bagnalla/tf_mnist | [
"8410b78568235c13696eb9dfa1133eaba1d68b74"
] | [
"dataset.py"
] | [
"########################################################################\n#\n# Class for creating a data-set consisting of all files in a directory.\n#\n# Example usage is shown in the file knifey.py and Tutorial #09.\n#\n# Implemented in Python 3.5\n#\n#############################################################... | [
[
"numpy.asarray",
"numpy.max",
"numpy.eye"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mckev/ml | [
"148d573a7070ed8bb240729431c3462e76e275e8"
] | [
"classes/ml/genetic.py"
] | [
"from typing import Optional\n\nimport numpy\n\n\nclass Genetic:\n\n @staticmethod\n def crossover_uniform(parent1: numpy.ndarray, parent2: numpy.ndarray, prob_crossover: float = 0.5):\n # prob_crossover of 0.0 will not have any crossover (i.e. offspring1 = parent1 and offspring2 = parent2)\n of... | [
[
"numpy.random.normal",
"numpy.random.random",
"numpy.empty",
"numpy.random.randint"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
qiufengdiewu/LPInsider | [
"92fcc2ad9e05cb634c4e3f1accd1220b984a027d"
] | [
"035textCNN_all.py"
] | [
"# coding=utf-8\nfrom sklearn import metrics\nfrom keras.layers import Reshape\nfrom keras.callbacks import EarlyStopping\nfrom keras import Input, Model\nfrom keras.layers import Dense, Conv1D, GlobalMaxPooling1D, Concatenate\nimport pandas as pd\nimport numpy as np\nimport gensim\nfrom sklearn import preprocessin... | [
[
"numpy.array",
"pandas.read_csv",
"sklearn.metrics.recall_score",
"sklearn.metrics.precision_score",
"sklearn.model_selection.StratifiedKFold",
"numpy.concatenate",
"sklearn.metrics.f1_score",
"numpy.load",
"sklearn.preprocessing.StandardScaler",
"sklearn.preprocessing.scal... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
AlessandroVol23/kdd-cup-2019 | [
"7f140d1d6213dc0d05d07a2c8bff9fe949b72ed8"
] | [
"src/data/raw_features.py"
] | [
"import os\nimport sys\nimport json\nimport math\nimport click\nimport logging\n\nimport pandas as pd\nimport numpy as np\nfrom tqdm import tqdm\n\nfrom pandas.io.json import json_normalize\n\nfrom sklearn.decomposition import TruncatedSVD\nfrom sklearn.feature_extraction.text import TfidfVectorizer\n\ndef read_in_... | [
[
"sklearn.decomposition.TruncatedSVD",
"pandas.concat",
"pandas.to_datetime",
"pandas.merge",
"pandas.notnull",
"numpy.isnan",
"numpy.repeat",
"pandas.DataFrame",
"numpy.std",
"numpy.mean",
"numpy.argsort",
"pandas.io.json.json_normalize",
"numpy.array",
"pan... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"0.19",
"0.24",
"0.20",
"0.25"
],
"scipy": [],
"tensorflow": []
}
] |
rahuja123/reid-strong-baseline | [
"dbc8da7badc616e8ba78471c6e77cc3b21b83759"
] | [
"engine/trainer.py"
] | [
"# encoding: utf-8\n\"\"\"\n@author: sherlock\n@contact: sherlockliao01@gmail.com\n\"\"\"\n\nimport logging\n\nimport torch\nimport torch.nn as nn\nfrom ignite.engine import Engine, Events\nfrom ignite.handlers import ModelCheckpoint, Timer\nfrom ignite.metrics import RunningAverage\n\nfrom utils.reid_metric impor... | [
[
"torch.cuda.device_count",
"torch.no_grad",
"torch.nn.DataParallel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
ForrestHurley/REngVelocityProfiling | [
"e32ad024248966cfa4e4282dfb0e9b972ce916b6"
] | [
"generate_regions.py"
] | [
"import numpy as np\nimport random\nfrom matplotlib import pyplot as plt\nfrom matplotlib import patches\n\nclass obstacle(object):\n def __init__(self,x=0,y=0,size=(1,1)):\n self.pos = np.array((x,y))\n if (len(size) > 2):\n pass\n #insert exception here\n if (len(size... | [
[
"numpy.linspace",
"matplotlib.patches.Rectangle",
"numpy.concatenate",
"numpy.add",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
