repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
huttzza/maskrcnn-benchmark | [
"d15971e4b602bb71e5494ce8973293fedf202e58"
] | [
"maskrcnn_benchmark/modeling/da_heads/da_heads.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\nfrom __future__ import print_function\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn\nfrom maskrcnn_benchmark.layers import GradientScalarLayer\n\nfrom .loss import make_da_heads_loss_evaluator\n\nclass DAImgHead(nn.Modu... | [
[
"torch.nn.Linear",
"torch.nn.init.constant_",
"torch.nn.AvgPool2d",
"torch.nn.functional.dropout",
"torch.nn.Conv2d",
"torch.nn.init.normal_"
]
] |
DevinCrowley/ardent | [
"5e731947e58b8670463521abe6a52d4962d4221f"
] | [
"ardent/visualization.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport nibabel as nib\nimport nilearn.plotting as niplot\n\ndef _scale_data(data, limit_mode=None, stdevs=4, quantile=0.01, limits=None):\n \"\"\"Returns a copy of data scaled such that the bulk of the values are mapped to the range [0, 1].\n \n Upper a... | [
[
"numpy.max",
"matplotlib.pyplot.colorbar",
"numpy.array",
"matplotlib.pyplot.setp",
"numpy.min",
"matplotlib.pyplot.subplots",
"numpy.mean",
"numpy.eye",
"numpy.std",
"matplotlib.pyplot.axes",
"numpy.linspace",
"matplotlib.pyplot.subplots_adjust"
]
] |
ivandrej/checkmatte | [
"48992e9eb777b609eab32e58d918f1fb41ca51f1",
"48992e9eb777b609eab32e58d918f1fb41ca51f1"
] | [
"evaluation/varying_misalignment.py",
"evaluation/evaluation_metrics.py"
] | [
"import argparse\nimport os\n\nimport pandas as pd\n\nimport evaluate_experiment\nimport perform_experiment\nfrom composite import read_metadata\n\n\ndef read_args():\n parser = argparse.ArgumentParser()\n parser.add_argument('--experiment-metadata', type=str, required=True)\n parser.add_argument('--experi... | [
[
"pandas.DataFrame.from_dict"
],
[
"numpy.int",
"numpy.zeros",
"numpy.exp",
"torch.from_numpy",
"numpy.transpose",
"numpy.sqrt"
]
] |
brightcoder01/sqlflow | [
"1b5b75a62908c6fa17fbfd1309a502c8c613fe3d"
] | [
"python/sqlflow_submitter/xgboost/dataset.py"
] | [
"# Copyright 2020 The SQLFlow Authors. All rights reserved.\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 ap... | [
[
"numpy.concatenate",
"sklearn.datasets.load_svmlight_files",
"sklearn.datasets.load_svmlight_file",
"scipy.sparse.vstack",
"numpy.prod"
]
] |
PatrickChoDev/CSA-3D | [
"34aa87194d653a93f16834d485738255f55112f0",
"34aa87194d653a93f16834d485738255f55112f0"
] | [
"det3d/ops/roipool3d/setup.py",
"det3d/solver/learning_schedules_fastai.py"
] | [
"from setuptools import setup\n\nfrom torch.utils.cpp_extension import BuildExtension, CUDAExtension\n\nsetup(\n name=\"roipool3d\",\n ext_modules=[\n CUDAExtension(\n \"roipool3d_cuda\",\n [\"src/roipool3d.cpp\", \"src/roipool3d_kernel.cu\",],\n extra_compile_args={\"c... | [
[
"torch.utils.cpp_extension.CUDAExtension"
],
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.plot",
"numpy.cos"
]
] |
PierreExeter/rl_reach | [
"4f9c46c8503a84edaa48f9dfd58054548552253a",
"4f9c46c8503a84edaa48f9dfd58054548552253a"
] | [
"code/tests/manual/7_test_jaco_env_with_log_plot.py",
"code/scripts/plot_experiment.py"
] | [
"\"\"\" Test env with random actions \"\"\"\n\nimport time\nimport gym\nimport gym_envs\nimport subprocess\nfrom collections import OrderedDict\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\n\nenv = gym.make('ReachingJaco-v7')\nplot_filename = \"plot_ReachingJaco-v7_rand.png\"\n\nenv.render()\nenv.reset()... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.subplots"
],
[
"matplotlib.pyplot.xlabel",
"pandas.DataFrame",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot... |
sebastianbernasek/dataincubator | [
"de29e86c917f107650d03d3331109cb992a6881c"
] | [
"modules/dynamics.py"
] | [
"from scipy.signal import savgol_filter\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef normalize_by_baseline(timeseries, baseline_length=4):\n baseline = timeseries.iloc[:baseline_length].mean(axis=0)\n normalized_timeseries = np.log2(timeseries / baseline)\n normalized_timeseries = normaliz... | [
[
"numpy.log2",
"matplotlib.pyplot.subplots"
]
] |
GabrielJie/PyMFEM | [
"fa654447ac6819c5aa0341397b91a299f4ce5492"
] | [
"mfem/common/chypre.py"
] | [
"'''\n CHypre (Complex Hypre)\n\n CHypreVec : ParVector\n CHypreMat : ParCSR\n\n container object to support complex using\n real value hypre\n\n it should work with pure real or pure imaginary\n case too.\n\n it follows the mathod naming convetion used\n in scipy.sparse. However, since it inherits the lis... | [
[
"scipy.sparse.coo_matrix",
"numpy.array",
"numpy.count_nonzero",
"numpy.empty",
"numpy.zeros",
"numpy.sum",
"numpy.hstack",
"numpy.real",
"numpy.any",
"numpy.iscomplexobj",
"numpy.cumsum",
"scipy.sparse.lil_matrix",
"scipy.sparse.csr_matrix",
"numpy.imag"
... |
prabhatnagarajan/chainer | [
"3029bbaa587c15b3539b55ee1fd357a4149e5aed"
] | [
"chainer/functions/connection/convolution_2d.py"
] | [
"import numpy\n\nimport chainer\nfrom chainer import backend\nfrom chainer.backends import cuda\nfrom chainer.backends import intel64\nfrom chainer import configuration\nfrom chainer import function_node\nimport chainer.functions\nfrom chainer.utils import argument\nfrom chainer.utils import conv\nfrom chainer.util... | [
[
"numpy.ascontiguousarray",
"numpy.tensordot",
"numpy.rollaxis"
]
] |
muyiguangda/tensorflow-keras-yolov3 | [
"04a873529e9941a576e7058e47f8991d188ba15b"
] | [
"train.py"
] | [
"\"\"\"\n@authors: Hulking\nApril 2019\n\"\"\"\n\nimport numpy as np\nimport keras.backend as K\nfrom keras.layers import Input, Lambda\nfrom keras.models import Model\nfrom keras.optimizers import Adam\nfrom keras.callbacks import TensorBoard, ModelCheckpoint, ReduceLROnPlateau, EarlyStopping\n\nfrom yolo3.model i... | [
[
"numpy.random.seed",
"numpy.array",
"numpy.zeros",
"numpy.random.shuffle"
]
] |
rflperry/mvlearn | [
"8db0f63a0a811d7458aa0bd6b187f9f551241927"
] | [
"mvlearn/semi_supervised/ctclassifier.py"
] | [
"# License: MIT\n#\n# Implements multi-view co-training classification for 2-view data.\n\nimport numpy as np\nfrom sklearn.naive_bayes import GaussianNB\n\nfrom .base import BaseCoTrainEstimator\nfrom ..utils.utils import check_Xs, check_Xs_y_nan_allowed\n\n\nclass CTClassifier(BaseCoTrainEstimator):\n r\"\"\"\... | [
[
"numpy.array",
"numpy.isnan",
"numpy.zeros",
"numpy.log",
"numpy.random.seed",
"sklearn.naive_bayes.GaussianNB",
"numpy.random.shuffle",
"numpy.finfo"
]
] |
Obarads/torch_point_cloud | [
"86e19cc5c1196f22f609f2d98504b913272cbba8"
] | [
"examples/function_and_class/knn.py"
] | [
"import numpy as np\n\nimport torch\nfrom torch.utils.data import DataLoader\n\n# local package\nfrom libs import tpcpath\nfrom libs.dataset import SimpleSceneDataset\nfrom libs.three_nn import three_nn # PointRCNN\n\n# torch-points-kernels\nimport torch_points_kernels as tpk\n\n# torchpcp pacakage\nfrom torchpcp.m... | [
[
"numpy.set_printoptions",
"torch.set_printoptions",
"torch.tensor"
]
] |
mjlbach/iGibson-baselines | [
"c97d310b99f848ba2469eacdc6a84888f990bcd3"
] | [
"ray/eric_model_bak.py"
] | [
