repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
emptylkj/PyBaMM | [
"1e81493048d5e50e8eaac61bb774d8a2e6019c10"
] | [
"tests/unit/test_solvers/test_base_solver.py"
] | [
"#\n# Tests for the Base Solver class\n#\nimport casadi\nimport pybamm\nimport numpy as np\nfrom scipy.sparse import csr_matrix\n\nimport unittest\n\n\nclass TestBaseSolver(unittest.TestCase):\n def test_base_solver_init(self):\n solver = pybamm.BaseSolver(rtol=1e-2, atol=1e-4)\n self.assertEqual(s... | [
[
"numpy.zeros_like",
"numpy.array",
"numpy.zeros",
"numpy.testing.assert_array_equal",
"numpy.ones",
"numpy.testing.assert_array_almost_equal",
"numpy.diag"
]
] |
ruth-ann/deepsnap | [
"35eeb5abdb304c53b2e0a68cbbeeaa55dca286a0"
] | [
"tests/test_graph_tensor_backend.py"
] | [
"import copy\nimport torch\nimport unittest\nimport numpy as np\nfrom tests.utils import simple_networkx_graph\nfrom deepsnap.graph import Graph\nfrom torch_geometric.datasets import Planetoid\n\n\nclass TestGraphTensorBackend(unittest.TestCase):\n\n def test_graph_basics(self):\n G, x, y, edge_x, edge_y,... | [
[
"torch.stack",
"torch.flip"
]
] |
Abezzam10/Deep-learning-TensorFlow_Keras | [
"38901310d44e7f92a1c8c977260d58ffc97af9dc"
] | [
"photo_face_classifier.py"
] | [
"import cv2\r\nimport sys\r\nimport numpy as np\r\n\r\nimagePath = sys.argv[1]\r\ncascPath = \"haarcascade_frontalface_default.xml\"\r\n\r\nfaceCascade = cv2.CascadeClassifier(cascPath)\r\n\r\n# Read the image\r\nimage = cv2.imread(imagePath)\r\ngray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\r\nnp.array(image, dtyp... | [
[
"numpy.array"
]
] |
khsk/Python-App-Capture | [
"a0b893765558f144399ec31f1f11fb0b30025cc7"
] | [
"capture.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Tue Sep 12 15:01:44 2017\r\n\r\n@author: \r\n\"\"\"\r\n\r\n\r\nimport sys\r\nreload(sys)\r\nsys.setdefaultencoding('cp932')\r\ntes = sys.getdefaultencoding()\r\n\r\nimport os\r\nimport cv2\r\nimport numpy as np\r\nimport pyws as m\r\nimport winxpgui\r\n\r\nfrom PIL i... | [
[
"numpy.asarray"
]
] |
snubeaver/pytorch_geo | [
"6c533ebac29c08eafe9171eba470a6aaa09d1b45"
] | [
"benchmark/baseline/cold_start_learning/cold_start.py"
] | [
"import argparse\nimport torch\nimport torch.nn.functional as F\nfrom gat_score import GATScore\nfrom torch.nn import Linear\nfrom datasets import get_planetoid_dataset\nfrom train_eval_cs import random_planetoid_splits, run\nimport pdb\nfrom torch_geometric.nn import GCNConv\n\nparser = argparse.ArgumentParser()\n... | [
[
"torch.nn.Linear",
"torch.index_select",
"torch.cat",
"torch.einsum"
]
] |
desh2608/beer | [
"57ccbd3cf5c415d854d02d2b114143f61a63305d",
"57ccbd3cf5c415d854d02d2b114143f61a63305d"
] | [
"beer/cli/subcommands/shmm/mksphoneloop.py",
"beer/cli/subcommands/hmm/accumulate.py"
] | [
"\n'create a subspace phone-loop model'\n\nimport argparse\nimport copy\nimport pickle\nimport sys\n\nimport torch\nimport yaml\n\nimport beer\n\n\n# Create a view of the emissions (aka modelset) for each units.\ndef iterate_units(modelset, nunits, nstates):\n for idx in range(nunits):\n start, end = idx ... | [
[
"torch.zeros_like",
"torch.ones",
"torch.zeros"
],
[
"numpy.load"
]
] |
Joel-hanson/pytorch-lightning | [
"83ab3eadb6bd32a761fd2e710a7a28778efa0360"
] | [
"tests/loggers/test_tensorboard.py"
] | [
"import os\nfrom argparse import Namespace\n\nimport pytest\nimport torch\nimport yaml\nfrom omegaconf import OmegaConf\nfrom packaging import version\n\nfrom pytorch_lightning import Trainer\nfrom pytorch_lightning.loggers import TensorBoardLogger\nfrom tests.base import EvalModelTemplate\n\n\n@pytest.mark.skipif(... | [
[
"torch.rand",
"torch.tensor"
]
] |
Brokenice0415/CASIA-HWDB1.1-cnn | [
"35fb7f87893c51a651705cd4dbb6b6f05e37fee2"
] | [
"src/3-train_subset.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport json\nimport sys\nimport time\n\nimport numpy as np\nnp.random.seed(1337)\n\nimport h5py\nfrom keras.layers.convolutional import Conv2D, MaxPooling2D\nfrom keras.layers.core import Dense, Dropout, Flatten\nfrom keras.models import Sequential\nfrom keras.regul... | [
[
"numpy.random.seed",
"numpy.random.normal",
"numpy.zeros"
]
] |
i4Ds/STIXCore | [
"9a765a33f2e924ead669b9b99afc1e41a4d2d8e8"
] | [
"stixcore/processing/tests/test_processing.py"
] | [
"import sys\nfrom pathlib import Path\n\nimport numpy as np\nimport pytest\n\nfrom astropy.io.fits.diff import FITSDiff\n\nfrom stixcore.data.test import test_data\nfrom stixcore.idb.idb import IDBPolynomialCalibration\nfrom stixcore.idb.manager import IDBManager\nfrom stixcore.io.soc.manager import SOCManager\nfro... | [
[
"numpy.array"
]
] |
victor-shepardson/pylivecode | [
"98da82921905ae32a9749792f3a04fd4b39c3551"
] | [
"scratch.py"
] | [
"import numpy as np\nfrom glumpy import app\nfrom livecode import *\n\nsize = np.array((900, 1800))\nscreen_size = np.array((1600, 900))\nwin_size = screen_size*2\n\ndef get_shaders(s):\n return ('shader/lib.glsl', 'shader/'+s+'.glsl')\n\nscreen = Layer(screen_size, get_shaders('display-stretch'))\npost = Layer(... | [
[
"numpy.array"
]
] |
joe3d1998/GraphFlow | [
"8a751e4fc69a1e0c06ded23b7d1096f3161931a1"
] | [
"src/core/utils/data_utils.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nModule to handle getting data loading classes and helper functions.\n\"\"\"\n\nimport json\nimport io\nimport torch\nimport numpy as np\nfrom scipy.sparse import *\nfrom collections import Counter, defaultdict\n\nfrom torch.utils.data import Dataset\n\nfrom .bert_utils import *\nfr... | [
[
"torch.zeros",
"numpy.max",
"numpy.zeros",
"numpy.min",
"torch.cuda.empty_cache",
"torch.LongTensor",
"numpy.average",
"torch.Tensor",
"torch.set_grad_enabled"
]
] |
Chenxiqiu/age_fire_code | [
"7e64cb24a70bc6d00eada7e613407b80e1e069a8"
] | [
"f0031b_MIPASorACEorAMICA_age_tiles.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt \nimport matplotlib.cm as cm\nimport pandas as pd\nimport clean.clean_03 as southtrac\nimport process.constants as c\nfrom matplotlib import gridspec\nfrom datetime import datetime\nimport winsound\nduration = 1000 # milliseconds\nfreq = 440 # Hz\nimport plotly... | [
[
"pandas.read_pickle",
"numpy.append",
"matplotlib.pyplot.colorbar",
"pandas.cut",
"matplotlib.cm.get_cmap",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.rc",
"numpy.arange",
"pandas.concat",
"numpy.meshgrid",
"matplotlib.gridspec.GridSpe... |
chaneyjd/rasa | [
"104a9591fc10b96eaa7fe402b6d64ca652b7ebe2"
] | [
"rasa/core/policies/rule_policy.py"
] | [
"import logging\nfrom typing import List, Dict, Text, Optional, Any, Set, TYPE_CHECKING, Union\n\nfrom tqdm import tqdm\nimport numpy as np\nimport json\n\nfrom rasa.shared.constants import DOCS_URL_RULES\nimport rasa.shared.utils.io\nfrom rasa.shared.core.events import FormValidation, UserUttered, ActionExecuted\n... | [
[
"numpy.argmax"
]
] |
easyautoml/easyml | [
"5c4a724836c5dbd9eb66a81ae33d3d63961a0f80"
] | [
"src/jobs/automl.py"
] | [