usnistgov/gpsdata | [
"23b2b9ecb13e64da24d6fb15bb2dd3b44c932308"
] | [
"labbench/_serialize.py"
] | [
"\"\"\"functions and CLI tools for mapping labbench objects onto config directories\"\"\"\n\nimport importlib\nimport inspect\nimport os\nfrom pathlib import Path\nimport pandas as pd\nfrom numbers import Number\n\nfrom ._rack import (\n Rack,\n RackMethod,\n Sequence,\n BoundSequence,\n import_as_ra... | [
[
"pandas.DataFrame"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
eduartorres/Project-Disaster-Response-Pipeline- | [
"3b0a29f4ebbfe6eb3fc204028d5e4fc5e9f2c956"
] | [
"app/run.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sun Oct 17 19:16:27 2021\n\n@author: FELIPE\n\"\"\"\n# Note: Read the header before running\n# =============================================================================\n# >>> Project: Disaster Response Pipeline (Udacity - Data Science Nanodegree) <<<\n\n# Sample scr... | [
[
"pandas.read_sql_table"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
SatishGitHubs/TensorFlow | [
"422b17b34f4f1380d2e487b3509bb97ff726edca"
] | [
"tensorflow/contrib/layers/python/layers/layers.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.utils.constant_value",
"tensorflow.python.ops.array_ops.shape",
"tensorflow.python.ops.nn.softmax",
"tensorflow.python.ops.nn.separable_conv2d",
"tensorflow.python.ops.nn.conv2d",
"tensorflow.python.ops.array_ops.identity",
"tensorflow.python.tr... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"1.12",
"1.13",
"1.7",
"0.12"
]
}
] |
tonouchi510/kfp-project | [
"67b78ae53cc3de594b8254999a4f553a8d5cec27"
] | [
"pipelines/head-pose-pipeline/training/capsulelayers.py"
] | [
"\"\"\"\nOriginal code taken from Author: Xifeng Guo, E-mail: `guoxifeng1990@163.com`, Github: `https://github.com/XifengGuo/CapsNet-Keras`\nand adjusted for the needs of this project.\n\nSome key layers used for constructing a Capsule Network. These layers can used to construct CapsNet on other dataset, \nnot just... | [
[
"tensorflow.matmul",
"tensorflow.keras.backend.tile",
"tensorflow.nn.softmax",
"tensorflow.multiply",
"tensorflow.keras.backend.permute_dimensions",
"tensorflow.shape",
"tensorflow.keras.backend.dot",
"tensorflow.transpose",
"tensorflow.keras.backend.ndim",
"tensorflow.kera... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10"
]
}
] |
ekta1224/jellyfish | [
"3271019434448b5916dcc920d640b81375b74c05"
] | [
"tests/read_snapshot_test.py"
] | [
"import numpy as np\nimport jellyfish\n\n\ndef loading_halo():\n path = '../examples/'\n snap_name = 'test_snap'\n nhost = 1000000\n nsat = 450000\n sim = jellyfish.Hello_sim(path, snap_name, nhost, nsat, 'host_dm', 'com_host', 'pos') \n pos = sim.read_MW_snap_com_coordinates()\n assert(len(pos... | [
[
"numpy.shape"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
nibraaska/td_wm | [
"543cd91e87ebd478e79d821fa8708885df5899c5"
] | [
"combined_model/all_stats/dynamic_t_non_obs_stats/newStats/reset_model.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[ ]:\n\n\nimport matplotlib as mpl\nimport matplotlib.pyplot as plt\n\nimport numpy as np\nnp.set_printoptions(threshold=np.inf)\n\nimport time, sys, random, pylab\nfrom math import fabs\n\nfrom random import randrange\nfrom random import choice\n\nfrom hrr import *\n\... | [
[
"numpy.dot",
"matplotlib.pyplot.tight_layout",
"numpy.random.seed",
"numpy.random.choice",
"numpy.arange",
"numpy.set_printoptions",
"matplotlib.pyplot.subplots",
"numpy.random.random_sample",
"numpy.ones",
"matplotlib.pyplot.plot",
"numpy.sign",
"numpy.mean",
"... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
AhmedYounes94/Keras-Self-Attention-Seq | [
"0ae0c32df3e73e6923e90894c6a901066eddf379"
] | [
"keras_self_attention/seq_self_attention.py"