"\"\"\"\nExample showing how to wrap the iGibson class using ray for rllib.\nMultiple environments are only supported on Linux. If issues arise, please ensure torch/numpy\nare installed *without* MKL support.\n\nThis example requires ray to be installed with rllib support, and pytorch to be installed:\n `pip ins... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Module.__init__"
]
] |
danielemingolla/sentiment_analysis_performances_comparison | [
"03c73257582f5a92285f8438c7390b0c806c31b1"
] | [
"src/models/train_LSTM.py"
] | [
"from keras.layers import Dense, Dropout, Embedding, LSTM, GlobalMaxPooling1D, SpatialDropout1D, Flatten\nfrom keras.models import Sequential\nfrom keras.utils import to_categorical\nfrom keras import layers\nfrom keras.preprocessing.sequence import pad_sequences\nfrom keras.preprocessing.text import Tokenizer\nimp... | [
[
"sklearn.externals.joblib.dump",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"sklearn.model_selection.RandomizedSearchCV",
"matplotlib.pyplot.figure",
"sklearn.metrics.classification_report",
"matplotlib.pyplot.style.use",
"pandas.concat",
... |
babayigit-arge/fire-smoke-detect-yolov4 | [
"c195d2d4d5b7c4fcf53142ac22b3fc2b96ace8d8"
] | [
"yolov4/scripts/process_fire_temp.py"
] | [
"'''\n 处理火灾检测数据集 VOC2020\n'''\nimport os\nimport numpy as np\n\n# xml_root = r'/home/ailab/dataset/Security_check/VOC2020/Annotations/'\n# xmls = os.listdir(xml_root)\n# f =open(r'/home/ailab/dataset/Security_check/VOC2020/ImageSets/Main/train.txt', 'w')\n# for xml in xmls:\n# f.write(xml.split('.')[0]+'\\n'... | [
[
"numpy.random.shuffle"
]
] |
JaydenL33/ReLearningPython | [
"60d54172eefb29f285ca8976350010829d312a16"
] | [
"DataScience/Ryan_SVMPython.py"
] | [
"#############################################################################\n# Author: Jayden Lee (Jayden.Lee@student.uts.edu.au)\n# Date: 6/10/19\n# Purpose: To use a SVM for our regression problem. \n# Source: \n# In Source Documentation\n########################################################################... | [
[
"numpy.savetxt",
"sklearn.metrics.precision_score",
"sklearn.metrics.accuracy_score",
"sklearn.svm.SVC",
"sklearn.model_selection.train_test_split",
"pandas.read_csv",
"sklearn.metrics.f1_score",
"sklearn.metrics.recall_score"
]
] |
TomasBombadil/tf-face-recognition | [
"f167d31a2f4e1b60462cb2331dde027d2fcac47a"
] | [
"src/tensorface/embedding.py"
] | [
"import os\n\nimport numpy as np\nimport tensorflow as tf\nfrom tensorflow.python.platform import gfile\n\nfrom tensorface.const import PRETREINED_MODEL_DIR\n\nMODEL_FILE_NAME = '20180402-114759/20180402-114759.pb'\n\n# to get Flask not complain\nglobal tf\n_tf = tf\nglobal sess\nsess = None\n\ndef load_model(pb_fi... | [
[
"tensorflow.get_default_graph",
"tensorflow.python.platform.gfile.FastGFile",
"numpy.mean",
"numpy.std",
"numpy.subtract",
"numpy.sqrt"
]
] |
afranck64/ultimatum | [
"313b840e6f0942c1c937aa8b3f2d26e5059c7a7f"
] | [
"snippets/generate_game_resp_summary copy.py"
] | [
"import os\nimport sys\nimport argparse\nimport pandas as pd\nfrom scipy import stats\n\nsys.path.append(os.path.abspath(\"..\"))\n\nfrom survey._app import CODE_DIR, app\nfrom core.models.metrics import gain_mean, rejection_ratio, gain\nfrom utils import get_con_and_dfs, get_all_con_and_dfs\nimport metrics\n\nSTAT... | [
[
"pandas.DataFrame",
"pandas.read_sql",
"pandas.notnull"
]
] |
yangarbiter/python-features | [
"ab0b9035454bd467800daba7f27a152c06eecb13"
] | [
"pipeline/removeOutliers.py"
] | [
"from shutil import copyfile\nimport os, csv, sys, numpy\n\nDATA_FOLDER = sys.argv[1]\nOUT_FOLDER = sys.argv[2]\n\nfracs = {}\nfor fileName in os.listdir(DATA_FOLDER):\n with open(os.path.join(DATA_FOLDER,fileName), 'r') as inFile:\n csvFile = csv.DictReader(inFile)\n noChange = 0\n didChang... | [
[
"numpy.std",
"numpy.mean"
]
] |
kanavsetia/qiskit-chemistry | [
"d03abb9c4c37dfc343bf224bb947b4f2439e2269"
] | [
"test/test_mp2info.py"
] | [
"# -*- coding: utf-8 -*-\n\n# Copyright 2018 IBM.\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_array_almost_equal"
]
] |
romanhaa/pandas | [
"3f67dc33088a088fe5a69ea2e3f3153565d53b3f"
] | [
"pandas/io/excel/_base.py"
] | [
"from __future__ import annotations\n\nimport abc\nimport datetime\nfrom io import BytesIO\nimport os\nfrom textwrap import fill\nfrom typing import (\n Any,\n Mapping,\n cast,\n)\nimport warnings\nimport zipfile\n\nfrom pandas._config import config\n\nfrom pandas._libs.parsers import STR_NA_VALUES\nfrom p... | [
[
"pandas.io.excel._util.get_writer",
"pandas.util._exceptions.find_stack_level",
"pandas.io.parsers.TextParser",
"pandas.io.common.validate_header_arg",
"pandas.io.excel._util.maybe_convert_usecols",
"pandas.util._decorators.deprecate_nonkeyword_arguments",
"pandas.io.common.IOHandles",... |
aj-tap/traffic-bot-counter | [
"2ef3ddcf3b3caca87d728e8b4ed6b8e7e6ffa161"
] | [
"gui/pages/result.py"
] | [
"\"\"\"\nThis page is similar to Menu class, but here we\nwill render the results and summon the graph.\n\nself = where the widgets will be rendered.\n\napp = to access app-bot and change bot properties and methods\nfor threshold, confidence, paths, intersection line.\n\nmain_container = where the menu will be rend... | [
[
"matplotlib.figure.Figure",
"matplotlib.backends.backend_tkagg.FigureCanvasTkAgg",
"matplotlib.backends.backend_tkagg.NavigationToolbar2Tk"
]
] |
dangom/rapidtide | [
"ab92bbb612623f8499a16e1e85cea643766f3af8"
] | [
"rapidtide/tests/test_findmaxlag.py"
] | [
"#!/usr/bin/env python\n\n\nimport os.path as op\n\nimport numpy as np\nimport pylab as plt\nfrom scipy import arange\n\nimport rapidtide.io as tide_io\nimport rapidtide.fit as tide_fit\nfrom rapidtide.tests.utils import get_test_data_path\n\n\ndef test_findmaxlag(display=False, debug=False):\n textfilename = op... | [
[
"numpy.array",
"scipy.arange"
]
] |
bregirl3/Post-Your-Work-On-Github-Project | [
"daf6e3e76aca42dab0ced59f36b0592cc1dd19a8"
] | [
"bikeshare.py"
] | [
"import time\nimport pandas as pd\nimport numpy as np\n\nCITY_DATA = { 'chicago': 'chicago.csv',\n 'new york city': 'new_york_city.csv',\n 'washington': 'washington.csv' }\n\ndef get_filters():\n \"\"\"\n Asks user to specify a city, month, and day to analyze.\n Returns:\n ... | [
[
"pandas.to_datetime",
"pandas.read_csv"
]
] |
Tiamat-Tech/ddsp | [
"cd57829b9caa8643d37994caf6e1ee0a7fc11ad8",
"cd57829b9caa8643d37994caf6e1ee0a7fc11ad8"
] | [
"ddsp/training/data_preparation/ddsp_prepare_tfrecord.py",
"ddsp/training/ddsp_run.py"
] | [
"# Copyright 2021 The DDSP 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 a... | [
[
"tensorflow.compat.v2.io.gfile.glob"
],
[
"tensorflow.compat.v2.config.experimental.list_physical_devices",
"tensorflow.compat.v2.config.experimental.set_memory_growth"
]
] |
akihironitta/pyro | [
"0ab6e474330942ff4ec2a87a6cc0c671943fc5cd"
] | [
"examples/scanvi/data.py"
] | [
"# Copyright Contributors to the Pyro project.\n# Copyright (c) 2020, YosefLab.\n# SPDX-License-Identifier: Apache-2.0 AND BSD-3-Clause\n\n\"\"\"\nThe data preprocessing code in this script is adapted from:\nhttps://github.com/YosefLab/scvi-tutorials/blob/50dd3269abfe0c375ec47114f2c20725a016736f/seed_labeling.ipynb... | [
