repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
HamidDoost/ImageProcessing | [
"cc63f6485f5ec2dc2cb8099533a3c0a2fbfe0c47"
] | [
"Shi_Thomas_corner_keypoints.py"
] | [
"'''\r\n===============================================================================\r\n-- Author: Hamid Doostmohammadi, Azadeh Nazemi\r\n-- Create date: 05/11/2020\r\n-- Description:\tThis code is for detection of corners keypoints by Shi-Thomas method. \r\n-- Status: In progress\r\n==================... | [
[
"numpy.int0"
]
] |
syberflea/materials | [
"c17c4a4d6f8487e59eac1df8c88ca92b73d6d2a5"
] | [
"pandas-gradebook-project/04-grouping-the-data.py"
] | [
"\"\"\"Calculate student grades by combining data from many sources.\n\nUsing Pandas, this script combines data from the:\n\n* Roster\n* Homework & Exam grades\n* Quiz grades\n\nto calculate final grades for a class.\n\"\"\"\nfrom pathlib import Path\nimport pandas as pd\nimport numpy as np\n\nHERE = Path(__file__)... | [
[
"pandas.merge",
"pandas.read_csv",
"pandas.concat",
"pandas.Series",
"pandas.DataFrame",
"numpy.ceil"
]
] |
SPECTRELWF/pytorch-cnn-study | [
"5c6a07f110ef973b1a910a528cdc0464efc2126d",
"5c6a07f110ef973b1a910a528cdc0464efc2126d"
] | [
"Densenet_COVID/densenet.py",
"Alexnet-MNIST/train.py"
] | [
"# !/usr/bin/python3\n# -*- coding:utf-8 -*-\n# Author:WeiFeng Liu\n# @Time: 2021/11/9 下午4:57\n\nimport torchvision\nimport torch.nn as nn\n\n\n\nclass my_densenet(nn.Module):\n def __init__(self):\n super(my_densenet, self).__init__()\n self.backbone = torchvision.models.densenet121(pretrained=Fal... | [
[
"torch.nn.Linear"
],
[
"torch.nn.CrossEntropyLoss",
"torch.cuda.is_available"
]
] |
lutqiys/smc-oopsi | [
"5856aab3fed0b711923a918848ab255911a66ba4"
] | [
"code/python/smc.py"
] | [
"import numpy, pylab, matplotlib\nimport random, os, bisect, re\n\n\nclass Variables(object):\n \"\"\"variables specifying the particulars of the trace and the preferences of the user.\"\"\"\n def __init__(self, F, dt, \n x=None, #stimulus (zeros vector of length T that has 1s in the frames ... | [
[
"numpy.log",
"numpy.imag",
"numpy.sqrt",
"numpy.min",
"numpy.power",
"numpy.arange",
"numpy.isnan",
"numpy.ones",
"numpy.finfo",
"numpy.max",
"numpy.random.normal",
"numpy.mean",
"numpy.random.uniform",
"numpy.repeat",
"numpy.exp",
"numpy.zeros",
... |
saltwater-tensor/POT | [
"9412f0ad1c0003e659b7d779bf8b6728e0e5e60f"
] | [
"ot/weak.py"
] | [
"\"\"\"\nWeak optimal ransport solvers\n\"\"\"\n\n# Author: Remi Flamary <remi.flamary@polytehnique.edu>\n#\n# License: MIT License\n\nfrom .backend import get_backend\nfrom .optim import cg\nimport numpy as np\n\n__all__ = ['weak_optimal_transport']\n\n\ndef weak_optimal_transport(Xa, Xb, a=None, b=None, verbose=F... | [
[
"numpy.dot",
"numpy.ones"
]
] |
SeanSyue/Insightface-IJB-release | [
"17b8bbc1ec48228ea30ce86114cc3f226fd47478"
] | [
"recognition/embedding.py"
] | [
"import argparse\nimport cv2\nimport numpy as np\nimport sys\nimport mxnet as mx\nimport datetime\nfrom skimage import transform as trans\nimport sklearn\nfrom sklearn import preprocessing\n\nclass Embedding:\n def __init__(self, prefix, epoch, ctx_ids=None):\n if ctx_ids is None:\n ctx_ids = [0]\n prin... | [
[
"numpy.fliplr",
"numpy.array",
"numpy.zeros",
"numpy.transpose"
]
] |
kjanjua26/dispflownet-tf | [
"569d334275839e6ec33af04c06604ab9a8488bb2"
] | [
"inference.py"
] | [
"import argparse\nimport tensorflow as tf\nimport numpy as np\nimport os\nfrom dispnet import DispNet\nfrom util import get_var_to_restore_list\nfrom matplotlib import pyplot as plt\nimport cv2\n\n# INPUT_SIZE = (384, 768, 3)\n# INPUT_SIZE = (540, 960, 3)\nDOWNGRADE_FACTOR = 64\n\ndef pad_image(immy,down_factor = D... | [
[
"tensorflow.floordiv",
"numpy.squeeze",
"tensorflow.equal",
"tensorflow.GPUOptions",
"tensorflow.image.decode_image",
"tensorflow.train.input_producer",
"numpy.where",
"tensorflow.read_file",
