repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
hanskrupakar/fastestimator | [
"1c3fe89ad8b012991b524a6c48f328b2a80dc9f6"
] | [
"fastestimator/backend/get_image_dims.py"
] | [
"# Copyright 2019 The FastEstimator 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 r... | [
[
"tensorflow.is_tensor"
]
] |
Pakirisu/ArknightsAutoHelper | [
"8b136c82794cfe9f364788d9c92f1e4c5b38c6cb",
"8b136c82794cfe9f364788d9c92f1e4c5b38c6cb"
] | [
"Arknights/base.py",
"imgreco/common.py"
] | [
"import logging.config\nimport os\nfrom collections import OrderedDict\nfrom random import randint, uniform, gauss\nfrom time import sleep, monotonic\n\nimport numpy as np\nfrom PIL import Image\n\n# from config import *\nimport config\nimport imgreco\nimport penguin_stats.loader\nimport penguin_stats.reporter\nimp... | [
[
"numpy.asarray"
],
[
"numpy.array",
"numpy.argmax",
"numpy.asarray"
]
] |
csho33/bacteria-ID | [
"3c00a712a6dbad9aefa19ac878a1e6db20590ca9"
] | [
"resnet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\n\n\nclass ResidualBlock(nn.Module):\n def __init__(self, in_channels, out_channels, stride=1):\n super(ResidualBlock, self).__init__()\n\n # Layers\n self.conv1 = nn.Conv1d(in_channels... | [
[
"torch.nn.Linear",
"torch.rand",
"torch.nn.SELU",
"torch.nn.Conv1d",
"torch.nn.Sequential",
"torch.nn.Sigmoid",
"torch.nn.LeakyReLU",
"torch.nn.Tanh",
"torch.nn.ReLU",
"torch.nn.BatchNorm1d",
"torch.nn.Softplus",
"torch.nn.functional.relu",
"torch.nn.ELU"
]
] |
zoulejiu/captcha_trainer | [
"3a4b79e7b00553c9cf78cc3720e6a50a1886a05a"
] | [
"trains.py"
] | [
"#!/usr/bin/env python3\n# -*- coding:utf-8 -*-\n# Author: kerlomz <kerlomz@gmail.com>\nimport tensorflow as tf\nimport core\nimport utils\nimport utils.data\nimport validation\nfrom config import *\nfrom tf_graph_util import convert_variables_to_constants\nfrom PIL import ImageFile\n\nImageFile.LOAD_TRUNCATED_IMAG... | [
[
"tensorflow.io.gfile.GFile",
"tensorflow.compat.v1.summary.FileWriter",
"tensorflow.compat.v1.logging.info",
"tensorflow.train.latest_checkpoint",
"tensorflow.Graph",
"tensorflow.Session",
"tensorflow.logging.info",
"tensorflow.keras.backend.set_session",
"tensorflow.train.get_... |
lpj0822/image_point_cloud_det | [
"7b20e2f42f3f2ff4881485da58ad188a1f0d0e0f",
"7b20e2f42f3f2ff4881485da58ad188a1f0d0e0f"
] | [
"easyai/tools/model_net_show.py",
"easyai/model/base_block/utility/filter_response_normalization.py"
] | [
"import os\nimport sys\nsys.path.insert(0, os.getcwd() + \"/..\")\nimport torch\nfrom easyai.model.backbone.utility.backbone_factory import BackboneFactory\nfrom easyai.model.utility.model_factory import ModelFactory\nfrom easyai.torch_utility.torch_onnx.model_show import ModelShow\nfrom easyai.helper.arguments_par... | [
[
"torch.randn"
],
[
"torch.max",
"torch.nn.init.ones_",
"torch.ones",
"torch.abs",
"torch.nn.init.zeros_",
"torch.Tensor",
"torch.pow"
]
] |
CasperKristiansson/Group-Project-II1302 | [
"2878ef514f0c114e5b6e7f4130264bbbf528bc0a"
] | [
"Backend/Machine Learning/Library/raw_data.py"
] | [
"\"\"\"\"\"\"\n__author__ = \"Casper Kristiansson\"\n__copyright__ = \"WeatherBrain\"\n\n__maintainer__ = \"Casper Kristiansson\"\n__email__ = \"casperkr@kth.se\"\n__status__ = \"Development\"\n\nimport pandas\n\n\ndef load_temperature_raw():\n \"\"\"This methid loads the raw temperature data from\n text file... | [
[
"pandas.to_datetime",
"pandas.DataFrame",
"pandas.concat"
]
] |
cv-small-snails/Text-Recognition-Pytorch | [
"cdb3b201faf0a3cec6ef075b8c4fc5f567798045"
] | [
"text.recognition.pytorch/models/backbones/resnet.py"
] | [
"from typing import Type, Any, Callable, Union, List, Optional\n\nimport torch\nimport torch.nn as nn\nfrom torch import Tensor\n\nfrom torchvision.models.utils import load_state_dict_from_url\n\n\n__all__ = [\n \"ResNet\",\n \"resnet18\",\n \"resnet34\",\n \"resnet50\",\n \"resnet101\",\n \"resne... | [
[
"torch.nn.Linear",
"torch.flatten",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.nn.init.constant_",
"torch.nn.init.kaiming_normal_",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.AdaptiveAvgPool2d"
]
] |
Sutthipong/thai-ner | [
"08576d563081f53662a4bd1e82354d3d386bb464"
] | [
"old/12092018/train2.py"
] | [
"# -*- coding: utf-8 -*-\n# เรียกใช้งานโมดูล\nfile_name=\"data\"\nimport codecs\nfrom pythainlp.tokenize import word_tokenize\n#import deepcut\nfrom pythainlp.tag import pos_tag\nfrom nltk.tokenize import RegexpTokenizer\nimport glob\nimport nltk\nimport re\n# thai cut\nthaicut=\"newmm\"\nfrom sklearn_crfsuite impo... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.model_selection.cross_validate",
"sklearn.metrics.make_scorer"
]
] |
elnazsn1988/Trading-Gym | [
"d4b36a6a50fa295ff8401b45786cf62cc89189c7"
] | [
"tests/gens/test_random.py"
] | [
"import numpy as np\nfrom tgym.gens import AR1, RandomWalk\n\n\ndef test_random_walk():\n rw = RandomWalk(ba_spread=0.1)\n val = rw.next()\n assert np.isclose(val[1] - val[0], 0.1)\n\n\ndef test_ar1():\n rw = AR1(a=0.1, ba_spread=0.1)\n val = rw.next()\n assert np.isclose(val[1] - val[0], 0.1)\n ... | [
[
"numpy.std",
"numpy.isclose",
"numpy.mean"
]
] |
mgh17/tierpsy-tracker | [
"a18c06aa80a5fb22fd51563d82c639b520742777",
"a18c06aa80a5fb22fd51563d82c639b520742777"
] | [
"tierpsy/analysis/ske_create/segWormPython/cleanWorm.py",
"tierpsy/features/open_worm_analysis_toolbox/features/path_features.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri May 22 18:10:04 2015\n\n@author: ajaver\n\"\"\"\n\nfrom .cython_files.cleanWorm_cython import extremaPeaksCircDist, removeSmallSegments, cleanContour\nfrom .cython_files.circCurvature import circCurvature\n\nimport numpy as np\n\n\ndef circCurvature_old(points, edgeL... | [
[
"numpy.ceil",
"numpy.array",
"numpy.zeros",
"numpy.lib.pad",
"numpy.round",
"numpy.sum",
"numpy.roll",
"numpy.diff",
"numpy.arctan2",
"numpy.linspace",
"numpy.vstack",
"numpy.convolve"
],
[
"numpy.full",
"numpy.isnan",
"numpy.errstate",
"numpy.ze... |
walogo/Pythonista-scripts | [
"760451a0cdbe5dd76008a4e616d74191385bbd8b"
] | [
"Pythonista/KB_shortcuts/functions_eval/function.py"
] | [
"from re import search, findall\nfrom numpy import arange\nfrom matplotlib import pyplot as plt\nfrom mpl_toolkits.mplot3d import Axes3D\nfrom matplotlib import cm\nfrom crunch import Crunch\nfrom io import BytesIO\nfrom ui import Image\nfrom numpy import ma\nfrom math import *\n\n\ndef create_ranges(ranges):\n\tad... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.step",
"numpy.arange",
"matplotlib.pyplot.figure"
]
] |
YeongHyeon/Super-Resolution_CNN | [
"1feb77eba7dbd59974ae948bf3e50f791fc0bfa2"
] | [
"run.py"
] | [
