repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
kparasch/xfields | [
"fd288588ee269bf0d18da24ef83f5f925e6c5e4f"
] | [
"xfields/beam_elements/electronlens_interpolated.py"
] | [
"import numpy as np\n\nimport xobjects as xo\nimport xtrack as xt\n\nfrom ..fieldmaps import TriLinearInterpolatedFieldMap\nfrom ..fieldmaps import TriCubicInterpolatedFieldMap\n\nfrom ..fieldmaps import TriCubicInterpolatedFieldMapData\nfrom ..fieldmaps import TriLinearInterpolatedFieldMapData\nfrom ..general impo... | [
[
"numpy.zeros"
]
] |
r09491/poorscrum | [
"cdbbc0db03fde842f546093f46e70d03a105bbbd"
] | [
"scripts/poorscrum_burndown.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n__author__ = \"sepp.heid@t-online.de\"\n__doc__ = \"\"\" \"\"\"\n\nimport argparse\nimport os\nimport sys\n\nfrom pptx import Presentation\nfrom pptx.exc import PackageNotFoundError\nfrom pptx.util import Inches\n\nfrom poorscrum import SPRINT_FILE, BURNDOWN_SAVE_N... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.close",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.bar"
]
] |
ingako/AOTrAdaBoost | [
"6e71e9ff7d0309c01a153ea928f9a46d3a67b093",
"6e71e9ff7d0309c01a153ea928f9a46d3a67b093"
] | [
"eval-bike-perf.py",
"plot-acc.py"
] | [
"#!/usr/bin/env python3\n\nimport os\nimport sys\nimport math\nimport pandas as pd\nimport numpy as np\nfrom dataclasses import dataclass\nfrom pprint import PrettyPrinter\n\nfrom scipy.stats import friedmanchisquare\n\ngenerator = \"bike-bk/bike-weekday-weekend\"\nbenchmark_list = [\"disable_transfer\",\n ... | [
[
"pandas.read_csv"
],
[
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"pandas.read_csv",
"matplotlib.pyplot.ticklabel_format"
]
] |
wavestate/wavestate-iirrational | [
"01d6dba8b2131fa2a099a74f17e6540f30cee606"
] | [
"src/wavestate/iirrational/v1/nyquist_move.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n# SPDX-License-Identifier: Apache-2.0\n# SPDX-FileCopyrightText: © 2021 Massachusetts Institute of Technology.\n# SPDX-FileCopyrightText: © 2021 Lee McCuller <mcculler@mit.edu>\n# NOTICE: authors should document their contributions in concisely in NOTICE\n# with deta... | [
[
"numpy.angle",
"numpy.exp"
]
] |
microsoft/archai | [
"50f70ccccf536466cc0370c8a63401e05dec33fd"
] | [
"scripts/plain_models/cifar_resnet/train_cifar100.py"
] | [
"# Copyright (c) Microsoft Corporation.\r\n# Licensed under the MIT license.\r\n\r\nimport torch\r\nfrom archai import cifar10_models\r\nfrom archai.common.trainer import Trainer\r\nfrom archai.common.config import Config\r\nfrom archai.common.common import common_init\r\nfrom archai.datasets import data\r\n\r\ndef... | [
[
"torch.device"
]
] |
Napuu/matalapaine | [
"84931e7b629be09b295c2c3def1cd15ae811f0c2"
] | [
"weather-data/lambda/dataset_processor.py"
] | [
"import boto3\nimport rasterio\nimport os\nimport numpy as np\nfrom osgeo import gdal\nfrom botocore.handlers import disable_signing\nfrom typing import List\nfrom datetime import datetime\n\nDATASET_TMP_PATH = \"/tmp/tmp.grib2\"\nGDAL_TMP_FILE = \"/tmp/temp.tiff\"\nFINAL_IMG = \"/tmp/final.jpeg\"\nNOAA_BUCKET = 'n... | [
[
"numpy.interp"
]
] |
margitantal68/sapimouse | [
"40b5ea6cf10c6f1d64b9dd0427d21138cc4f75e2"
] | [
"util/fcn.py"
] | [
"import os\r\nimport time\r\nimport numpy as np\r\nimport pandas as pd\r\nimport tensorflow.keras as keras\r\nfrom pathlib import Path\r\nfrom sklearn.ensemble import RandomForestClassifier\r\nfrom sklearn.preprocessing import LabelEncoder, OneHotEncoder \r\nfrom sklearn.model_selection import train_test_split\r\nf... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.layers.GlobalAveragePooling1D",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.Activation",
"tensorflow.keras.models.Model",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Dense",
"tensorflow.ker... |
yenlow/coursera_dl | [
"b092a290d5120b2dfeecce65fd9ae63df470adee"
] | [
"Sequence Models/utils.py"
] | [
"import numpy as np\n\ndef softmax(x):\n e_x = np.exp(x - np.max(x))\n return e_x / e_x.sum(axis=0)\n\ndef smooth(loss, cur_loss):\n return loss * 0.999 + cur_loss * 0.001\n\ndef print_sample(sample_ix, ix_to_char):\n txt = ''.join(ix_to_char[ix] for ix in sample_ix)\n txt = txt[0].upper() + txt[1:] ... | [
[
"numpy.max",
"numpy.zeros_like",
"numpy.dot",
"numpy.zeros",
"numpy.log",
"numpy.random.seed",
"numpy.copy",
"numpy.random.randn"
]
] |
slibby/PyAEZ | [
"fffba1028586c9d14a8c3a1377a12a05868b8403"
] | [
"code/EconomicSuitability.py"
] | [
"\r\n\"\"\"\r\nPyAEZ\r\nWritten by Thaileng Thol\r\n\r\nBETA version - under development and in testing phase\r\n\"\"\"\r\n\r\nimport numpy as np\r\nfrom scipy import stats\r\n\r\nclass EconomicSuitability(object):\r\n\r\n def __init__(self):\r\n self.crop_name_list = []\r\n self.net_revenue_list =... | [
[
"numpy.divide",
"numpy.array",
"numpy.zeros",
"scipy.stats.linregress",
"numpy.mean",
"numpy.amax",
"numpy.amin",
"numpy.all"
]
] |
check-spelling/webbpsf | [
"88d2915e623750dff8be4b9ddbdf15ed15285f4f"
] | [
"webbpsf/optics.py"
] | [
"import os\nimport poppy\nimport poppy.utils\nimport numpy as np\nimport matplotlib\nimport matplotlib.pyplot as plt\n\nfrom astropy.table import Table\nimport astropy.io.fits as fits\nimport astropy.units as units\n\nfrom scipy.interpolate import griddata, RegularGridInterpolator\nfrom scipy.ndimage import rotate\... | [
[
"matplotlib.pyplot.text",
"numpy.ones_like",
"numpy.argmin",
"numpy.where",
"numpy.sign",
"numpy.finfo",
"numpy.cos",
"numpy.deg2rad",
"scipy.interpolate.griddata",
"numpy.concatenate",
"numpy.full",
"numpy.sin",
"numpy.indices",
"scipy.poly1d",
"scipy.n... |
jeanne-ber/vicreg | [
"5e7b38f4586384bbb0d9a035352fab1d8f03b3b4"
] | [
"main_vicreg.py"
] | [
"# Copyright (c) Meta Platforms, Inc. and affiliates.\n# All rights reserved.\n\n# This source code is licensed under the license found in the\n# LICENSE file in the root directory of this source tree.\n\n\nfrom pathlib import Path\nimport argparse\nimport json\nimport math\nimport os\nimport sys\nimport time\n\nim... | [
[
"torch.nn.Linear",
"torch.distributed.get_world_size",
"torch.cat",
"torch.stack",
"torch.cuda.amp.autocast",
"torch.load",
"torch.where",
"torch.nn.SyncBatchNorm.convert_sync_batchnorm",
"torch.norm",
"torch.utils.data.DataLoader",
"torch.zeros_like",
"torch.nn.fun... |
ichimei/dlcot | [
"6ba405a5fc75be7b5c93c5615d99e1311dc85187"
] | [
"modeling/backbone/drn.py"
] | [
"import torch.nn as nn\nimport math\nimport torch.utils.model_zoo as model_zoo\nfrom dlcot.modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d\n\nwebroot = 'http://dl.yf.io/drn/'\n\nmodel_urls = {\n 'resnet50': 'https://download.pytorch.org/models/resnet50-19c8e357.pth',\n 'drn-c-26': webroot + '... | [
[
"torch.rand",
"torch.nn.MaxPool2d",
"torch.nn.Sequential",
"torch.utils.model_zoo.load_url",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