"tensorflow.ConfigProto",
"tensorflow.train.Saver",
"matplotlib.pyplot.figure"... |
nanpuhaha/SerpentAI-Image | [
"3e7d4c134e4a52bad5f9ce9af95717b05ce3f34f"
] | [
"serpent_image/image.py"
] | [
"import io\nimport pathlib\nimport uuid\n\nimport numpy as np\n\nimport skimage.io\nimport skimage.color\nimport skimage.filters\nimport skimage.metrics\nimport skimage.morphology\nimport skimage.segmentation\nimport skimage.transform\n\nfrom PIL import Image as PILImage\n\nfrom sklearn.cluster import KMeans\n\n\nc... | [
[
"sklearn.cluster.KMeans",
"numpy.min",
"numpy.empty_like",
"numpy.dstack",
"numpy.full",
"numpy.full_like",
"numpy.max",
"numpy.mean",
"numpy.array",
"numpy.where",
"numpy.sum"
]
] |
wenh18/OnDeviceNAS | [
"d6e39500b794ddd9737ef4bc631cf4f977b47617",
"d6e39500b794ddd9737ef4bc631cf4f977b47617"
] | [
"mytimm/models/layers/split_batchnorm.py",
"mytimm/models/efficientnet_blocks.py"
] | [
"\"\"\" Split BatchNorm\n\nA PyTorch BatchNorm layer that splits input batch into N equal parts and passes each through\na separate BN layer. The first split is passed through the parent BN layers with weight/bias\nkeys the same as the original BN. All other splits pass through BN sub-layers under the '.aux_bn'\nna... | [
[
"torch.nn.BatchNorm2d",
"torch.cat"
],
[
"torch.nn.Linear",
"torch.nn.Identity",
"torch.nn.Conv2d",
"torch.nn.functional.adaptive_avg_pool2d"
]
] |
AlexBlack2202/iou-tracker | [
"fe53ac5533dbc0ed20919c15ebba5abae1b38e30"
] | [
"util.py"
] | [
"# ---------------------------------------------------------\n# IOU Tracker\n# Copyright (c) 2017 TU Berlin, Communication Systems Group\n# Licensed under The MIT License [see LICENSE for details]\n# Written by Erik Bochinski\n# ---------------------------------------------------------\n\nimport numpy as np\nimport... | [
[
"numpy.max",
"numpy.genfromtxt"
]
] |
rckitson/machine_learning | [
"842bbf2ed095cb45617b011b8738851cab7bbfb1",
"842bbf2ed095cb45617b011b8738851cab7bbfb1"
] | [
"trafficSimulation/traffic.py",
"optimizers/test_optimizer.py"
] | [
"#!/opt/anaconda3/bin/python3\n\"\"\" Class definitions and a main routine to simulate traffic \"\"\"\nimport os\nimport subprocess\nimport glob\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\nclass Car:\n \"\"\" A class for modeling cars in traffic \"\"\"\n\n def __init__(self, aggression=1.0, ahea... | [
[
"matplotlib.pyplot.scatter",
"matplotlib.pyplot.ylim",
"numpy.arange",
"numpy.cos",
"numpy.sin",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.close",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pyplot.legend",
"numpy.random.random",
"nu... |
YosefLab/scVI | [
"73952af10292852b8e5b7319409678cc66d85a47",
"73952af10292852b8e5b7319409678cc66d85a47",
"73952af10292852b8e5b7319409678cc66d85a47"
] | [
"scvi/dataloaders/_semi_dataloader.py",
"scvi/module/base/_base_module.py",
"scvi/model/_autozi.py"
] | [
"from typing import List, Optional, Union\n\nimport numpy as np\n\nfrom scvi import REGISTRY_KEYS\nfrom scvi.data import AnnDataManager\nfrom scvi.data._utils import get_anndata_attribute\n\nfrom ._concat_dataloader import ConcatDataLoader\n\n\nclass SemiSupervisedDataLoader(ConcatDataLoader):\n \"\"\"\n Data... | [
[
"numpy.random.choice",
"numpy.asarray",
"numpy.arange",
"numpy.unique",
"numpy.concatenate",
"numpy.where"
],
[
"torch.tensor"
],
[
"numpy.log",
"torch.zeros",
"torch.distributions.Beta",
"numpy.arange",
"torch.sum",
"torch.no_grad",
"torch.logsumexp... |
joelhaynie/cs760_final_project | [
"85f19be8fdc046dff3e1325e1ef85aca702d4000"
] | [
"src/vggish_inference_demo.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 requi... | [
[
"tensorflow.Graph",
"scipy.io.wavfile.write",
"numpy.clip",
"numpy.sin",
"tensorflow.python_io.TFRecordWriter",
"tensorflow.Session",
"tensorflow.app.run"
]
] |
varunjha089/tensorflow_cookbook | [
"94af4606dd918fe446984670560fb11190b97bc5",