] | [
"import keras\nimport keras.backend as K\nimport tensorflow as tf\n\n\nclass SeqSelfAttention(keras.layers.Layer):\n\n ATTENTION_TYPE_ADD = 'additive'\n ATTENTION_TYPE_MUL = 'multiplicative'\n\n def __init__(self,\n units=32,\n attention_width=None,\n attenti... | [
[
"tensorflow.gather_nd",
"tensorflow.ones",
"tensorflow.eye"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"1.12",
"1.4",
"1.13",
"1.5",
"1.7",
"0.12",
"1.0",
"1.2"
]
}
] |
yinzhangyue/PDF_tool | [
"ff1c689478e0d40370724ad88da78ef8bd0bf3d1",
"ff1c689478e0d40370724ad88da78ef8bd0bf3d1"
] | [
"Model/mmdet/core/post_processing/bbox_nms.py",
"frontend/tool/a.py"
] | [
"import torch\n\nfrom mmdet.ops.nms import nms_wrapper\n\n\ndef multiclass_nms(multi_bboxes,\n multi_scores,\n score_thr,\n nms_cfg,\n max_num=-1,\n score_factors=None):\n \"\"\"NMS for multi-class bboxes.\n\n Args:\n ... | [
[
"torch.cat"
],
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Drob-AI/The-Observer | [
"80540be5fa5e9a6a7b9123702b701998105a48a6"
] | [
"src/mod_suggest/tree_trainer.py"
] | [
"import random\nimport numpy as np\nfrom sklearn import tree\nfrom sklearn import neighbors\nfrom sklearn import svm\nfrom sklearn import grid_search\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.grid_search import GridSearchCV\nfrom sklearn import cross_validation\nfrom sklearn.ensemble import RandomFo... | [
[
"sklearn.cross_validation.StratifiedKFold",
"sklearn.ensemble.RandomForestClassifier",
"numpy.arange",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.grid_search.GridSearchCV",
"sklearn.tree.DecisionTreeClassifier",
"sklearn.svm.SVC",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Chop1/mmtracking | [
"fd62f33e399f9931b94dbdb33e201ae348af2cd8",
"fd62f33e399f9931b94dbdb33e201ae348af2cd8",
"fd62f33e399f9931b94dbdb33e201ae348af2cd8"
] | [
"mmtrack/datasets/sot_imagenet_vid_dataset.py",
"mmtrack/datasets/builder.py",
"mmtrack/models/track_heads/stark_head.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport numpy as np\nfrom mmdet.datasets import DATASETS\n\nfrom mmtrack.datasets.parsers import CocoVID\nfrom .base_sot_dataset import BaseSOTDataset\n\n\n@DATASETS.register_module()\nclass SOTImageNetVIDDataset(BaseSOTDataset):\n \"\"\"ImageNet VID dataset of si... | [
[
"numpy.array"
],
[
"torch.manual_seed",
"torch.utils.data.sampler.RandomSampler",
"numpy.random.seed"
],
[
"torch.nn.BatchNorm1d",
"torch.nn.functional.softmax",
"torch.cat",
"torch.nn.Conv2d",
"torch.zeros_like",
"torch.sum",
"torch.nn.Embedding",
"torch.ma... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
8M-An/greyatom-python-for-data-science | [
"5c6dd729120aa003de0095cddd2093b0a16ecab9"
] | [
"numpy/code.py"
] | [
"# --------------\n# Importing header files\r\nimport numpy as np\r\nimport warnings\r\n\r\nwarnings.filterwarnings('ignore')\r\n\r\n#New record\r\nnew_record=[[50, 9, 4, 1, 0, 0, 40, 0]]\r\n#Reading file\r\ndata = np.genfromtxt(path, delimiter=\",\", skip_header=1)\r\n\r\n#Code starts here\r\n\r\ncensus=np.c... | [
[
"numpy.concatenate",
"numpy.std",
"numpy.genfromtxt"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
eriknw/numpy | [
"d13a4f06ea84da112d5069b3fde148e307e7f94c"
] | [
"numpy/random/tests/test_generator_mt19937.py"
] | [
"import sys\n\nimport pytest\n\nimport numpy as np\nfrom numpy.linalg import LinAlgError\nfrom numpy.testing import (\n assert_, assert_raises, assert_equal, assert_allclose,\n assert_warns, assert_no_warnings, assert_array_equal,\n assert_array_almost_equal, suppress_warnings)\n\nfrom numpy.random import ... | [
[
"numpy.random.MT19937",
"numpy.testing.assert_no_warnings",
"numpy.asarray",
"numpy.vstack",
"numpy.dtype",
"numpy.all",
"numpy.iinfo",