[
"torch.zeros",
"numpy.array",
"torch.cat",
"torch.nn.functional.one_hot",
"numpy.zeros",
"scipy.sparse.csr_matrix.todense",
"numpy.ones",
"torch.randperm",
"torch.from_numpy",
"torch.distributions.Poisson",
"torch.where"
]
] |
pyiron/pysqa | [
"f300c8676305690d3033d633e6baa190ee6a01ba"
] | [
"pysqa/wrapper/gent.py"
] | [
"# coding: utf-8\n# Copyright (c) Max-Planck-Institut für Eisenforschung GmbH - Computational Materials Design (CM) Department\n# Distributed under the terms of \"New BSD License\", see the LICENSE file.\n\nimport pandas\nfrom pysqa.wrapper.slurm import SlurmCommands\n\n\n__author__ = \"Jan Janssen\"\n__copyright__... | [
[
"pandas.DataFrame"
]
] |
aatifjiwani/nums | [
"40e225a4dd34a8df87702c271dc673711f2264a3"
] | [
"nums/core/array/application.py"
] | [
"# coding=utf-8\n# Copyright (C) 2020 NumS Development 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 requir... | [
[
"numpy.product",
"numpy.array",
"numpy.zeros_like",
"numpy.__getattribute__",
"numpy.ones_like",
"numpy.result_type",
"numpy.sum",
"numpy.diff"
]
] |
kritikush/hub | [
"22b2f6f2539df760f77824f1f4c92a41007313de"
] | [
"tfhub_dev/tools/validator.py"
] | [
"# Copyright 2020 The TensorFlow Hub 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 ... | [
[
"tensorflow.io.gfile.exists",
"tensorflow.io.gfile.GFile",
"tensorflow.io.gfile.walk",
"tensorflow.python.saved_model.loader_impl.parse_saved_model"
]
] |
JosephZheng1998/CNN-Emotion-Detection | [
"f56e99103be7a90a52b8ee51c8ae30cdd0051d5c"
] | [
"autoencoder/Training.py"
] | [
"import os\nimport numpy as np\nfrom PIL import Image\n\nimport torch\nimport torchvision\nfrom torchvision import transforms\nimport torchvision.models as models\nfrom torchvision.datasets import ImageFolder\nimport torch.nn as nn\nimport torch.optim as optim\nimport torch.nn.functional as F\nfrom torch.utils.data... | [
[
"torch.device",
"torch.argmax",
"torch.nn.MSELoss",
"torch.no_grad",
"torch.cuda.empty_cache",
"torch.cuda.is_available",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.utils.data.DataLoader",
"torch.nn.CrossEntropyLoss"
]
] |
mingyangzhang/CCGAD | [
"52568aa7892f23c25d516022d27e0bb41b53a6cf"
] | [
"utils/graph_utils.py"
] | [
"import numpy as np\nimport scipy.sparse as sp\n\nnp.random.seed(0)\n\n\ndef nx_sample_neighbor(nx_g, start_node):\n\n neighbors = [nd for nd in nx_g.neighbors(start_node)]\n return np.random.choice(neighbors, size=1)[0]\n\n\ndef random_walk_with_restart(g, node_idx, restart_prob, length):\n trace = [node_... | [
[
"numpy.isinf",
"scipy.sparse.coo_matrix",
"numpy.random.rand",
"numpy.random.choice",
"scipy.sparse.diags",
"numpy.random.seed",
"numpy.power",
"numpy.unique"
]
] |
s-shailja/challenge-iclr-2021 | [
"28ad9d126597166bc41715f77c8cf366b8fba975"
] | [
"mihaelanistor/metrics/grassmannian/chordal_distance_2norm.py"
] | [
"from abc import ABC\n\nimport numpy as np\nfrom geomstats.geometry.grassmannian import GrassmannianCanonicalMetric\n\n\nclass GrassmannianChordal2NormMetric(GrassmannianCanonicalMetric, ABC):\n\tdef __init__(self, n, p):\n\t\tsuper().__init__(n, p)\n\n\tdef dist(self, point_a, point_b):\n\t\t\"\"\"Chordal 2-norm d... | [
[
"numpy.dot"
]
] |
RaulRPrado/ctamclib | [
"ed18de64724deec403ed5ee06971c377562331ef"
] | [
"simtools/ray_tracing.py"
] | [
"import logging\nimport subprocess\nimport matplotlib.pyplot as plt\nfrom copy import copy\nfrom pathlib import Path\nfrom math import pi, tan\n\nimport numpy as np\nimport astropy.units as u\nfrom astropy.io import ascii\nfrom astropy.table import QTable\n\nimport simtools.config as cfg\nimport simtools.io_handler... | [
[
"numpy.std",
"numpy.mean"
]
] |
reixd/iexfinance | [
"53848f99e2ed54f61a1971d55a3b1b38dc00d2fa"
] | [
"iexfinance/stats.py"
] | [
"from datetime import datetime, timedelta\r\n\r\nimport pandas as pd\r\n\r\nfrom .base import _IEXBase\r\nfrom iexfinance.utils.exceptions import IEXQueryError\r\n# Data provided for free by IEX\r\n# Data is furnished in compliance with the guidelines promulgated in the IEX\r\n# API terms of service and manual\r\n#... | [
[
"pandas.DataFrame",
"pandas.concat"
]
] |
ChangQingAAS/MFDDPG_Path_Planning | [
"dd2af3bbb4807b2d248da46b99607153f75b4a56"
] | [
"vis/draw_result.py"
] | [
"import seaborn as sns\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pylab\nimport csv\nimport random\nimport sys\nimport os\n\n\ndef get_data(path):\n epoch = []\n num_reach_target = []\n num_hit_obs = []\n num_out_of_range = []\n num_moving = []\n with open(path, \"r+\", encoding=... | [
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylabel"
]
] |
Jjschwartz/highway-env | [
"e289d5f513d6162eadba6a54f2541ca7b193ef6a"
] | [
"highway_env/envs/common/observation.py"
] | [
"from typing import List, Dict, TYPE_CHECKING, Optional, Union\nfrom gym import spaces\nimport numpy as np\nimport pandas as pd\n\nfrom highway_env import utils\nfrom highway_env.envs.common.finite_mdp import compute_ttc_grid\nfrom highway_env.road.lane import AbstractLane\nfrom highway_env.utils import distance_to... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.dot",
"numpy.linalg.norm",
"numpy.reshape",
"numpy.zeros",
"numpy.sin",
"pandas.DataFrame",
"numpy.ones",
"numpy.roll",
"numpy.shape",
"numpy.arange",
"numpy.arctan2",
"numpy.cos",
"numpy.clip",
"numpy.floor... |
rwalkerlewis/spatialdata | [
"515c8d9dec21d261d0d654b5c30e6759565268d2"
] | [
"tests/pytests/spatialdb/TestGenSimpleDBApp.py"
] | [
"# ======================================================================\n#\n# Brad T. Aagaard, U.S. Geological Survey\n#\n# This code was developed as part of the Computational Infrastructure\n# for Geodynamics (http://geodynamics.org).\n#\n# Copyright (c) 2010-2017 University of California, Davis\n#\n# See COPYI... | [
[
"numpy.array",
"numpy.reshape",
"numpy.zeros"
]
] |
cadalyjr/molecool | [
"cabbd54b57c847c5c7659fe4be6b0223df6cd753"
] | [
"molecool/measure.py"
] | [
"\"\"\"\nContains functions related to calculations important for characterizing molecule structure.\n\"\"\"\n\nimport numpy as np\n\ndef calculate_distance(rA, rB):\n \"\"\"\n This function calculates the distance between two points given as numpy arrays.\n\n Parameters\n ----------\n rA, rB : np.ad... | [
[
"numpy.linalg.norm",
"numpy.dot",
"numpy.degrees"
]
] |
mirochaj/ares | [
"b3335ad30435ee0d7f17d0110aa164a35f252d78",
"b3335ad30435ee0d7f17d0110aa164a35f252d78",
"b3335ad30435ee0d7f17d0110aa164a35f252d78"
] | [
"ares/populations/GalaxyAggregate.py",
"tests/test_sources_bh.py",
"ares/simulations/Simulation.py"
] | [
"\"\"\"\n\nGalaxyAggregate.py\n\nAuthor: Jordan Mirocha\nAffiliation: University of Colorado at Boulder\nCreated on: Sat May 23 12:13:03 CDT 2015\n\nDescription:\n\n\"\"\"\n\nimport sys\nimport numpy as np\nfrom ..util import read_lit\nimport os, inspect, re\nfrom types import FunctionType\nfrom .Halo import HaloPo... | [
[
"numpy.any",
"numpy.log",
"numpy.diff"
],
[
"numpy.logspace"
],
[
"numpy.max",