"c1fa5051c860ecb6de875db975465ced06f43ba6",
"c1fa5051c860ecb6de875db975465ced06f43ba6",
"c1fa5051c860ecb6de875db975465ced06f43ba6"
] | [
"03_Linear_Regression/04_Loss_Functions_in_Linear_Regressions/04_lin_reg_l1_vs_l2.py",
"07_Natural_Language_Processing/02_Working_with_Bag_of_Words/02_bag_of_words.py",
"07_Natural_Language_Processing/07_Sentiment_Analysis_With_Doc2Vec/07_sentiment_with_doc2vec.py",
"08_Convolutional_Neural_Networks/05_Stylen... | [
"# Linear Regression: L1 vs L2\n#----------------------------------\n#\n# This function shows how to use TensorFlow to\n# solve linear regression via the matrix inverse.\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport tensorflow as tf\nfrom sklearn import datasets\nfrom tensorflow.python.framework im... | [
[
"matplotlib.pyplot.legend",
"tensorflow.matmul",
"matplotlib.pyplot.title",
"sklearn.datasets.load_iris",
"tensorflow.placeholder",
"matplotlib.pyplot.plot",
"tensorflow.global_variables_initializer",
"tensorflow.abs",
"tensorflow.train.GradientDescentOptimizer",
"tensorflo... |
pcwuyu/PaddleGAN | [
"b4ff90f0c92c4d8dcaa8e25267151b82fc7aa268",
"b4ff90f0c92c4d8dcaa8e25267151b82fc7aa268"
] | [
"ppgan/models/starganv2_model.py",
"ppgan/models/generators/msvsr.py"
] | [
"# code was heavily based on https://github.com/clovaai/stargan-v2\n# Users should be careful about adopting these functions in any commercial matters.\n# https://github.com/clovaai/stargan-v2#license\n\nfrom paddle.fluid.layers.nn import soft_relu\nfrom .base_model import BaseModel\n\nfrom paddle import nn\nimport... | [
[
"numpy.ones"
],
[
"numpy.zeros"
]
] |
Stanford-ILIAD/Learn-Imperfect-Varying-Dynamics | [
"25191f7b076033ac9dbe8fd08f2a92e3caa57cb3"
] | [
"imperfect_envs/driving/envs/gridworld_continuous.py"
] | [
"import io\nfrom typing import Text\nimport gym\nfrom gym import spaces\nfrom PIL import Image\nimport numpy as np\nimport scipy.special\nfrom driving.world import World\nfrom driving.entities import TextEntity, Entity\nfrom driving.agents import Car, Building, Goal\nfrom driving.geometry import Point\nfrom typing ... | [
[
"numpy.cos",
"numpy.linalg.norm",
"numpy.sin",
"numpy.append",
"numpy.array"
]
] |
z8674558/idocp | [
"946524db7ae4591b578be2409ca619961572e7be"
] | [
"examples/anymal/python/trotting.py"
] | [
"import idocp\nimport numpy as np\nimport math\n\n\nLF_foot_id = 12\nLH_foot_id = 22\nRF_foot_id = 32\nRH_foot_id = 42\ncontact_frames = [LF_foot_id, LH_foot_id, RF_foot_id, RH_foot_id] \npath_to_urdf = '../anymal_b_simple_description/urdf/anymal.urdf'\nbaumgarte_time_step = 0.04\nrobot = idocp.Robot(path_to_urdf, ... | [
[
"numpy.array",
"numpy.zeros",
"numpy.full"
]
] |
rajatbansal01/Bulk-Email-Sender | [
"6f0f40167eddefaddf7a2353335a8b38cf285bca"
] | [
"code.py"
] | [
"import smtplib\nimport pandas as pd\n\n#Read Emails\ne=pd.read_excel('emails.xlsx') #here provide the excel file which is contaning the email addresses.\nemails_to_send=e['students'].values #students is the header for the emails.\nprint(emails_to_send)\n\n#Create and log to server\nserver = smtplib.SMTP('smtp.gmai... | [
[
"pandas.read_excel"
]
] |
FreJoe/federated | [
"124947b8b354f381fcb9726e0f055756ed626860"
] | [
"tensorflow_federated/python/core/impl/transforming_executor_test.py"
] | [
"# Lint as: python3\n# Copyright 2019, The TensorFlow Federated 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# ... | [
[
"tensorflow.compat.v1.enable_v2_behavior"
]
] |
gimac/OpenRadar | [
"cab1b60ebc69be635860e474b2b6564a25befb5c"
] | [
"mmwave/dataloader/adc.py"
] | [
"# Copyright 2019 The OpenRadar Authors. All Rights Reserved.\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n# http://www.apache.org/licenses/LICENSE-2.0\n# Unless required by ap... | [
[
"numpy.frombuffer",
"numpy.zeros"
]
] |
opendifferentialprivacy/smartnoise-sdk | [
"34154e5a45ef8ea1ced72bcbad44e0bf35ded872"
] | [
"sql/snsql/reader/base.py"
] | [