"from utils import config\nfrom utils.transform import Input, Output, Excel, get_experiments_url, get_predict_url, get_experiments_dataset_url, \\\n get_file_url, distribution_density, get_evaluation_url, Histogram\nfrom utils import services\nfrom sklearn.metrics import accuracy_score, f1_score, balanced_accura... | [
[
"numpy.array",
"numpy.isnan",
"sklearn.metrics.mean_squared_error",
"sklearn.metrics.confusion_matrix",
"numpy.round",
"pandas.DataFrame",
"sklearn.metrics.precision_score",
"sklearn.metrics.balanced_accuracy_score",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.mean_a... |
GODA47/Fasttext | [
"9781430b60954516d968feb6e9ca03fc20ed24da"
] | [
"utils/SubwordHash.py"
] | [
"import os\nimport numpy as np\nfrom tqdm import tqdm\nfrom nltk import word_tokenize\nimport re\nimport nltk\nimport math\nimport torch\nfrom nltk import word_tokenize\nfrom nltk import WordNetLemmatizer\nfrom nltk.corpus import stopwords \n\nfrom .replace_dict import rep\nfrom .config import *\n\nlem = WordNetLem... | [
[
"numpy.array",
"torch.cuda.is_available",
"numpy.random.choice",
"torch.tensor"
]
] |
awesome-archive/buffalo | [
"1bcb76b61161e74324ca71ed05ce0576598798b5"
] | [
"buffalo/data/prepro.py"
] | [
"# -*- coding: utf-8 -*-\nimport numpy as np\n\n\nclass PreProcess(object):\n def __init__(self, opt):\n self.opt = opt\n\n def pre(self, header):\n pass\n\n def __call__(self, v):\n return v\n\n def post(self, db):\n pass\n\n\nclass OneBased(PreProcess):\n def __init__(se... | [
[
"numpy.max",
"numpy.min",
"numpy.log"
]
] |
rhLahr/CNN_coffee_ring_effect | [
"1445d1d97dfc04fd79ff1dabde0761af550ea394"
] | [
"main_test.py"
] | [
"import numpy as np\r\nfrom PIL import Image\r\nimport torch\r\nimport torch.nn as nn\r\nfrom load_test_data import load_test_data\r\nfrom sklearn.metrics import confusion_matrix\r\nfrom model_result import model_result\r\nimport matplotlib.pyplot as plt\r\nimport seaborn as sn\r\nimport pandas as pd\r\n\r\n\r\ncla... | [
[
"torch.nn.Linear",
"numpy.zeros",
"torch.nn.Sigmoid",
"torch.nn.MaxPool2d",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"matplotlib.pyp... |
yghlc/rs_img_proc | [
"2f704b0c6ac456b6893142f1900c732ea2b8c637"
] | [
"tools/plot_Images_histogram_test.py"
] | [
"#!/usr/bin/env python\n# Filename: plot_Images_histogram_test.py \n\"\"\"\nintroduction:\n# run \"pytest plot_Images_histogram_test.py \" or \"pytest \" for test, add \" -s for allowing print out\"\n# \"pytest can automatically search *_test.py files \"\n\nauthors: Huang Lingcao\nemail:huanglingcao@gmail.com\nadd... | [
[
"numpy.histogram",
"numpy.loadtxt",
"numpy.arange"
]
] |
GIShkl/GAOFEN2021_CHANGEDETECTION | [
"5b7251cb1e951a04c7effacab6c1233232158472"
] | [
"models/backbone/resnet.py"
] | [
"import torch.utils.model_zoo as model_zoo\nimport torch\nimport torch.nn as nn\n\n\n__all__ = ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101',\n 'resnet152', 'resnext50_32x4d', 'resnext101_32x8d']\n\n\ndef conv3x3(in_planes, out_planes, stride=1, groups=1, dilation=1):\n return nn.Conv2d(in... | [
[
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.load",
"torch.nn.AdaptiveAvgPool2d"
]
] |
Computational-Plant-Science/smart | [
"852f9651555cc24ff3603b5b44937bf07ffe9480"
] | [
"dev_code/demo_color_seg.py"
] | [
"'''\nName: color_segmentation.py\n\nVersion: 1.0\n\nSummary: K-means color clustering based segmentation. This is achieved \n by converting the source image to a desired color space and \n running K-means clustering on only the desired channels, \n with the pixels being grouped into a desir... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.count_nonzero",
"numpy.zeros",
"numpy.sum",
"sklearn.cluster.KMeans",
"numpy.ones",
"numpy.where"
]
] |
Pragyanstha/SummerCamp2021 | [
"caa8bba64020ba52bdef2b23a7a54de93e93b8af"
] | [
"models_search/ViT_custom_local544444_256_rp.py"
] | [
"import torch\nimport torch.nn as nn\nimport math\nimport numpy as np\nfrom models_search.ViT_helper import DropPath, to_2tuple, trunc_normal_\nfrom models_search.diff_aug import DiffAugment\nimport torch.utils.checkpoint as checkpoint\n\n\nclass matmul(nn.Module):\n def __init__(self):\n super().__init__... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.meshgrid",
"torch.nn.LayerNorm",
"torch.nn.init.constant_",
"torch.nn.AvgPool2d",
"numpy.sqrt",
"torch.zeros",
"torch.nn.Identity",
"torch.nn.functional.leaky_relu_",
"torch.nn.Sequential",
"torch.linspace",
"torch.nn.Pixel... |
kimbfs/Proyecto | [
"3065b2d721365d3e92d93bc449c1cea92bbf4ed8"
] | [
"common/utils.py"
] | [
"import os\nimport numpy as np\nimport time\nimport cv2, colorsys\nfrom PIL import Image\nfrom matplotlib.colors import rgb_to_hsv, hsv_to_rgb\n\nfrom common.backbones.efficientnet import swish\nfrom common.backbones.mobilenet_v3 import hard_sigmoid, hard_swish\n\n\ndef optimize_tf_gpu(tf, K):\n if tf.__version_... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.ones",
"numpy.random.shuffle",
"numpy.around"
]
] |
blankandwhite1/mit-amazon-last-mile | [
"e760f1d0847b3e2b1ac085f2a2e979093c56d54c"
] | [
"src/zoneTSP_exp.py"
] | [
"import os\r\nimport random\r\nfrom os import path\r\nimport numpy as np\r\nfrom tsp_solver.greedy import solve_tsp\r\nfrom typing import Dict, List\r\nimport time\r\nimport random as rng\r\nfrom sklearn.model_selection import ShuffleSplit\r\n\r\nimport fy_score\r\nimport readData as rd\r\nimport zoneTSP as zt\r\ni... | [
[
"matplotlib.pyplot.annotate",
"numpy.dot",
"matplotlib.pyplot.xlim",
"numpy.exp",
"numpy.min",
"numpy.unique",
"numpy.linalg.norm",
"matplotlib.pyplot.savefig",
"numpy.array",
"scipy.spatial.Voronoi",
"numpy.zeros",
"matplotlib.pyplot.title",
"matplotlib.pyplot.... |
hackingmaterials/amset | [
"99d9a7d25f47696820ca704af36c46bad9cc49d4"
] | [
"amset/deformation/potentials.py"
] | [
"import logging\n\nimport numpy as np\nfrom pymatgen.analysis.elasticity.strain import Deformation\nfrom pymatgen.core.tensors import TensorMapping\n\nfrom amset.constants import defaults\nfrom amset.electronic_structure.kpoints import (\n get_kpoint_indices,\n get_kpoints_from_bandstructure,\n get_mesh_fr... | [
[
"numpy.max",
"numpy.array",
"numpy.linalg.norm",
"numpy.zeros",
"numpy.any",
"numpy.where",
"numpy.abs",
"numpy.linalg.inv"
]
] |
dlilien/demcoreg | [
"9ac182ac4f7d65220efd1ae37f1396a82264fe6b"
] | [
"demcoreg/dem_mask.py"
] | [
"#! /usr/bin/env python\n\"\"\"\nUtility to automate reference surface identification for raster co-registration\n\nNote: Initial run may take a long time to download and process required data (NLCD, global bareground, glacier polygons)\n\nCan control location of these data files with DATADIR environmental variable... | [
[
"numpy.logical_or",
"numpy.array",
"scipy.ndimage.morphology.binary_dilation",
"numpy.ma.masked_greater",
"numpy.ma.median",
"numpy.ma.getmaskarray",
"numpy.logical_and",
"numpy.ma.array"
]
] |
abdallah1097/pytorch_ner | [
"b1729d97ccb168e5796045cf9b387b35536803eb",
"b1729d97ccb168e5796045cf9b387b35536803eb"