sht47/mmtracking | [
"5a25e418e9c598d1b576bce8702f5e156cbbefe7"
] | [
"mmtrack/core/utils/visualization.py"
] | [
"import random\n\nimport cv2\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport mmcv\nimport numpy as np\nimport seaborn as sns\nfrom matplotlib.patches import Rectangle\n\n\ndef random_color(seed):\n \"\"\"Random a color according to the input seed.\"\"\"\n random.seed(seed)\n colors = sns.color_... | [
[
"matplotlib.use",
"matplotlib.pyplot.text",
"matplotlib.pyplot.autoscale",
"matplotlib.patches.Rectangle",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.margins",
"matplotlib.pyplot.draw",
"matplotlib.pyplot.pause",
"matplotlib.pyplot.show",
"numpy.clip",
"matplotlib.... |
iammcy/Fed-Learning | [
"5de2930061cdf7803456b7e73b7934d5e334e2c9",
"5de2930061cdf7803456b7e73b7934d5e334e2c9"
] | [
"src/model.py",
"src/client.py"
] | [
"from torch import nn\nimport torch.nn.functional as F\n\nclass LinearModel(nn.Module):\n def __init__(self) -> None:\n super(LinearModel, self).__init__()\n self.flatten = nn.Flatten()\n self.linear_relu_stack = nn.Sequential(\n nn.Linear(28*28, 512),\n nn.ReLU(),\n ... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.nn.MaxPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.Flatten"
],
[
"torch.no_grad",
"torch.cuda.is_available",
"torch.nn.CrossEntropyLoss"
]
] |
flatten-official/flatten-scripts | [
"b19a2275ebd4607b8534d82b7d8035bde6a9b8a9"
] | [
"archive/confirmed_cases/covidOntario.py"
] | [
"'''\ncovidOntario.py\nA script to get up to date Covid-19 Data from the public health units of Ontario.\nAuthor: Ivan Nesterovic\nBorn: 2020-03-25\n'''\n\n## NOTE: Some Public Health units have put their data in text so text parsing is necessary, this may break and require checking over.\n\nimport bs4\nimport requ... | [
[
"pandas.read_csv"
]
] |
peixinhou/mindspore | [
"fcb2ec2779b753e95c762cf292b23bd81d1f561b"
] | [
"mindspore/nn/metrics/bleu_score.py"
] | [
"# Copyright 2021 Huawei Technologies Co., Ltd\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable l... | [
[
"numpy.array",
"numpy.log",
"numpy.zeros",
"numpy.sum",
"numpy.ones",
"numpy.exp"
]
] |
SaiMahimaIyer/Data-Analytics | [
"2516e7f2de332808dfc9f483db2a0c0dc6f728da"
] | [
"Exploratory Data Analysis on Titanic Dataset.py"
] | [
"#!/usr/bin/env python\n# coding: utf-8\n\n# In[1]:\n\n\nimport numpy as np\nimport pandas as pd\nimport pandas_profiling\n\n\n# In[2]:\n\n\ndf = pd.read_csv(\n \"https://raw.githubusercontent.com/datasciencedojo/datasets/master/titanic.csv\"\n )\n\n\n# In[3]:\n\n\ndf.profile_report()\n\n\n# In[5]:\n\n\npro... | [
[
"pandas.read_csv"
]
] |
charliealpha094/Project_Data_Visualization | [
"ccd55db58927dbbcfd57ab750fe7b21754c2b2dc"
] | [
"Chapter_15_Generating_Data/try_15.1/five_cubic.py"
] | [
"#Done by Carlos Amaral (19/07/2020)\n\n\n#Try 15.1- Cubes\n\nimport matplotlib.pyplot as plt \n\nx_values = [1, 2, 3, 4, 5]\ny_values = [1, 8, 27, 64, 125]\n\nplt.style.use('seaborn')\nfig, ax = plt.subplots()\nax.plot(x_values, y_values, linewidth = 3)\n\n#Set chart title and label axes\nax.set_title(\"Cubic Numb... | [
[
"matplotlib.pyplot.show",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.style.use"
]
] |
aleaf/SFRmaker | [
"4b87d29f5486f283fecc024be36cf81d429bdcca"
] | [
"sfrmaker/test/test_preprocessing.py"
] | [
"\"\"\"\nTest the preprocessing module\n\"\"\"\nimport os\nfrom pathlib import Path\nimport yaml\nimport numpy as np\nimport pandas as pd\nimport geopandas as gpd\nfrom shapely.geometry import box\nimport pytest\nfrom gisutils import df2shp, shp2df\nfrom sfrmaker.checks import check_monotonicity\nfrom sfrmaker.prep... | [
[
"pandas.to_datetime",
"pandas.testing.assert_frame_equal",
"numpy.array_equal",
"pandas.DataFrame",
"numpy.allclose",
"numpy.all",
"pandas.read_csv"
]
] |
frankiert/layout-parser | [
"f89a18f3d0a51a07f9a70598d06ca586dc4dd1c3"
] | [
"src/layoutparser/io/basic.py"
] | [
"# Copyright 2021 The Layout Parser 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#\n# Unless requ... | [
[
"pandas.read_csv",
"pandas.isna"
]
] |
HapeMask/Theano | [
"89aac420cb6cc64328e23ee5dbe33c280b1eb980"
] | [
"theano/tensor/nnet/tests/test_neighbours.py"
] | [
"from __future__ import absolute_import, print_function, division\nimport numpy as np\nimport unittest\n\nimport theano\nfrom theano import shared, function\nimport theano.tensor as T\nfrom theano.tensor.nnet.neighbours import images2neibs, neibs2images, Images2Neibs\n\nfrom theano.tests import unittest_tools\n\nmo... | [
[
"numpy.random.rand",
"numpy.asarray",
"numpy.ones",
"numpy.allclose",
"numpy.prod"
]
] |
oxquantum/CVAE_for_QE | [
"01f3070b9ddc4b6d54ad5d6573749b7270d95bee"
] | [
"util_conv.py"
] | [
"import numpy as np\nimport tensorflow as tf\nfrom tensorflow.python.framework import tensor_shape\n\n# Convert an input_shape to n, which is the integer satisfying 2^n = height\n# Input_shape: (height, width), list or tuple, length 2\n# Assume height == width\ndef convert_shape_to_depth(input_shape):\n height, ... | [
[
"tensorflow.contrib.layers.batch_norm",
"tensorflow.variance_scaling_initializer",
"tensorflow.shape",
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.python.framework.tensor_shape.as_dimension",
"tensorflow.reshape",
"tensorflow.nn.conv2d_transpose",
"te... |
nightlessbaron/pytorch-lightning | [
"239bea5c29cef0d1a0cfb319de5dbc9227aa2a53",
"239bea5c29cef0d1a0cfb319de5dbc9227aa2a53"
] | [
"tests/core/test_results.py",
"tests/base/models.py"
] | [
"# Copyright The PyTorch Lightning team.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law... | [
[
"torch.zeros",
"torch.distributed.get_world_size",
"torch.eq",
"torch.distributed.init_process_group",
"torch.multiprocessing.spawn",
"torch.cuda.device_count",
"torch.tensor",
"torch.load"
],
[
"torch.nn.Linear",
"torch.rand",
"torch.nn.Dropout",
"torch.nn.LSTM... |
annomator/annomator_package_beta_0.1 | [
"134d5c3b2818cf196021ed1ce61424259e80d7f6"
] | [
"annotate/annotate_json_boxes.py"
] | [
"# Copyright 2019 Annomator Written by Arend Smits\n# Copyright 2019 The TensorFlow 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. You may obtain a copy of the License at\n# http://www.apache.org/l... | [
[
"matplotlib.use",
"tensorflow.Session",
"matplotlib.pyplot.close"
]
] |
joaoalvarenga/TensorFlowASR | [
"72cd5d2b932d66ddd61e79ab41bb0d64cb8c4919"
] | [
"tensorflow_asr/optimizers/schedules.py"
] | [
"# Copyright 2020 Huy Le Nguyen (@usimarit)\r\n#\r\n# Licensed under the Apache License, Version 2.0 (the \"License\");\r\n# you may not use this file except in compliance with the License.\r\n# You may obtain a copy of the License at\r\n#\r\n# http://www.apache.org/licenses/LICENSE-2.0\r\n#\r\n# Unless require... | [
[
"tensorflow.python.ops.math_ops.maximum",
"tensorflow.python.framework.ops.name_scope_v2",
"tensorflow.python.ops.math_ops.cast",