"import pandas as pd\n\n\nclass Reader:\n ENGINE = None\n\n @property\n def engine(self):\n return self.ENGINE.lower() if self.ENGINE else None\n\n def execute(self, query, *ignore, accuracy: bool = False):\n raise NotImplementedError(\"Execute must be implemented on the inherited class\")... | [
[
"pandas.DataFrame"
]
] |
Chenlu-Wu/CarND-LaneLines | [
"db836515cbd8064c78ced5fe7a90ba06e8292603"
] | [
"lane_line_tracking.py"
] | [
"#importing some useful packages\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nimport numpy as np\nimport cv2\nimport os\nimport math\nget_ipython().run_line_magic('matplotlib', 'inline')\n\n\ndef grayscale(img):\n \"\"\"Applies the Grayscale transform\n This will return an image with on... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.image.imread",
"numpy.zeros_like",
"numpy.array",
"numpy.zeros",
"matplotlib.pyplot.figure"
]
] |
Taye310/hmd | [
"46d453392213b8ead39f8e850054fc7bbb81146b"
] | [
"eval/pred_hmd_ja.py"
] | [
"import numpy as np\nimport cv2, argparse, pickle, sys, PIL.Image\nimport openmesh as om\nfrom tqdm import trange\nsys.path.append(\"../src/\")\nfrom predictor import joint_predictor\nfrom predictor import anchor_predictor\nfrom mesh_edit import fast_deform_dja\nfrom mesh_edit import fast_deform_dsa\nfrom renderer ... | [
[
"numpy.rollaxis",
"numpy.expand_dims",
"numpy.absolute",
"numpy.asarray",
"numpy.ones",
"numpy.concatenate",
"numpy.round",
"numpy.zeros_like",
"numpy.load",
"numpy.array",
"numpy.zeros"
]
] |
gwallison/OH_injection_wells_compile | [
"70ffd6bfc99932d1364574335cc289ca23390655",
"70ffd6bfc99932d1364574335cc289ca23390655"
] | [
"processInjectionInput.py",
"Injection_Wells1.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Sat Dec 1 09:21:40 2018\n\n@author: @gary.allison\n\nThis code is used to take ODNR files for Brine disposal fee and \neventually create a file to be used to show overall injection volumes.\n\nThe ODNR data have several limitations that we must find and account for: \n ... | [
[
"pandas.merge",
"pandas.read_excel",
"pandas.concat",
"pandas.api.types.is_numeric_dtype",
"pandas.DataFrame",
"pandas.api.types.is_string_dtype",
"pandas.to_numeric"
],
[
"pandas.concat",
"pandas.read_excel",
"pandas.merge",
"pandas.to_numeric",
"pandas.DataFra... |
FGlazov/IL2Stats_ByAircraftMod | [
"acf66eb3f31a7e789d61a5c60d32fd30dbcedf4b"
] | [
"src/mod_stats_by_aircraft/reservoir_sampling.py"
] | [
"import json\nimport random\n\nimport numpy as np\n\nSAMPLE = 'SAMPLE' # A sample of ammo breakdowns. Holds up to SAMPLE_SIZE many elements.\nSAMPLE_SIZE = 50\nRESERVOIR_COUNTER = 'RESERVOIR_COUNTER' # Helper int that is used for \"reservoir sampling\", single pass fair sampling.\n\n\n# https://stackoverflow.com/... | [
[
"numpy.asarray",
"numpy.append",
"numpy.empty"
]
] |
RonKbS/pandas | [
"ba1b6571bd507c27072900d778adf81a99affc7a",
"ba1b6571bd507c27072900d778adf81a99affc7a",
"ba1b6571bd507c27072900d778adf81a99affc7a",
"ba1b6571bd507c27072900d778adf81a99affc7a"
] | [
"pandas/core/dtypes/missing.py",
"pandas/tests/extension/arrow/test_bool.py",
"pandas/tests/arithmetic/test_period.py",
"pandas/tests/util/test_assert_almost_equal.py"
] | [
"\"\"\"\nmissing types & inference\n\"\"\"\nimport numpy as np\n\nfrom pandas._config import get_option\n\nfrom pandas._libs import lib\nimport pandas._libs.missing as libmissing\nfrom pandas._libs.tslibs import NaT, iNaT\n\nfrom .common import (\n _NS_DTYPE,\n _TD_DTYPE,\n ensure_object,\n is_bool_dtyp... | [
[
"pandas._libs.missing.checknull",
"numpy.array_equal",
"numpy.isfinite",
"numpy.asarray",
"numpy.isnan",
"pandas._libs.lib.is_scalar",
"pandas._config.get_option",
"pandas._libs.missing.checknull_old",
"pandas._libs.lib.values_from_object",
"numpy.prod",
"numpy.array",
... |
cpadavis/piffy3pipeline | [
"c12f8e719d45409b85c20e34479d7ff238a1247d"
] | [
"collect.py"
] | [