"numpy.zeros_like",
"numpy.array",
"numpy.ones_like",
"numpy.log",
"numpy.minimum",
"numpy.interp",
"numpy.min",
"numpy.diff",
"numpy.arange",
"numpy.sort",
"numpy... |
jaavad/muzero-general | [
"cbe089c63480f983c457518d1768fe2db6f562df"
] | [
"games/spiel.py"
] | [
"import datetime\nimport pathlib\n\nimport numpy\nimport torch\n\nfrom .abstract_game import AbstractGame\n\n\n# This is a Game wrapper for open_spiel games. It allows you to run any game in the open_spiel library.\n\ntry:\n import pyspiel\n\nexcept ImportError:\n import sys\n\n sys.exit(\n \"You ne... | [
[
"torch.cuda.is_available"
]
] |
daizutabi/ivory | [
"d961e6c05ece112d99b8f8c2d6dad530f60b7303"
] | [
"tests/tensorflow/test_tensorflow_mnist.py"
] | [
"import numpy as np\n\n\ndef test_mnist(client):\n run = client.create_run(\"mnist\")\n run.start(\"train\")\n run.start(\"test\")\n assert run.results.train[\"output\"].shape == (800, 10)\n assert run.results.val[\"output\"].shape == (200, 10)\n assert run.results.test[\"output\"].shape == (100, ... | [
[
"numpy.allclose"
]
] |
iwyoo/tf_ConvWTA | [
"a423f6ff8683e0bcf9b0269e0d4e31d068dfae14"
] | [
"model.py"
] | [
"import tensorflow as tf\n\n\"\"\"\nConvolutioanl Winner-Take-All Autoencoder TensorFlow implementation.\nUsage :\n ae = ConvWTA(sess)\n\n # 1. to train an Autoencoder\n loss = ae.loss(x)\n train = optimizer.minimize(loss)\n sess.run(train, feed_dict={...})\n\n # 2. to get the sparse codes\n h = ae.encoder(x... | [
[
"tensorflow.shape",
"tensorflow.zeros",
"tensorflow.nn.relu",
"tensorflow.nn.conv2d",
"tensorflow.constant_initializer",
"tensorflow.ones",
"tensorflow.train.Saver",
"tensorflow.transpose",
"tensorflow.variable_scope",
"tensorflow.variables_initializer",
"tensorflow.get... |
shenjean/DeepMicrobes | [
"43b654b0b26a265dd91166eece5c9f74e423d7dc"
] | [
"models/custom_layers.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport tensorflow as tf\nimport tensorflow.contrib.slim as slim\n\n\ndef embedding_layer(inputs, vocab_size, embedding_dim, initializer):\n \"\"\"Looks up embedding vectors for each k-mer.\"\"\"\n ... | [
[
"tensorflow.abs",
"tensorflow.shape",
"tensorflow.concat",
"tensorflow.nn.bidirectional_dynamic_rnn",
"tensorflow.contrib.layers.variance_scaling_initializer",
"tensorflow.matmul",
"tensorflow.contrib.rnn.CoupledInputForgetGateLSTMCell",
"tensorflow.reshape",
"tensorflow.transp... |
nfergu/GPflow | [
"d9951946d64542268b85610593495e187343d42e"
] | [
"doc/source/notebooks/intro_to_gpflow2.pct.py"
] | [
"# ---\n# jupyter:\n# jupytext:\n# formats: ipynb,.pct.py:percent\n# text_representation:\n# extension: .py\n# format_name: percent\n# format_version: '1.3'\n# jupytext_version: 1.4.2\n# kernelspec:\n# display_name: Python 3\n# language: python\n# name: python3\n# ---... | [
[
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.function",
"tensorflow.saved_model.save",
"tensorflow.Module",
"tensorflow.GradientTape",
"tensorflow.train.CheckpointManager",
"tensorflow.random.set_seed",
"tensorflow.Variable",
"tensorflow.math.sin",
"numpy.sqrt"... |
unmeshvrije/scikit-kge | [
"e393d4f09ef95589a9a330fa0bedae2b79fb8a48",
"e393d4f09ef95589a9a330fa0bedae2b79fb8a48"
] | [
"skge/base.py",
"eval-embeddings.py"
] | [
"from __future__ import print_function\nimport argparse\nimport numpy as np\nfrom numpy import argsort\nfrom numpy.random import shuffle\nfrom collections import defaultdict as ddict\nfrom skge.param import Parameter, AdaGrad\nimport timeit\nimport pickle\nimport pdb\nimport logging\nfrom sklearn.metrics import pre... | [
[
"numpy.full",
"numpy.array",
"numpy.dot",
"numpy.zeros",
"sklearn.metrics.precision_recall_curve",
"numpy.random.seed",
"numpy.sum",
"numpy.exp",
"numpy.random.shuffle",
"numpy.mean",
"numpy.split",
"numpy.any",
"numpy.where",
"numpy.sqrt",
"numpy.argsor... |
taoualiw/MyMoneyManager-App | [
"d824b4a3d4e23a3f0dee48d9e6da65c87696f08b"
] | [
"mmm/functions.py"
] | [
"import pandas as pd\nimport os\nimport numpy as np\nnp.set_printoptions(precision=2)\n\ndef import_transFileUFCU(path_transfilename):\n df = pd.read_csv(path_transfilename)\n acc = df.account_id.values\n df[\"account\"]= [acc[i] for i in range(len(acc))]\n df[\"date\"] = pd.DatetimeIndex(df['posted_at'... | [
[
"numpy.array",
"pandas.DatetimeIndex",
"numpy.set_printoptions",
"numpy.str",
"pandas.read_csv"
]
] |
CHH3213/two_loggers | [
"11b2016e424753aac85404e6a48f3b15b2448734"
] | [
"omni_diff_rl/scripts/TD3-master/CBF.py"
] | [
"import numpy as np\r\nfrom scipy.optimize import minimize\r\n\r\n\r\ndef QPfun(ud):\r\n def fun(u):\r\n return (u[0] - ud[0])**2 / 2\r\n return fun\r\n\r\n\r\ndef constrains(State):\r\n '''\r\n State[0] = Xp\r\n State[1] = Yp\r\n State[2] = th_p (rad)\r\n State[3] = Xe\r\n State[4] =... | [
[
"numpy.array",
"numpy.sin",
"numpy.cos",
"numpy.einsum"
]
] |
j0a8c2k1/pysat | [
"4ae1afd80e15e4449397d39dce8c3e969c32c422",
"4ae1afd80e15e4449397d39dce8c3e969c32c422"
] | [
"pysat/instruments/pysat_testsmall.py",
"pysat/instruments/supermag_magnetometer.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nProduces fake instrument data for testing.\n\"\"\"\n\nimport pandas as pds\nimport numpy as np\nimport pysat\n\n# pysat required parameters\nplatform = 'pysat'\nname = 'testing'\n# dictionary of data 'tags' and corresponding description\ntags = {'':'Regular testing data set'}\n# di... | [
[
"pandas.DateOffset",
"numpy.arange",
"numpy.mod"
],
[
"numpy.array",
"pandas.DataFrame",
"pandas.DateOffset",
"pandas.datetime.strptime",
"pandas.concat",
"pandas.read_csv"
]
] |
sahareslami/Garfield | [
"b620816fe88b2cb2cef4a889342e6b1ad32a0395",
"b620816fe88b2cb2cef4a889342e6b1ad32a0395"
] | [
"pytorch_impl/libs/garfieldpp/server.py",
"pytorch_impl/applications/Centralized/trainer.py"
] | [
"# coding: utf-8\n###\n # @file server.py\n # @author Arsany Guirguis <arsany.guirguis@epfl.ch>\n #\n # @section LICENSE\n #\n # Copyright (c) 2020 Arsany Guirguis.\n #\n # Permission is hereby granted, free of charge, to any person obtaining a copy\n # of this software and associated documentation files (the \"... | [
[
"torch.device",
"torch.no_grad",
"torch.cuda.is_available",
"torch.cuda.device_count"
],
[
"torch.device",
"torch.cuda.manual_seed_all",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.optim.lr_scheduler.MultiStepLR",
"torch.cuda.is_available"
]
] |
dashbrookhart/msds621 | [
"39c4c87d25449b568cbb84fe7ea6eb398113f5b9"
] | [
"code/linreg/reg_support.py"
] | [
"import numpy as np\nimport math\n\ndef diamond(lmbda=1, n=100):\n \"get points along diamond at distance lmbda from origin\"\n points = []\n x = np.linspace(0, lmbda, num=n // 4)\n points.extend(list(zip(x, -x + lmbda)))\n\n x = np.linspace(0, lmbda, num=n // 4)\n points.extend(list(zip(x, x - l... | [
[
"numpy.array",
"numpy.linspace",
"numpy.sin",
"numpy.cos"
]
] |
Combustion-Zhen/flamelet2table | [
"2bc083188308ea5193eaa2abd18fb01021bea4da"
] | [
"FM2csv.py"
] | [
"\"\"\"\nA python script to transfer FlameMaster output to csv tables\n\"\"\"\n\nimport numpy as np\nfrom scipy.interpolate import interp1d\nimport os\nimport sys\nimport glob\nimport argparse\nfrom name_params import params2name\n\ndef FM2csv(mode = 'SLFM', \n flamelet_prefix = 'CH4_p01_0',\n F... | [