"tensorflow.python.ops.math_ops.floor",
"tensorflow.python.ops.math_ops.pow",
"tensorflow.python.framework.ops.convert_to_tensor",
"tensorflow.math.minimum"... |
mattianeroni/IndustryAlgorithms | [
"ff76c55a4fa655b8566e63a8a7e6ffeba76d6acd"
] | [
"picking/algorithms/zhong.py"
] | [
"from __future__ import annotations\nfrom typing import Dict, List, Tuple, Union, Optional, cast, NewType\n\nimport random\nimport numpy as np # type: ignore\nimport time\n\n\n\n\n# The type Velocity is defined\nVelocity = NewType (\"Velocity\", List[Tuple[Tuple[int, int], float]])\n\n\n\n\n\n\n\n\n\n\ndef _compute... | [
[
"numpy.exp",
"numpy.log"
]
] |
Gaoyifei1011/AmapProgram | [
"d45a27abf9f508d922f37abc34f00da6d0aab4a0"
] | [
"FundamentalFunctions/MiddleShanxiAreaDataVisualization.py"
] | [
"import matplotlib.pyplot as plt\r\nimport numpy as np\r\nimport pandas as pd\r\n\r\n\"\"\"\r\nCopy from Jupyter Notebook\r\n\"\"\"\r\n# TODO: In the future version will insert into the 山西省道路信息分析系统 page.\r\n\r\n# 设置字体，否则中文会显示异常\r\nplt.rcParams['font.sans-serif'] = ['Microsoft YaHei']\r\nplt.rcParams['axes.unicode_m... | [
[
"matplotlib.pyplot.xlabel",
"pandas.read_excel",
"matplotlib.pyplot.title",
"matplotlib.pyplot.savefig",
"numpy.arange",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.subplot"
]
] |
ziotom78/polycomp | [
"03415c4f04bdc6b98d2b12e1a6957509c15a6e24"
] | [
"setup.py"
] | [
"#!/usr/bin/env python3\n# -*- mode: python -*-\n\nfrom setuptools import setup, find_packages\nfrom setuptools.extension import Extension\nimport os.path as path\nfrom distutils.version import LooseVersion as Version\nimport numpy as np\n\nhere = path.abspath(path.dirname(__file__))\n\nwith open(path.join(here, 'p... | [
[
"numpy.get_include"
]
] |
matthiaszimmermann/blm | [
"ae70e5845578da9c3b7ff2cdd47829a88004cb5d"
] | [
"app/app.py"
] | [
"from flask import Flask, render_template, request\nfrom model import LSCCNN\nfrom PIL import Image\nfrom io import BytesIO\n\nimport logging\nimport numpy as np\nimport base64\nimport cv2\n\nMODEL_FILENAME = './model/scale_4_epoch_46.pth'\nMODEL = None\n\nEMOJI_FILENAME = './blm_fist.png'\nEMOJI = None\n\napp = Fl... | [
[
"numpy.array"
]
] |
ashishfarmer/pyro | [
"11a96cde05756def826c232d76f9cff66f6e6d4f",
"54d48627a7c5c0575c2fe69d5b6c80f3c47b287b"
] | [
"pyro/ops/integrator.py",
"pyro/distributions/transforms/affine_coupling.py"
] | [
"# Copyright (c) 2017-2019 Uber Technologies, Inc.\n# SPDX-License-Identifier: Apache-2.0\n\nfrom torch.autograd import grad\n\n\ndef velocity_verlet(z, r, potential_fn, kinetic_grad, step_size, num_steps=1, z_grads=None):\n r\"\"\"\n Second order symplectic integrator that uses the velocity verlet algorithm.... | [
[
"torch.autograd.grad"
],
[
"torch.distributions.utils._sum_rightmost",
"torch.cat",
"torch.exp"
]
] |
ratschlab/immunopepper | [
"1c10c10c721273535ac57cd466a18b685641f83b"
] | [
"tests/parquet_test/columnar_write.py"
] | [
"import pandas as pd\nimport pyarrow as pa\nfrom pyarrow import parquet as pq\nimport numpy as np\nimport os\n\noutdir = '/Users/laurieprelot/Documents/Projects/tmp_kmer/parquet_test'\n\ndf = pd.DataFrame({\"Day\":{\"0\":1,\"1\":2,\"2\":3,\"3\":4,\"4\":5,\"5\":6,\"6\":7,\"7\":8},\"Year\":{\"0\":2018,\"1\":2018,\"2\... | [
[
"pandas.DataFrame"
]
] |
torkjellsdatter/pisa | [
"7b26b0ac40c873a87786286acfd1c96abf724a99",
"7b26b0ac40c873a87786286acfd1c96abf724a99",
"7b26b0ac40c873a87786286acfd1c96abf724a99"
] | [
"pisa/utils/random_numbers.py",
"pisa/scripts/make_toy_events.py",
"pisa/stages/osc/pi_prob3.py"
] | [
"#! /usr/bin/env python\n\n\"\"\"\nUtilities to handle random numbers needed by PISA in a consistent and\nreproducible manner.\n\n\"\"\"\n\n\nfrom __future__ import division\n\nfrom collections import Sequence\n\nimport numpy as np\n\nfrom pisa.utils.log import set_verbosity\n\n\n__all__ = ['get_random_state',\n ... | [
[
"numpy.random.RandomState"
],
[
"numpy.max",
"numpy.full",
"numpy.isclose",
"scipy.stats.norm.ppf",
"numpy.asarray",
"numpy.log",
"scipy.stats.norm",
"numpy.sum",
"numpy.min",
"numpy.diff",
"numpy.where",
"numpy.isscalar",
"numpy.power",
"numpy.log10... |
miwoow/ppt | [
"28b115445d63c15a04a13d9f80beec573e00af40"
] | [
"children_math/gen.py"
] | [
"#!/bin/env/python\n#encoding:utf-8\n\nfrom numpy import random\n\nMAX_INT = 50 \n\nPATERN=\"%-13s\"\n\ndef two_arg_problem():\n sel = '+'\n a = random.randint(1, MAX_INT-1)\n if random.randint(0, 1) == 0:\n sel = '+'\n if a < 10:\n b = random.randint(11-a, MAX_INT - a)\n el... | [
[
"numpy.random.randint"
]
] |
SimScaleGmbH/external-building-aerodynamics | [
"8ab6ce7bf7e0835d9b200c55461cd6966479f94a"
] | [
"examples/AIJ Case D/TKE_API.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Mon Aug 2 19:34:28 2021\n\n@author: MohamadKhairiDeiri\n\"\"\"\n\nimport pathlib\n\nimport matplotlib as mpl\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom scipy import stats\n\nimport simscale_eba.ResultProcessing as res\n\nresult = res... | [
[
"numpy.square",
"numpy.isnan",
"pandas.read_excel",
"scipy.stats.linregress",
"matplotlib.pyplot.subplots",
"numpy.mean",
"numpy.invert",
"numpy.sqrt",
"scipy.stats.sem"
]
] |
zhyever/Monocular-Depth-Estimation-Toolbox | [
"c591b9711321450387ffa7322ec1db9a340347c2"
] | [
"depth/apis/inference.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport matplotlib.pyplot as plt\nimport mmcv\nimport torch\nfrom mmcv.parallel import collate, scatter\nfrom mmcv.runner import load_checkpoint\n\nfrom depth.datasets.pipelines import Compose\nfrom depth.models import build_depther\n\n\ndef init_depther(config, chec... | [
[
"torch.no_grad"
]
] |
ADALabUCSD/vista | [
"3cf4486c3b06c93b7841da180ab46ad6e433cac8"
] | [
"spark/code/python/cnn/alexnet.py"
] | [
"'''\nCopyright 2018 Supun Nakandala and Arun Kumar\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n http://www.apache.org/licenses/LICENSE-2.0\nUnless required by applicable law or agre... | [
[
"tensorflow.reshape",
"tensorflow.constant",
"tensorflow.variable_scope",
"tensorflow.get_variable",
"tensorflow.nn.softmax",
"tensorflow.get_collection",
"tensorflow.cast"
]
] |
SamarthH/qiskit-metal | [
"4a5a002b898429500913174c088564a787869b65"
] | [
"qiskit_metal/tests/test_analyses_2_functionality.py"
] | [
"# -*- coding: utf-8 -*-\n\n# This code is part of Qiskit.\n#\n# (C) Copyright IBM 2017, 2021.\n#\n# This code is licensed under the Apache License, Version 2.0. You may\n# obtain a copy of this license in the LICENSE.txt file in the root directory\n# of this source tree or at http://www.apache.org/licenses/LICENSE... | [
[
"pandas.DataFrame",
"numpy.linspace",
"numpy.array_equal"
]
] |
ai-cv/rq | [
"032c41ed7c263456c1f1beccd2a4d5515400366e"
] | [
"CodesInBooks/ContourDetection/BoundingBox.py"
] | [