"import os, argparse\nos.environ[\"CUDA_VISIBLE_DEVICES\"]=\"0\"\n\nimport tensorflow as tf\n\nimport source.neuralnet as nn\nimport source.datamanager as dman\nimport source.tf_process as tfp\nimport source.stamper as stamper\nstamper.print_stamp()\n\ndef main():\n\n srnet = nn.SRNET()\n\n dataset = dman.Dat... | [
[
"tensorflow.compat.v1.train.Saver",
"tensorflow.compat.v1.global_variables_initializer",
"tensorflow.compat.v1.InteractiveSession"
]
] |
ybai62868/CornerNet-Lite | [
"cad0fb248be1da38451042ff6c5b9979e67a0729"
] | [
"core/models/CornerNet_Squeeze.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom .py_utils import TopPool, BottomPool, LeftPool, RightPool # corner pooling\n\nfrom .py_utils.utils import convolution, corner_pool, residual\nfrom .py_utils.losses import CornerNet_Loss\nfrom .py_utils.modules import hg_module, hg, hg_net\n\nclass fire_module(nn.Module):... | [
[
"torch.nn.init.constant_",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.ConvTranspose2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
adeckert23/soccer-proj | [
"4f86993b98c6a1153bdc1c57cc8d04053302967d"
] | [
"src/radar1_class.py"
] | [
"import numpy as np\nimport pylab as pl\n\nclass Radar1(object):\n def __init__(self, figure, title, labels, rect=None):\n if rect is None:\n rect = [0.05, 0.05, .85, .85]\n\n self.n = len(title)\n self.angles = np.arange(0, 360, 360.0/self.n)\n\n self.axes = [figure.add_ax... | [
[
"numpy.deg2rad",
"numpy.arange"
]
] |
ushita37/shortest_path | [
"a04eea43480809f528fa4b8d5878b23f11e58c1b"
] | [
"early_works/yamanote_inner_track.py"
] | [
"# © 2021 ushita37\n\nimport numpy as np\n# import pandas as pd\n\n# ekimei = pd.read_csv('stationName.csv', header=None, encoding='Shift-JIS').values.tolist()\n# ekimeiList = ekimei[0]\n\n# pandasを使うと正常に動作しないことがあるので、上記の4・6・7行目をコメントアウトし、以下の10・11行目を実行している\nF = open('stationName.csv')\nekimeiList = F.readline().repla... | [
[
"numpy.loadtxt"
]
] |
ml-boringtao/rnn | [
"d7c7fd3ced77d7db061e4077a3532f74d2788886"
] | [
"training/helpers/callbacks.py"
] | [
"from keras.callbacks import BaseLogger\nimport matplotlib.pyplot as plt\nimport numpy as np \nimport json\nimport os\nfrom .utils import Utils\n\nclass TrainingMonitor(BaseLogger):\n def __init__(self, figPath, jsonPath=None, startAt=0):\n super(TrainingMonitor, self).__init__()\n self.figPath = f... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.style.use"
]
] |
sdss/mangaSampleDB | [
"36c0b2113a9c0a163d47c844656af350d80310b1"
] | [
"python/mangaSampleDB/utils/catalogue.py"
] | [
"#!/usr/bin/env python3\n# encoding: utf-8\n\"\"\"\n\ncatalogue.py\n\nCreated by José Sánchez-Gallego on 18 Feb 2016.\nLicensed under a 3-clause BSD license.\n\nRevision history:\n 18 Feb 2016 J. Sánchez-Gallego\n Initial version\n\n\"\"\"\n\nfrom __future__ import division\nfrom __future__ import print_fun... | [
[
"numpy.where"
]
] |
kevinkevin556/STASD | [
"db88c4302c6ddb0dc4b4d291f72d09dd4c9db38e"
] | [
"modules/ptt_region_crawler.py"
] | [
"from bs4 import BeautifulSoup\nimport pandas as pd\nimport requests\nimport re\nimport time\n\ndef get_post_num(region, date, verbose=True, init_index=None, return_index=False):\n\tdate_timestamp = pd.Timestamp(date)\n\tmax_index = get_max_index(region)\n\n\tif init_index is None:\n\t\ti = max_index\n\t\tcurrent_y... | [
[
"pandas.Timestamp",
"pandas.Timestamp.today"
]
] |
martsec/arcitectural_elements_identifier | [
"87607e87f714443c5aa37c96896b76a4f6f424d4"
] | [
"arch_elements/etl/transform.py"
] | [
"from sklearn.preprocessing import OneHotEncoder\r\nfrom sklearn.model_selection import train_test_split\r\nimport tensorflow as tf\r\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\r\nimport numpy as np\r\nfrom collections.abc import Callable\r\n\r\nclass OneHot:\r\n def __init__(self):\r\n... | [
[
"numpy.concatenate",
"numpy.array",
"tensorflow.keras.preprocessing.image.ImageDataGenerator",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.OneHotEncoder",
"numpy.expand_dims"
]
] |
we3lab/coals_controls | [
"4a9a368123d292b300d6bd4c978230c0552838fd"
] | [
"Code/function_dictionary_library/interaction_term_variable_creation.py"
] | [
"import numpy as np\n\n\ndef interaction_term_variable_creation(X, variable_1, variable_2):\n i = 0\n width_variable_1 = np.shape(variable_1)\n if len(width_variable_1) == 1:\n width_variable_1 = width_variable_1 + (1,)\n width_variable_1 = width_variable_1[1]\n width_variable_2 = np.shape(var... | [
[
"numpy.column_stack",
"numpy.shape"
]
] |
davedavedavid/plato | [
"097e26ef6de5d1fa1392ebe01cfc4576e5dd7ae9"
] | [
"plato/utils/unary_encoding.py"
] | [
"\"\"\"Implements unary encoding, used by Google's RAPPOR, as the local differential privacy mechanism.\n\nReferences:\n\nWang, et al. \"Optimizing Locally Differentially Private Protocols,\" ATC USENIX 2017.\n\nErlingsson, et al. \"RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response,\"\nACM CCS 201... | [
[
"numpy.where",
"numpy.random.binomial",
"numpy.random.choice",
"numpy.zeros"
]
] |
Praveen76/Wav2Keyword | [
"40c3bdd92c2ed43e421a4756426dbfd6158e8b94"
] | [
"recognize.py"
] | [
"import torch\nimport argparse\nimport soundfile as sf\nimport torch.nn.functional as F\nimport itertools as it\nfrom fairseq import utils\nfrom fairseq.models import BaseFairseqModel\nfrom examples.speech_recognition.w2l_decoder import W2lViterbiDecoder\nfrom fairseq.data import Dictionary\nfrom fairseq.models.wav... | [
[
"torch.nn.functional.layer_norm",
"torch.IntTensor",
"torch.no_grad",
"torch.FloatTensor",
"torch.from_numpy",
"torch.load"
]
] |
Jhilbertxtu/JDComments_Analyze | [
"9a93c7cfc572509fce5e0f82702d8d55d029ef8f"
] | [
"svm.py"
] | [
"import pandas as pd\nfrom sklearn.decomposition import PCA\nfrom sklearn import svm\n'''\n10条数据,但模型是100维的,所以复制够100,只取前10\n第1次 c=2 完全正确4,完全错误2,模糊4\n[1. 0. 0. 1. 1. 0. 0. 0. 1. 1. 1. 0. 0. 1. 1. 0. 0. 0. 1. 1. 1. 0. 0. 1.\n 1. 0. 0. 0. 1. 1. 1. 0. 0. 1. 1. 0. 0. 0. 1. 1. 1. 0. 0. 1. 1. 0. 0. 0.\n 1. 1. 1. 0. 0. 1. 1... | [
[
"pandas.read_csv",
"sklearn.decomposition.PCA",
"sklearn.svm.SVC"
]
] |
USF-Seismology/mtuq | [
"92b863a53c9af909b2153c5c671741e020964384"
] | [
"mtuq/graphics/attrs.py"
] | [
"import os\n\nfrom matplotlib import pyplot\nfrom os.path import join\n\nfrom mtuq.util import warn\n\n\ndef plot_time_shifts(*args, **kwargs):\n \"\"\" Creates \"spider plots\" showing how time shifts vary geographically\n\n Within the specified directory, a separate PNG figure will be created for \n each... | [
[
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.close",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.scatter"
]
] |