] | [
"tests/test_nn_modules/test_rnn.py",
"pytorch_ner/onnx.py"
] | [
"import unittest\n\nimport torch\nimport torch.nn as nn\n\nfrom pytorch_ner.nn_modules.rnn import DynamicRNN\n\nembeddings = torch.randn(10, 20, 128) # [batch_size, seq_len, emb_dim]\nlengths = torch.arange(start=20, end=10, step=-1)\n\n\nrnn = DynamicRNN(\n rnn_unit=nn.RNN,\n input_size=128,\n hidden_siz... | [
[
"torch.Size",
"torch.randn",
"torch.arange"
],
[
"torch.no_grad",
"torch.tensor",
"torch.onnx.export"
]
] |
comscope/comsuite | [
"b80ca9f34c519757d337487c489fb655f7598cc2"
] | [
"ComRISB/pygtool/gw_gutz/plot_dos.py"
] | [
"import numpy as np\nimport h5py\nfrom pyglib.estructure import dos as _dos\nfrom future_builtins import zip\n\n\nwith h5py.File(\"../GPARAMBANDS.h5\", 'r') as f:\n w_k = f[\"/kptwt\"][...]\n bnd_ne = f[\"/NE_LIST\"][...]\n nsym = f[\"/symnop\"][0]\n nkp = f[\"/kptdim\"][0]\n nbmax = f[\"/nbmax\"][0]... | [
[
"matplotlib.pyplot.xlim",
"numpy.asarray",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
smihael/yolact | [
"26dd23d55b356a4f4bb04198d984c8796bb68cda"
] | [
"data/config.py"
] | [
"from backbone import ResNetBackbone, VGGBackbone, ResNetBackboneGN, DarkNetBackbone\nfrom math import sqrt\nimport torch\n\n# for making bounding boxes pretty\nCOLORS = ((244, 67, 54),\n (233, 30, 99),\n (156, 39, 176),\n (103, 58, 183),\n ( 63, 81, 181),\n ( 33,... | [
[
"torch.nn.functional.relu",
"torch.nn.functional.softmax"
]
] |
Victorpc98/CE888-Project | [
"99c20adc78eb53ac4d3c87543ef8da1ef4d10adc"
] | [
"main.py"
] | [
"import sys, getopt\nfrom src.uct import OXOState,OthelloState,NimState,UCT\nfrom src.dataCollector import DataCollector\nfrom src.rfc import RandomForest\nfrom src.svm import SVM\nfrom src.mlp import MLPClassifier\nimport argparse\nimport pandas as pd\nimport datetime\nfrom src.definitions import ROOT_DIR,RESULTS_... | [
[
"pandas.DataFrame"
]
] |
jayvicson/Vote-Goat-Backend | [
"d5880ccbd03e08e69f793f28bd8da74285252c7e"
] | [
"hug_server/hug_script_nn_only_without_hug.py"
] | [
"# Required for NN\r\nfrom tqdm import tqdm\r\nfrom sklearn import dummy, metrics, cross_validation, ensemble\r\nfrom keras.models import load_model\r\nimport numpy as np\r\nimport pandas\r\nimport os\r\nimport zipfile\r\nimport requests\r\nimport keras.models as kmodels\r\nimport keras.layers as klayers\r\nimport ... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.reshape",
"numpy.zeros",
"numpy.ones",
"numpy.arange",
"numpy.argsort",
"numpy.int_",
"pandas.read_csv"
]
] |
Sewanex/wav2vec2-service | [
"fe9c5fa61bfe85f3e36c78cf71a3bcbe3959ac13"
] | [
"convert_torch_to_onnx.py"
] | [
"from onnxruntime.quantization.quantize import quantize\nfrom transformers import Wav2Vec2ForCTC\nimport torch\nimport argparse\n\ndef convert_to_onnx(model_id_or_path, onnx_model_name):\n print(f\"Converting {model_id_or_path} to onnx\")\n model = Wav2Vec2ForCTC.from_pretrained(model_id_or_path)\n audio_l... | [
[
"torch.randn",
"torch.onnx.export"
]
] |
stone3311/HyperGAN | [
"eed4869688ac4273a661cbbd03db0ec1dad89049"
] | [
"hypergan/samplers/batch_walk_sampler.py"
] | [
"from PIL import Image\nfrom hypergan.samplers.base_sampler import BaseSampler\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport time\n\nclass BatchWalkSampler(BaseSampler):\n def __init__(self, gan, samples_per_row=4, session=None):\n BaseSampler.__init__(self, gan, samples_per_row)\n ... | [
[
"torch.zeros",
"torch.gt",
"torch.lt",
"torch.norm",
"torch.ones",
"torch.ones_like",
"torch.nn.Hardtanh"
]
] |
wpeebles/gangealing | [
"870eab8f1685f62000f98a05d983e2a2ed78e68c"
] | [
"applications/mixed_reality.py"
] | [
"\"\"\"\nThis script directly applies our method to video, finding dense correspondences across time in an input video. This works\nby applying GANgealing per-frame without using any temporal information.\n\"\"\"\nimport torch\nimport numpy as np\nimport math\nfrom datasets import img_dataloader\nfrom prepare_data ... | [
[
"torch.cat",
"torch.inference_mode",
"torch.eye",
"numpy.stack",
"torch.where"
]
] |
nicococo/tilitools | [
"a9b62e2a6aa10322e2433f399634d3423704ccab"
] | [
"scripts/exm_multiclass.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nfrom ssvm import SSVM\nfrom latent_svdd import LatentSVDD\nfrom latent_ocsvm import LatentOCSVM\nfrom latent_pca import LatentPCA\n\nfrom so_multiclass import SOMultiClass\n\n\nif __name__ == '__main__':\n NUM_CLASSES = 3\n NUM_DATA = 40 # per class\n\n... | [
[
"numpy.random.rand",
"numpy.reshape",
"numpy.zeros",
"matplotlib.pyplot.contourf",
"matplotlib.pyplot.grid",
"numpy.ones",
"matplotlib.pyplot.title",
"matplotlib.pyplot.figure",
"numpy.eye",
"numpy.arange",
"matplotlib.pyplot.scatter",
"numpy.append",
"matplotli... |
tdunlap607/PyRef | [
"b15a25a9d43a1021e700be78b5c80af0ec9aab7d"
] | [
"repomanager/repo_changes.py"
] | [
"import ast\nimport os\nimport astunparse\nimport pandas as pd\nfrom git import Repo\n\n\n# get the the changes in the latest commits and store them in a dataframe\ndef last_commit_changes(repo_path):\n modified_files = []\n repo = Repo(repo_path)\n for item in repo.head.commit.diff('HEAD~1').iter_change_t... | [
[
"pandas.DataFrame"
]
] |
connorlee77/ssd_keras | [
"0e1b9cff4300fe6e11a4345aa47d740f76bdcef2"
] | [
"models/keras_ssd512.py"
] | [
"'''\r\nA Keras port of the original Caffe SSD512 network.\r\n\r\nCopyright (C) 2018 Pierluigi Ferrari\r\n\r\nLicensed under the Apache License, Version 2.0 (the \"License\");\r\nyou may not use this file except in compliance with the License.\r\nYou may obtain a copy of the License at\r\n\r\n http://www.apache.o... | [
[
"numpy.any",
"numpy.array",
"numpy.linspace"
]
] |
alex1770/Covid-19 | [
"0212593bf5d9bcbb7009c7d1fb1710116ad8bf32",
"0212593bf5d9bcbb7009c7d1fb1710116ad8bf32",
"0212593bf5d9bcbb7009c7d1fb1710116ad8bf32"
] | [
"VOCgrowth/EarlyOmicronEstimates_UK/bestfit+resid.py",
"zoeappdeconv.py",
"VOCgrowth/EarlyOmicronEstimate/extractsgtf.py"
] | [
"# py bestfit2+resid.py < file\n# Format: Date, #Oldvariant, #Newvariant\n# log(#New/#Old) ~= a + b*day\n# Square errors are weighted by 1/(1/#Old+1/#New).\n\nfrom stuff import *\nimport numpy as np\nimport sys\nfrom math import sqrt\n\nA=[];D=[];dt=[]\nfor x in sys.stdin:\n y=x.split()\n a,d=float(y[1]),float(y[... | [
[
"numpy.linalg.solve",
"numpy.array",
"numpy.log"
],
[
"numpy.array",
"numpy.linalg.lstsq",
"numpy.zeros",
"scipy.stats.gamma.sf"
],
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"numpy.roll",
"numpy.argmax",
"numpy.arange",
"numpy.dtype",
... |
karaage0703/denpa-gardening | [
"ed0288b600203e787b5d50f81100a4a738ec2014"
] | [
"photo-exif-date-print.py"
] | [
"# -*- coding: utf-8 -*-\nimport cv2\nimport sys\nimport numpy as np\nfrom PIL import Image, ImageDraw, ImageFont\nfrom PIL.ExifTags import TAGS, GPSTAGS\n\nfont_color = (255, 255, 255)\n\ndef get_exif(file,field):\n img = Image.open(file)\n exif = img._getexif()\n\n exif_data = []\n for id, value in ex... | [
[