"numpy.nextafter",
"numpy.testing.assert_equal",
"numpy.uint32",
"numpy.unique",
"numpy.testing.suppress_warnings",
"numpy.ara... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
manoloesparta/deeps | [
"5e073da05305f275b1f5930ea2a2746141cb9d1e"
] | [
"churn_modeling/main.py"
] | [
"import pandas as pd\nimport numpy as np\n\nfrom train import train_model\nfrom save_model import save_model\nfrom load_model import load_model\nfrom preprocessing import preprocessing\nfrom one_sample import one_sample\n\nfrom pathlib import Path\n\nfrom sklearn.metrics import classification_report\n\ndataset = pd... | [
[
"pandas.read_csv",
"sklearn.metrics.classification_report"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"2.0",
"1.4",
"1.1",
"1.5",
"1.2",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
bryan-brancotte/rank-aggregation-with-ties | [
"15fffb0b1bee3d6cef7090486a7c910e5f51195d"
] | [
"sources/rnt/mediane/algorithms/Schulze/Schulze.py"
] | [
"from mediane.algorithms.median_ranking import MedianRanking # , DistanceNotHandledException\nfrom mediane.distances.enumeration import GENERALIZED_KENDALL_TAU_DISTANCE, GENERALIZED_INDUCED_KENDALL_TAU_DISTANCE, \\\n PSEUDO_METRIC_BASED_ON_GENERALIZED_INDUCED_KENDALL_TAU_DISTANCE, GENERALIZED_KENDALL_TAU_DISTAN... | [
[
"numpy.zeros",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
huonw/stellargraph | [
"60edf4a6268f29b49b7c768c382e235af4108506"
] | [
"demos/node-classification-graphsage/graphsage-cora-example.py"
] | [
"# -*- coding: utf-8 -*-\n#\n# Copyright 2018 Data61, CSIRO\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.feature_extraction.DictVectorizer",
"sklearn.model_selection.train_test_split"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
feiga/fedlearner | [
"99a19934b872a9fba6d85ae018b0ec145612fbca"
] | [
"test/test_compressed_raw_data_visitor.py"
] | [
"# Copyright 2020 The FedLearner 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.compat.v1.gfile.Exists",
"tensorflow.compat.v1.enable_eager_execution"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
arthur-e/spotpy | [
"d689678a98fcd26769d581218024d5f058f0d027"
] | [
"spotpy/algorithms/abc.py"
] | [
"# -*- coding: utf-8 -*-\n'''\nCopyright (c) 2018 by Tobias Houska\nThis file is part of Statistical Parameter Optimization Tool for Python(SPOTPY).\n:author: Patrick Lauer\n'''\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import ... | [
[
"numpy.cumsum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
peter9811/meerk40t | [
"370b0bb4df2d310d6d8bed9179ab29960e8b3d62"
] | [
"svgelements.py"
] | [
"# -*- coding: ISO-8859-1 -*-\n\nimport re\n\ntry:\n from collections.abc import MutableSequence # noqa\nexcept ImportError:\n from collections import MutableSequence # noqa\nfrom copy import copy\n\nfrom math import (\n ceil,\n cos,\n radians,\n sin,\n sqrt,\n hypot,\n atan,\n atan2... | [
[
"scipy.special.ellipeinc",
"numpy.cos",
"numpy.sin",
"numpy.interp",
"scipy.integrate.quad",
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
JeroenDM/sampling_based_tube_following_2 | [
"b710b69c80600d35e31297184e8008b144ca1ec7"
] | [
"figure_1_sample_examples.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import\n\nfrom acrolib.quaternion import Quaternion\nfrom acrobotics.util import get_default_axes3d, plot_reference_frame\nfrom acrobotics.util import rot_z\n\nfrom acrobotics.path.sampling import Samp... | [
[
"matplotlib.pyplot.figaspect",
"matplotlib.pyplot.tight_layout",
"numpy.eye",
"matplotlib.pyplot.savefig",
"numpy.deg2rad",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
KeisukeNagakawa/cisim | [
"2f52b34ccd915f4b5a23f1ba502ecfdabf8aecfb"
] | [
"tests/test_stats.py"
] | [