[
"numpy.array",
"scipy.interpolate.interp1d",
"numpy.arange",
"numpy.ceil"
]
] |
Pjer-zhang/LOFAR-Sun-tools | [
"ee0ff1274f6c2894501503c89288fe3096b2700b"
] | [
"lofarSun/IM/IMdata.py"
] | [
"from scipy.io import readsav\nimport matplotlib.dates as mdates\nimport matplotlib as mpl\nimport datetime\nimport glob\nimport os\n\nfrom astropy import units as u\nfrom astropy.coordinates import EarthLocation, SkyCoord\nfrom astropy.io import fits\nfrom astropy.time import Time\n\nimport numpy as np\nfrom skima... | [
[
"matplotlib.pyplot.xlim",
"scipy.ndimage.shift",
"matplotlib.patches.Ellipse",
"numpy.cos",
"numpy.max",
"matplotlib.pyplot.colorbar",
"scipy.ndimage.rotate",
"numpy.log",
"matplotlib.dates.set_epoch",
"numpy.arange",
"matplotlib.pyplot.gca",
"numpy.log10",
"num... |
joncamp/jetbot_ros | [
"c20cc30f0ba421d4c806b5fe6942eb29bb79bed3"
] | [
"gazebo/pygazebo_classifier.py"
] | [
"#!/usr/bin/env python3\r\n# -*- coding: utf-8 -*-\r\n\r\nimport os\r\nimport time\r\nimport signal\r\nimport argparse\r\nimport asyncio\r\nimport pygazebo\r\nimport numpy as np\r\n\r\nfrom PIL import Image\r\nfrom pynput import keyboard\r\nfrom datetime import datetime\r\nfrom navigation_model import NavigationMod... | [
[
"numpy.reshape",
"numpy.frombuffer"
]
] |
djf604/ribohmm_refactor | [
"6bd0056aa8a9c7851d458995b23d5407821dc38a"
] | [
"ribohmm/core/seq.py"
] | [
"import numpy as np\nfrom pkg_resources import Requirement, resource_listdir, resource_filename\nfrom ribohmm.utils import STARTCODONS, STOPCODONS\n\n# set regex for start and stop codons\nSTARTS = {codon_name: i for i, codon_name in enumerate(STARTCODONS, start=1)}\nSTOPS = {codon_name: i for i, codon_name in enum... | [
[
"numpy.load",
"numpy.log2",
"numpy.zeros"
]
] |
bradyneal/covid-xprize-comp | [
"d515f58b009a0a3e2421bc83e7ac893f3c3a1ece"
] | [
"ongoing/prescriptors/prescribe.py"
] | [
"import os\nimport argparse\nimport numpy as np\nimport pandas as pd\nimport time\n\nimport zipfile\nimport os.path\n\nfrom ongoing.prescriptors.neat_multi.neat_prescriptor_many_objective import Neat as Neat2D\nfrom ongoing.prescriptors.neat_13D.neat_prescriptor_many_objective import Neat as Neat13D\nfrom ongoing.p... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.argmin",
"pandas.DataFrame",
"numpy.timedelta64",
"pandas.concat",
"numpy.cumsum",
"pandas.read_csv"
]
] |
manandey/datasets | [
"10d4e5d179d6cd78007acb34829bb32e7cbbff62"
] | [
"src/datasets/features/features.py"
] | [
"# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets 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/LICE... | [
[
"numpy.array",
"pandas.isna",
"numpy.asarray",
"numpy.sum",
"numpy.arange",
"numpy.all",
"numpy.insert",
"numpy.vstack"
]
] |
shmulike/robot_snake_10 | [
"d6e34a3ef50e1e022f26853addf3783434529d2e"
] | [
"script/gui_v4.py"
] | [
"#!/usr/bin/env python3\r\n# license removed for brevity\r\n\r\nfrom tkinter import ttk\r\nfrom tkinter import *\r\nimport numpy as np\r\nimport rospy\r\nfrom std_msgs.msg import Float32MultiArray, Int32MultiArray\r\nfrom functools import partial\r\nimport cv2\r\nfrom PIL import Image, ImageTk\r\nimport threading\r... | [
[
"numpy.zeros",
"numpy.floor"
]
] |
alitekin2fx/KiKit | [
"bd7400aafe058e0794635af04da77a13e892c2db"
] | [
"kikit/panelize.py"
] | [
"from kikit import pcbnew_compatibility\nfrom kikit.pcbnew_compatibility import pcbnew\nfrom kikit.common import normalize\nfrom pcbnew import (GetBoard, LoadBoard,\n FromMM, ToMM, wxPoint, wxRect, wxRectMM, wxPointMM)\nfrom enum import Enum, IntEnum\nfrom shapely.geometry import (Polygon, MultiPolygon, Point, L... | [
[
"numpy.array",
"numpy.sin",
"numpy.cos"
]
] |
johnpeterflynn/surface-texture-inpainting-net | [
"b2de05eaa47c9bcca53b9aee12b6012ac2c05156"
] | [
"datasets/imagegraph_dataloader.py"
] | [
"import os\nimport glob\nimport random\nimport cv2\nimport numpy as np\nimport torch\nimport matplotlib.pyplot as plt\nimport open3d\nfrom skimage import io, img_as_float32\nfrom scipy import ndimage\nfrom torch_geometric.data import Data, DataListLoader\nfrom torch_geometric.loader import DataLoader as GraphLevelD... | [
[
"torch.zeros",
"numpy.array",
"torch.cat",
"numpy.random.choice",
"scipy.ndimage.rotate",
"numpy.reshape",
"torch.from_numpy",
"numpy.random.randint",
"torch.tensor",
"numpy.arange",
"numpy.repeat",
"numpy.flip",
"torch.reshape"
]
] |
monarch-initiative/N2V | [
"8ae02ca125f1d24ca158c2849f2d9bb1711920b9",
"8ae02ca125f1d24ca158c2849f2d9bb1711920b9"
] | [
"embiggen/edge_prediction/edge_prediction_sklearn/random_forest_edge_prediction.py",
"embiggen/sequences/tensorflow_sequences/gcn_edge_label_prediction_training_sequence.py"
] | [
"\"\"\"Submodule wrapping Random Forest for edge prediction.\"\"\"\nfrom typing import Dict, Any\nfrom sklearn.ensemble import RandomForestClassifier\nfrom embiggen.edge_prediction.edge_prediction_sklearn.decision_tree_edge_prediction import DecisionTreeEdgePrediction\nfrom embiggen.edge_prediction.edge_prediction_... | [
[
"sklearn.ensemble.RandomForestClassifier"
],
[
"numpy.pad"
]
] |
robotastic/tensorflow | [
"b88f9f60de706dbe78acf9189b9fa04bdc7a6836"
] | [
"tensorflow/python/framework/dtypes_test.py"
] | [
"# Copyright 2015 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... | [
[
"numpy.array",
"tensorflow.python.platform.googletest.main",
"numpy.empty",
"tensorflow.python.framework.dtypes._TYPE_TO_STRING.items",
"tensorflow.python.framework.dtypes.as_dtype",
"numpy.finfo",
"tensorflow.core.framework.types_pb2.DataType.values",
"tensorflow.python.tf2.enable... |
sksingh22698/Breast-Cancer-Detection | [
"c474341e0dd570fee59c139380ac094c6d6a7561"
] | [
"proj.py"
] | [
"import sys\r\nimport numpy\r\nimport matplotlib\r\nimport pandas\r\nimport sklearn\r\n\r\n\r\nprint('Python: {}'.format(sys.version))\r\nprint('Numpy: {}'.format(numpy.__version__))\r\nprint('matplotlib: {}'.format(matplotlib.__version__))\r\nprint('Python: {}'.format(pandas.__version__))\r\nprint('Python: {}'.for... | [
[
"numpy.array",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.svm.SVC",
"sklearn.model_selection.KFold",
"sklearn.metrics.accuracy_score",
"sklearn.metrics.classification_report",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.show",
"pandas.read_csv",
"... |
DennissimOS/platform_external_tensorflow | [
"8ee732dae6202eac9c9ef1f14a94ba96fde677ce",
"e5a536fbd36ed64a7a63516299a3061944864080"
] | [
"tensorflow/python/tools/freeze_graph.py",
"tensorflow/python/layers/utils.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.platform.gfile.GFile",
"tensorflow.python.saved_model.loader.load",
"tensorflow.python.platform.gfile.FastGFile",
"tensorflow.python.platform.app.run",
"tensorflow.python.client.session.Session",
"tensorflow.python.training.saver.Saver",
"tensorflow.core.protobuf.met... |
RadjaHachilif/agotool | [
"2fcc3fd5a156053b528ec927bab79ddaf7af2dec",
"2fcc3fd5a156053b528ec927bab79ddaf7af2dec"
] | [