"numpy.array"
]
] |
covidcaremap/chime | [
"4ba3bed63315d8eefae8293f5a51641c12a1daf9"
] | [
"tests/penn_chime/test_models.py"
] | [
"from datetime import date\n\nimport pytest\nimport pandas as pd\nimport numpy as np\nfrom datetime import timedelta\n\nfrom penn_chime.models import (\n sir,\n sim_sir,\n get_growth_rate,\n SimSirModel,\n)\n\nfrom src.penn_chime.constants import EPSILON\n\n\ndef test_sir():\n \"\"\"\n Someone who... | [
[
"pandas.DataFrame",
"numpy.arange"
]
] |
Antoinehoff/Project_II | [
"120209e695f4f25ecdc6797f683e2b23894689f4"
] | [
"src/appearance.py"
] | [
"import os\nimport numpy\nimport pyopencl as cl\n\n\nclass AppearanceCL(object):\n\n def __init__(self, lambda_occ, esim, appearance_norm_weight):\n os.environ[\"PYOPENCL_COMPILER_OUTPUT\"] = \"1\"\n self.cl_context = cl.create_some_context(False)\n self.queue = cl.CommandQueue(self.cl_conte... | [
[
"numpy.ndarray",
"numpy.int32",
"numpy.zeros",
"numpy.double"
]
] |
tuix/tutorials | [
"733d35a8a39df079e8c2432c441b70785ab08440"
] | [
"openml_data_integration/protobuf_generator/openml_1480/server.py"
] | [
"# date: 2021.07.14\n# author: Raul Saavedra raul.saavedra.felipe@iais.fraunhofer.de\n\nimport grpc\nfrom concurrent import futures\nimport time\nimport numpy\n\n# import constant with the hardcoded openml data ID number\nimport myconstants\n\n# import the generated grpc related classes for python\nimport model_pb2... | [
[
"numpy.uint32"
]
] |
YihengZhang-CV/Sequence-Contrastive-Learning | [
"f0b1b48731de808694e57da348e366df57dcd8c7"
] | [
"downstream/finetune/train.py"
] | [
"import argparse\nimport os\nimport time\nimport json\n\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.distributed as dist\nfrom torch.nn.parallel import DistributedDataParallel\nfrom torchvision import transforms\n\nfrom seco_util import clip_transforms\nfrom seco_util.util import ClipGaussianBl... | [
[
"torch.cat",
"torch.stack",
"torch.distributed.init_process_group",
"torch.nn.parallel.DistributedDataParallel",
"torch.cuda.set_device",
"torch.utils.data.DataLoader",
"torch.utils.data.distributed.DistributedSampler",
"torch.load",
"torch.cuda.amp.GradScaler",
"torch.dist... |
9xEzreaL/WBC_AttGAN | [
"32c8f0bd38fb8cc6ebc4b3994031873ea6f47ed4"
] | [
"util/loss.py"
] | [
"from __future__ import print_function\n\nimport torch\nimport torch.nn as nn\n\n\nclass SupConLoss(nn.Module):\n \"\"\"Supervised Contrastive Learning: https://arxiv.org/pdf/2004.11362.pdf.\n It also supports the unsupervised contrastive loss in SimCLR\"\"\"\n def __init__(self, temperature=0.07, contrast... | [
[
"torch.isnan",
"torch.max",
"torch.arange",
"torch.unbind",
"torch.eq",
"torch.full_like",
"torch.eye",
"torch.ones_like",
"torch.matmul",
"torch.exp"
]
] |
adrn/exoplanet | [
"24ee1fc4a7d984295740464888ca3ab9d20edb0a"
] | [
"tests/utils_test.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport numpy as np\nimport pymc3 as pm\n\nfrom exoplanet.utils import eval_in_model, optimize\n\n\ndef test_eval_in_model(seed=123409):\n np.random.seed(seed)\n x_val = np.random.randn(5, 3)\n x_val2 = np.random.randn(5, 3)\n with pm.Model():\n x = pm.Normal(\"x\", sha... | [
[
"numpy.random.seed",
"numpy.allclose",
"numpy.random.randn"
]
] |
bluesheepcj/WorkWork | [
"598baf9c7ec8f17089954f18a4135f69b53af670"
] | [
"person/btyang/stock/TryWork/TestMain/Test.py"
] | [
"import numpy as np\n\nimport re\n\n# 将正则表达式编译成Pattern对象\npattern = re.compile(r'(SH[\\w\\W]+)\\.csv')\n# pattern = re.compile(r'ˆSH')\n\n# 使用Pattern匹配文本，获得匹配结果，无法匹配时将返回None\nmatch = pattern.match('SHfjdfj984r3.csv')\n\nif match:\n # 使用Match获得分组信息\n print(match.group(1));\n\n### 输出 ###\n# hello\n\nmat = np.ze... | [
[
"numpy.zeros",
"numpy.append"
]
] |
femtotrader/pythalesians | [
"febdfbabc9f99b0ae3eb0b20ce4c5ed6a34c0bbb"
] | [
"chartesians/graphicsconstants.py"
] | [
"__author__ = 'saeedamen' # Saeed Amen / saeed@thalesians.com\n\n#\n# Copyright 2015 Thalesians Ltd. - http//www.thalesians.com / @thalesians\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the\n# License. You may obtain a copy of the Licen... | [
[
"matplotlib.use"
]
] |
cg-saarland/GloBiE | [
"23cb52e8c06716667eca2c174f3f732b20315098"
] | [
"service.py"
] | [
"import json\nimport numpy\nimport math\nimport os\nimport argparse\nimport sys\nimport random\n\n# add dependencies for auto-py-to-exe\n# https://github.com/pyinstaller/pyinstaller/issues/4363#issuecomment-522350024\n# import numpy.random.common\n# import numpy.random.bounded_integers\n# import numpy.random.entrop... | [
[
"numpy.ndarray",
"numpy.zeros"
]
] |
Waterpine/dataprep-1 | [
"4032acb1d1f2c413d4cb000d17e8ffa611315f9f",
"4032acb1d1f2c413d4cb000d17e8ffa611315f9f"
] | [
"dataprep/clean/clean_currency.py",
"dataprep/tests/clean/test_clean_phone.py"
] | [
"\"\"\"\nClean and validate a DataFrame column containing currencies\n\"\"\"\n\n# pylint: disable=too-many-arguments, line-too-long, too-many-locals, too-many-branches, too-many-statements, too-many-return-statements,\n\nimport json\nfrom os import path\nfrom operator import itemgetter\nfrom typing import Any, List... | [
[
"numpy.round"
],
[
"pandas.DataFrame",
"pandas.Series"
]
] |
nithinksath96/MMdetection_TensorRT_FP16 | [
"c8379b209d4deeff9350baf5bbedfc95fb8941f4"
] | [
"mmdet/models/necks/fpn.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\nfrom mmcv.cnn import xavier_init\n\nfrom mmdet.core import auto_fp16\nfrom ..registry import NECKS\nfrom ..utils import ConvModule\n\n\n@NECKS.register_module\nclass FPN(nn.Module):\n \"\"\"\n Feature Pyramid Network.\n\n This is an implementation of... | [
[
"torch.nn.functional.relu",
"torch.nn.functional.interpolate",
"torch.nn.functional.max_pool2d",
"torch.nn.ModuleList"
]
] |
gut-space/svarog | [
"d68020a8f104da3b30a29ad24cc0ac64cf12ef5c"
] | [
"station/receiver.py"
] | [
"import datetime\nimport logging\nimport os\nimport shutil\nimport sys\nimport typing\n\nfrom matplotlib.pyplot import imread\n\nfrom utils.functional import first\nfrom utils.models import get_satellite\nfrom utils.dates import from_iso_format\nfrom utils.configuration import open_config\nfrom submitobs import sub... | [
[
"matplotlib.pyplot.imread"
]
] |
rallen10/maddpg | [
"7e68d12474fae83777ba85694277ac2c3abff2a2"
] | [
"maddpg/common/distributions.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport maddpg.common.tf_util as U\nfrom tensorflow.python.ops import math_ops\nfrom multiagent.multi_discrete import MultiDiscreteLegacy\nfrom tensorflow.python.ops import nn\n\nclass Pd(object):\n \"\"\"\n A particular probability distribution\n \"\"\"\n de... | [
[
"tensorflow.exp",
"tensorflow.shape",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.concat",
"tensorflow.python.ops.math_ops.less",
"tensorflow.sigmoid",
"numpy.log",
"tensorflow.round",
"tensorflow.nn.sigmoid_cross_entropy_with_logits",
"tensorflow.constan... |
MartinSantaGitHub/machinelearning-az | [
"d672073e63eb09e5f3ba7cc8bdc6980d7e21c291",