salil91/GASP-python | [
"26f84f03458765ebc07f5d2286e8a250b7fad898"
] | [
"gasp/population.py"
] | [
"# coding: utf-8\n# Copyright(c) Henniggroup.\n# Distributed under the terms of the MIT License.\n\nfrom __future__ import division, unicode_literals, print_function\n\n\"\"\"\nPopulation module:\n\nThis module contains classes used to hold the population of organisms.\n\n1. InitialPopulation: represents the initia... | [
[
"numpy.delete",
"numpy.subtract",
"numpy.linalg.norm",
"scipy.spatial.qhull.ConvexHull"
]
] |
CptPirx/opendr_internal | [
"9204f254c4a32ce4298dd4b95cabaab8f60fd3c7"
] | [
"src/opendr/perception/multimodal_human_centric/rgbd_hand_gesture_learner/rgbd_hand_gesture_learner.py"
] | [
"# Copyright 2020-2021 OpenDR European Project\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 applicab... | [
[
"torch.device",
"torch.utils.tensorboard.SummaryWriter",
"torch.no_grad",
"numpy.transpose",
"torch.utils.data.DataLoader",
"torch.nn.CrossEntropyLoss",
"numpy.expand_dims"
]
] |
tneumann/cgtools | [
"8f77b6a4642fe79ac85b8449ebd3f72ea0e56032"
] | [
"tests/test_indexing.py"
] | [
"import numpy as np\nimport numpy.testing as npt\nfrom cgtools.indexing import valid_indices\n\n\ndef test_valid_indices_randomized_tests():\n for axes in range(1, 10):\n shape = np.random.randint(1, 10, axes)\n a = np.empty(shape)\n indices = np.random.randint(-5, 15, (500, axes))\n ... | [
[
"numpy.random.randint",
"numpy.empty"
]
] |
Alicegaz/torchok | [
"7b8f95df466a25b1ad8ee93bed1a3c7516440cf4"
] | [
"src/optim/optimizers/lamb.py"
] | [
"\"\"\" PyTorch Lamb optimizer w/ behaviour similar to NVIDIA FusedLamb\n\nThis optimizer code was adapted from the following (starting with latest)\n* https://github.com/HabanaAI/Model-References/blob/2b435114fe8e31f159b1d3063b8280ae37af7423/PyTorch/nlp/bert/pretraining/lamb.py\n* https://github.com/NVIDIA/DeepLea... | [
[
"torch.zeros",
"torch.sqrt",
"torch.no_grad",
"torch.enable_grad",
"torch.minimum",
"torch.tensor",
"torch.zeros_like",
"torch.where"
]
] |
Othinus099/int | [
"44d83c5d37f91957666ce65120543608a8a7f6a2"
] | [
"projects/UniDet/unidet/modeling/roi_heads/multi_dataset_fast_rcnn.py"
] | [
"import logging\r\nimport math\r\nfrom typing import Dict, Union\r\nimport torch\r\nfrom fvcore.nn import giou_loss, smooth_l1_loss\r\nfrom torch import nn\r\nfrom torch.nn import functional as F\r\n\r\nfrom detectron2.config import configurable\r\nfrom detectron2.layers import Linear, ShapeSpec, batched_nms, cat, ... | [
[
"torch.nn.Linear",
"torch.nn.ModuleList",
"torch.nn.init.constant_",
"torch.nn.init.normal_",
"torch.flatten"
]
] |
zack28/TakenMind-Internship | [
"7fb7c1c0b255ee233f18fd9ab4fa76a9b2c992d7"
] | [
"Data Manipulation with Pandas/ranking_sorting.py"
] | [
"import numpy as np\r\nimport pandas as pd\r\nfrom pandas import Series,DataFrame\r\nfrom numpy.random import randn\r\n\r\ns1=Series([500,1000,1500],index=['a','c','b'])\r\nprint(s1)\r\n\r\n#sorting by index\r\nprint(s1.sort_index())\r\n\r\n#sort by values\r\nprint(s1.sort_values())\r\n\r\n#ranking of series\r\npri... | [
[
"numpy.random.randn",
"pandas.Series"
]
] |
antsfamily/pyopt | [
"e1d240321f954219daa44c5c7f73f6ad3f0e6427"
] | [
"pyopt/utils/tools.py"
] | [
"from __future__ import division, print_function, absolute_import\nimport numpy as np\nfrom scipy import signal\n\n\ndef cshift(x, L):\n\n N = np.size(x)\n\n if np.size(x, 0) > 1:\n raise ValueError(\"Input x must be 1-d vector!\")\n\n L = int(L)\n\n y = np.zeros(x.shape)\n print(x.shape, y.sh... | [
[
"numpy.array",
"numpy.zeros",
"numpy.size",
"scipy.signal.convolve2d",
"numpy.floor"
]
] |
dhawalaashay/Image_Classifier | [
"c0f38069e11475c504d846edb1e22b420dbd4850"
] | [
"train_model.py"
] | [
"# import Python Modules /dependencies\nimport time\nimport torch\nimport argparse\nimport matplotlib\nimport numpy as np\nimport torch.nn.functional as F\nimport matplotlib.pyplot as plt\n\nfrom PIL import Image\nfrom torch import nn, optim\nfrom collections import OrderedDict\nfrom workspace_utils import active_s... | [
[
"torch.nn.NLLLoss",
"torch.device",
"torch.nn.Dropout",
"torch.nn.Linear",
"torch.nn.LogSoftmax",
"torch.no_grad",
"torch.nn.ReLU",
"torch.exp"
]
] |
AIllIll/hyperface-new | [
"b62fef1c8733d53d66e674b23cc3e44c7b13466c"
] | [
"scripts/extensions/imgviewer_extension.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport multiprocessing\nimport numpy as np\n\nfrom chainer import variable\nfrom chainer.training import extension\n\nfrom . import imgviewer\n\n# logging\nfrom logging import getLogger, NullHandler, INFO\nlogger = getLogger(__name__)\nlogger.addHandler(NullHandler())\n# logging for imgv... | [
[
"numpy.transpose"
]
] |
asvspoof/ASVspoof2019_system | [
"b85d256d564e93806c4cadc2257863b4f1b0f588"
] | [
"source-code/modelsummary.py"
] | [
"from torchsummary import summary\nimport torch\n\nfrom ResNet import DKU_ResNet\n\nif __name__ == '__main__':\n\n use_cuda = torch.cuda.is_available()\n device = torch.device(\"cuda\" if use_cuda else \"cpu\")\n print(\"Use\", device)\n model = DKU_ResNet(num_classes=2).to(device)\n summary(model,(1... | [
[
"torch.device",
"torch.cuda.is_available"
]
] |
LongmaoTeamTf/deep_recommenders | [
"168dabe4ef3a38cc582d019766cf3de576bc8af1"
] | [
"deep_recommenders/keras/models/ranking/fm.py"
] | [
"#!/usr/bin/python3\n# -*- coding: utf-8 -*-\n\nimport tensorflow as tf\n\n\n@tf.keras.utils.register_keras_serializable()\nclass FM(tf.keras.layers.Layer):\n \"\"\" Factorization Machine \"\"\"\n\n def __init__(self, **kwargs):\n super(FM, self).__init__(**kwargs)\n\n def build(self, input_shape):\... | [
[
"tensorflow.keras.layers.DenseFeatures",
"tensorflow.keras.layers.Dense",
"tensorflow.reduce_sum",
"tensorflow.stack",
"tensorflow.pow",
"tensorflow.nn.sigmoid",
"tensorflow.keras.utils.register_keras_serializable"
]
] |
luiscruz/physalia | [
"364951d94e02b60092785db46a8c7a7299ffe2a4"
] | [
"physalia/fixtures/models.py"
] | [
"\"\"\"Fixtures for models module.\"\"\"\n\nfrom physalia.models import Measurement\nimport numpy\n\n\ndef create_measurement(use_case='login',\n app_pkg='com.package',\n duration=2,\n energy_consumption=30):\n \"\"\"Fake data for measurement.\"\"... | [
[
"numpy.random.seed",
"numpy.random.normal"
]
] |
gpvi/w2_AI | [
"fc6742c09237f7502585916a4d96a494996cd2ec"
] | [
"iris_KNN.py"
] | [
"from sklearn.datasets import load_iris\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.neighbors import KNeighborsClassifier\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.datasets import fetch_20newsgroups\nfrom sklearn.feature... | [
[
"sklearn.model_selection.train_test_split",