"app/python/testing/modules_and_functions/test_userinput_old.py",
"app/runserver.py"
] | [
"import sys, os\nsys.path.insert(0, os.path.dirname(os.path.abspath(os.path.realpath(__file__))))\n\nimport pandas as pd\nimport numpy as np\nfrom itertools import zip_longest\nimport pytest\n\nimport userinput, variables\n\nTEST_FN_DIR = os.path.join(os.path.dirname(os.path.abspath(os.path.realpath(__file__))), \"... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"pandas.Series"
],
[
"pandas.read_csv",
"pandas.set_option"
]
] |
CPJKU/score_following_game | [
"f04e977b09cceb49588dcf8e216909d815a54519"
] | [
"score_following_game/agents/optim_utils.py"
] | [
"\nimport numpy as np\nimport torch.optim as optim\n\nfrom ast import literal_eval as make_tuple\n\n\ndef cast_optim_params(optim_params):\n \"\"\"\n\n :param optim_params:\n :return:\n \"\"\"\n for k in optim_params.keys():\n\n # check if argument is a parameter tuple\n if isinstance(o... | [
[
"numpy.float"
]
] |
p-koo/exponential_activations | [
"9032a360c1abb0f07b824e3ce6d20707efe306fd",
"9032a360c1abb0f07b824e3ce6d20707efe306fd",
"9032a360c1abb0f07b824e3ce6d20707efe306fd"
] | [
"code/controls/initialization_sweep_step3_filter_match.py",
"code/model_zoo/basset.py",
"code/tfomics/explain.py"
] | [
"import os, sys\nfrom six.moves import cPickle\nimport numpy as np\nimport pandas as pd\nimport helper\nfrom tfomics import utils\n\n#------------------------------------------------------------------------------------------------\n# JASPAR filter indices\n\narid3 = ['MA0151.1', 'MA0601.1', 'PB0001.1']\ncebpb = ['M... | [
[
"numpy.where",
"numpy.std",
"numpy.array",
"numpy.mean"
],
[
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Model",
"tensorflow.keras.layers.MaxPool1D"
],
[... |
dark-ai/pypytorch | [
"d28e0f858ad7c33a14e4bb71dc68ae56ba97c5cf"
] | [
"examples/pypytorchscripts/cifar10/dataset/cifar10.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport os\nimport pickle\nimport numpy as np\nfrom PIL import Image\nimport pypytorch as ppt\nfrom pypytorch.data import Dataset\nimport pypytorch.data.transform as transform\n\n\ndef load_data(filename):\n with open(filename, 'rb') as f:\n data = pickle.load(f, encoding='latin... | [
[
"numpy.concatenate"
]
] |
mofumofuchan/attention_branch_network | [
"4634fe927bf7a9a6a4486d923a05933fd6bd5df4"
] | [
"models/cifar/wrn.py"
] | [
"import math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n__all__ = ['wrn']\n\nclass BasicBlock(nn.Module):\n def __init__(self, in_planes, out_planes, stride, dropRate=0.0):\n super(BasicBlock, self).__init__()\n self.bn1 = nn.BatchNorm2d(in_planes)\n self.relu1 ... | [
[
"torch.nn.Linear",
"torch.nn.functional.avg_pool2d",
"torch.nn.Sigmoid",
"torch.nn.Sequential",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.functional.dropout",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
Juddd/ignite | [
"00a208a4e7a7783e9ddac18931085fca2f0dec47",
"00a208a4e7a7783e9ddac18931085fca2f0dec47"
] | [
"tests/ignite/engine/test_deterministic.py",
"tests/ignite/distributed/comp_models/test_xla.py"
] | [
"import os\nimport random\nimport sys\nfrom unittest.mock import patch\n\nimport numpy as np\nimport pytest\nimport torch\nimport torch.nn as nn\nfrom torch.optim import SGD\nfrom torch.utils.data import BatchSampler, DataLoader, RandomSampler\n\nimport ignite.distributed as idist\nfrom ignite.engine import Events\... | [
[
"torch.nn.Linear",
"numpy.random.rand",
"torch.utils.data.RandomSampler",
"torch.cuda.is_available",
"torch.load",
"torch.randint_like",
"torch.norm",
"torch.manual_seed",
"torch.randint",
"torch.utils.data.DataLoader",
"torch.nn.Flatten",
"torch.device",
"torch... |
CT83/Independent-Coursework | [
"5c7f93a7e05e64b13cb821f603efc54c92ad96c6"
] | [
"Machine-Learning-A-Z-Udemy-master/Machine Learning A-Z Template Folder/Part 3 - Classification/Section 14 - Logistic Regression/Logistic_Regression/Mlogistic_regression.py"
] | [
"# Logistic Regression\n\n# Importing the libraries\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\n\n# Importing the dataset\ndataset = pd.read_csv('Social_Network_Ads.csv')\nX = dataset.iloc[:,[2,3]].values\ny = dataset.iloc[:, 4].values\n\n# Splitting the dataset into the Training set ... | [
[
"sklearn.metrics.confusion_matrix",
"sklearn.preprocessing.StandardScaler",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.colors.ListedColormap",
"sklearn.linear_model.LogisticRegression",
"matplotlib.pyplot.ylabel",
"matplotlib.... |
therealjtgill/mixture_density_network | [
"0851e56365762c5752ed21254a5d01e784568ff5"
] | [
"mdn_synthesis.py"
] | [
"import tensorflow as tf\r\nimport numpy as np\r\nimport os\r\nimport sys\r\nfrom window_cell import WindowCell\r\n\r\nnp.set_printoptions(threshold=sys.maxsize)\r\n\r\nclass AttentionMDN(object):\r\n '''\r\n Contains useful methods for training, testing, and validating a mixture\r\n density network.\r\n '''\r\... | [
[
"tensorflow.exp",
"numpy.set_printoptions",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.sqrt",
"tensorflow.stack",
"tensorflow.nn.softmax",
"tensorflow.nn.tanh",
"tensorflow.nn.rnn_cell.BasicLSTMCell",
"tensorflow.random_normal",
"numpy.concatenate",
"ten... |
Meteor-han/ReLMole | [
"ec8f2d3ec7b8edb6cd34aede36a980bab3dc35c2"
] | [
"task_ddi/run_ddi.py"
] | [
"import os, sys, argparse, time\nimport json\nfrom tqdm import tqdm\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch_geometric.data import DataLoader\nfrom tensorboardX import SummaryWriter\nsys.path.append('..')\nfrom models.ddi_predictor import DDIPred... | [
[
"torch.nn.Sigmoid",
"torch.no_grad",
"torch.save",
"torch.load",
"torch.nn.BCEWithLogitsLoss"
]
] |
opengeostat/pygslib | [
"7fb0c201eba6304b1914cf88a437aa9dc42e7021"
] | [
"setup.py"
] | [
"\"\"\"\r\npygslib: GSLIB in python\r\n\r\nCopyright 2020, Adrian Martinez Vargas.\r\nLicensed under MIT.\r\n\r\n\"\"\"\r\nimport setuptools #required to build wheels\r\nimport sys\r\nimport os\r\n\r\n# get version from package\r\nexec(open('pygslib/version.py').read())\r\n\r\nversion = __version__\r\ndescription ... | [
[
"numpy.distutils.core.setup",
"numpy.distutils.core.Extension"
]
] |
parkinkon1/simclr | [
"2c1a19baf28e91db119ab32df75d3a6e474dc1b1"
] | [
"stl10_pky.py"
] | [
"\nimport argparse\nimport time\nimport torchvision\nimport torch\nfrom torchvision import transforms as T\nfrom PIL import Image\nimport importlib.util\n\nimport tensorflow_datasets as tfds\nimport tensorflow_hub as hub\nimport sys\nimport os\nimport yaml\nimport re\nimport numpy as np\nimport subprocess\nimport r... | [
[
"numpy.array",
"numpy.empty",
"numpy.random.seed",
"tensorflow.Session",
"numpy.save",
"torch.manual_seed",
"tensorflow.placeholder",
"numpy.fromfile",
"numpy.append",
"tensorflow.global_variables_initializer"
]
] |
UniHD-CEG/camuy | [
"6f651a41ff3eb30d8ab3233ce20cc5f48f9cbfcb"
] | [
"mpusim_separable_conv2d/mpusim_separable_conv2d_op_impl.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n# Modifications copyright (c) 2020 Computing Systems Group.\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# ... | [
[