"d672073e63eb09e5f3ba7cc8bdc6980d7e21c291"
] | [
"codigo/10 - Model Selection & Boosting/1 - Model Selection/k_fold_validation.py",
"codigo/03 - Classification/2 - K-Nearest Neighbors (K-NN)/knn.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Thu Dec 24 17:34:40 2020\n\n@author: msantamaria\n\"\"\"\n\n# k - Fold Cross Validation\n\n# Importar las librerías\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importar el data set \ndataset = pd.read_csv(\"Social_Network_Ads.csv\")\nX ... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.preprocessing.StandardScaler",
"sklearn.svm.SVC",
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"sklearn.model_selection.cross_val_score"
],
[
"sklearn.metrics.confusion_matrix",
"sklearn.preprocessing.StandardScaler... |
albireox/sdssdb | [
"02d165d3a4347e8241aacdbdca0cec86058c8d29"
] | [
"python/sdssdb/utils/ingest.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n#\n# @Author: José Sánchez-Gallego (gallegoj@uw.edu)\n# @Date: 2019-09-21\n# @Filename: ingest.py\n# @License: BSD 3-clause (http://www.opensource.org/licenses/BSD-3-Clause)\n\nimport functools\nimport io\nimport multiprocessing\nimport os\nimport re\nimport warnings... | [
[
"numpy.ma.is_masked",
"numpy.isscalar"
]
] |
haqishen/transformers | [
"d38bbb225f7b847e8be4e969cb9b40e7e4d798a6"
] | [
"src/transformers/activations.py"
] | [
"import math\n\nimport torch\nimport torch.nn.functional as F\n\n\ndef swish(x):\n return x * torch.sigmoid(x)\n\n\ndef _gelu_python(x):\n \"\"\" Original Implementation of the gelu activation function in Google Bert repo when initially created.\n For information: OpenAI GPT's gelu is slightly differen... | [
[
"torch.sigmoid",
"torch.pow"
]
] |
JMFlin/auto-preference-finder | [
"07dd2e6b2b28398ca9bfb6ad328c578eb9987417"
] | [
"roles/modeling/fast/model.py"
] | [
"# https://www.tensorflow.org/tutorials/load_data/images\n# https://www.tensorflow.org/tutorials/keras/overfit_and_underfit\n# https://www.tensorflow.org/tutorials/keras/save_and_load\nimport tensorflow as tf\nimport logging\nimport os\nimport os.path\nfrom tensorflow.keras import layers\nfrom google.cloud import s... | [
[
"tensorflow.keras.Input",
"tensorflow.keras.layers.add",
"tensorflow.keras.layers.SeparableConv2D",
"tensorflow.keras.preprocessing.image_dataset_from_directory",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.layers.experimental.preprocessing.RandomRotation",
"tensorflow.kera... |
sebalp1987/anomaly_detection_answers | [
"fee2eb08302c1e340acd910d1777016625c25def"
] | [
"models/inception_model.py"
] | [
"import numpy as np\r\nimport pandas as pd\r\nfrom keras.utils import to_categorical\r\nfrom keras import layers, Input, regularizers\r\nfrom keras.models import Model\r\nfrom sklearn import metrics\r\nfrom keras.optimizers import SGD, Adam\r\nfrom keras.callbacks import EarlyStopping\r\nimport STRING\r\nfrom resou... | [
[
"numpy.array",
"sklearn.preprocessing.StandardScaler",
"numpy.random.seed",
"sklearn.feature_selection.VarianceThreshold",
"numpy.linspace",
"pandas.concat",
"pandas.read_csv",
"pandas.Series"
]
] |
czc567/UniGNN | [
"bbb061f393b847ff6c7c20cab9e1ecb8f1c3eb96"
] | [
"prepare.py"
] | [
"from model import *\nimport torch, numpy as np, scipy.sparse as sp\nimport torch.optim as optim, torch.nn.functional as F\n\n\ndef accuracy(Z, Y):\n \n return 100 * Z.argmax(1).eq(Y).float().mean().item()\n\n\nimport torch_sparse\n\ndef fetch_data(args):\n from data import data \n dataset, _, _ = data.... | [
[
"numpy.isinf",
"numpy.array",
"scipy.sparse.diags",
"scipy.sparse.csc_matrix",
"torch.optim.Adam",
"numpy.where",
"numpy.power"
]
] |
KohMat/carracing-dreamer | [
"1e46bf0e6bcbb45adc2fef1b9b65f54e2706f77d"
] | [
"dreamer/utils/plot.py"
] | [
"from typing import Union\n\nimport numpy as np\nfrom visdom import Visdom\n\n\nclass Plot:\n def __init__(self, x_label=\"Epoch\", y_label=\"Loss\", visdom=None):\n self.impl = LinePlot(x_label=x_label, y_label=y_label, visdom=visdom)\n\n def add(\n self,\n epoch: Union[int, float, np.fl... | [
[
"numpy.array"
]
] |
reigHns/RANZCR-CLiP---Catheter-and-Line-Position-Challenge | [
"80d4177bf74f9ffa5f7906687ebe648832ec84e1"
] | [
"src/test.py"
] | [
"from src.model_blocks import *\nimport torch.nn as nn\nimport timm\nfrom src.activations import Swish_Module\nfrom src.config import YAMLConfig\nimport typing\nimport gc\nfrom src.utils import *\n\n\"\"\" Test two pytorch models are the same \"\"\"\n\n\n\"\"\"\nThis is a testing for RANZCR. Note that the model wei... | [
[
"torch.nn.Linear",
"torch.rand",
"torch.cat",
"torch.nn.Dropout",
"torch.hub.load_state_dict_from_url",
"torch.torch.nn.Linear",
"torch.load",
"torch.nn.AdaptiveAvgPool2d",
"torch.torch.nn.Dropout",
"torch.nn.Flatten"
]
] |
Syps/osu_beatmap_generator | [
"684b5356bbf79ba847b3ab20e2b6b3a73d7721ad"
] | [
"osu_map_gen/train/train.py"
] | [
"import _pickle as cPickle\nimport collections\nimport operator\nimport os\nimport pdb\nimport random\nfrom functools import reduce\nfrom typing import List\n\nimport h5py\nimport joblib\nimport matplotlib.pyplot as plt\nimport numpy as np\nfrom skimage.util import view_as_windows\nfrom sklearn.preprocessing import... | [
[
"tensorflow.python.keras.callbacks.ModelCheckpoint",
"numpy.load",
"tensorflow.python.keras.layers.Dense",
"tensorflow.python.keras.layers.BatchNormalization",
"tensorflow.python.keras.models.Sequential",
"numpy.concatenate",
"tensorflow.python.keras.layers.MaxPooling2D",
"numpy.fu... |
ZhiningLiu1998/mesa | [
"fd024e4754570374b1f0935e00ca1eab6b23f584"
] | [
"sac_src/sac.py"
] | [
"import os\nimport torch\nimport torch.nn.functional as F\nfrom torch.optim import Adam, lr_scheduler\nfrom sac_src.utils import soft_update, hard_update\nfrom sac_src.model import GaussianPolicy, QNetwork, DeterministicPolicy\n\n\nclass SAC(object):\n def __init__(self, num_inputs, action_space, args):\n\n ... | [
[
"torch.zeros",
"torch.device",
"torch.optim.lr_scheduler.StepLR",
"torch.min",
"torch.no_grad",
"torch.optim.Adam",
"torch.FloatTensor",
"torch.nn.functional.mse_loss",
"torch.tensor",
"torch.load",
"torch.Tensor"
]
] |
marcoag/traffic_editor | [
"486b6e0c03fdc5e8db460e0fa983038fc186397c"
] | [
"building_map_tools/building_map/wall.py"
] | [
"import math\nimport os\nimport shutil\n\nimport numpy as np\n\nfrom xml.etree.ElementTree import SubElement\nfrom ament_index_python.packages import get_package_share_directory\n\nfrom .edge import Edge\nfrom .param_value import ParamValue\n\n\nclass Wall:\n def __init__(self, yaml_node, wall_params):\n\n ... | [
[
"numpy.array",
"numpy.zeros",
"numpy.vstack"
]
] |
MODU-FTNC/google-research | [
"88481d10a87947ffb9305dc7665682e008b27391",
"e244dbf3c619a0429368e382f5a5f89e0d220c6a"
] | [
"meta_learning_without_memorization/pose_code/maml_bbb_2.py",
"robust_loss/util.py"
] | [
"# coding=utf-8\n# Copyright 2019 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... | [
[
"tensorflow.compat.v1.map_fn",
"tensorflow.compat.v1.zeros",