"from unittest import TestCase\nfrom cisim.stats import BinomCI, HyperCI\n\n\nclass Testbinom(TestCase):\n\n def test_validation(self):\n self.assertRaises(ValueError, BinomCI, -100, 10, 0.05)\n self.assertRaises(ValueError, BinomCI, 100, -10, 0.05)\n self.assertRaises(ValueError, BinomCI, 1... | [
[
"scipy.stats.hypergeom.cdf"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
chxw20/volta | [
"57022a7e33d458a8245ffcd3131ae2f94375dd12"
] | [
"volta/datasets/visual_entailment_dataset.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\n# Copyright (c) 2020, Emanuele Bugliarello (@e-bug).\n\n# This source code is licensed under the MIT license found in the\n# LICENSE file in the root directory of this source tree.\n\nimport os\nimport logging\nimport jsonlines\nimport _pickle as cPickle\n\nimpor... | [
[
"torch.zeros",
"torch.from_numpy",
"torch.tensor",
"numpy.array",
"numpy.zeros"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
sismetanin/jiant | [
"00bc77ca633e8dcf83c40f7c6ef5bae9f359d999"
] | [
"jiant/scripts/download_data/dl_datasets/files_tasks.py"
] | [
"import json\nimport logging\nimport os\nimport pandas as pd\nimport re\nimport shutil\nimport tarfile\nfrom operator import itemgetter\nfrom collections import Counter\n\nimport jiant.scripts.download_data.utils as download_utils\nimport jiant.utils.display as display\nimport jiant.utils.python.filesystem as files... | [
[
"pandas.isnull"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"0.19",
"1.1",
"1.5",
"1.2",
"0.24",
"0.20",
"1.0",
"0.25",
"1.3"
],
"scipy": [],
"tensorflow": []
}
] |
rauldiaz/PointNetLK | [
"23e26d2668d82578a5c9a129555f52e10104499b"
] | [
"experiments/icp.py"
] | [
"\"\"\" ICP algorithm\n\n References:\n (ICP)\n [1] Paul J. Besl and Neil D. McKay,\n \"A method for registration of 3-D shapes\",\n PAMI Vol. 14, Issue 2, pp. 239-256, 1992.\n (SVD)\n [2] K. S. Arun, T. S. Huang and S. D. Blostein,\n \"Least-Squares Fitting of Two 3-D Point Sets... | [
[
"numpy.dot",
"numpy.linalg.svd",
"numpy.expand_dims",
"numpy.abs",
"numpy.eye",
"numpy.ones",
"numpy.linalg.det",
"numpy.copy",
"scipy.spatial.KDTree",
"numpy.mean",
"numpy.zeros_like",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.show",
"matplotlib.... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"1.7",
"1.0",
"0.10",
"1.2",
"0.14",
"0.19",
"1.5",
"0.12",
"0.17",
"0.13",
"1.6",
"1.4",
"1.9",
"1.3",
"1.10",
"0.15",
"0.18",
"0.16"... |
austospumanto/kedro | [
"4f89c8fd32c6660affa5ff7d4fe2b096d5de9c95"
] | [
"kedro/extras/datasets/pandas/xml_dataset.py"
] | [
"# Copyright 2021 QuantumBlack Visual Analytics Limited\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# THE SOFTWARE IS PR... | [
[
"pandas.read_xml"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"1.3",
"1.5",
"2.0",
"1.4"
],
"scipy": [],
"tensorflow": []
}
] |
CorbinFoucart/FEMexperiment | [
"9bad34d9ed7cbdd740e3a4b67f433779dd53b264"
] | [
"codes/src/msh/mesh.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\n@package src.msh.mesh\nCreated on Sun Apr 24 20:51:08 2011\nContains the Mesh classes\n\n@author: Matt Ueckermann\n@author: Corbin Foucart\n@note While the elements are certainly numbered CCW, the edges may not be. The\n edge numbering comes from mk_basis.int_el_pqr, and is do... | [
[
"numpy.ix_",
"numpy.ones_like",
"numpy.tile",
"numpy.cumsum",
"numpy.concatenate",
"numpy.append",
"numpy.zeros_like",
"numpy.any",
"numpy.column_stack",
"numpy.array",
"numpy.zeros",
"numpy.sum"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
RemotePixel/remotepixel-py | [
"bd58db7a394c84651d05c4e6f83da4cd3d4c26f3"
] | [
"remotepixel/cbers_ndvi.py"
] | [