"sklearn.neighbors.KNeighborsClassifier",
"sklearn.datasets.load_iris",
"sklearn.preprocessing.StandardScaler"
]
] |
grechaw/ray_lightning | [
"2390e9c75b140af03811c8360f0ad63c4afebe95"
] | [
"ray_lightning/util.py"
] | [
"import io\nfrom typing import Callable\n\nimport torch\nfrom pytorch_lightning.accelerators import GPUAccelerator\nfrom pytorch_lightning import Trainer, LightningModule\n\nimport ray\n\n\nclass DelayedGPUAccelerator(GPUAccelerator):\n \"\"\"Same as GPUAccelerator, but doesn't do any CUDA setup.\n\n This all... | [
[
"torch.save",
"torch.cuda.is_available"
]
] |
songlab-cal/contact-geometry | [
"81cb7e56af7bccaf5b7f6dde52d9f2adbe89e8bd"
] | [
"self_contacts/utils.py"
] | [
"import numpy as np\nimport pickle as pkl\n\nfrom functional_groups import SMARTS_ATOM_MAP\n\nDATA_FOLDER = 'raw_contacts'\nVDMS_FOLDER = 'contacts'\nIFG_REPS_FOLDER = 'ifg_reps'\n\nAMINO_ACIDS = {'ALA', 'ARG', 'ASN', 'ASP', 'CYS', 'GLU', 'GLN', 'GLY', 'HIS', 'ILE', 'LEU',\n 'LYS', 'MET',... | [
[
"numpy.linalg.svd",
"numpy.array",
"numpy.linalg.det",
"numpy.mean"
]
] |
dmunozc/finpy | [
"93a0ad41f6f7938b5147398494054eb57c6645b0"
] | [
"finmarketpy_examples/events_examples.py"
] | [
"__author__ = 'saeedamen'\n\n# for logging\nimport pandas\nimport pytz\n\nfrom chartpy import Chart, Style\n\nfrom findatapy.market import Market, MarketDataGenerator, MarketDataRequest\nfrom findatapy.timeseries import Calculations\nfrom findatapy.util import LoggerManager\n\nfrom finmarketpy.economics import Even... | [
[
"pandas.DataFrame"
]
] |
Zensho/CS91-Proj | [
"876d5e977800af42382f8c6398eb62ccff202497"
] | [
"DL_Models/tf_models/Xception/Xception.py"
] | [
"import tensorflow as tf\nfrom config import config\nfrom utils.utils import *\nimport logging\nfrom DL_Models.tf_models.ConvNet import ConvNet\n\n\nclass XCEPTION(ConvNet):\n \"\"\"\n The Xception architecture. This is inspired by Xception paper, which describes how 'extreme' convolutions can be represented\... | [
[
"tensorflow.keras.layers.Activation",
"tensorflow.keras.layers.BatchNormalization",
"tensorflow.keras.layers.SeparableConv1D"
]
] |
hellotrik/trik | [
"142e0ef667802a5366e7ebca62e00633e2aa3813"
] | [
"examples/2x16x16x16x3_multi_classification.py"
] | [
"# -*- coding:utf-8 -*-\r\nimport numpy as np\r\nimport numpy as np\r\nimport matplotlib.pyplot as plt\r\nimport trik\r\n# 每类随机生成点的个数。\r\npoints_sum = 100\r\n# 调用paradox的数据生成器生成三螺旋的3类数据。\r\ndata = trik.yu.helical_data(points_sum, 3, max_radius=2*np.pi)\r\n# 组合数据。\r\nc_x = data[0][0] + data[1][0] + data[2][0]\r\nc_y... | [
[
"numpy.max",
"numpy.array",
"matplotlib.pyplot.contourf",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.plot",
"numpy.min",
"matplotlib.pyplot.show"
]
] |
XDUNZC/mmdetection_coco | [
"366777bdd40cd5d92a1e165bf20e6e062913f875"
] | [
"mmdet/models/detectors/test_mixins.py"
] | [
"import logging\nimport sys\n\nimport torch\n\nfrom mmdet.core import (bbox2roi, bbox_mapping, merge_aug_bboxes,\n merge_aug_masks, merge_aug_proposals, multiclass_nms)\n\nlogger = logging.getLogger(__name__)\n\nif sys.version_info >= (3, 7):\n from mmdet.utils.contextmanagers import compl... | [
[
"torch.from_numpy"
]
] |
dsctt/PettingZoo | [
"b839259e961798cfc23b6f82c6ba0898b55cda60"
] | [
"pettingzoo/test/render_test.py"
] | [
"import random\n\nimport numpy as np\n\n\ndef collect_render_results(env, mode):\n results = []\n\n env.reset()\n for i in range(5):\n if i > 0:\n for agent in env.agent_iter(env.num_agents // 2 + 1):\n obs, reward, done, info = env.last()\n if done:\n ... | [
[
"numpy.flatnonzero"
]
] |
Vatican-X-Formers/tensor2tensor | [
"103baef53d539a90f5b478ac590b9b1d79ecb756"
] | [
"tensor2tensor/data_generators/imagenet.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Tensor2Tensor Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requir... | [
[
"tensorflow.compat.v1.equal",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.reduce_sum",
"tensorflow.compat.v1.to_float",
"tensorflow.compat.v1.constant",
"tensorflow.compat.v1.reshape",
"tensorflow.compat.v1.name_scope",
"tensorflow.compat.v1.greater_equal",
"tensorflow.... |
mmyers1/hatchet | [
"bed9127b479f7a1bed32392380777d426e1dfe62"
] | [
"src/hatchet/utils/cluster_bins.py"
] | [
"#!/usr/bin/python3\n\nimport os, shutil\nimport sys\nimport math\nimport copy\nimport numpy as np\n\nfrom .ArgParsing import parse_cluster_bins_args\nfrom . import Supporting as sp\n\n\ndef main(args=None):\n sp.log(msg=\"# Parsing and checking input arguments\\n\", level=\"STEP\")\n args = parse_cluster_bin... | [
[
"numpy.random.seed",
"numpy.array",
"numpy.argmin"
]
] |
ASGuard-UCI/ld-metric | [
"87a52ca8cf11d2b8675d7504f9b4ac073addd984"
] | [
"scnn/model.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision.models as models\n\n\nclass SCNN(nn.Module):\n def __init__(\n self,\n input_size,\n ms_ks=9,\n pretrained=True,\n ):\n \"\"\"\n Argument\n ms_ks: kern... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.Softmax",
"torch.nn.Sigmoid",
"torch.nn.AvgPool2d",
"torch.nn.functional.interpolate",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.tensor",
"torch.nn.BCELoss",
"torch.nn.Drop... |
mattiasu96/recsys-challenge-2021-twitter | [
"80b78050739a93165cbaaf256bd13932582a8930"
] | [
"train_NN_parametric_class.py"
] | [
"from sklearn.metrics import average_precision_score, log_loss\nfrom sklearn.model_selection import train_test_split\nimport dask.dataframe as dd\nimport os, sys\nimport time\nimport RootPath\nfrom Scripts.utilities import start_cluster\nimport tensorflow as tf\nfrom tensorflow.keras.models import Sequential\nfrom ... | [
[
"tensorflow.keras.metrics.AUC",
"numpy.save",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Dropout",
"numpy.finfo",
"sklearn.metrics.average_precision_score",
"sklearn.metrics.log_loss",
"tensorflow.keras.layers.experimental.preprocessing.Normalization",
"tensorflo... |
MichielCottaar/mcot.core | [
"de00c15b946a99a048694f3d8b6ad822a835b299",
"de00c15b946a99a048694f3d8b6ad822a835b299"
] | [
"mcot/core/_scripts/split/run.py",
"mcot/core/_scripts/function/normalize.py"
] | [
"#!/usr/bin/env python\n\"\"\"Run part of the voxel-wise job\"\"\"\nfrom loguru import logger\nimport nibabel as nib\nfrom fsl.data.image import addExt\nfrom subprocess import run as srun\nimport numpy as np\nfrom typing import Sequence, Tuple\nimport string\nimport itertools\nimport tempfile\nimport sys\n\n\ndef g... | [
[
"numpy.where",
"numpy.linspace",
"numpy.log"
],
[
"numpy.concatenate",
"numpy.std",
"numpy.diag"
]
] |
obi-wan76/webbpsf | [
"ca3a3b6c26d4c263b906f29fb06e5f6d9b1e9a02"
] | [
"webbpsf/webbpsf_core.py"
] | [