"tensorflow.compat.v1.load_op_library",
"tensorflow.compat.v1.concat",
"tensorflow.python.framework.ops.convert_to_tensor",
"tensorflow.compat.v1.split",
"tensorflow.python.ops.array_ops.shape",
"tensorflow.python.framework.ops.name_scope"
]
] |
seawavve/Random_CNN | [
"5dee90ddc8a79d4b4f2d9c5bd83e62e910c6fc83"
] | [
"CNN/0902_rand_cnn.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"0902_rand_cnn.ipynb\n\nAutomatically generated by Colaboratory.\n\nOriginal file is located at\n https://colab.research.google.com/drive/1p6_O9ie0cDHaiKxQBn935uTVwj85cEz9\n\"\"\"\n\n'''\npilab seawavve\nrandom cnn\n2020.05.20~\n\nAcc: 91.28% Epoch:75\n\n\n****PATCH NOTE****\n0520... | [
[
"tensorflow.keras.utils.to_categorical",
"tensorflow.keras.layers.Add",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.datasets.fashion_mnist.load_data",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Conv2D",
"tensorflow.keras.layers.Dense",
"tenso... |
mcernak/asteroid | [
"ed25e166a3bd338547248938116ba614ecfa4b3e",
"ed25e166a3bd338547248938116ba614ecfa4b3e"
] | [
"asteroid/filterbanks/griffin_lim.py",
"asteroid/models/dccrnet.py"
] | [
"import torch\nimport math\n\nfrom . import Encoder, Decoder, STFTFB # noqa\nfrom .stft_fb import perfect_synthesis_window\nfrom . import transforms\nfrom ..dsp.consistency import mixture_consistency\n\n\ndef griffin_lim(mag_specgram, stft_enc, angles=None, istft_dec=None, n_iter=6, momentum=0.9):\n \"\"\"Estim... | [
[
"torch.rand_like"
],
[
"torch.nn.functional.pad"
]
] |
RJRL12138/Regression-Examples | [
"8819818e74395d98a9cd6d7fb7ef06f316a8c233"
] | [
"dataHandler.py"
] | [
"import pandas as pd\nfrom sklearn.model_selection import train_test_split\n\nclass DataLoader:\n def __init__(self):\n self.dataset = None\n self.sensor = None\n self.target = None\n\n def load(self,file,isTest=False):\n if not isTest:\n print(\"loading\")\n ... | [
[
"sklearn.model_selection.train_test_split",
"pandas.DataFrame",
"pandas.read_csv"
]
] |
dataminer996/DSTC10_Track3_QS_Goal_Diggers | [
"24fe45c9a7098cf21c3278758fa8d9d073644a36",
"24fe45c9a7098cf21c3278758fa8d9d073644a36",
"24fe45c9a7098cf21c3278758fa8d9d073644a36"
] | [
"task4/generate/generagefeature/tools/test_sg_net.py",
"task4/generate/generagefeature/from_system_bin.py",
"task4/generate/generagefeature/scene_graph_benchmark/scene_parser.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\n# Copyright (c) 2021 Microsoft Corporation. Licensed under the MIT license. \n# Set up custom environment before nearly anything else is imported\n# NOTE: this should be the first import (no not reorder)\nimport sys\nimport os\nsys.path.appen... | [
[
"torch.distributed.init_process_group",
"torch.cuda.set_device",
"torch.cuda.empty_cache"
],
[
"numpy.array"
],
[
"torch.nn.functional.adaptive_avg_pool2d",
"numpy.sort",
"numpy.argsort",
"torch.from_numpy"
]
] |
casszhao/contextualizing-hate-speech-models-with-explanations | [
"adee4ef6fc4f1cb7b0be45c77a7a8e39a125873e"
] | [
"new_subjectivity_score.py"
] | [
"import nltk\nnltk.download('sentiwordnet')\nnltk.download('wordnet')\nnltk.download('averaged_perceptron_tagger')\nnltk.download('stopwords')\nnltk.download('punkt')\nfrom textblob import TextBlob\n\nfrom nltk.corpus import wordnet as wn\n\nimport pandas as pd\nimport numpy as np\nfrom nltk.stem import WordNetLemm... | [
[
"pandas.DataFrame",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.linspace",
"matplotlib.pyplot.rc",
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read... |
DavorJordacevic/DeepLearningFaceRecognitionSystem | [
"b0664226d2352d7f844aa07a70566b10e9e5362c"
] | [
"utils/videoProcessor.py"
] | [
"import cv2\nimport time\nimport dlib\nimport mtcnn\nimport numpy as np\n\n### THIS WILL BE DELETED ###\n\nclass VideoProcessor:\n def __init__(self, video_source, cfg):\n\n self.video_source = video_source\n self.detector_type = cfg[\"face_detector\"]\n self.dnn_detector_path = cfg[\"face_d... | [
[
"numpy.array"
]
] |
SohamChattopadhyayEE/RRCNN | [
"3bcd84bb44b68dea1d8e4dbd25923c8d4e7953ed"
] | [
"train.py"
] | [
"import os\r\nimport numpy as np\r\nimport argparse\r\nimport json\r\nimport torch\r\nimport torch.nn as nn\r\n\r\nfrom model.models import model_version\r\nfrom dataset.dataset import dataset\r\nfrom utils.optimizer import optimizer_function\r\nfrom utils.loss import loss_function\r\n\r\n\r\nparser = argparse.Argu... | [
[
"numpy.array",
"torch.no_grad",
"torch.cuda.is_available",
"torch.tensor",
"torch.load"
]
] |
sanjibs/k2gap | [
"218d5ae646541a7e566553f7a31d5bc2495d622c"
] | [
"k2gap/k2gap.py"
] | [
"#Copyright (c) 2021 Sanjib Sharma\n\"\"\"\nA module for K2GAP target selection function\n\n\nExample:\n\nimport k2gap\ninsurvey=k2gap.sf(cno,ra,dec,jmag,hmag,kmag)\nor\ninsurvey=k2gap.sf(cno,ra,dec,jmag,hmag,kmag,simulate_onsilicon=True)\n\n\"\"\"\n\n\nimport numpy as np\nimport json\nimport os\n\ndef read_json(fi... | [
[
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.exp",
"numpy.where",
"numpy.radians",
"numpy.cos",
"numpy.sqrt",
"numpy.unique",
"numpy.isin"
]
] |
DreaJulca/uxsense | [
"538800f3e071660f4a8242c90b25f500b8667aa8"
] | [
"models/pt_3dpose/detectron/utils/image.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.isclose",
"numpy.sqrt"
]
] |
yakir4123/jesse | [
"e7dcc1022c6c1077a5812caeb4753c84af531332"
] | [
"jesse/services/metrics.py"
] | [
"from datetime import datetime, timedelta\nfrom typing import List, Any, Union\n\nimport numpy as np\nimport pandas as pd\nfrom quantstats import stats\n\nimport jesse.helpers as jh\nfrom jesse.models import CompletedTrade\nfrom jesse.store import store\n\n\ndef candles_info(candles_array: np.ndarray) -> dict:\n ... | [
[
"pandas.DataFrame.from_records",
"numpy.isnan",
"pandas.DataFrame",
"numpy.where",
"numpy.clip"
]
] |
SylvainLan/pysap | [
"38c0d43f61adb952c3768d33f1ca41c5769fef2b"
] | [
"examples/astro/galaxy_deconvolution.py"
] | [
"\"\"\"\nGalaxy Image Deconvolution\n==========================\n\nCredit: S. Farrens\n\nIn this tutorial we will deconvolve the PSF effects from an example galaxy\nimage.\n\nImport astro data\n-----------------\n\nThe example galaxy image is convolved with the example PSF and random noise is\nadded simulating an o... | [
[
"numpy.abs"
]
] |
dmytrov/stochasticcontrol | [
"a289d5c0953c4a328b2177f51168588248c00f2c"
] | [
"code/states/delayedfeedback.py"
] | [
"import time\nimport numpy as np\nimport psychopy.visual as pv\nimport utils.logger as ulog\nimport statemachine.machine as sm\nimport statemachine.states as sms\nfrom psychopy.visual.circle import Circle\nfrom statemachine.states import TextMessage, Sequence\nimport utils.soundfeedback as fbk\nfrom states.common i... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.sin",
"numpy.random.seed",
"numpy.arctan2",
"numpy.cos",
"numpy.linspace"
]
] |
Sara-X/transformers | [
"6d9e11a1939815910e9274cc1109b632cfa84db4"
] | [
"tests/test_tokenization_wav2vec2.py"
] | [
"# coding=utf-8\n# Copyright 2021 The HuggingFace Team. 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#\... | [
[
"numpy.allclose",
"numpy.var",