"\"\"\"remotepixel.cbers_ndvi module.\"\"\"\n\nimport re\nfrom functools import partial\nfrom concurrent import futures\n\nimport numpy as np\nimport numexpr as ne\n\nimport rasterio\nfrom rasterio import warp\n\nfrom remotepixel.utils import cbers_parse_scene_id, get_area\nfrom rio_tiler.utils import linear_rescal... | [
[
"numpy.all",
"numpy.seterr",
"numpy.any"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
PyOCL/pyopencl-examples | [
"620e263660fd0c621ce2a0b9899b10bfc194c009"
] | [
"4-3-expand/clustering.py"
] | [
"#!/usr/bin/python3\nimport os\nimport time\nimport random\nimport numpy\nimport pyopencl as cl\nimport pyopencl.array\n\ndef plot_grouping_result(point_cids, group_ids, point_info):\n assert len(point_cids) != 0\n import matplotlib.pyplot as plt\n markers = ['p', '*', '+', 'x', 'd', 'o', 'v', 's', 'h']\n ... | [
[
"matplotlib.pyplot.scatter",
"numpy.array_equal",
"numpy.int32",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.xlabel",
"numpy.array",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
JackyXiao98/chinese_ocr | [
"62c45fd6df0959144fad411cf90ee136047802c3"
] | [
"ctpn/text_detect.py"
] | [
"import os\nimport sys\nimport cv2\nimport numpy as np\nimport tensorflow as tf\nfrom lib.utils.timer import Timer\nfrom lib.fast_rcnn.config import cfg\nfrom lib.fast_rcnn.test import test_ctpn\nfrom lib.networks.factory import get_network\nfrom lib.text_connector.detectors import TextDetector\nfrom lib.text_conn... | [
[
"tensorflow.train.get_checkpoint_state",
"numpy.linalg.norm",
"tensorflow.ConfigProto",
"tensorflow.GPUOptions",
"tensorflow.Session",
"tensorflow.train.Saver"
]
] | [
{
"matplotlib": [],
"numpy": [
"1.10",
"1.12",
"1.11",
"1.19",
"1.24",
"1.13",
"1.16",
"1.9",
"1.18",
"1.23",
"1.21",
"1.22",
"1.20",
"1.7",
"1.15",
"1.14",
"1.17",
"1.8"
],
"pandas": [],
... |
ChuckHastings/cugraph | [
"f73b7b47124f56cf17202492f469270c0a1858a1"
] | [
"python/cugraph/sssp/test_sssp.py"
] | [
"# Copyright (c) 2019, NVIDIA CORPORATION.\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 ... | [
[
"scipy.io.mmread",
"numpy.finfo"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [
"0.13",
"1.6",
"0.14",
"1.10",
"0.15",
"1.4",
"0.16",
"1.9",
"0.19",
"1.5",
"0.18",
"1.2",
"1.7",
"0.12",
"1.0",
"0.17",
"1.3",
"1.8"
... |
dpastoresc/NarrativeDynamics | [
"bc0c502744c215274d34a23cbce6ad6a9d39a333"
] | [
"processTweetsCreateNetwork.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nSpyder Editor\n\nThis is a temporary script file.\n\"\"\"\n\nimport pandas as pd\nimport numpy as np\n\n\nimport mysql.connector\nfrom sqlalchemy import create_engine\n\nimport nltk\nimport re\nfrom nltk.corpus import stopwords\nimport string\nfrom bs4 import BeautifulSoup\nimport ... | [
[
"pandas.read_json",
"pandas.read_sql"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [
"0.23",
"0.21",
"2.0",
"1.4",
"1.3",
"0.19",
"1.1",
"1.5",
"0.24",
"0.20",
"1.0",
"0.25",
"1.2"
],
"scipy": [],
"tensorflow": []
}
] |
YihsunEthanCheng/dog-breed-classifier | [
"3c036bdb7f31a92894aef9d46148dd2be916cbac"
] | [
"dog_breed_detector.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Jun 11 00:22:40 2018\r\n\r\n@author: Ethan Cheng\r\n\"\"\"\r\nfrom sklearn.datasets import load_files \r\nfrom keras.utils import np_utils\r\nimport numpy as np\r\nfrom glob import glob\r\nfrom keras.preprocessing import image \r\nfrom tqdm... | [
[
"numpy.hstack",
"matplotlib.pyplot.imshow",
"numpy.expand_dims",
"sklearn.datasets.load_files",
"numpy.array",
"numpy.vstack"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
SchenbergZY/keras-transformer-xl-yue | [
"2d286e521992e8a13e5b883a6c5315f8967f7e48"
] | [
"tests/test_transformer_xl.py"
] | [
"import os\nimport tempfile\nfrom unittest import TestCase\nimport numpy as np\nfrom keras_transformer_xl.backend import keras\nfrom keras_transformer_xl import build_transformer_xl, set_custom_objects\n\n\nclass TestTransformerXL(TestCase):\n\n def test_build(self):\n model = build_transformer_xl(\n ... | [