"\"\"\"\nCollect fit parameters and plot their values\n\nCalculate stats over full set of stars\n\nMostly just copied form stats rho stats\n\"\"\"\nfrom __future__ import print_function, division\nimport glob\nimport galsim\nimport treecorr\nimport numpy as np\nimport os\nfrom matplotlib.figure import Figure\nfrom ... | [
[
"pandas.merge",
"numpy.sqrt",
"pandas.DataFrame",
"numpy.square",
"pandas.read_csv",
"matplotlib.backends.backend_agg.FigureCanvasAgg",
"numpy.arange",
"pandas.cut",
"numpy.ma.zeros",
"pandas.read_hdf",
"pandas.concat",
"numpy.logspace",
"numpy.multiply.at",
... |
surprisedong/RepDistiller | [
"91e34141588524a4bf628873552b4919db8506ca"
] | [
"helper/loops.py"
] | [
"from __future__ import print_function, division\n\nimport sys\nimport time\nimport torch\nimport pdb\nfrom .util import AverageMeter, accuracy\nimport math\n\ndef train_vanilla(epoch, train_loader, model, criterion, optimizer, opt):\n \"\"\"vanilla training\"\"\"\n model.train()\n\n batch_time = AverageMe... | [
[
"torch.no_grad",
"torch.cuda.is_available"
]
] |
jmontgom10/pyPol | [
"7c63475856256fa754cb1df04dac4dce9eff7bd8"
] | [
"01_buildIndex.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nRestructures the rawFileIndex from PRISM_pyBDP to contain ONLY the science\nimages, and break those up into individual groups based on changes in\n\n1) OBJECT (object name)\n2) FILTER (optical filter value)\n3) EXPTIME (the exposure time of the images)\n4) BINNING (the 1x1, 2x2, 3x... | [
[
"numpy.sqrt",
"numpy.unique",
"numpy.cos",
"numpy.logical_or",
"numpy.array",
"numpy.where"
]
] |
abhyuday07/market-plots | [
"335fb5f09a64471cf6260cc9f306d0fcd91cb4b2"
] | [
"variance.py"
] | [
"import sys\nimport numpy as np\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport pathlib\nimport matplotlib.style as style\n\nimport alpha_vantage\nimport plot_style\n\n\ndef show_variance(symbol, interval='MONTHLY'):\n returns = alpha_vantage.get_stock_returns_history(symbol, interval)\n variance ... | [
[
"matplotlib.pyplot.gca",
"numpy.sqrt",
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.savefig",
"numpy.mean",
"matplotlib.pyplot.close",
"numpy.var",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.hist",
"matplotlib.pyplot.ylabel"
]
] |
PacktPublishing/The-Deep-Learning-Challenge | [
"0539bd010b67cc6a7d53b59d7a32fc72051eb216"
] | [
"Section 2/source/solution2.py"
] | [
"# Alternative solutions:\n# - Get classes names from:\n# ~/.keras/models/imagenet_class_index.json\n# - Get classes at http://image-net.org/challenges/LSVRC/2014/browse-synsets\nimport conf\nfrom keras.applications.vgg19 import VGG19\nfrom keras.applications.vgg19 import decode_predictions\nimport numpy as np\nf... | [
[
"numpy.ones"
]
] |
fzahle/OpenMDAO | [
"709401e535cf6933215abd942d4b4d49dbf61b2b",
"709401e535cf6933215abd942d4b4d49dbf61b2b",
"709401e535cf6933215abd942d4b4d49dbf61b2b",
"ce53b0a0862ac1162d5daad7b0ca34ae085ee47c",
"ce53b0a0862ac1162d5daad7b0ca34ae085ee47c"
] | [
"openmdao/core/tests/test_driver.py",
"openmdao/solvers/linear/tests/test_linear_block_jac.py",
"openmdao/test_suite/components/misc_components.py",
"openmdao/core/tests/test_group.py",
"openmdao/solvers/solver.py"
] | [
"\"\"\" Unit tests for the Driver base class.\"\"\"\n\nfrom __future__ import print_function\n\nfrom distutils.version import LooseVersion\nfrom six import StringIO\nimport sys\nimport unittest\n\nimport numpy as np\n\nimport openmdao\nfrom openmdao.api import Problem, IndepVarComp, Group, ExecComp, ScipyOptimizeDr... | [
[
"numpy.array",
"numpy.zeros",
"numpy.isinf",
"numpy.ones"
],
[
"numpy.array"
],
[
"numpy.sqrt"
],
[
"numpy.arange",
"numpy.ones",
"numpy.array",
"numpy.zeros",
"numpy.sum"
],
[
"numpy.isnan",
"numpy.isinf"
]
] |
lilyminium/openff-toolkit | [
"a5ed656b84e1999560f4898a87f238a6ddf0aac6"
] | [
"openff/toolkit/utils/toolkits.py"
] | [