"import cv2\nimport numpy as np\nimport imutils\n\n\nimg = cv2.pyrDown(cv2.imread(\"../data/imgs/hg.png\", cv2.IMREAD_UNCHANGED))\nret, thresh = cv2.threshold(cv2.cvtColor(img.copy(), cv2.COLOR_BGR2GRAY), 127, 255, cv2.THRESH_BINARY)\n# contours = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)... | [
[
"numpy.int0"
]
] |
JuAbels/CAVE | [
"344cf9bf6d205cfe892780cd13c94e67a5e8549c"
] | [
"cave/analyzer/compare_default_incumbent.py"
] | [
"import os\nimport logging\nfrom collections import OrderedDict\n\nfrom pandas import DataFrame\nimport numpy as np\n\nfrom cave.analyzer.base_analyzer import BaseAnalyzer\nfrom cave.html.html_helpers import figure_to_html\n\nclass CompareDefaultIncumbent(BaseAnalyzer):\n def __init__(self, default, incumbent):\... | [
[
"pandas.DataFrame"
]
] |
VIROBO-15/ML-algo-from-scratch | [
"58d08dce1499b2d2084102be0be7e2403611b1e6"
] | [
"Gaussian_NAive_bayes2.py"
] | [
"import numpy as np\nfrom sklearn.datasets import load_iris\nfrom sklearn.model_selection import train_test_split\nfrom math import pi\n\n\niris = load_iris()\nx_train,x_test,y_train,y_test=train_test_split(iris.data,iris.target,train_size=120,random_state=1000)\n#print(x_train)\n\nclc= np.zeros((3,1))\nlst1,lst2,l... | [
[
"numpy.array",
"numpy.zeros",
"numpy.mean",
"numpy.var",
"sklearn.model_selection.train_test_split",
"sklearn.datasets.load_iris"
]
] |
sourcery-ai-bot/cxplain | [
"ff3310c3042d70d4f857f824d9c2a096d1a03898",
"ff3310c3042d70d4f857f824d9c2a096d1a03898"
] | [
"cxplain/backend/model_builders/base_model_builder.py",
"cxplain/util/count_vectoriser.py"
] | [
"\"\"\"\nCopyright (C) 2019 Patrick Schwab, ETH Zurich\n\nPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated\ndocumentation files (the \"Software\"), to deal in the Software without restriction, including without limitation\nthe rights to use, copy, modify,... | [
[
"tensorflow.keras.backend.int_shape",
"tensorflow.python.keras.layers.Input",
"tensorflow.compat.v1.train.RMSPropOptimizer",
"tensorflow.compat.v1.train.AdamOptimizer",
"tensorflow.python.keras.callbacks.ModelCheckpoint",
"tensorflow.compat.v1.train.MomentumOptimizer",
"tensorflow.pyth... |
hogansung/deep-reinforcement-learning | [
"5170ca42bdfdb16cc5c2b86c61bee304015a6254"
] | [
"maddpg/OUNoise.py"
] | [
"import numpy as np\nimport torch\n\n\n# from https://github.com/songrotek/DDPG/blob/master/ou_noise.py\nclass OUNoise:\n def __init__(self, action_dimension, scale=0.1, mu=0, theta=0.15, sigma=0.2):\n self.action_dimension = action_dimension\n self.scale = scale\n self.mu = mu\n self... | [
[
"numpy.ones",
"torch.tensor"
]
] |
ekalosak/GPy | [
"ff82f12c3d321bfc3ce6615447fad25aea9de6bd",
"ff82f12c3d321bfc3ce6615447fad25aea9de6bd",
"ff82f12c3d321bfc3ce6615447fad25aea9de6bd"
] | [
"GPy/inference/latent_function_inference/pep.py",
"GPy/likelihoods/gamma.py",
"GPy/util/netpbmfile.py"
] | [
"from .posterior import Posterior\nfrom ...util.linalg import jitchol, tdot, dtrtrs, dtrtri, pdinv\nfrom ...util import diag\nimport numpy as np\nfrom . import LatentFunctionInference\nlog_2_pi = np.log(2*np.pi)\n\nclass PEP(LatentFunctionInference):\n '''\n Sparse Gaussian processes using Power-Expectation P... | [
[
"numpy.square",
"numpy.dot",
"numpy.log",
"numpy.sum",
"numpy.eye",
"numpy.sqrt",
"numpy.diag"
],
[
"scipy.special.psi",
"scipy.special.gamma",
"scipy.special.polygamma",
"numpy.log",
"numpy.exp",
"numpy.atleast_1d"
],
[
"numpy.max",
"numpy.ndind... |
gronlund/kmeans1d | [
"585386d4678000691706acdb954911be8fea1c5c"
] | [
"plot.py"
] | [
"import argparse\nimport csv\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nCLOCKS_PER_SEC = 1000000\n\n\ndef main(k_plot, constant=False, csvfilename='timing.csv'):\n with open(csvfilename) as time_file:\n csv_reader = csv.reader(time_file)\n fasts = []\n medis = []\n ns =... | [
[
"numpy.array",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ticklabel_format"
]
] |
ZurMaD/DAIN | [
"22570e51e84f7dfd48ba4f88e6ee7c9ff1b0b123"
] | [
"my_package/Interpolation/setup.py"
] | [
"#!/usr/bin/env python3\nimport os\nimport torch\n\nfrom setuptools import setup, find_packages\nfrom torch.utils.cpp_extension import BuildExtension, CUDAExtension\n\ncxx_args = ['-std=c++11']\n\nnvcc_args = [\n '-gencode', 'arch=compute_50,code=sm_50',\n '-gencode', 'arch=compute_52,code=sm_52',\n '-genc... | [
[
"torch.utils.cpp_extension.CUDAExtension"
]
] |
sfermigier/quantipy3 | [
"6b1a5404a70b1a419493f612c39127d7baed4124"
] | [
"tests/test_complex_logic.py"
] | [
"import unittest\nimport os.path\nimport numpy as np\nimport pandas as pd\nfrom pandas.util.testing import assert_frame_equal\nfrom . import test_helper\nimport copy\n\nfrom operator import lt, le, eq, ne, ge, gt\n\nfrom pandas.core.index import Index\n__index_symbol__ = {\n Index.union: ',',\n Index.intersec... | [
[
"pandas.DataFrame.from_csv"
]
] |
lukadvisor/BCNet | [
"d55263c0543ecf27f1f72e03a1a1eafb7b18ae88"
] | [
"detectron2/data/samplers/distributed_sampler.py"
] | [
"import itertools\nimport math\nfrom collections import defaultdict\nfrom typing import Optional\nimport torch\nfrom torch.utils.data.sampler import Sampler\n\nfrom detectron2.utils import comm\n\n\nclass TrainingSampler(Sampler):\n \"\"\"\n In training, we only care about the \"infinite stream\" of training ... | [
[
"torch.trunc",
"torch.arange",
"torch.Generator",
"torch.randperm",
"torch.tensor"
]
] |
benjydel/ssd_keras | [
"3cbbfa631dc1f5c66ce299f0c433cacb52c6cab1"
] | [
"inference_ssd300.py"
] | [
"# Needed libraries\nimport argparse\n\nfrom ssd_encoder_decoder.ssd_output_decoder import decode_detections\nfrom data_generator.object_detection_2d_misc_utils import apply_inverse_transforms\n\nimport numpy as np\nimport random\nimport cv2\n\nfrom threading import Thread\nfrom datetime import datetime\nimport tim... | [
[
"numpy.array",
"tensorflow.python.platform.gfile.GFile",
"numpy.set_printoptions",
"tensorflow.GraphDef",
"tensorflow.Session",
"tensorflow.import_graph_def"
]
] |
akaashsidhu/statsmodels | [
"fadf25911739a3611980278aabf751e2df6e6680"
] | [
"statsmodels/tsa/holtwinters.py"
] | [
"\"\"\"\nNotes\n-----\nCode written using below textbook as a reference.\nResults are checked against the expected outcomes in the text book.\n\nProperties:\nHyndman, Rob J., and George Athanasopoulos. Forecasting: principles and\npractice. OTexts, 2014.\n\nAuthor: Terence L van Zyl\nModified: Kevin Sheppard\n\"\"\... | [
[
"numpy.finfo",
"numpy.zeros_like",
"numpy.log",
"numpy.arange",
"numpy.ndim",
"numpy.log10",
"scipy.optimize.minimize",
"scipy.optimize.brute",
"numpy.array",
"scipy.spatial.distance.sqeuclidean",
"scipy.stats.boxcox",
"scipy.optimize.basinhopping",
"numpy.zeros... |
deepakdalakoti/Bayesian_neural_net | [
"1ee554d64550377dfa4295bb05e61bab98e43ee4"
] | [
"meshes/naca-2412-airfoil/airfoil-mesh.py"
] | [