"numpy.asarray",
"numpy.mean"
]
] |
ishine/nlp-dialogue | [
"d47c1438cb5c45c2c2aebfb82fea92bef4c3d65c"
] | [
"dialogue/tensorflow/beamsearch.py"
] | [
"# Copyright 2021 DengBoCong. 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 appl... | [
[
"tensorflow.argmax",
"tensorflow.concat"
]
] |
kilimanjaro2/MRIQC_monkey | [
"f70c410d7459d4970351949e10443725187c0df2",
"f70c410d7459d4970351949e10443725187c0df2"
] | [
"mriqc/interfaces/viz.py",
"mriqc/utils/misc.py"
] | [
"# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-\n# vi: set ft=python sts=4 ts=4 sw=4 et:\n\"\"\"Visualization interfaces.\"\"\"\nfrom pathlib import Path\nimport numpy as np\nfrom nipype.interfaces.base import (\n traits,\n TraitedSpec,\n File,\n BaseInterfaceInputSpec,\n i... | [
[
"numpy.loadtxt",
"numpy.atleast_2d"
],
[
"pandas.DataFrame",
"pandas.read_csv"
]
] |
jjudy60334/my-nlp-wrangler | [
"cd0e941ab224a5614550060e15255a786923fdd8"
] | [
"tests/test_cleaner.py"
] | [
"import unittest\nfrom unittest import TestCase\n\nimport pandas as pd\nfrom mynlpwrangler.cleaner import ArticleCleaner\nimport pandas.testing as pd_testing\n\n\nclass TestCleaner(TestCase):\n def setUp(self) -> None:\n self.data = {\"id\": [\"10001\", \"11375\", \"23423\"], \"text\": [\n \"He... | [
[
"pandas.DataFrame",
"pandas.testing.assert_frame_equal"
]
] |
xi2pi/gamlss | [
"497af26671316679c1648185ec49c009dffb0e9d"
] | [
"1D/gamlss_distributions.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri Feb 9 08:20:58 2018\n\n@author: Christian Winkler\n\"\"\"\nimport matplotlib.pyplot as plt\nfrom scipy import asarray as ar,exp\nfrom scipy.special import erf, gamma\nimport numpy as np\n\ndef NO(x,M,S):\n return 1/(np.sqrt(2*np.pi)*S)*exp(-(x-M)**2/(2*S**2))\n\n... | [
[
"scipy.exp",
"scipy.special.gamma",
"numpy.log",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.exp",
"numpy.arange",
"numpy.sqrt",
"numpy.abs",
"matplotlib.pyplot.show"
]
] |
bjlfzs/Fundus-vessel-segmentation | [
"26ffabb7bd9b215ca6d3b03bd0aae1c0141b56e7"
] | [
"test.py"
] | [
"import joblib,copy\nimport torch.backends.cudnn as cudnn\nfrom torch.utils.data import DataLoader\nimport torch,sys\nfrom tqdm import tqdm\n\nfrom collections import OrderedDict\nfrom lib.visualize import save_img,group_images,concat_result\nimport os\nimport argparse\nfrom lib.logger import Logger, Print_Logger\n... | [
[
"torch.no_grad",
"torch.cuda.is_available",
"torch.utils.data.DataLoader"
]
] |
Wingham1/hessidf | [
"18e63e25f9989565f1f361458f7ff8e53f4579e9"
] | [
"flare_classifier/intersect_hessi_goes.py"
] | [
"\"\"\"\nThis script uses data from the hessi mission to find the location (x, y, in arcsec) of flares and their dates,\nand the goes mission to find the class of flares and their dates, then it makes a new dataset with the date, class and location of each flare,\nthe dataset is exported to a csv file so it can be ... | [
[
"pandas.DataFrame.from_dict"
]
] |
mabounassif/t3f | [
"28acf14812481f6a47ea6dbedeb55048e2e6203b",
"28acf14812481f6a47ea6dbedeb55048e2e6203b"
] | [
"t3f/initializers.py",
"t3f/tensor_train.py"
] | [
"import numpy as np\nimport tensorflow as tf\n\nfrom t3f.tensor_train import TensorTrain\nfrom t3f.tensor_train_batch import TensorTrainBatch\nfrom t3f.tensor_train_base import TensorTrainBase\nfrom t3f import shapes\n\n\ndef _validate_input_parameters(is_tensor, shape, **params):\n \"\"\"Internal function for val... | [
[
"numpy.concatenate",
"numpy.array",
"tensorflow.zeros",
"tensorflow.eye",
"tensorflow.random_normal",
"numpy.ones",
"tensorflow.ones",
"numpy.any",
"numpy.prod",
"tensorflow.name_scope",
"numpy.abs",
"numpy.append",
"numpy.sqrt",
"numpy.insert",
"numpy.v... |
gavincangan/pyro | [
"d9115a6da7edd7e3fecd6b89a850cc137d7e7e9a",
"d9115a6da7edd7e3fecd6b89a850cc137d7e7e9a",
"d9115a6da7edd7e3fecd6b89a850cc137d7e7e9a",
"d9115a6da7edd7e3fecd6b89a850cc137d7e7e9a"
] | [
"examples/rsa/search_inference.py",
"pyro/distributions/iaf.py",
"tests/contrib/gp/test_models.py",
"pyro/contrib/oed/eig.py"
] | [
"\"\"\"\nInference algorithms and utilities used in the RSA example models.\n\nAdapted from: http://dippl.org/chapters/03-enumeration.html\n\"\"\"\n\nfrom __future__ import absolute_import, division, print_function\n\nimport collections\n\nimport six\nimport torch\nfrom six.moves import queue\n\nimport pyro\nimport... | [
[
"torch.zeros",
"torch.rand",
"torch.stack",
"torch.is_tensor",
"torch.tensor",
"torch.pow"
],
[
"torch.zeros",
"torch.stack",
"torch.nn.Sigmoid",
"torch.nn.LogSigmoid",
"torch.exp"
],
[
"torch.Size",
"torch.zeros",
"torch.stack",
"torch.sin",
... |
DLR-SC/memilio | [
"e83243df95e21b5841e3bc077a667fe5446da866"
] | [
"pycode/memilio-epidata/memilio/epidata_test/test_epidata_getCommuterMobility.py"
] | [
"#############################################################################\n# Copyright (C) 2020-2021 German Aerospace Center (DLR-SC)\n#\n# Authors:\n#\n# Contact: Martin J. Kuehn <Martin.Kuehn@DLR.de>\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except i... | [
[
"pandas.DataFrame",
"pandas.ExcelWriter"
]
] |
vghost2008/wml | [
"d0c5a1da6c228e321ae59a563e9ac84aa66266ff",
"d0c5a1da6c228e321ae59a563e9ac84aa66266ff",
"d0c5a1da6c228e321ae59a563e9ac84aa66266ff",
"d0c5a1da6c228e321ae59a563e9ac84aa66266ff",
"d0c5a1da6c228e321ae59a563e9ac84aa66266ff"
] | [
"optimizer/padam.py",
"object_detection2/data/mtest.py",
"datasets_tools/create_voc_tf_record_by_coco.py",
"object_detection2/modeling/proposal_generator/rpn_giou_outputs.py",
"object_detection2/modeling/roi_heads/mask_head.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nfrom tensorflow.python.eager import context\nfrom tensorflow.python.framework import ops\nfrom tensorflow.python.ops import control_flow_ops\nfrom tensorflow.python.ops import math_ops\nfrom tensorflow... | [
[
"tensorflow.python.eager.context.executing_eagerly",
"tensorflow.python.ops.math_ops.cast",
"tensorflow.python.ops.state_ops.scatter_add",
"tensorflow.python.ops.control_flow_ops.group",
"tensorflow.python.framework.ops.colocate_with",
"tensorflow.python.ops.state_ops.assign",
"tensorf... |
lygztq/gomoku | [
"c833d4234291b9518a9fc2e6893a1380d927261a"
] | [
"src/pygomoku/GameServer.py"
] | [
"import numpy as np\nfrom pygomoku.Board import Board\nfrom pygomoku import Player\n\ndef change_color(color):\n if color == Board.kPlayerBlack:\n return Board.kPlayerWhite\n elif color == Board.kPlayerWhite:\n return Board.kPlayerBlack\n else:\n return color\n\nclass GameServer(object... | [
[
"numpy.array"
]
] |
bhatiaharsh/naturalHHD | [
"7a8efd44fb7c348a53fae05f59a9098ba0f4046b"
] | [
"pynhhd-v1.1/pynhhd/spherical.py"
] | [
"'''\nCopyright (c) 2015, Harsh Bhatia (bhatia4@llnl.gov)\nAll rights reserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are met:\n1. Redistributions of source code must retain the above copyright notice, this\nlist of ... | [
[
"numpy.concatenate",
"numpy.add",
"numpy.zeros",
"numpy.radians",
"numpy.subtract",
"numpy.stack",
"numpy.arange",
"numpy.cos",
"numpy.gradient"
]
] |
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