"#!/usr/bin/env python\n\"\"\"\nWrapper classes for providing a minimal consistent interface to cheminformatics toolkits\n\nCurrently supported toolkits:\n\n* The `OpenEye Toolkit <https://docs.eyesopen.com/toolkits/python/quickstart-python/index.html>`_\n* The `RDKit <http://www.rdkit.org/>`_\n* `AmberTools <http:... | [
[
"numpy.square",
"numpy.all",
"numpy.mean",
"numpy.fill_diagonal",
"numpy.iinfo",
"numpy.zeros_like",
"numpy.ma.array",
"numpy.zeros",
"numpy.isclose"
]
] |
Dahk/pywren-ibm-cloud | [
"560a587e35dfe8f6dff4b85cc4bc722ec5f7fd9d"
] | [
"lithops/plots.py"
] | [
"#\n# (C) Copyright IBM Corp. 2020\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or ag... | [
[
"matplotlib.patches.Patch",
"numpy.linspace",
"numpy.arange",
"pandas.DataFrame",
"numpy.max",
"numpy.searchsorted",
"numpy.array"
]
] |
knshnb/optuna | [
"9c3d6685f0814bcbd66d7aaa22d50789d969f8e7",
"9c3d6685f0814bcbd66d7aaa22d50789d969f8e7"
] | [
"tests/test_transform.py",
"tutorial/20_recipes/009_ask_and_tell.py"
] | [
"import math\nfrom typing import Any\n\nimport numpy\nimport pytest\n\nfrom optuna._transform import _SearchSpaceTransform\nfrom optuna._transform import _untransform_numerical_param\nfrom optuna.distributions import BaseDistribution\nfrom optuna.distributions import CategoricalDistribution\nfrom optuna.distributio... | [
[
"numpy.array"
],
[
"numpy.array",
"sklearn.datasets.make_classification",
"sklearn.model_selection.train_test_split",
"sklearn.linear_model.LogisticRegression"
]
] |
yethranayeh/Daily-Mood-Rater | [
"0bf2ee688d066dd01bb388e00172a2d9e15ec043"
] | [
"mood_graph.py"
] | [
"import sys, mood_db\nimport matplotlib.pyplot as plt\nimport mplcursors\nfrom matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas\nfrom PyQt5.QtWidgets import QApplication, QWidget\nfrom PyQt5.QtGui import QIcon\nfrom pathlib import Path\nfrom datetime import datetime\n\ncur_dir = Path.cwd(... | [
[
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.subplot2grid",
"matplotlib.pyplot.ylabel"
]
] |
nileshkulkarni/acsm | [
"83bc7f22582c594a60381fe60ea7b83ec295d93c"
] | [
"acsm/utils/visualizer.py"
] | [
"'''Code adapted from https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix'''\nimport numpy as np\nimport os\nimport ntpath\nimport time\nimport visdom\nfrom . import visutil as util\nfrom . import html\nfrom make_html import HTML\nimport os.path as osp\nimport pdb\nfrom .logger import Logger\n# from loguru impo... | [
[
"numpy.array"
]
] |
vuiseng9/nncf_pytorch | [
"c2b1f069c867327203629201aecae3b7815e7895",
"c2b1f069c867327203629201aecae3b7815e7895",
"c2b1f069c867327203629201aecae3b7815e7895"
] | [
"nncf/experimental/onnx/statistics/statistics.py",
"examples/experimental/torch/classification/bootstrap_nas.py",
"tests/tensorflow/test_sanity_sample.py"
] | [
"\"\"\"\n Copyright (c) 2022 Intel Corporation\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n http://www.apache.org/licenses/LICENSE-2.0\n Unless required by applicable law or agr... | [
[
"numpy.allclose"
],
[
"torch.nn.CrossEntropyLoss"
],
[
"tensorflow.io.gfile.isdir",
"tensorflow.train.latest_checkpoint",
"tensorflow.config.list_physical_devices"
]
] |
swsachith/differential-privacy-library | [
"b5014276204d70c6fb1f0e2aff11fefc1a0d226d"
] | [
"diffprivlib/models/logistic_regression.py"
] | [
"# MIT License\n#\n# Copyright (C) IBM Corporation 2019\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated\n# documentation files (the \"Software\"), to deal in the Software without restriction, including without limitation the\n# rights to use, copy, ... | [
[
"sklearn.utils.check_X_y",
"numpy.sqrt",
"numpy.unique",
"numpy.asarray",
"sklearn.utils.check_array",
"sklearn.utils.multiclass.check_classification_targets",
"sklearn.utils.check_consistent_length",
"scipy.optimize.fmin_l_bfgs_b",
"numpy.linalg.norm",
"numpy.ones",
"s... |
Open-EO/openeo-udf | [
"cdd910c5da1f752991415d8732e5dbdcfeac2366"
] | [