"'''\n// NACA 2412 Airfoil\n// Created using Gmsh (http://gmsh.info/)\n// Mesh Distributed by: Notre Dame CICS (MIT Liscense)\n// - Associated publication:\n// doi: https://doi.org/10.1016/j.jcp.2019.01.021\n// github: https://github.com/cics-nd/rans-uncertainty\n'''\n\nimport pygmsh #See: https://pypi.org/project/... | [
[
"numpy.array",
"numpy.genfromtxt",
"numpy.zeros"
]
] |
jwohlwend/flop | [
"c5bbd4c5fae6291e2a056e68b44bcf97e4d757bf"
] | [
"examples/enwik8_tf/eval.py"
] | [
"# coding: utf-8\nimport argparse\nimport time\nimport math\nimport os, sys\n\nimport torch\n\nfrom data_utils import get_lm_corpus\nfrom mem_transformer import MemTransformerLM\nfrom utils.exp_utils import get_logger\n\nparser = argparse.ArgumentParser(description='PyTorch Transformer Language Model')\nparser.add_... | [
[
"torch.device",
"torch.no_grad",
"torch.load"
]
] |
torchgan/torchgan | [
"cfd5da4b7ffcec544c6cc4a22257edf40fd31f9d"
] | [
"torchgan/losses/auxclassifier.py"
] | [
"import torch\n\nfrom .functional import auxiliary_classification_loss\nfrom .loss import DiscriminatorLoss, GeneratorLoss\n\n__all__ = [\n \"AuxiliaryClassifierGeneratorLoss\",\n \"AuxiliaryClassifierDiscriminatorLoss\",\n]\n\n\nclass AuxiliaryClassifierGeneratorLoss(GeneratorLoss):\n r\"\"\"Auxiliary Cla... | [
[
"torch.randint",
"torch.randn"
]
] |
HJReachability/learning_feedback_linearization | [
"cb655ade4cfbf53f5dd19f79c943f7665666f2cb"
] | [
"sandbox/train_stuff.py"
] | [
"import gym\nimport tensorflow as tf\nimport spinup\nimport numpy as np\n\n#defining arguments for environment\nenvargs = {\"uscaling\": 0.1}\n\n#making environment lambda function\n#env = lambda : gym.make(\"quadrotor_14d_env:Quadrotor14dEnv-v0\", uscaling=0.1, dynamicsScaling = 0)\nenv = lambda : gym.make(\"custo... | [
[
"numpy.random.randint"
]
] |
JenkoB/resolwe-bio | [
"a958cf3fc82ebc37f527e1b156753f2324a33803"
] | [
"resolwe_bio/tools/genehcluster.py"
] | [
"#!/usr/bin/env python2\n# pylint: disable=missing-docstring,invalid-name,import-error\n# XXX: Refactor to a comand line tool and remove pylint disable\n\"\"\"Hierarchical clustering of expression time courses.\"\"\"\nfrom __future__ import absolute_import, division, print_function\n\nimport argparse\nimport json\n... | [
[
"numpy.array",
"scipy.spatial.distance.pdist",
"numpy.array_equal",
"numpy.isnan",
"scipy.stats.spearmanr",
"numpy.interp",
"numpy.corrcoef",
"numpy.nanmax"
]
] |
MahmudulAlam/Recurrently-Semantic-Segmentation | [
"64f988e3e278ef7807cdb2dd48c79eb1bbc66519"
] | [
"visualize.py"
] | [
"import colorsys\nimport numpy as np\n\n\ndef random_colors(N, bright=True):\n brightness = 1.0 if bright else 0.7\n hsv = [(i / N, 1, brightness) for i in range(N)]\n colors = list(map(lambda c: colorsys.hsv_to_rgb(*c), hsv))\n return colors\n\n\ndef apply_mask(image, mask, color, alpha=0.5):\n for ... | [
[
"numpy.where"
]
] |
RangK/models | [
"a1ce90442e3205b82ffca3badd3c65408f4450cb"
] | [
"research/object_detection/inputs.py"
] | [
"# Copyright 2017 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.shape",
"tensorflow.minimum",
"tensorflow.concat",
"tensorflow.expand_dims",
"tensorflow.random_uniform",
"tensorflow.ones_like",
"tensorflow.equal",
"tensorflow.reshape",
"tensorflow.constant",
"tensorflow.estimator.export.ServingInputReceiver",
"tensorflow... |
okteto/demos | [
"15f2af3aae4802b03f43ddbead51e493e54ee2af"
] | [
"cpu/Detection/SSD/examples/SSD320_inference.py"
] | [
"#\n# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless ... | [
[
"tensorflow.logging.set_verbosity",
"tensorflow.train.latest_checkpoint",
"tensorflow.ConfigProto",
"tensorflow.estimator.RunConfig",
"tensorflow.app.run"
]
] |
Bobeye/rllab | [
"53c0afb73f93c4a78ff21507914d7f7735c21ea9",
"53c0afb73f93c4a78ff21507914d7f7735c21ea9"
] | [
"rllab/misc/ext.py",
"dam_files/GPOMDP_SVRG_WV_ada_verA_reacher_fr_nver_2.py"
] | [
"from path import Path\nimport sys\nimport pickle as pickle\nimport random\nfrom rllab.misc.console import colorize, Message\nfrom collections import OrderedDict\nimport numpy as np\nimport operator\nfrom functools import reduce\n\nsys.setrecursionlimit(50000)\n\n\ndef extract(x, *keys):\n if isinstance(x, (dict... | [
[
"tensorflow.set_random_seed",
"numpy.concatenate",
"numpy.asarray",
"numpy.random.RandomState",
"numpy.random.seed",
"numpy.mean",
"numpy.random.shuffle",
"numpy.std"
],
[
"numpy.concatenate",
"numpy.array",
"numpy.cov",
"numpy.trace",
"numpy.zeros",
"nu... |
leo603222/fix-displace-between-selection-area-and-mouse-pos | [
"1f9031884a980432795b69487bd659f5e4ef91aa"
] | [
"tests/imageview/test_imageview.py"
] | [
"import pyqtgraph as pg\nimport numpy as np\n\napp = pg.mkQApp()\n\ndef test_nan_image():\n img = np.ones((10,10))\n img[0,0] = np.nan\n v = pg.image(img)\n v.imageItem.getHistogram()\n app.processEvents()\n v.window().close()\n\ndef test_init_with_mode_and_imageitem():\n data = np.random.randi... | [
[
"numpy.ones",
"numpy.random.randint"
]
] |
bowang-lab/CONCERTO | [
"a6b59778eb4d2a964ca1795fa6368eeb579c1bf7"
] | [
"src/models.py"
] | [
"import torch as th\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport pandas as pd\nimport numpy as np\nfrom dgl.nn import MaxPooling, AvgPooling, GlobalAttentionPooling\nfrom dgl import function as fn\nfrom dgl.nn.pytorch.softmax import edge_softmax\nfrom dgllife.model import GATPredictor, GIN, load_... | [
[
"torch.nn.Linear",
"torch.nn.Dropout",
"torch.cat",
"numpy.ceil",
"torch.nn.AvgPool1d",
"torch.nn.Conv1d",
"torch.nn.Sequential",
"torch.nn.ELU",
"torch.no_grad",
"torch.nn.ReLU",
"torch.nn.BatchNorm1d",
"pandas.Series",
"torch.nn.MaxPool1d",
"torch.mean",
... |
RonMeiburg/orqviz | [
"fd3e345ac76325cc1f8bd0d523af33689af31fda"
] | [
"tests/orqviz/hessians/hessians_test.py"
] | [
"import os\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfrom orqviz.hessians import (\n get_Hessian,\n get_Hessian_SPSA_approx,\n perform_1D_hessian_eigenvector_scan,\n plot_1D_hessian_eigenvector_scan_result,\n)\nfrom orqviz.utils import load_viz_object, save_viz_object\n\n\ndef COST_FUNCT... | [
[
"numpy.testing.assert_array_almost_equal",
"numpy.sum",
"numpy.sin",
"numpy.random.rand"
]
] |
ksu-hmi/mouth-check | [
"f659a8c76707eb7f974dc3fbdd93b1324315f91b"
] | [
"masksMaker.py"
] | [
"import numpy as np\nfrom utils import pairwise\nfrom tqdm import tqdm\nimport os\nimport json\nfrom PIL import Image, ImageDraw\nfrom skimage.draw import polygon2mask\nimport cv2\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport sys\n\n\n\npathImgSrc = \"data\\\\img\\\\ori\"\npathImgDst = \"data\\\\img... | [
[
"pandas.DataFrame",
"numpy.zeros",
"numpy.maximum"
]
] |
leichen2018/dgl | [
"820caa02d022618fc4c2a835e44695f744b0fdca"
] | [
"examples/pytorch/line_graph/test.py"
] | [
"\"\"\"\nSupervised Community Detection with Hierarchical Graph Neural Networks\nhttps://arxiv.org/abs/1705.08415\n\nAuthor's implementation: https://github.com/joanbruna/GNN_community\n\"\"\"\n\nfrom __future__ import division\nimport time\nfrom datetime import datetime as dt\n\nimport argparse\nfrom itertools imp... | [