[
"numpy.random.random",
"numpy.zeros",
"numpy.ones"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
krumo/Detectron | [
"48e3236fe2296afcd7b67a29c487cfe85f5860e1"
] | [
"detectron/datasets/json_dataset.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.sum",
"numpy.ones",
"numpy.append",
"numpy.argsort",
"numpy.array",
"numpy.zeros",
"numpy.where",
"numpy.empty"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
DongChengdongHangZhou/caffe-to-pytorch | [
"5e3104f3aa77d35bad5d2de235b067460c136fd5"
] | [
"caffe2pth/detection.py"
] | [
"# -*- coding:utf-8 -*-\n\"\"\"2017.12.16 by xiaohang\nBorrow from: github: https://github.com/marvis/pytorch-caffe\n\"\"\"\n\nimport torch\nimport torch.nn as nn\nfrom torch.autograd import Function\nfrom torch.autograd import Variable\nimport torch.nn.functional as F\n\n\ndef point_form(boxes):\n \"\"\" Conver... | [
[
"torch.Tensor",
"torch.cat",
"torch.zeros",
"torch.nn.functional.cross_entropy",
"torch.exp",
"torch.mul",
"torch.log",
"torch.FloatTensor",
"torch.nn.functional.smooth_l1_loss",
"torch.clamp",
"torch.index_select",
"torch.autograd.Variable"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
gregor-robinson/lolo | [
"54fd08c90b19b5849d1b2bbfbfea04a856935c84"
] | [
"python/lolopy/tests/test_metrics.py"
] | [
"from lolopy.metrics import (root_mean_squared_error, standard_confidence, standard_error, uncertainty_correlation)\nfrom numpy.random import multivariate_normal, uniform, normal, seed\nfrom unittest import TestCase\n\n\nclass TestMetrics(TestCase):\n\n def test_rmse(self):\n self.assertAlmostEqual(root_m... | [
[
"numpy.random.uniform",
"numpy.random.multivariate_normal",
"numpy.random.normal",
"numpy.random.seed"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
kaldap/image-analogies | [
"0867aedfae7dfc0d27c42805a3d07f7b9eb7eaa2"
] | [
"image_analogy/losses/patches.py"
] | [
"import sys\nfrom itertools import product\n\nimport numpy as np\nimport torch\nfrom tensorflow.keras import backend as K\nfrom tensorflow import image as TFI\nimport tensorflow as tf\nfrom sklearn.feature_extraction.image import reconstruct_from_patches_2d\n\n\ndef make_patches(x, patch_size, patch_stride):\n '... | [
[
"tensorflow.keras.backend.conv2d",
"tensorflow.keras.backend.permute_dimensions",
"sklearn.feature_extraction.image.reconstruct_from_patches_2d",
"tensorflow.keras.backend.square",
"tensorflow.keras.backend.shape",
"tensorflow.keras.backend.expand_dims",
"tensorflow.keras.backend.argma... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
azmikamis/tf-transform-examples | [
"2ad36823a7f202312ca2e5b665485aa42bcaa4e2"
] | [
"03_simple_example_readtransform.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport pprint\nimport tempfile\n\nimport apache_beam as beam\nimport tensorflow as tf\nimport tensorflow_transform as tft\nimport tensorflow_transform.beam.impl as tft_beam\nfrom tensorflow_transform.b... | [
[
"tensorflow.FixedLenFeature"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": [
"1.10",
"1.12",
"1.4",
"1.13",
"1.5",
"1.7",
"0.12",
"1.0",
"1.2"
]
}
] |
smsegal/PerceptualSimilarity | [
"f685b3c346dd7c6232a5cacfdbfd5cc95b145403",
"f685b3c346dd7c6232a5cacfdbfd5cc95b145403"
] | [
"perceptual_similarity/models/networks_basic.py",
"compute_dists_pair.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\n\nfrom .pretrained_networks import vgg16, alexne... | [
[
"torch.nn.Sequential",
"torch.nn.Dropout",
"torch.mean",
"torch.Tensor",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.BCELoss",
"torch.nn.Sigmoid",
"torch.nn.Upsample",