"src/openeo_udf/api/udf_wrapper.py"
] | [
"from openeo_udf.api.datacube import DataCube\nfrom openeo_udf.api.udf_data import UdfData\nfrom typing import Dict, Callable\nimport xarray\nimport numpy\nimport pandas\nfrom pandas import Series\n\n\ndef apply_timeseries(series: Series, context:Dict)->Series:\n \"\"\"\n Do something with the timeseries\n ... | [
[
"numpy.rollaxis",
"numpy.asarray",
"pandas.Series"
]
] |
Naman9639/sunpy | [
"24c0cfbd9b03d7f9554bc86036fac2b78a5fcc56",
"24c0cfbd9b03d7f9554bc86036fac2b78a5fcc56",
"24c0cfbd9b03d7f9554bc86036fac2b78a5fcc56",
"24c0cfbd9b03d7f9554bc86036fac2b78a5fcc56"
] | [
"examples/plotting/simple_differential_rotation.py",
"examples/plotting/great_arc_example.py",
"examples/plotting/aia_example.py",
"sunpy/visualization/wcsaxes_compat.py"
] | [
"\"\"\"\n============================\nSimple Differential Rotation\n============================\n\nThe Sun is known to rotate differentially, meaning that the rotation rate\nnear the poles (rotation period of approximately 35 days) is not the same as\nthe rotation rate near the equator (rotation period of approxi... | [
[
"matplotlib.pyplot.title",
"matplotlib.pyplot.ylim",
"numpy.arange",
"numpy.sin",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.subplot",
"numpy.zeros_like",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"matplotlib.pyplot.subp... |
Medicine-and-Algorithm/sidechainnet | [
"bd3abe3482157380d2221468500aabf468cb82d1",
"bd3abe3482157380d2221468500aabf468cb82d1"
] | [
"sidechainnet/utils/align.py",
"sidechainnet/utils/parse.py"
] | [
"\"\"\"Functionality for aligning protein sequences in ProteinNet vs SidechainNet.\"\"\"\n\nimport numpy as np\nfrom Bio import Align\n\nfrom sidechainnet.structure.build_info import NUM_COORDS_PER_RES, PRODY_CA_DIST\nfrom sidechainnet.utils.download import ASTRAL_ID_MAPPING, determine_pnid_type\nfrom sidechainnet.... | [
[
"numpy.empty",
"numpy.linalg.norm",
"numpy.vstack"
],
[
"numpy.asarray"
]
] |
hunto/image_classification_sota | [
"8264872d58fb1735978fc796fea7e6bceb302eae",
"8264872d58fb1735978fc796fea7e6bceb302eae"
] | [
"tools/convert.py",
"lib/utils/scheduler.py"
] | [
"import os\nimport torch\nimport torch.nn as nn\nimport logging\nimport time\nfrom torch.nn.parallel import DistributedDataParallel as DDP\n\nfrom lib.models.builder import build_model\nfrom lib.models.loss import CrossEntropyLabelSmooth\nfrom lib.models.utils.dbb.dbb_block import DiverseBranchBlock\nfrom lib.datas... | [
[
"torch.nn.CrossEntropyLoss",
"torch.no_grad",
"torch.nn.parallel.DistributedDataParallel"
],
[
"torch.optim.lr_scheduler.LambdaLR",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.optim.lr_scheduler.StepLR"
]
] |
dimasad/ceacoest | [
"4a5eb946e118145d054cac785cc8b4d834c28192"
] | [
"ceacoest/modelling/symquat.py"
] | [
"\"\"\"Symbolic quaterion operations, dynamics and rotations.\"\"\"\n\n\nimport numpy as np\nimport sympy\n\n\ndef derivative(quat, omega, renorm_gain=0):\n [q0, q1, q2, q3] = quat\n [p, q, r] = omega\n err = 1 - (q0**2 + q1**2 + q2**2 + q3**2)\n q0dot = -0.5 * (p*q1 + q*q2 + r*q3) + renorm_gain*err*q0\... | [
[
"numpy.array"
]
] |
ElieKadoche/floris | [
"d18f4d263ecabf502242592f9d60815a07c7b89c"
] | [
"floris/tools/flow_data.py"
] | [
"# Copyright 2021 NREL\n\n# Licensed under the Apache License, Version 2.0 (the \"License\"); you may not\n# use this file except in compliance with the License. You may obtain a copy of\n# the License at http://www.apache.org/licenses/LICENSE-2.0\n\n# Unless required by applicable law or agreed to in writing, soft... | [
[
"sklearn.neighbors.KNeighborsRegressor",
"numpy.min",
"numpy.unique",
"numpy.column_stack"
]
] |
CameronBodine/dash_doodler | [
"6b1936d48bf2f9742d0ddf1225cbb960bef3d8bd"
] | [
"utils/plot_label_generation.py"
] | [