[
"torch.device",
"torch.cat",
"torch.max",
"torch.no_grad",
"numpy.mean",
"torch.ones",
"torch.from_numpy",
"numpy.std",
"torch.load",
"torch.chunk",
"torch.sum"
]
] |
trhongbinwang/data_science_journey | [
"3f1437942109250cc41207d39e6bcb6e4ff17730"
] | [
"python/pandas/pandas_command.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Mon Aug 29 11:07:14 2016\r\n\r\npandas command collection\r\n\r\n\r\n\"\"\"\r\n\r\nimport pandas as pd\r\n\r\nimport numpy as np\r\n\r\n# create df from dict\r\ndata = {'name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'], \r\n 'year': [2012, 2012, 2013, 2014, 20... | [
[
"pandas.DataFrame"
]
] |
korobool/codefinder | [
"02ffe34066547fb1a9d996ddabf0ede753b26ef6"
] | [
"train.py"
] | [
"import numpy as np\nimport tensorflow as tf\nfrom sklearn.metrics import accuracy_score\n\ntf.reset_default_graph()\n\nfrom model import *\n\nf1_ = open('loss_test_track.json', 'w')\nf2_ = open('loss_train_track.json', 'w')\nbatch_size = 100\nmax_batches = 11801\nbatches_for_test = 100\nbatches_for_print = 10\nepo... | [
[
"tensorflow.Session",
"tensorflow.reset_default_graph",
"tensorflow.train.Saver",
"sklearn.metrics.accuracy_score",
"numpy.float32",
"tensorflow.global_variables_initializer"
]
] |
mamalmaleki/hands_on_ml | [
"086fa254847bda2c3b3b7e27997ee0ecd7152171"
] | [
"ch02/ex0202_randomized_search_cv.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\nnp.random.seed(42)\n\nimport os\nimport tarfile\nimport urllib.request\n\nDOWNLOAD_ROOT = \"https://raw.githubusercontent.com/ageron/handson-ml2/master/\"\nHOUSING_PATH = os.path.join(\"datasets\", \"housing\")\nHOUSING_URL = DOWNLOAD_ROOT + \"datasets/housing... | [
[
"sklearn.impute.SimpleImputer",
"scipy.stats.expon",
"pandas.cut",
"numpy.log",
"sklearn.preprocessing.StandardScaler",
"numpy.random.seed",
"scipy.stats.reciprocal",
"matplotlib.pyplot.title",
"sklearn.model_selection.RandomizedSearchCV",
"matplotlib.pyplot.figure",
"m... |
cr1m5onk1ng/text_similarity | [
"2123621bf153683b35e9433835237812605bd42f"
] | [
"src/compression/prune.py"
] | [
"import transformers\nfrom transformers.models.auto.configuration_auto import AutoConfig\nfrom transformers import AutoModel, AutoModelForSequenceClassification\nfrom transformers import AutoTokenizer\nfrom src.dataset.wic_dataset import *\nfrom transformers import AutoTokenizer\nfrom src.models.modeling import Bas... | [
[
"torch.device",
"torch.cuda.amp.autocast"
]
] |
nils-werner/keras | [
"78f26df8fb2b8aa5c6262aef44a494a8335a9c6e"
] | [
"tests/keras/utils/data_utils_test.py"
] | [
"\"\"\"Tests for functions in data_utils.py.\n\"\"\"\nimport os\nimport sys\nimport tarfile\nimport threading\nimport zipfile\nfrom itertools import cycle\n\nimport numpy as np\nimport pytest\nfrom six.moves.urllib.parse import urljoin\nfrom six.moves.urllib.request import pathname2url\n\nfrom keras.utils import Se... | [
[
"numpy.ones"
]
] |
k15z/kevz-nnet | [
"e870b02e032903510b3cbac6e604fa58b4b84b44"
] | [
"nnet/layers/softmax.py"
] | [
"import numpy as np\n\nclass Softmax:\n\tdef __init__(self, input_dims, output_dims):\n\t\tself.input_dims = input_dims\n\t\tself.output_dims = output_dims\n\t\tself.weight = np.random.normal(0.0, 1.0 / np.sqrt(output_dims), (output_dims, input_dims))\n\n\tdef _softmax(self, y):\n\t\tresult = []\n\t\tfor i, y_i in ... | [
[
"numpy.max",
"numpy.array",
"numpy.dot",
"numpy.vectorize",
"numpy.sum",
"numpy.sqrt",
"numpy.outer"
]
] |
JPchico/parsevasp | [
"9e43076657007145e2dbab17b5a57fff7b778442"
] | [
"tests/test_xml_regular.py"
] | [
"import os\nimport pytest\nimport numpy as np\nfrom parsevasp.vasprun import Xml\nimport utils\n\"\"\"Test parsew, the regular extraction for both terminated\nand truncated XML files.\n\n\"\"\"\n@pytest.fixture(scope='module', autouse=True)\ndef set_precision(request):\n np.set_printoptions(precision=8)\n\n\n@py... | [
[
"numpy.testing.assert_allclose",
"numpy.array",
"numpy.set_printoptions",
"numpy.allclose",
"numpy.all"
]
] |
SuiMingYang/ProductTypeClassify | [
"ad5c76e71f21dccd2c1190eff96848146c0790c8"
] | [
"api.py"
] | [
"from sklearn.externals import joblib\nimport pickle\nfrom sklearn.feature_extraction.text import CountVectorizer\nimport jieba\nfrom collections import Counter\n\n\"\"\"\n调用代码\n\"\"\"\n\nif __name__ == \"__main__\":\n def put_category(l):\n l=loaded_model.predict(vec.transform(jieba.lcut(l)))\n l=... | [
[
"sklearn.externals.joblib.load"
]
] |
jswalens/labyrinth | [
"d6a9359cafcc0ed02c5cd6c152551386e1e160f8"
] | [
"results/process-results.py"
] | [
"import sys\nimport re\nfrom collections import defaultdict\nimport numpy\n\nif len(sys.argv) >= 2:\n FILE = sys.argv[1]\nelse:\n FILE = \"20190817T1454-1cc19b18.csv\"\n\nif len(sys.argv) >= 3:\n OUTPUT = sys.argv[2]\nelse:\n # E.g. 20190817T1454-1cc19b18.csv to\n # 20190817T1454-1cc19b18-medians.csv... | [
[
"numpy.median",
"numpy.percentile"
]
] |
mattroos/dino | [
"5e5a599a5f315bad9bf85112f29d5671822af484"
] | [
"eval_linear.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates.\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 ... | [
[
"torch.nn.Linear",
"torch.nn.Identity",
"torch.cat",
"torch.cuda.synchronize",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.no_grad",
"torch.nn.parallel.DistributedDataParallel",
"torch.utils.data.DataLoader",
"torch.utils.data.distributed.DistributedSampler",
"torc... |
KLeeDE/Python | [
"0a12ffdabb25586ab47d10d5a320033918155eac"
] | [
"Ch5_Cartopy/5_Python_Week5_cartopy.py"
] | [
"# -*- coding: utf-8 -*-\r\n\"\"\"\r\nCreated on Thu Dec 3 12:03:49 2020\r\n\r\n@author: Kyungmin Lee\r\n\"\"\"\r\n\r\n# R / Week3 Assignment\r\n\r\nimport warnings\r\nwarnings.filterwarnings(\"ignore\")\r\n\r\nimport cartopy\r\nimport cartopy.crs as ccrs\r\nimport matplotlib.pyplot as plt\r\n\r\nhelp(ccrs.PlateCa... | [
[
"matplotlib.pyplot.contourf",
"matplotlib.cm.get_cmap",
"numpy.linspace",
"numpy.mean",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.axes",
"numpy.deg2rad",
"matplotlib.patches.Rectangle",
"numpy.meshgrid"
]
] |
hanseungwook/SimSiam | [
"ff363f2cfdee07ecfee6c25ae3e920fdb9302e57"
] | [
"models/backbones/wrn.py"
] | [
"import math\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\n\"\"\"\nOriginal Author: Wei Yang\n\"\"\"\n\n__all__ = ['wrn']\n\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 =... | [
[
"torch.nn.Linear",
"torch.nn.functional.avg_pool2d",
"torch.nn.ModuleList",
"torch.nn.Sequential",
"torch.nn.BatchNorm2d",
"torch.nn.functional.dropout",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.randn"
]
] |
i14kawanaka/AtCoder | [
"1dd24b42ef672a64c592dc6479a80c4fe8383abc"
] | [
"ABC/205/C.py"
] | [
"import numpy as np\ns1 = input().split()\nA = int(s1[0])\nB = int(s1[1])\nC = int(s1[2])\n\nif(C%2 == 0): #偶数\n if(np.abs(A)==np.abs(B)):\n print(\"=\")\n elif(np.abs(A)>np.abs(B)):\n print(\">\")\n else:\n print(\"<\")\nelse:\n if(A==B):\n print(\"=\")\n elif(A>B):\n ... | [