"\"\"\"\n============\nWebbPSF Core\n============\n\nAn object-oriented modeling system for the JWST instruments.\n\nClasses:\n * SpaceTelescopeInstrument\n * JWInstrument\n * MIRI\n * NIRCam\n * NIRSpec\n * NIRISS\n * FGS\n\nWebbPSF makes use of python's ``logging`` facility for log me... | [
[
"numpy.max",
"numpy.array",
"numpy.ceil",
"numpy.reshape",
"numpy.asarray",
"numpy.round",
"numpy.min",
"numpy.mean",
"numpy.identity",
"numpy.remainder",
"numpy.arange",
"numpy.arctan2",
"numpy.sqrt",
"numpy.isscalar",
"numpy.meshgrid",
"numpy.mod"
... |
robert-s-lee/Keras-3D-Image-Classification | [
"8f7173df8ce3780d7be049947f8e0323b53b316d"
] | [
"train.py"
] | [
"\"\"\"\nTitle: 3D Image Classification from CT Scans\nAuthor: [Hasib Zunair](https://twitter.com/hasibzunair)\nDate created: 2020/09/23\nLast modified: 2020/09/23\nDescription: Train a 3D convolutional neural network to predict presence of pneumonia.\n\"\"\"\n\"\"\"\n## Introduction\nThis example will show the ste... | [
[
"tensorflow.keras.callbacks.TensorBoard",
"tensorflow.keras.utils.get_file",
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.Model",
"tensorflow.keras.layers.BatchNormalization",
"numpy.c... |
DefTruth/landmarksaug | [
"71d978a062e4a7c8fe90ca62c8dff109ea7718e7"
] | [
"torchlm/metrics/metrics.py"
] | [
"import numpy as np\nfrom scipy.integrate import simps\nfrom typing import List, Tuple\n\n__all__ = [\"nme\", \"fr_and_auc\"]\n\n\ndef nme(lms_pred: np.ndarray, lms_gt: np.ndarray, norm: float) -> float:\n \"\"\"\n :param lms_pred: (n,2) predicted landmarks.\n :param lms_gt: (n,2) ground truth landmarks.\n... | [
[
"scipy.integrate.simps",
"numpy.linalg.norm",
"numpy.arange",
"numpy.count_nonzero"
]
] |
taiga4112/pDESy | [
"ff2a77a3f7ad1714960dfabfcb977279a0b53d09"
] | [
"pDESy/model/component.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom .base_component import BaseComponent\nimport numpy as np\n\n\nclass Component(BaseComponent):\n \"\"\"Component\n Component class for expressing target product.\n This class is implemented from BaseComponent.\n\n Args:\n name (str):\n ... | [
[
"numpy.random.seed",
"numpy.random.rand"
]
] |
qarik-hanrattyjen/apache-airflow-backport-providers-google-2021.3.3 | [
"630dcef73e6a258b6e9a52f934e2dd912ce741f8"
] | [
"venv/lib/python3.9/site-packages/google/cloud/bigquery_storage_v1/reader.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 ... | [
[
"pandas.DataFrame",
"pandas.Series",
"pandas.concat"
]
] |
sandialabs/OperonSEQer | [
"62622204b646ff86dbb11f35d04bb486ef2fdb2f"
] | [
"OperonSEQer/mergepreds.py"
] | [
"import csv\nimport sys\nimport configargparse\nimport pandas as pd\n\n\nif __name__ == '__main__':\n\n\tif len (sys.argv) < 5 :\n\t\tprint(\"Usage: python mergepred2021.py -f file\\nNumber of arguements is \" + str(len(sys.argv)))\n\t\tsys.exit (1)\n\n\tp = configargparse.ArgParser(description='this script merges ... | [
[
"pandas.DataFrame",
"pandas.merge"
]
] |
jiangtaoo2333/mmpose | [
"00e12ddc224b492e9c903df96d09aa04c3f2a5f3"
] | [
"mmpose/models/heads/topdown_heatmap_base_head.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nfrom abc import ABCMeta, abstractmethod\n\nimport numpy as np\nimport torch.nn as nn\n\nfrom mmpose.core.evaluation.top_down_eval import keypoints_from_heatmaps\n\n\nclass TopdownHeatmapBaseHead(nn.Module):\n \"\"\"Base class for top-down heatmap heads.\n\n Al... | [
[
"numpy.prod",
"numpy.array",
"numpy.ones",
"numpy.zeros"
]
] |
koursaros-ai/bert | [
"a37324c394c33b67385fb309523b859f1465f842"
] | [
"optimization.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team 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# Unl... | [
[
"tensorflow.zeros_initializer",
"tensorflow.multiply",
"tensorflow.group",
"tensorflow.contrib.tpu.CrossShardOptimizer",
"tensorflow.gradients",
"tensorflow.constant",
"tensorflow.train.polynomial_decay",
"tensorflow.sqrt",
"tensorflow.train.get_or_create_global_step",
"ten... |
HuangStomach/machine-learning | [
"47689469c431e2a833437b38832d3fdceda7b2b2"
] | [
"introduction_to_machine_learning_with_python/2.3/two_moons_random_forest.py"
] | [
"import matplotlib\nmatplotlib.use('MacOSX')\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport mglearn\n\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.datasets import make_moons\n\nX, y = make_moons(n_samples=100, noise=0.25, random_state=3)\nfrom sklearn.model_s... | [
[
"matplotlib.use",
"sklearn.ensemble.RandomForestClassifier",
"matplotlib.pyplot.subplots",
"sklearn.model_selection.train_test_split",
"matplotlib.pyplot.show",
"sklearn.datasets.make_moons"
]
] |
Qidian213/NAIC2019 | [
"23e05a8a096168ccfa4d1743467fdf78ffcaabba"
] | [
"data/datasets/eval_reid.py"
] | [
"# encoding: utf-8\n\"\"\"\n@author: liaoxingyu\n@contact: sherlockliao01@gmail.com\n\"\"\"\nimport os\nimport numpy as np\nimport shutil\nimport cv2\nimport json\nimport shutil\n\ndef eval_func(distmat, q_pids, g_pids, q_camids, g_camids,q_img_paths, g_img_paths, max_rank=210):\n \"\"\"Evaluation with market15... | [
[
"numpy.asarray",
"numpy.mean",
"numpy.any",
"numpy.invert",
"numpy.argsort"
]
] |
Capgemini-Invent-France/CarbonAI | [
"ef9ccf2c6460e09241304f5618f9a6d082c3f65e"
] | [
"carbonai/power_meter.py"
] | [
"#!/usr/bin/python\n# -*- coding: utf-8 -*-\n\"\"\"\nPowerMeter\n---------\nMain Python class or entrypoint to monitor the power consumption of\nan algorithm.\n\"\"\"\n\n__all__ = [\"PowerMeter\"]\n\nimport datetime\nimport getpass\nimport json\nimport logging\nimport os\nimport shutil\nimport sys\nimport traceback... | [
[
"pandas.DataFrame",
"pandas.read_csv",
"pandas.read_excel"
]
] |
maxim-borisyak/pyca | [
"2da2e25ba5ba47e1e5f70a31a2a4af4ecde01834"
] | [
"setup.py"
] | [
"\"\"\"\n Py Cellular Automata.\n\"\"\"\n\nfrom setuptools import setup, find_packages, Extension\n\nfrom codecs import open\nimport os\nimport os.path as osp\nimport numpy as np\n\ndef get_includes():\n env = os.environ\n\n includes = []\n\n for k in ['CPATH', 'C_INCLUDE_PATH', 'INCLUDE_PATH']:\n if k in en... | [
[
"numpy.get_include"
]
] |
Ugness/CIPS_SR | [
"abce872f5bc1b84afb9634a7dd1991e8c74d7616"
] | [
"calculate_fid.py"
] | [
"import argparse\nimport os\n\nimport torch\nimport torchvision\nfrom torch_fidelity import calculate_metrics\nimport numpy as np\n\nimport model\nfrom dataset import ImageDataset\nfrom tensor_transforms import convert_to_coord_format\n\n\n@torch.no_grad()\ndef calculate_fid(model, fid_dataset, bs, size, num_batche... | [
[
"torch.no_grad",
"torch.randn",
"torch.load"
]
] |
kashif/agents | [
"104a68bf9e61756f173452e1a339b4ddc121e8c5"
] | [
"agents/tools/loop.py"
] | [