"tensorflow.contrib.layers.python.layers.batch_norm",
"tensorflow.compat.v1.matmul",
"tensorflow.compat.v1.reduce_sum",
"tensorflow.compat.v1.to_float",
"tensorflow.compat.v1.reshape",
"tensorflow.compat.v1.gradients",
... |
ChristophHoenes/EWoMan | [
"f2d0457926e3ccef2e704b05d1df38345d826a5d"
] | [
"generate_plots_all.py"
] | [
"import pickle\nimport numpy as np\nfrom matplotlib import pyplot as plt\n\n\ndef plot_stat_mean(stat_key='mean', methods=['method_1', 'method3'], enemy=2, seeds=None, prefix=None, fancy=False, savepath=''):\n runs = []\n max_list = []\n\n if seeds is None:\n seeds = [111, 222, 333, 444, 555, 666, 7... | [
[
"numpy.asarray",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.suptitle",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.close",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show"
]
] |
tblazina/pymc3 | [
"9d90c891de5a2f491c51f8311b387f051e27538a"
] | [
"pymc3/tests/test_model.py"
] | [
"# Copyright 2020 The PyMC Developers\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 appli... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.random.binomial",
"numpy.array_equal",
"numpy.zeros",
"numpy.random.RandomState",
"numpy.testing.assert_almost_equal",
"numpy.log",
"numpy.ones",
"numpy.random.randn",
"numpy.exp",
"numpy.ma.masked_values",
... |
ShabbirHasan1/kinetick | [
"9846210535e4f86bbac3611ff7883fd89103fb53"
] | [
"kinetick/strategies/macd_super_strategy.py"
] | [
"# Copyright 2021 vin8tech\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or agreed to in w... | [
[
"pandas.DataFrame",
"pandas.option_context",
"numpy.vectorize"
]
] |
rockingdingo/ParlAI | [
"ceb009e1d81d2fec22454667559c6ff02a5624b9"
] | [
"examples/drqa/interactive.py"
] | [
"# Copyright (c) 2017-present, Facebook, Inc.\n# All rights reserved.\n# This source code is licensed under the BSD-style license found in the\n# LICENSE file in the root directory of this source tree. An additional grant\n# of patent rights can be found in the PATENTS file in the same directory.\n\"\"\"Simple inte... | [
[
"torch.cuda.set_device",
"torch.cuda.is_available"
]
] |
AlanPXD/IC-AutoEncoder | [
"ec73cd9928f47e57b7f3ec66efc5ebe37a418199"
] | [
"modules/TensorBoardWriter.py"
] | [
"from abc import ABC, abstractmethod\nfrom os import write\nfrom pandas.core.frame import DataFrame\nfrom tensorflow.python.keras.engine.training import Model\nfrom tensorflow.python.ops import summary_ops_v2\nimport tensorflow as tf\n\n\nclass TensorBoardWriterABC (ABC):\n \"\"\"\n This class \n \"\"\... | [
[
"tensorflow.summary.create_file_writer",
"tensorflow.summary.image",
"tensorflow.python.ops.summary_ops_v2.keras_model",
"tensorflow.summary.scalar"
]
] |
mtopalid/Neurosciences | [
"8531d59f8370f0cf7f1b4b1f72e4bf11b96e1354"
] | [
"basal-ganglia/topalidou-et-al-2014/cython/single-trial.py"
] | [
"# -*- coding: utf-8 -*-\n# -----------------------------------------------------------------------------\n# Copyright (c) 2014, Nicolas P. Rougier\n# Distributed under the (new) BSD License.\n#\n# Contributors: Nicolas P. Rougier (Nicolas.Rougier@inria.fr)\n# -------------------------------------------------------... | [
[
"numpy.zeros"
]
] |
hitzkrieg/CourteousStyleTransfer | [
"24bfc4cacc121aa60d8949d2c4817fe142b0b3ef"
] | [
"data_prep_code/cluster_embeddings_emotional.py"
] | [
"import numpy as np\nfrom sklearn.cluster import KMeans\nfrom sklearn.metrics import pairwise_distances_argmin_min\nfrom tqdm import tqdm\nfrom sklearn.cluster import DBSCAN, MiniBatchKMeans\nfrom sklearn import metrics\nfrom time import time \nimport pickle\n\ndef unpickle_2(filename):\n\twith open(filename, 'rb')... | [
[
"sklearn.metrics.silhouette_score",
"numpy.zeros_like",
"sklearn.cluster.DBSCAN",
"sklearn.cluster.MiniBatchKMeans"
]
] |
rtiglobalhealth/trachoma | [
"5aac19f7af45ed99a14e6712cda7e8c1f4118bbd"
] | [
"src/py/test_patches_2class.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.keras import layers\nfrom tensorflow.keras.applications.resnet50 import preprocess_input\nimport json\nimport os\nimport glob\nimport sys\ni... | [
[
"numpy.array",
"tensorflow.data.Dataset.from_generator",
"tensorflow.keras.models.load_model",
"tensorflow.config.list_physical_devices",
"pandas.read_csv",
"numpy.around",
"tensorflow.config.set_visible_devices"
]
] |
Orithu/curl_rainbow | [
"f372bd538b9381684c3e300f4be7353ecb2a980c"
] | [
"agent/agentBYOL.py"
] | [
"# -*- coding: utf-8 -*-\n# MIT License\n#\n# Copyright (c) 2017 Kai Arulkumaran\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the ri... | [
[
"torch.nn.functional.normalize",
"torch.nn.ReplicationPad2d",
"torch.no_grad",
"torch.linspace",
"numpy.random.randint",
"torch.load",
"numpy.random.random",
"torch.sum"
]
] |
daringpig/RL-from-morvan | [
"d10ff281f60c6828dc38db0d308d4ad8f220f4b9"
] | [
"contents/2_Q_Learning_maze/RL_brain.py"
] | [
"\"\"\"\nThis part of code is the Q learning brain, which is a brain of the agent.\nAll decisions are made in here.\n\nView more on my tutorial page: https://morvanzhou.github.io/tutorials/\n\"\"\"\n\nimport numpy as np\nimport pandas as pd\n\n\nclass QLearningTable:\n def __init__(self, actions, learning_rate=0... | [
[
"numpy.max",
"pandas.DataFrame",
"numpy.random.uniform",
"numpy.random.choice"
]
] |
apulis/mmaction | [
"fb6c5710dbb6d88a5564b64c096fdd5a749494dd"
] | [
"mmaction/datasets/video_dataset.py"
] | [
"import mmcv\nimport glob\nimport numpy as np\nimport os.path as osp\nfrom mmcv.parallel import DataContainer as DC\nfrom torch.utils.data import Dataset\n\nfrom .transforms import (GroupImageTransform)\nfrom .utils import to_tensor\n\ntry:\n import decord\nexcept ImportError:\n pass\n\n\nclass RawFramesRecor... | [
[
"numpy.random.rand",
"numpy.zeros",
"numpy.ones",
"numpy.random.randint",
"numpy.transpose"
]
] |
Smallflyfly/3d_pose_estimation_regression_method_sunrgbd | [
"7ec26c4efcde774c7fca565e608b955f54f4af1b"
] | [
"lib/layer_utils/proposal_target_layer.py"
] | [
"# --------------------------------------------------------\n# Faster R-CNN\n# Copyright (c) 2015 Microsoft\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Ross Girshick, Sean Bell and Xinlei Chen\n# --------------------------------------------------------\nfrom __future__ import absolute_... | [
[
"torch.autograd.Variable",
"torch.cat"
]
] |
robertlugg/keras-idiomatic-programmer | [
"6e33411d9eb1b170387aa0a9e7cf34fbbc84e59c",
"6e33411d9eb1b170387aa0a9e7cf34fbbc84e59c"
] | [
"zoo/unet/unet_c.py",
"zoo/alexnet/alexnet_p.py"
] | [
"# Copyright 2020 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.keras.layers.Dropout",
"tensorflow.keras.layers.MaxPooling2D",
"tensorflow.keras.Model",
"tensorflow.keras.Input",
"tensorflow.keras.layers.Cropping2D",
"tensorflow.keras.layers.Concatenate"
],
[
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Dense",
... |
marcomusy/welsh_embryo_stager | [
"9a9280bf6681d625568c97bb22334bb7cdfa12ea"
] | [