[
"numpy.abs"
]
] |
Peiiii/detro | [
"26d74468d7554dc20b2a2daf7ec5009302c820f2"
] | [
"detro/packages/circledet/network.py"
] | [
"from .resnet_backbone import resnet18\nfrom torch import nn\nimport torch\nimport torch.nn.functional as F\nfrom detro.networks.components import BiFPN, Center_layer, Offset_layer, Reg_layer, Heatmap_layer\nfrom detro.networks.losslib import center_loss, distance_loss\n\n\nclass FeatureFusionNetwork(nn.Module):\n ... | [
[
"torch.cat",
"torch.nn.functional.upsample",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d"
]
] |
idea-iitd/graphgen | [
"0c74511faeed593dcfa7a6c59fc177812232f7d2"
] | [
"metrics/stats.py"
] | [
"import concurrent.futures\nimport os\nimport pickle\nimport subprocess as sp\nimport tempfile\nfrom datetime import datetime\nfrom functools import partial\nimport numpy as np\nimport networkx as nx\n\nimport metrics.mmd as mmd\n\nPRINT_TIME = True\nMAX_WORKERS = 48\n\n\ndef degree_worker(G):\n return np.array(... | [
[
"numpy.histogram",
"numpy.array",
"numpy.sum"
]
] |
ogzgbkn/rover_20 | [
"ca35debe3decb67fd1a3270ce478984ae7af8f60",
"4582036b06bc60774efaf79fdb6806d0ce20efd7"
] | [
"arm_20/geometric_approach/geometrical_ik_v3.py",
"rover_20_image/src/rover_send_color.py"
] | [
"import rospy\nimport math\nfrom std_msgs.msg import Float64 as F64\nimport numpy as np\nfrom random import randint\nfrom calculations import *\nfrom sensor_msgs.msg import Joy\nfrom Arm import *\n\n\nglobal x,xi,y,yi,z,zi,w,flag,button\nflag=False\nx=54.0\ny=50.0\nz=0.0\nxi=0.0\nyi=0.0\nzi=0.0\nbutton=0.0\npitch=0... | [
[
"numpy.degrees"
],
[
"numpy.array",
"numpy.ones"
]
] |
always-newbie161/pyprobml | [
"eb70c84f9618d68235ef9ba7da147c009b2e4a80",
"eb70c84f9618d68235ef9ba7da147c009b2e4a80",
"eb70c84f9618d68235ef9ba7da147c009b2e4a80"
] | [
"scripts/Old/8mer.py",
"scripts/pca_digits.py",
"scripts/coiled_pytorch_finetune.py"
] | [
"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nDEFAULT_SITES = ['HOXC4_REF_R2', 'CRX_REF_R1']\n\ndef load_data(file_name, normalize=False):\n #Function to load the data source file \n data = pd.read_csv(file_name, sep=',')\n data = data.iloc[:, 1:] # Remove index column\n assert d... | [
[
"numpy.max",
"numpy.array",
"numpy.vectorize",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.title",
"pandas.qcut",
"numpy.mean",
"matplotlib.pyplot.figure",
"numpy.where",
"numpy.size",
"matplotlib.pyplot.show",
"pandas.read_csv"
],
[
"numpy.array",
"num... |
sagarchotalia/Pick-and-Place-Robot-Eklavya | [
"79005767e457018a2cbf397b7bd4887c009fb6c9"
] | [
"Script/Scene_Script.py"
] | [
"# -*- coding: utf-8 -*-\n# importing modules\nimport time\nimport numpy as np\nimport cv2\nfrom zmqRemoteApi import RemoteAPIClient\nfrom bp3d import Bin, Item, bp3D\n# connecting via ZMQ Api at port 23000 \nclient = RemoteAPIClient('localhost',23000)\n# getting simulation handles\nsim = client.getObject('sim')\ns... | [
[
"numpy.frombuffer"
]
] |
vladsterz/GraphCMR | [
"710527332583e81926e677dd596e4a3a5f2a9811"
] | [
"opendr/helpers.py"
] | [
"__author__ = 'pol'\n\nfrom utils import *\nimport opendr\nimport geometry\nimport numpy as np\nfrom math import radians\nfrom opendr.camera import ProjectPoints\nfrom opendr.renderer import TexturedRenderer\nfrom opendr.lighting import SphericalHarmonics\nfrom opendr.lighting import LambertianPointLight\nimport ch... | [
[
"numpy.array",
"numpy.empty",
"numpy.zeros",
"numpy.tile",
"numpy.repeat",
"numpy.vstack"
]
] |
holyseven/WassersteinGAN.tensorflow | [
"29b51b5aefc97537eb148d4ea353ca12d268c166"
] | [
"utils.py"
] | [
"__author__ = 'shekkizh'\n# Utils used with tensorflow implemetation\nimport tensorflow as tf\nimport numpy as np\nimport scipy.misc as misc\nimport os, sys\nfrom six.moves import urllib\nimport tarfile\nimport zipfile\nfrom tqdm import trange\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1 import Im... | [
[
"tensorflow.constant_initializer",
"tensorflow.nn.conv2d",
"tensorflow.nn.lrn",
"tensorflow.ones",
"tensorflow.control_dependencies",
"tensorflow.nn.avg_pool",
"tensorflow.python.training.moving_averages.assign_moving_average",
"tensorflow.identity",
"tensorflow.summary.histogr... |
marc-h-lambert/L-RVGA | [
"e7cd0c9745c87fb68828f28b1856a9616da933b1"
] | [
"XP_LRVGA_LinearRegression.py"
] | [
"###################################################################################\n# THE KALMAN MACHINE LIBRARY #\n# Code supported by Marc Lambert #\n############################################################... | [
[
"numpy.array",
"matplotlib.ticker.MultipleLocator",
"numpy.zeros",
"numpy.random.seed",
"matplotlib.pyplot.savefig",
"numpy.ones",
"matplotlib.ticker.LogLocator",
"numpy.identity",
"matplotlib.pyplot.tight_layout"
]
] |
Koushul/FindAllRNA | [
"a2c41831f67be2cd52629ebc2ef24cfca3e172f5"
] | [
"FindAllRNA/Archieved/models.py"
] | [
"import os\n\nimport warnings\n\nfrom encoders import AbstractSequenceEncoder\nwarnings.simplefilter(action='ignore', category=FutureWarning)\n\nimport tensorflow as tf\nfrom tensorflow import keras\nimport numpy as np\n# from tensorflow.python.keras.backend import GraphExecutionFunction\n\nfrom tensorflow.keras.la... | [
[
"tensorflow.keras.layers.Conv1D",
"tensorflow.keras.layers.Flatten",
"tensorflow.keras.layers.MaxPooling1D",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.Dropout",
"tensorflow.keras.layers.LeakyReLU",
"tensorflow.keras.Sequential",
"tensorflow.keras.layers.GaussianNois... |
Unprocessable/pandas | [
"2c8e53efa2f5c6470a9d65da55461f3d3ea9b961"
] | [
"pandas/core/reshape/pivot.py"
] | [
"import numpy as np\n\nfrom pandas.util._decorators import Appender, Substitution\n\nfrom pandas.core.dtypes.cast import maybe_downcast_to_dtype\nfrom pandas.core.dtypes.common import is_integer_dtype, is_list_like, is_scalar\nfrom pandas.core.dtypes.generic import ABCDataFrame, ABCSeries\n\nimport pandas.core.comm... | [
[
"pandas.util._decorators.Substitution",
"pandas.core.common.maybe_make_list",
"pandas.core.dtypes.common.is_scalar",
"pandas.DataFrame",
"pandas.core.dtypes.cast.maybe_downcast_to_dtype",
"pandas.core.series.Series",
"pandas.core.index._get_objs_combined_axis",
"pandas.core.index.M... |
BoChenGroup/Pydpm | [
"7498f195665f60e56700f57bc6c6c24896dc7485"
] | [
"pydpm/_model/_cpgbn.py"
] | [
"\"\"\"\n===========================================\nConvolutional Poisson Gamma Belief Network\nChaojie Wang Sucheng Xiao Bo Chen and Mingyuan Zhou\nPublished in International Conference on Machine Learning 2019\n\n===========================================\n\n\"\"\"\n\n# Author: Chaojie Wang <xd_silly@163.c... | [
[
"numpy.dot",
"numpy.random.rand",
"numpy.sum",
"numpy.ones",
"numpy.load",
"numpy.save",
"numpy.where"
]
] |
ch135/pyCFTrack | [
"18cf5b36b9b4796b44640357f32eadca963ccc07"