"# Copyright 2017 The TensorFlow Agents 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 appli... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.shape",
"tensorflow.get_default_graph",
"tensorflow.cond",
"tensorflow.where",
"tensorflow.reduce_any",
"tensorflow.Variable",
"tensorflow.gfile.MakeDirs",
"tensorflow.placeholder",
"tensorflow.control_dependencies",
"tensorfl... |
varunjha089/computerscience | [
"bd90079e4a8701e92c9f88f598bfa86203b6cbb7"
] | [
"Labs/AI and Machine Learning/Cognitive Toolkit/resources/cntk2images.py"
] | [
"\n#\n\nfrom os import walk\nfrom PIL import Image\nimport numpy as np\n\ninputFile = ''\n\nwith open(inputFile) as f:\n images = f.readlines()\n\nimages = [line.strip() for line in images]\n\nw, h = 28, 28\n\nimgcnt = 0;\n\n\nfor imageline in images:\n\n\tdataparts = imageline.split(\" |features \")\n\timagedat... | [
[
"numpy.zeros"
]
] |
BEPb/Python-100-days | [
"8f846962cd45342aa2490ec2e86df358ae0ef281"
] | [
"Game_AI_and_Reinforcement_Learning/ConnectX/v1/encoder_decoder_c4.py"
] | [
"\"\"\"\nPython 3.9 список функций\nНазвание файла encoder_decoder_c4.py\n\nсписок функций для кодирования / декодирования класса платы Connect4 для ввода / интерпретации в нейронную сеть\n\nVersion: 0.1\nAuthor: Andrej Marinchenko\nDate: 2021-12-20\n\"\"\"\n#!/usr/bin/env python\n\nimport numpy as np\nfrom connect... | [
[
"numpy.zeros"
]
] |
ripplesaround/ETDI_NL | [
"4b77444d8ef5dee1f020e4d30e6cfc24fb5945c9"
] | [
"proposed/models/modeling.py"
] | [
"\"\"\" Modeling layer Implementation \"\"\"\r\n\r\nimport numpy as np\r\nimport torch\r\nimport torch.nn as nn\r\nimport torch.nn.functional as F\r\nfrom torch.nn.parameter import Parameter\r\n\r\n\r\ndef call_bn(bn, x):\r\n return bn(x)\r\n\r\n\r\nclass NoiseModel(nn.Module):\r\n def __init__(self, num_clas... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.cat",
"torch.nn.functional.avg_pool2d",
"torch.nn.BatchNorm2d",
"torch.nn.init.kaiming_normal_",
"torch.nn.Conv2d",
"torch.nn.functional.dropout2d",
"torch.eye",
"torch.nn.functional.relu",
"torch.nn.functional.max_pool2d",
... |
weigq/pytorch-cyclegan-pix2pix | [
"ef49a77964aaefdb1b95067ec50426f15b7137e1",
"ef49a77964aaefdb1b95067ec50426f15b7137e1"
] | [
"options/base_options.py",
"models/test_model.py"
] | [
"\"\"\"\nrunning basic options\n\"\"\"\n\nimport argparse\nimport os\nfrom util import util\nimport torch\n\n\nclass BaseOptions():\n def __init__(self):\n self.parser = argparse.ArgumentParser()\n self.initialized = False\n self.opt = None\n\n def initialize(self):\n self.parser.a... | [
[
"torch.cuda.set_device"
],
[
"torch.autograd.Variable"
]
] |
ssm-jax/ssm-book | [
"f3bfa29a1c474b7dc85792a563df0f29736a44c6"
] | [
"_build/jupyter_execute/kevin.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# # Kevin's noodling\n# \n# In this chapter, we do blah.\n# For more details, see [](sec:bar), where we discuss bar.\n# \n# \n# ## Python\n\n# In[1]:\n\n\nfrom matplotlib import rcParams, cycler\nimport matplotlib.pyplot as plt\nimport numpy as np\nplt.ion()\n\n\n# In[2]:... | [
[
"numpy.array",
"matplotlib.pyplot.ion",
"numpy.random.seed",
"numpy.random.randn",
"matplotlib.pyplot.subplots",
"numpy.linspace",
"numpy.logspace"
]
] |
AI-confused/Tianchi_Similarity | [
"9c3e76b7ac19f07e948d68270b0b747de92a413f"
] | [
"run_bert.py"
] | [
"from __future__ import absolute_import\nimport argparse\nimport csv\nimport logging\nimport os\nimport random\nimport sys\nfrom io import open\nimport pandas as pd\nimport numpy as np\nimport torch\nimport time\n# from scipy.stats import spearmanr\nimport collections\nimport torch.nn as nn\nfrom collections import... | [
[
"numpy.concatenate",
"torch.cuda.manual_seed_all",
"torch.utils.data.RandomSampler",
"torch.isnan",
"numpy.random.seed",
"torch.norm",
"torch.no_grad",
"torch.utils.data.SequentialSampler",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.is_available",
"... |
KiwiCodesStuff/FairMOT | [
"8e6f5c6a82f15bf951f35bbd8592e558938dfd2f"
] | [
"src/track.py"
] | [
"# ------------------------------------------------------------------------------\n# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License.\n# ------------------------------------------------------------------------------\n\nfrom __future__ import absolute_import\nfrom __future... | [
[
"numpy.sum",
"numpy.dot",
"numpy.asarray",
"torch.from_numpy"
]
] |
cuhksz-nlp/RE-TaMM | [
"3de913b778ca0fa9ac35ff04244e45c61c1a38df"
] | [
"data_utils.py"
] | [
"import os\nimport json\nimport logging\nimport numpy as np\nimport torch\nfrom torch.utils.data import Dataset\nfrom collections import defaultdict\nfrom dep_parser import DepInstanceParser\n\ndef change_word(word):\n if \"-RRB-\" in word:\n return word.replace(\"-RRB-\", \")\")\n if \"-LRB-\" in word... | [
[
"torch.tensor",
"numpy.zeros"
]
] |
zdanial/Bayesian-Optimization | [
"a4779e992da15d21fa3fc425293cfb1f2621f81f"
] | [
"example/example_remote.py"
] | [
"import os\nimport shutil\nimport subprocess\nimport time\n\nimport numpy as np\nimport requests\n\ndata = {\n \"search_param\": {\n \"emissivity\": {\"type\": \"r\", \"range\": [0.95, 1], \"N\": 2, \"precision\": 2},\n \"offset\": {\"type\": \"r\", \"range\": [-10, 10], \"N\": 2, \"precision\": 2}... | [
[
"numpy.sum",
"numpy.random.randn",
"numpy.sqrt"
]
] |
pacovi/jira-agile-metrics | [
"0c8810a8348ea21145db71f7e3681adc65a6b02c"
] | [
"jira_agile_metrics/calculators/ageingwip.py"
] | [
"import logging\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\n\nfrom ..calculator import Calculator\nfrom ..utils import set_chart_style\n\nfrom .cycletime import CycleTimeCalculator\n\nlogger = logging.getLogger(__name__)\n\nclass AgeingWIPChartCalculator(Calcula... | [
[
"pandas.isnull",
"matplotlib.pyplot.close",
"matplotlib.pyplot.subplots",
"pandas.Timestamp.now",
"pandas.concat"
]
] |
RustedSwords/HackTheMountains | [
"28b7853674e9ff1694f74841c5963c34be251680"
] | [
"drowsiness_detector.py"
] | [
"import numpy as np\nimport imutils\nimport time\nimport timeit\nimport dlib\nimport cv2\nimport matplotlib.pyplot as plt\nfrom scipy.spatial import distance as dist\nfrom imutils.video import VideoStream\nfrom imutils import face_utils\nfrom threading import Thread\nfrom threading import Timer\nfrom check_cam_fps ... | [
[
"numpy.random.seed",
"scipy.spatial.distance.euclidean"
]
] |
DrMichaelCornish/PyBaMM | [
"a31e2095600bb92e913598ac4d02b2b6b77b31c1"
] | [
"pybamm/simulation.py"
] | [
"#\n# Simulation class\n#\nimport pickle\nimport pybamm\nimport numpy as np\nimport copy\nimport warnings\nimport sys\n\n\ndef is_notebook():\n try:\n shell = get_ipython().__class__.__name__\n if shell == \"ZMQInteractiveShell\": # pragma: no cover\n # Jupyter notebook or qtconsole\n ... | [