"utils.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nimport numpy as np\nfrom vedo.utils import sortByColumn\nfrom vedo import Plotter, Points, Spline\nfrom scipy import signal\nimport os\n\n#########################################################################\nclass SplinePlotter(Plotter):\n\n def __init__(sel... | [
[
"numpy.array",
"numpy.asarray",
"numpy.round",
"numpy.load",
"numpy.polyfit",
"numpy.abs",
"numpy.poly1d",
"numpy.linspace",
"scipy.signal.find_peaks"
]
] |
ShanleiMu/RecBole-1 | [
"9ec15faf90126dfb512901d0f2303ef3c2efb71d"
] | [
"recbole/model/general_recommender/nncf.py"
] | [
"# -*- coding: utf-8 -*-\r\n# @Time : 2021/1/14\r\n# @Author : Chengyuan Li\r\n# @Email : 2017202049@ruc.edu.cn\r\n\r\nr\"\"\"\r\nNNCF\r\n################################################\r\nReference:\r\n Ting Bai et al. \"A Neural Collaborative Filtering Model with Interaction-based Neighborhood.\" in CIKM 2... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.mul",
"torch.cat",
"numpy.zeros",
"torch.nn.Conv1d",
"torch.nn.Sigmoid",
"numpy.random.shuffle",
"torch.nn.ReLU",
"torch.nn.init.normal_",
"torch.tensor",
"torch.nn.BCELoss",
"sklearn.metrics.jaccard_score",
"tor... |
mtrazzi/understanding-rl | [
"b02595b0aec3e9632ef5d9814e925384931089bd"
] | [
"chapter6/figures.py"
] | [
"import argparse\nfrom td import OneStepTD\nfrom off_pol_td import OffPolicyTD\nfrom driving import DrivingEnv, TRAVEL_TIME\nfrom sarsa import Sarsa\nfrom windy_gridworld import WindyGridworld\nimport numpy as np\nfrom randomwalk import RandomWalk, NotSoRandomWalk, LEFT, RIGHT\nfrom cliff import TheCliff\nimport ma... | [
[
"numpy.max",
"numpy.array",
"numpy.linalg.norm",
"numpy.zeros",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"numpy.min",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure",
"numpy.mean",
"matplotlib.pyplot.close",
"ma... |
cclauss/petastorm | [
"12fc6542005c6dc7c99997604b939536cca79fa9"
] | [
"examples/mnist/tf_example.py"
] | [
"# Copyright (c) 2017-2018 Uber Technologies, 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 app... | [
[
"tensorflow.train.start_queue_runners",
"tensorflow.zeros",
"tensorflow.train.batch",
"tensorflow.train.Coordinator",
"tensorflow.argmax",
"tensorflow.matmul",
"tensorflow.Session",
"tensorflow.reshape",
"tensorflow.losses.sparse_softmax_cross_entropy",
"tensorflow.local_va... |
kyokono/tacotts | [
"bafb03f62405f5b93c098356051daf57d1defa6e"
] | [
"train.py"
] | [
"import argparse\nfrom datetime import datetime\nimport math\nimport numpy as np\nimport os\nimport subprocess\nimport time\nimport tensorflow as tf\nimport traceback\n\nfrom datasets.datafeeder import DataFeeder\nfrom hparams import hparams, hparams_debug_string\nfrom models import create_model\nfrom text import s... | [
[
"tensorflow.train.Coordinator",
"tensorflow.summary.scalar",
"tensorflow.summary.histogram",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.Variable",
"tensorflow.norm",
"tensorflow.variable_scope",
"tensorflow.reduce_max",
"tensorflow.device",
"tensorflow.... |
stanford-futuredata/supg | [
"cff4e7eb9b657e79a8f1d8e245e23bcad543126c"
] | [
"supg/selector/naive_recall.py"
] | [
"from typing import Sequence\n\nimport numpy as np\nimport math\n\nfrom supg.datasource import DataSource\nfrom supg.sampler import Sampler, ImportanceSampler\nfrom supg.selector.base_selector import BaseSelector, ApproxQuery\n\n\ndef calc_lb(p, n, delta, T):\n # Lower bound on the precision of a sample with fai... | [
[
"numpy.concatenate",
"numpy.sum",
"numpy.repeat"
]
] |
louwenjjr/nplinker | [
"22e957d0f3326775ca5c1f850073067c6fb256d6",
"22e957d0f3326775ca5c1f850073067c6fb256d6"
] | [
"prototype/nplinker/scoring/iokr/run_iokr_novel.py",
"prototype/nplinker/scoring/iokr/spectrum_filters.py"
] | [
"# Copyright 2021 The NPLinker 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 ... | [
[
"numpy.array",
"numpy.save"
],
[
"numpy.array"
]
] |
vrozova/cell_morphology | [
"8148e5cd5b20dc010eab2a83026aec0467573e54"
] | [
"randomforest.py"
] | [
"import os\nimport pandas as pd\nimport numpy as np\nimport preprocessing as proc\nimport randomforest as rf\nfrom pandas.api.types import CategoricalDtype\nimport seaborn as sns\nfrom matplotlib import pyplot as plt\nfrom scipy import stats\nimport joblib\n\nfrom imblearn.over_sampling import SMOTE\nfrom sklearn.m... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.metrics.mean_squared_error",
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"sklearn.model_selection.RandomizedSearchCV",
"sklearn.metrics.accuracy_score",
"numpy.mean",
"m... |
GitHub30/adanet | [
"a84211247e0e336ef5cfc47da598df37a75d66a8",
"a84211247e0e336ef5cfc47da598df37a75d66a8"
] | [
"adanet/core/summary.py",
"adanet/core/freezer_test.py"
] | [
"\"\"\"Tensorboard summaries for the single graph AdaNet implementation.\n\nCopyright 2018 The AdaNet Authors. All Rights Reserved.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n h... | [
[
"tensorflow.py_func",
"tensorflow.constant",
"tensorflow.summary.Summary"
],
[
"tensorflow.matmul",
"tensorflow.local_variables_initializer",
"tensorflow.global_variables_initializer",
"tensorflow.identity",
"tensorflow.random_normal",
"tensorflow.SparseTensor",
"tensor... |
fedarko/q2-qemistree | [
"611ab6d38fed8f59dda35984e49fa73d7431bc50"
] | [
"q2_qemistree/_transformer.py"
] | [
"from .plugin_setup import plugin\nfrom ._semantics import TSVMolecules\nimport pandas as pd\nimport qiime2\n\n\ndef _read_dataframe(fh):\n # Using `dtype=object` and `set_index` to avoid type casting/inference\n # of any columns or the index.\n df = pd.read_csv(fh, sep='\\t', header=0, dtype='str')\n r... | [
[
"pandas.read_csv"
]
] |
MM-Vision/pretrainedmodels.pytorch | [
"24efb031ad7a9fa2b209286c1fc7ace29a3a8a62"
] | [
"pretrainedmodels/imagenet/utils.py"
] | [
"from functools import partial\nfrom math import pi, cos\n\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.optim.lr_scheduler as lr_scheduler\nimport torchvision.transforms as transforms\n\nfrom .transforms import ColorJitter, Lighting\n\n\ndef create_optimizer(optimizer_config, model, niters=0):\... | [
[
"torch.optim.lr_scheduler.StepLR",
"torch.optim.Adam",
"torch.optim.SGD",
"torch.optim.lr_scheduler.ExponentialLR",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.optim.lr_scheduler.LambdaLR"
]
] |
jgonzalezab/workflow-DL-HPC | [
"773c32d71766c4d046dce4114cb4b2dd61138727"
] | [
"experiments/statistical-downscaling/precipitation/code/train.py"
] | [
"import os\nimport json\nimport numpy as np\nfrom time import time\nfrom keras.layers import Input, Conv2D, Flatten, Dense, UpSampling2D, \\\n Conv2DTranspose, Concatenate, BatchNormalization, \\\n ZeroPadding2D, LeakyReLU, LocallyConnected2D\nfrom keras.models import... | [
[
"tensorflow.math.lgamma",
"tensorflow.config.experimental.set_memory_growth",
"numpy.min",
"numpy.mean",
"numpy.std",
"tensorflow.config.experimental.list_physical_devices"
]
] |
YunqiuXu/H-KGA | [