] | [
"cftracker/kcf.py"
] | [
"\nimport numpy as np\nimport cv2\nfrom lib.utils import cos_window,gaussian2d_rolled_labels\nfrom lib.fft_tools import fft2,ifft2\nfrom .base import BaseCF\nfrom .feature import extract_hog_feature,extract_cn_feature\n\nclass KCF(BaseCF):\n def __init__(self, padding=1.5, features='gray', kernel='gaussian'):\n ... | [
[
"numpy.array",
"numpy.clip",
"numpy.mean",
"numpy.argmax",
"numpy.conj",
"numpy.sqrt",
"numpy.size",
"numpy.floor"
]
] |
duyniem/tsai | [
"5eb1c375883986a3ebba5a2f8eddf2e4b9f86f85"
] | [
"tsai/data/validation.py"
] | [
"# AUTOGENERATED! DO NOT EDIT! File to edit: nbs/000b_data.validation.ipynb (unless otherwise specified).\n\n__all__ = ['check_overlap', 'check_splits_overlap', 'leakage_finder', 'balance_idx', 'TrainValidTestSplitter',\n 'plot_splits', 'get_splits', 'TSSplitter', 'TimeSplitter', 'get_predefined_splits', ... | [
[
"sklearn.model_selection.KFold",
"matplotlib.patches.Patch",
"sklearn.model_selection.StratifiedKFold"
]
] |
josborne-noaa/PyFerret | [
"8496508e9902c0184898522e9f89f6caea6d4539"
] | [
"pyfermod/stats/stats_stats.py"
] | [
"\"\"\"\nReturns the (unweighted) mean, variance, skew, and kurtoses\nof an array of values\n\"\"\"\n\nfrom __future__ import print_function\n\nimport math\nimport numpy\nimport pyferret\nimport scipy.stats\n\n\ndef ferret_init(id):\n \"\"\"\n Initialization for the stats_stats.py Ferret PyEF\n \"\"\"\n ... | [
[
"numpy.logical_not",
"numpy.array",
"numpy.isnan",
"numpy.empty",
"numpy.ones",
"numpy.mean",
"numpy.allclose",
"numpy.fabs",
"numpy.power",
"numpy.var"
]
] |
movingpictures83/Transform | [
"229e5ebc9015ee34f62bf68a2cc15b2b1756784f"
] | [
"TransformPlugin.py"
] | [
"import sys\nimport numpy\nimport math\nclass TransformPlugin:\n def input(self, filename):\n self.myfile = filename\n\n def run(self):\n filestuff = open(self.myfile, 'r')\n self.firstline = filestuff.readline()\n lines = []\n for line in filestuff:\n lines.append(line)\n\n ... | [
[
"numpy.zeros"
]
] |
taokz/FuzzyFL | [
"337a4a52e006db2dfb10b53d2c141a812c9adb21"
] | [
"gaussian_mf.py"
] | [
"\"\"\"\nImplementation of gaussian membership function\n\nAuthor: Kai Zhang (www.kaizhang.us)\nhttps://github.com/taokz\n\"\"\"\n\nimport numpy as np \n\ndef gaussmf(elements, mean, sigma):\n\t\"\"\"\n\tinput:\n\t\telements: (array) elements of the set\n\t\tmean: (real) mean of the set\n\t\tsigma (real) standart d... | [
[
"numpy.square",
"numpy.dot",
"numpy.linalg.inv",
"numpy.exp"
]
] |
beyucel/gpytorch | [
"a5394937495756945b831d83035349579d8fac31",
"a5394937495756945b831d83035349579d8fac31"
] | [
"gpytorch/utils/transforms.py",
"test/lazy/test_block_diag_lazy_tensor.py"
] | [
"#!/usr/bin/env python3\n\nimport torch\n\n\ndef inv_softplus(x):\n return torch.log(torch.exp(x) - 1)\n\n\ndef inv_sigmoid(x):\n return torch.log(x / (1 - x))\n\n\ndef _get_inv_param_transform(param_transform, inv_param_transform=None):\n reg_inv_tf = TRANSFORM_REGISTRY.get(param_transform, None)\n if ... | [
[
"torch.log",
"torch.exp"
],
[
"torch.zeros",
"torch.eye",
"torch.randn"
]
] |
bchao1/stereo-magnification | [
"031376675430a459f4bde768eb5c652f1d22a0a4"
] | [
"geometry/projector.py"
] | [
"#!/usr/bin/python\n#\n# Copyright 2018 Google LLC\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by app... | [
[
"tensorflow.zeros",
"tensorflow.concat",
"tensorflow.expand_dims",
"tensorflow.matmul",
"tensorflow.contrib.resampler.resampler",
"tensorflow.meshgrid",
"tensorflow.reshape",
"tensorflow.transpose",
"tensorflow.ones_like",
"tensorflow.constant",
"tensorflow.ones",
"... |
Karthik-Git-Sudo786/cisco-kubeflow-starter-pack | [
"49013953c0cf0de508bb05f1837809d84e6ea2d2"
] | [
"apps/networking/network-traffic/onprem/pipelines/custom_visualization.py"
] | [
"\nfrom sklearn.metrics import precision_recall_curve\nimport matplotlib.pyplot as plt\nrd = pd.read_excel('network_source.xlsx',index=None,sheet_name='Sheet1')\nprecision, recall, _ = precision_recall_curve(np.array(rd['actual']),np.array(rd['pred']))\nplt.step(recall, precision, color='g', alpha=0.2, where='post'... | [
[
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.step",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.figure",
"matplotlib.pyplot.fill_between",
"matplotlib.pyplot.ylabel... |
TensorVision/MediSeg | [
"222fcab98d82f48f09304eda3cfbfe4d6ac825b7"
] | [
"AP3/basic_local_classifier.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"A basic classifier which uses only local features.\"\"\"\n\nimport os.path\nfrom PIL import Image\nimport scipy.misc\nimport scipy.ndimage\n\nimport logging\nimport sys\nimport time\nimport numpy as np\nimport json\n\nlogging.basicConfig(format='%(asctime)s %... | [
[
"numpy.concatenate",
"numpy.array",
"numpy.zeros",
"sklearn.utils.shuffle"
]
] |
harisankarh/IndianNLP-Transliteration | [
"0e0dd8139c75477346c985201b51315b3a4e4f48"
] | [
"tasks/rnn_xlit_runner.py"
] | [
"''' RNN Seq2Seq (Encoder-Decoder) training setup\n'''\n\nimport torch\nfrom torch.utils.data import DataLoader\nimport numpy as np\nimport os\nimport sys\nimport json\nfrom tqdm import tqdm\nimport utilities.running_utils as rutl\nfrom utilities.lang_data_utils import XlitData, GlyphStrawboss, merge_xlit_jsons\nfr... | [
[
"torch.nn.CrossEntropyLoss",
"torch.no_grad",
"torch.manual_seed",
"torch.cuda.is_available",
"torch.utils.data.DataLoader",
"torch.mean"
]
] |
am-3/TimeZoned | [
"e8ae2e90c2d6addf13b145aa2a4c7a9a66c1346e"
] | [
"progs/timezonefinder-master/timezonefinder-master/timezonefinder/helpers.py"
] | [
"# -*- coding:utf-8 -*-\nfrom math import asin, atan2, ceil, cos, degrees, floor, radians, sin, sqrt\n\nfrom numpy import int64\n\nfrom timezonefinder.global_settings import COORD2INT_FACTOR, INT2COORD_FACTOR, MAX_HAVERSINE_DISTANCE\n\n\ndef inside_polygon(x, y, coordinates):\n \"\"\"\n Implementing the ray c... | [
[
"numpy.int64"
]
] |
jialinwu17/seg_every_thing | [
"46f1c371136372f81efe986a34f6154ffec48063"
] | [
"lib/core/test.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.zeros_like",
"numpy.array",
"numpy.zeros",
"numpy.round",
"numpy.tile",
"numpy.exp",
"numpy.mean",
"numpy.where",
"numpy.savez",
"numpy.amax",
"numpy.vstack",
"numpy.sort",
"numpy.expand_dims",
"numpy.hstack",
"numpy.unique",
"numpy.maximum"
... |
open-mmlab/mmflow | [
"203ea55ad8a4f99fcb394371aa0ba4423d3debcc"
] | [
"mmflow/utils/collect_env.py"
] | [
"# Copyright (c) OpenMMLab. All rights reserved.\nimport os.path as osp\nimport subprocess\nimport sys\nfrom collections import defaultdict\n\nimport cv2\nimport mmcv\nimport torch\nimport torchvision\nfrom mmcv.utils import get_build_config, get_git_hash\n\nimport mmflow\n\n\ndef collect_env() -> dict:\n \"\"\"... | [
[
"torch.cuda.is_available",
"torch.cuda.get_device_name",
"torch.cuda.device_count"
]
] |
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