[
"numpy.round",
"numpy.diff"
]
] |
anjunhu/flakes | [
"1a4a50a7c36b6cd26283e2eede1117ac0995e348"
] | [
"tis-OpenCV.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Nov 21 09:46:46 2016\n\nSample for tisgrabber to OpenCV Sample 2\n\nOpen a camera by name\nSet a video format hard coded (not recommended, but some peoples insist on this)\nSet properties exposure, gain, whitebalance\n\"\"\"\nimport ctypes as C\nimport tisgrabber as ... | [
[
"numpy.ones"
]
] |
henryL7/fastNLP | [
"7255128dec92a2f09a6f16c708d67b608f22529e"
] | [
"fastNLP/action/trainer.py"
] | [
"import _pickle\n\nimport numpy as np\nimport torch\n\nfrom fastNLP.action.action import Action\nfrom fastNLP.action.action import RandomSampler, Batchifier\nfrom fastNLP.action.tester import POSTester\nfrom fastNLP.modules.utils import seq_mask\n\n\nclass BaseTrainer(Action):\n \"\"\"Base trainer for all traine... | [
[
"numpy.square",
"torch.zeros",
"numpy.array",
"numpy.random.rand",
"numpy.matmul",
"torch.autograd.Variable",
"torch.cuda.is_available",
"torch.Tensor",
"torch.nn.CrossEntropyLoss"
]
] |
akshaykurmi/rl | [
"5575695c9af7f1981753fbb21855e5cde617d123"
] | [
"rl/agents/vpg_gae.py"
] | [
"import numpy as np\nimport tensorflow as tf\n\nfrom rl.replay_buffer import ReplayField, OnePassReplayBuffer, Advantage, RewardToGo\nfrom rl.utils import GradientAccumulator, MeanAccumulator, tf_standardize\n\n\nclass VPGGAE:\n def __init__(self, env, policy_fn, vf_fn, lr_policy, lr_vf, gamma, lambda_, vf_updat... | [
[
"tensorflow.size",
"tensorflow.GradientTape",
"tensorflow.expand_dims",
"tensorflow.function",
"tensorflow.squeeze",
"tensorflow.keras.optimizers.Adam"
]
] |
xwx1989119/zipline | [
"5cb37da2cf77b811fa7bfc0107619582008de55d"
] | [
"zipline/data/bundles/csvdir.py"
] | [
"\"\"\"\nModule for building a complete dataset from local directory with csv files.\n\"\"\"\nimport os\nimport sys\n\nfrom logbook import Logger, StreamHandler\nfrom numpy import empty\nfrom pandas import DataFrame, read_csv, Index, Timedelta, NaT\nfrom trading_calendars import register_calendar_alias\n\nfrom zipl... | [
[
"pandas.DataFrame",
"pandas.Timedelta"
]
] |
kahoooo/athena-public | [
"583aee106677cba7fa5ea4e3689e2cfb81796e25"
] | [
"tst/regression/scripts/tests/gr/hydro_shocks_hlle.py"
] | [
"# Test script for relativistic hydro shock tubes in GR with HLLE\n\n# Modules\nimport logging\nimport numpy as np\nimport sys\nimport scripts.utils.athena as athena\nimport scripts.utils.comparison as comparison\nsys.path.insert(0, '../../vis/python')\nimport athena_read # noqa\nathena_read.check_nan_flag = True\... | [
[
"numpy.isnan"
]
] |
phuongnm-bkhn/OpenNMT-py | [
"554a826139f1bfc55f4ea6a3e7491858c2afec4c"
] | [
"onmt/decoders/combined_transformer_rnn.py"
] | [
"\"\"\"\nImplementation of \"Attention is All You Need\"\n\"\"\"\n\nimport torch\nimport torch.nn as nn\n\nfrom onmt.decoders.decoder import DecoderBase, RNNDecoderBase\nfrom onmt.encoders.combined_transformer_rnn import EmbeddingSkipped\nfrom onmt.models.stacked_rnn import StackedLSTM, StackedGRU\nfrom onmt.module... | [
[
"torch.zeros",
"torch.nn.Dropout",
"torch.nn.LayerNorm",
"torch.stack",
"torch.gt",
"torch.ones"
]
] |
spider-specimens/waibao-spider | [
"4b7623df3cf56cd33754fcee49149637f7409b2e"
] | [
"src/dakun.py"
] | [
"'''\n 大鲲 爬虫\n'''\nimport requests\nfrom headers import Headers\nfrom bs4 import BeautifulSoup\nimport time\nimport re\nimport numpy as np\nfrom storage import Storage\n\nheaders = Headers()\nstorage = Storage()\n\n\nclass DakunSpider(object):\n\n # 获取列表数据\n def fetch_list(self, _type, page):\n url ... | [
[
"numpy.random.rand"
]
] |
Nhat-Thanh/SRCNN-TF | [
"9e9d7ae8f75d1c8a33b470f49d02c8f2ce6a134b"
] | [
"utils/dataset.py"
] | [
"from utils.common import *\nimport tensorflow as tf\nimport numpy as np\nimport os\n\nclass dataset:\n def __init__(self, dataset_dir, subset):\n self.dataset_dir = dataset_dir\n self.subset = subset\n self.data = tf.convert_to_tensor([])\n self.labels = tf.convert_to_tensor([])\n ... | [
[
"numpy.array",
"tensorflow.convert_to_tensor",
"numpy.load",
"numpy.save",
"numpy.arange",
"numpy.absolute"
]
] |
awnonbhowmik/2D-Diophantine-Encoder | [
"734e2e5aeccd66f213f60a51ce1ae22b72bba59b"
] | [
"main.py"
] | [
"from collections import abc\nfrom sympy.solvers.diophantine.diophantine import base_solution_linear\nfrom random import randint\nfrom numpy import gcd\n\n\ndef encrypt(msg):\n ascii_lst = [ord(c) for c in msg]\n print(\"\\nASCII List: {}\".format(ascii_lst))\n\n a, b = randint(1, 10), randint(1, 10)\n\n ... | [
[
"numpy.gcd"
]
] |
willyspinner/High-Performance-Face-Recognition | [
"c5caad61be97fd20f9c47a727278ff938dc5cc8f"
] | [
"src/Look Across Elapse- Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition.TensorFlow/network.py"
] | [
"import tensorflow as tf \r\nimport numpy as np \r\nimport layers2 as L \r\nL.set_gpu('0')\r\nimport modeleag as M \r\n\r\nIMG_SIZE = 128\r\nAGE_CATEGORY = 10\r\nZ_DIM = 50\r\n\r\nclass EncoderNet(M.Model):\r\n\tdef initialize(self):\r\n\t\t# should modify the network structure for better training\r\n\t\tself.c1 = ... | [
[
"tensorflow.abs",
"tensorflow.image.total_variation",
"tensorflow.concat",
"tensorflow.GradientTape",
"tensorflow.sigmoid",
"tensorflow.ones_like",
"tensorflow.random.uniform",
"tensorflow.reshape",
"tensorflow.zeros_like",
"tensorflow.tile",
"tensorflow.nn.tanh",
"... |
itsliupeng/read_Detectron.pytorch | [
"aac793a459484c301cb203d9041f0de71dd00aa2"
] | [
"tools/infer_video_mask_kp.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport argparse\nimport distutils.util\nimport os\nimport sys\nimport pprint\nimport subprocess\nfrom collections import defaultdict\nfrom six.moves import xrange\n\n# Use a non-interactive backend\nim... | [
[
"matplotlib.use",
"torch.cuda.is_available",
"torch.load"
]
] |
LeiaInc/pyrender | [
"f933ba1d96a75fb4ede325a7f6d4b7667bf2f917"
] | [
"pyrender/mesh.py"
] | [
"\"\"\"Meshes, conforming to the glTF 2.0 standards as specified in\nhttps://github.com/KhronosGroup/glTF/tree/master/specification/2.0#reference-mesh\n\nAuthor: Matthew Matl\n\"\"\"\nimport copy\n\nimport numpy as np\nimport trimesh\n\nfrom .primitive import Primitive\nfrom .constants import GLTF\nfrom .material i... | [
[
"numpy.array",
"numpy.linalg.norm",
"numpy.minimum",
"numpy.mean",
"numpy.diff",
"numpy.repeat",
"numpy.maximum"
]
] |
sailingfree/Python-VPP | [
"c4730494ae86dc78260ccd94fe05c85141760360"
] | [