"torch.nn.LeakyReLU"
],
[
"numpy.array"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
},
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
dmgav/ptycho_gui | [
"4474008f85b0aad4519fb2236be8b81c8c6e818f"
] | [
"nsls2ptycho/core/widgets/mplcanvas.py"
] | [
"import os\nfrom PyQt5 import QtCore, QtWidgets, QtGui\n\nfrom matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas\nfrom matplotlib.figure import Figure\nfrom matplotlib.pyplot import Axes\nimport matplotlib.cm as cm\nfrom mpl_toolkits.axes_grid1.axes_divider import make_axes_area_auto_adjus... | [
[
"matplotlib.backends.backend_qt5agg.FigureCanvasQTAgg.__init__",
"matplotlib.figure.Figure",
"matplotlib.pyplot.Axes",
"matplotlib.backends.backend_qt5agg.FigureCanvasQTAgg.updateGeometry",
"numpy.array",
"matplotlib.backends.backend_qt5agg.FigureCanvasQTAgg.setSizePolicy"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mldiego/sonode | [
"19726b437d3aba94c9f621afa519b0d3a71bbfea"
] | [
"experiments/function_fitting/double_function/plot_triple_func.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom matplotlib import rc\nimport seaborn as sns\n\n\nfig = plt.figure(figsize=[10, 4])\nfig.subplots_adjust(hspace=0., wspace=0)\n\n\nsns.set_style('dark')\nrc('font', family='serif')\nrc('text', usetex=True)\nax1 = plt.subplot(1, 2, 1)\nfilename = 'results./do... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.xlabel",
"numpy.load",
... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
mbrukman/cloudml-samples | [
"6002cf7b57112f98b20ab11a37c1b17f7337e8cf"
] | [
"cloudml-template/template/trainer/task.py"
] | [
"#!/usr/bin/env python\n\n# Copyright 2017 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#\... | [
[
"tensorflow.gfile.DeleteRecursively",
"tensorflow.gfile.Exists",
"tensorflow.logging.set_verbosity",
"tensorflow.estimator.EvalSpec",
"tensorflow.estimator.RunConfig",
"tensorflow.estimator.train_and_evaluate",
"tensorflow.estimator.FinalExporter"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Sara-X/text-to-text-transfer-transformer | [
"2f3c40073cc45e11d5fe222a5c6088bb7d95071c"
] | [
"t5/models/hf_model.py"
] | [
"# Copyright 2020 The T5 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 law or agr... | [
[
"tensorflow.compat.v1.io.gfile.exists",
"tensorflow.compat.v1.io.gfile.makedirs",
"tensorflow.compat.v1.io.gfile.remove",
"torch.load",
"tensorflow.compat.v1.io.gfile.GFile",
"torch.utils.tensorboard.writer.SummaryWriter",
"tensorflow.compat.v1.data.Dataset.from_tensor_slices",
"te... | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
hardikkarena/DCASE2019_task3 | [
"cee08dec6fa9f508be4b4de85adeadefddec4793"
] | [
"classif/utils_classif.py"
] | [
"\nimport numpy as np\nimport os, re\n\n\n#########################################################################\n# Some of these functions have been inspired on a framework by Marius Miron developed for a pydata workshop\n# https://github.com/nkundiushuti/pydata2017bcn/blob/master/util.py\n#####################... | [
[
"numpy.ceil"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
shoarora/polytune | [
"86f31ba3f41ea47edcfa0442a29a79a2a46deaeb"
] | [
"lmtuners/lightning_modules/lm.py"
] | [
"\"\"\"Pytorch lightning module for language modelling.\"\"\"\nimport logging\nimport os\nfrom argparse import Namespace\n\nimport pytorch_lightning as pl\nimport torch\nfrom pytorch_lamb import Lamb\nfrom transformers import get_linear_schedule_with_warmup\n\nlogger = logging.getLogger(__name__)\n\n\nclass LMTrain... | [
[
"torch.exp",
"torch.sum",
"torch.stack",
"torch.argmax"
]
] | [
{
"matplotlib": [],
"numpy": [],
"pandas": [],
"scipy": [],
"tensorflow": []
}
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.