"694a36baf9e51ffb97be269d8182a2b906eb0da5"
] | [
"dqn_memory_priortized_replay_buffer.py"
] | [
"# part of the code are from https://github.com/hill-a/stable-baselines/\nimport random\nfrom collections import namedtuple\nimport numpy as np\nimport torch\nfrom generic import to_np\nfrom segment_tree import SumSegmentTree, MinSegmentTree\n\n\nTransition = namedtuple('Transition', ('observation_list', \n ... | [
[
"numpy.any",
"numpy.array",
"numpy.random.randint",
"torch.stack"
]
] |
aculich/openmappr | [
"c9e5b4cfc974a6eda9cbc8a0ea6f8a96ce35efba"
] | [
"athena/athena/algorithms/NetworkAnalysis/Silhouette.py"
] | [
"import numpy as np\nimport networkx as nx\n\n# algorithms related to comparing cluster and evaluating cluster quality\n\n# sim is an n by n similarity matrix\n# clusters is an n-element array of clsuter assignments of each node\n# References\n# .. [1] `Peter J. Rousseeuw (1987). \"Silhouettes: a Graphical Ai... | [
[
"numpy.array",
"numpy.zeros",
"numpy.mean",
"numpy.any",
"numpy.arange",
"numpy.unique",
"numpy.maximum"
]
] |
HaoZeke/pytorch | [
"4075972c2675ef34fd85efd60c9bad75ad06d386"
] | [
"torch/testing/_internal/common_methods_invocations.py"
] | [
"from functools import wraps, partial\nfrom itertools import product, chain, islice\nimport itertools\nimport collections\nimport copy\nfrom enum import Enum\nimport operator\nimport random\nimport unittest\nimport math\n\nimport torch\nimport numpy as np\nfrom torch._six import inf\nimport collections.abc\n\nfrom ... | [
[
"numpy.product",
"numpy.random.choice",
"torch.triu_indices",
"numpy.sign",
"numpy.empty",
"torch.linalg.cholesky",
"torch.testing._internal.common_utils.is_iterable_of_tensors",
"torch.lu_unpack",
"numpy.prod",
"torch.tensor",
"torch.testing._internal.common_utils.make... |
kishimoto-banana/numpy | [
"9b7e890b014f6ad3b4288246f0565f7afd6eca84",
"9b7e890b014f6ad3b4288246f0565f7afd6eca84"
] | [
"numpy/f2py/tests/test_crackfortran.py",
"numpy/lib/recfunctions.py"
] | [
"import pytest\n\nimport numpy as np\nfrom numpy.testing import assert_array_equal\nfrom . import util\n\n\nclass TestNoSpace(util.F2PyTest):\n # issue gh-15035: add handling for endsubroutine, endfunction with no space\n # between \"end\" and the block name\n code = \"\"\"\n subroutine subb(k)\n ... | [
[
"numpy.array",
"numpy.testing.assert_array_equal"
],
[
"numpy.concatenate",
"numpy.result_type",
"numpy.array",
"numpy.ma.masked_all",
"numpy.empty",
"numpy.ascontiguousarray",
"numpy.sum",
"numpy.fromiter",
"numpy.ones",
"numpy.lib._iotools._is_string_like",
... |
BIGBALLON/Hiphop-Gym | [
"c05085c1650c4e2f4f72cfb7bde4fc2d6dc7cd33"
] | [
"models/dqn.py"
] | [
"import os\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.nn.functional as F\nimport numpy as np\nfrom gym import logger\nfrom .utils import check_reward, plot_figure, weight_init\nfrom .utils import ReplayBuffer\n\nMEMORY_CAPACITY = 100000\nINIT_REPLAY_SIZE = 50000\nTARGET_UPDATE_I... | [
[
"torch.nn.Linear",
"torch.nn.MSELoss",
"torch.max",
"torch.no_grad",
"torch.FloatTensor",
"torch.nn.Conv2d",
"torch.cuda.is_available",
"torch.tensor",
"numpy.random.uniform",
"torch.load",
"numpy.random.randint",
"torch.LongTensor",
"torch.mean"
]
] |
GreenAI-Uppa/deep_learning_mcmc | [
"c3e31cd158fd6011fbc92eae5396db7575b39a92"
] | [
"tests/test_apiv2_binary_linear.py"
] | [
"import time, os\nfrom torchvision import datasets\nfrom torch.utils.data import DataLoader\nfrom torchvision.transforms import ToTensor\nimport json\nimport torch\nimport numpy as np, math\nfrom deep_learning_mcmc import nets, optimizers, stats, selector \n\ntraining_data = datasets.CIFAR10(root=\"/home/paul/data/... | [
[
"torch.cuda.is_available",
"torch.utils.data.DataLoader"
]
] |
AmirHosseinNamadchi/PyNite | [
"8cc1fe3262e1efe029c6860394d2436601272e33"
] | [
"PyNite/Plate3D.py"
] | [
"from numpy import zeros, delete, matrix, array, matmul, transpose, insert, cross, divide, add\nfrom numpy.linalg import inv, norm\nfrom PyNite.LoadCombo import LoadCombo\n\n# A rectangular plate bending element\nclass Plate3D():\n\n def __init__(self, Name, iNode, jNode, mNode, nNode, t, E, nu,\n ... | [
[
"numpy.array",
"numpy.matrix",
"numpy.linalg.norm",
"numpy.zeros",
"numpy.cross"
]
] |
timgates42/mars | [
"bfa3a7d7d8f100b495581c8bab2143c8f261a7f1"
] | [
"mars/dataframe/base/tests/test_base_execution.py"
] | [
"# Copyright 1999-2020 Alibaba Group Holding Ltd.\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 appl... | [
[
"numpy.random.rand",
"numpy.random.choice",
"pandas.qcut",
"pandas.Timestamp",
"pandas.concat",
"numpy.random.bytes",
"numpy.dtype",
"pandas.Timedelta",
"pandas.DataFrame",
"numpy.random.randint",
"numpy.arange",
"pandas.testing.assert_index_equal",
"pandas.test... |
shankar1729/qimpy | [
"5a4c1ea1fedc88909d426ce54101d6d07fa82e8c"
] | [
"src/qimpy/electrons/_scf.py"
] | [
"from __future__ import annotations\nimport qimpy as qp\nimport torch\nfrom typing import Optional, Sequence\n\n\nclass SCF(qp.utils.Pulay[qp.grid.FieldH]):\n \"\"\"Electronic self-consistent field iteration.\"\"\"\n\n __slots__ = (\n \"mix_fraction_mag\",\n \"q_kerker\",\n \"q_metric\",\... | [
[
"torch.clamp"
]
] |
DeqingQu/AudioClassier | [
"0d92aebe295bf94052455106ab946f6f029127b1"
] | [
"code/spectrogram_classifier.py"
] | [
"import tensorflow as tf\nimport numpy as np\nimport os\n# import matplotlib.pyplot as plt\n# from PIL import Image\nimport time\n\ndef get_files(filepath, train_ratio=0.8):\n train_files = []\n train_labels = []\n test_files = []\n test_labels = []\n\n foldernames = os.listdir(filepath)\n for fol... | [
[
"tensorflow.nn.in_top_k",
"tensorflow.train.start_queue_runners",
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.train.slice_input_producer",
"tensorflow.nn.lrn",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.global_variables_initializer",
"... |
Glacier-program/pytorch | [
"208b3d1029b465da89e04a95a6c02d1c7fee559b"
] | [
"test/jit/test_hooks.py"
] | [
"import os\nimport sys\nimport unittest\n\nimport torch\nfrom jit.test_hooks_modules import *\n\n# Make the helper files in test/ importable\npytorch_test_dir = os.path.dirname(os.path.dirname(os.path.realpath(__file__)))\nsys.path.append(pytorch_test_dir)\nfrom torch.testing._internal.jit_utils import JitTestCase\... | [
[
"torch.jit.script"
]
] |
OkomoJacob/MLAIDS | [
"5f9d3394fede8fd8625577b44844f2626b205844"
] | [
"1.Simple Linear Regression/2.Linear-Regr_SalaryVSYear_OF_Exprnce/salary_linear_regression.py"
] | [
"# Simple Linear Regression\n# Importing the libraries\nfrom sklearn.linear_model import LinearRegression\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importing the dataset\ndataset = pd.read_csv('Salary_Data.csv')\nX = dataset.iloc[:, :-1].values\ny = dataset.iloc[:, 1].values\n\n... | [
[
"sklearn.linear_model.LinearRegression",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.scatter",
"pandas.read_csv"
]
] |
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