"test/Resistance.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n__author__ = \"Marin Lauber\"\n__copyright__ = \"Copyright 2020, Marin Lauber\"\n__license__ = \"GPL\"\n__version__ = \"1.0.1\"\n__email__ = \"M.Lauber@soton.ac.uk\"\n\nimport numpy as np\nfrom src.HydroMod import HydroMod\nfrom src.YachtMod import Yacht, Keel, Ru... | [
[
"numpy.linspace"
]
] |
leRoderic/VA_19 | [
"86b02e38c30a2163cb7dae1f52f551e6d30f35f7"
] | [
"P5/LM_filters.py"
] | [
"'''\nThe Leung-Malik (LM) Filter Bank, implementation in python\n\nT. Leung and J. Malik. Representing and recognizing the visual appearance of\nmaterials using three-dimensional textons. International Journal of Computer\nVision, 43(1):29-44, June 2001.\n\nReference: http://www.robots.ox.ac.uk/~vgg/research/texcl... | [
[
"numpy.array",
"numpy.sin",
"numpy.dot",
"numpy.reshape",
"numpy.zeros",
"numpy.exp",
"numpy.arange",
"numpy.sqrt",
"numpy.cos",
"numpy.meshgrid"
]
] |
godzilla-but-nicer/boolmininfo | [
"50281b1a9d8a0718815910edf4123d67c532aa66"
] | [
"boolmininfo/eca/plot_eca_pid_correlations.py"
] | [
"import numpy as np\nimport pandas as pd\nimport seaborn as sns\nimport matplotlib.pyplot as plt\n\n# load all of the neccesary dataframes\nwedge = pd.read_csv(snakemake.config['eca_decompositions']['wedge'])\nccs = pd.read_csv(snakemake.config['eca_decompositions']['ccs'])\nimin = pd.read_csv(snakemake.config['eca... | [
[
"pandas.isnull",
"numpy.array",
"numpy.triu_indices",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.pyplot.title",
"matplotlib.pyplot.xlabel",
"numpy.mean",
"matplotlib.pyplot.figure",
"numpy.random.uniform",
"matplotlib.pyplot.ylabel",
"pandas.read_c... |
AnalystSubranjit/h2o-3 | [
"b34e50ab81970ebd999eb8236de1580219293cdb"
] | [
"h2o-py/tests/testdir_algos/gbm/pyunit_gbm_monotone_synthetic.py"
] | [
"from h2o.estimators.xgboost import *\nfrom h2o.estimators.gbm import *\nfrom tests import pyunit_utils\nimport numpy as np\n\n\ndef train_models(iter):\n print(\"Iteration %s\" % iter)\n \n number_of_dpoints = 1000\n x1_positively_correlated_with_y = np.random.random(size=number_of_dpoints)\n x2_neg... | [
[
"numpy.random.normal",
"numpy.sin",
"numpy.cos",
"numpy.random.random",
"numpy.column_stack"
]
] |
dendisuhubdy/ALAE | [
"471301aa671928748ffbd9cc191278e1ec8f29c4"
] | [
"dataset_preparation/prepare_mnist_tfrecords.py"
] | [
"# Copyright 2019-2020 Stanislav Pidhorskyi\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... | [
[
"tensorflow.python_io.TFRecordOptions",
"tensorflow.train.Int64List",
"numpy.asarray",
"tensorflow.python_io.TFRecordWriter",
"numpy.stack"
]
] |
TinghuiWang/pymrt | [
"e096d712b897ebf8483c95a726933ee8b3d09432"
] | [
"pymrt/performance/ar.py"
] | [
"\"\"\"Event-based Performance Metrics\n\nThis file implements event-based performance metrics for activity recognition.\n\nReference:\n\n - Minnen, David, Tracy Westeyn, Thad Starner, J. Ward, and Paul Lukowicz.\n Performance metrics and evaluation issues for continuous activity\n recognition. Perform... | [
[
"numpy.empty",
"numpy.dtype",
"numpy.zeros"
]
] |
santhoshkolloju/squash-generation | [
"3a4728e40bf801bb72497a8b24a37e7443c36d65"
] | [
"squash/filter.py"
] | [
"import numpy as np\nimport json\nimport pickle\nimport random\nimport sys\nimport os\nimport spacy\n\nfrom collections import defaultdict\n\nfrom squad_eval_utils import (\n f1_metric,\n exact_match_metric,\n metric_max_over_candidates,\n recall_metric,\n precision_metric,\n normalize\n)\n\nnlp =... | [
[
"numpy.max",
"numpy.ceil",
"numpy.argmax"
]
] |
juandados/gait-inference | [
"19d29919be5cbf984ddbf76da442c59e07bb32bc"
] | [
"code/utils.py"
] | [
"import os\nimport datetime\nimport matplotlib.pyplot as plt\nimport cv2\nimport pandas as pd\nimport numpy as np\nimport xml.etree.ElementTree as et\nimport re\n\nfrom time import time\nfrom keras.preprocessing.image import ImageDataGenerator, Iterator, array_to_img, img_to_array, load_img\nfrom keras.models impor... | [
[
"numpy.max",
"matplotlib.pyplot.text",
"numpy.array",
"numpy.empty",
"numpy.zeros",
"matplotlib.patches.Rectangle",
"pandas.concat",
"pandas.DataFrame",
"numpy.exp",
"numpy.mean",
"matplotlib.pyplot.figure",
"numpy.vstack",
"numpy.flip",
"pandas.Series",
... |
pjavia/GAN | [
"3e8dfac34b5a32818286310ea96706c93494565a"
] | [
"dcgan/cifar.py"
] | [
"import cPickle\nimport numpy as np\nimport cv2\n\nrepository = []\n\nfor i in range(1, 6):\n\n name = 'cifar/data_batch_'+str(i)\n\n with open(name, 'rb') as fo:\n data = cPickle.load(fo)\n\n\n collect = data.get('data')\n\n\n for j in collect:\n red = []\n green = []\n blue... | [
[
"numpy.array"
]
] |
hereagain-Y/DeepTCR_COVID19 | [
"da7ff94ed94d6370c9585fdf9f32e4f1140d54c5"
] | [
"scripts/demographics/icu_admit.py"
] | [
"\"\"\" Demographics - Fraction of paitents admitted to the ICU in the NIH/NIAID cohort\"\"\"\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom matplotlib.colors import LinearSegmentedColormap\nimport matplotlib\nmatplotlib.rc('font', family='sans-serif')\nplt.... | [
[
"numpy.array",
"pandas.DataFrame",
"numpy.sum",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"matplotlib.rc",
"pandas.pivot",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.style.use",
"numpy.hstack",
"pandas.read_csv",
"numpy.unique"
]
] |
LuCeHe/trellisnet | [
"ec1de0a5ee09ef5a4c5bca4c83456dec8cbdf4c8"
] | [
"TrellisNet/char_PTB/utils.py"
] | [
"import unidecode\nimport torch\nfrom collections import Counter\nimport observations\nimport os\nimport pickle\nimport sys\nsys.path.append(\"../\")\nfrom model import *\n\n\ndef read_file(filename):\n file = unidecode.unidecode(open(filename).read())\n return file, len(file)\n\n\nclass Dictionary(object):\n... | [
[
"torch.save"
]
] |
RejectHumanity/LIBS_library | [
"d655743d82467c13ae1a95c01599c97f0d9c8069"
] | [
"src/eval/dummies.py"
] | [
"from sklearn.base import BaseEstimator, RegressorMixin\nfrom sklearn.utils import check_array, check_X_y\nfrom sklearn.utils.validation import check_is_fitted\n\nclass Average_Dummy(BaseEstimator, RegressorMixin):\n\n def __init__(self, *args, **kwargs):\n pass\n \n\n def fit(self, X, y, *args, **kwargs)... | [
[
"sklearn.utils.check_array"
]
] |
tavuong/covid-data-kit | [
"d1d9eec1efaa293d98d4b85a8d5fef9b4e0b2f6a"
] | [
"covid19-datakit.py"
] | [
"import sys, getopt\nimport matplotlib.pyplot as plt\nimport matplotlib.dates\nfrom datetime import datetime\nfrom datetime import date\nimport csv\nfrom lib.tavuong_visual import *\nfrom lib.user_visual import *\n\ndef main(argv):\n# --------------------------------------\n# ARGUMENT Processing\n inputfile = ''... | [
[
"matplotlib.pyplot.subplots"
]
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.