"# Written by Dr Daniel Buscombe, Marda Science LLC\n# for the USGS Coastal Change Hazards Program\n#\n# MIT License\n#\n# Copyright (c) 2020, Marda Science LLC\n#\n# Permission is hereby granted, free of charge, to any person obtaining a copy\n# of this software and associated documentation files (the \"Software\"... | [
[
"matplotlib.pyplot.imshow",
"matplotlib.pyplot.title",
"matplotlib.pyplot.colorbar",
"matplotlib.pyplot.subplot",
"matplotlib.colors.ListedColormap",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.close",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.figure"
]
] |
leoninekev/training-frcnn-google-ml-engine | [
"0df1a4e772c806d35aeb5b74d3394a828489cd9a"
] | [
"move_to_cloudshell/trainer/data_augment.py"
] | [
"import cv2\nimport numpy as np\nimport copy\n\nfrom tensorflow.python.lib.io import file_io\nimport io\n\nfrom PIL import Image\n\ndef url2img(uri):#IO function compliant to loading gs:// url images \n\tfile= file_io.FileIO(uri, mode='rb')\n\tfile = file.read()\n\timg= Image.open(io.BytesIO(file)).convert('RGB')\n... | [
[
"numpy.random.choice",
"numpy.asarray",
"tensorflow.python.lib.io.file_io.FileIO",
"numpy.transpose",
"numpy.random.randint"
]
] |
andrearosasco/DistilledReplay | [
"2a4efa88d22b9afc7016f07549114688f346dbe8",
"2a4efa88d22b9afc7016f07549114688f346dbe8",
"2a4efa88d22b9afc7016f07549114688f346dbe8",
"2a4efa88d22b9afc7016f07549114688f346dbe8"
] | [
"model/cnn2.py",
"pmnist_exp/config_joint.py",
"scifar10_exp/config_naive.py",
"smnist_exp/config_joint.py"
] | [
"import torch.nn as nn\r\nimport torch.nn.functional as F\r\n\r\n\r\nclass Model(nn.Module):\r\n def __init__(self, config):\r\n super(Model, self).__init__()\r\n self.conv1 = nn.Conv2d(3, 16, (3, 3), padding=1)\r\n self.conv1_bn = nn.BatchNorm2d(16)\r\n\r\n self.conv2 = nn.Conv2d(16,... | [
[
"torch.nn.Linear",
"torch.nn.Conv2d",
"torch.nn.BatchNorm2d"
],
[
"torch.FloatTensor"
],
[
"numpy.array"
],
[
"numpy.array",
"torch.FloatTensor",
"numpy.pad"
]
] |
JThissen/machine_learning | [
"82e2b003fb25111dc2d9ac1c1b2fd637e9f4fdbc"
] | [
"recurrent_neural_network_1/program.py"
] | [
"import torch\nimport torch.nn as nn\nimport string\nimport os\nimport time\nimport random\nfrom torch.functional import Tensor\nfrom utils import Utils\nfrom recurrent_neural_network import RecurrentNeuralNetwork\nfrom typing import List, Tuple, Any\n\nclass Program():\n def __init__(self, learning_rate: float = ... | [
[
"torch.nn.NLLLoss",
"torch.no_grad",
"torch.cuda.is_available",
"torch.load"
]
] |
4evernaive/YOLOv3Tiny_Face_Mask | [
"4053aac90d6eaece71662b1fcc96b3d974663bc2"
] | [
"yolo_face.py"
] | [
"import os\nimport numpy as np\nimport cv2.cv2 as cv2\nfrom imutils.video import FPS\nimport argparse\nimport datetime\nimport time\nimport uuid\nimport random\nimport pyimgur\nfrom store_image import storeImage\nfrom linebot import LineBotApi\nfrom fire import getName, getDevice, getLink, getAll\nfrom bigdataProxy... | [
[
"numpy.take",
"numpy.random.seed",
"numpy.isnan",
"numpy.argmax",
"numpy.array"
]
] |
ypeng22/ProgLearn | [
"671ff6a03c156bab3eedbd9e112705eeabd59da7"
] | [
"proglearn/tests/test_transformer.py"
] | [
"import pytest\nimport numpy as np\nfrom numpy.testing import assert_allclose\nfrom sklearn.exceptions import NotFittedError\n\nfrom proglearn.transformers import TreeClassificationTransformer\n\n\nclass TestTreeClassificationTransformer:\n def test_init(self):\n TreeClassificationTransformer()\n a... | [
[
"numpy.random.seed",
"numpy.ones",
"numpy.random.normal",
"numpy.array",
"numpy.zeros"
]
] |
donfiguerres/COVID-19-Tracker-PH | [
"af98f3cdc83093363035e775c4b517535f8d950d"
] | [
"tests/unit/test_trackerchart.py"
] | [
"\"\"\"Unit tests for the trackerchart module.\"\"\"\n\nimport pandas as pd\nimport pytest\n\nimport trackerchart as tc\n\n\ndef test_filter_date_range():\n columns = [\"date\", \"fruit\"]\n data = [\n [\"2021-10-09\", \"apple\"],\n [\"2021-10-10\", \"banana\"],\n [\"2021-10-11\", \"calam... | [
[
"pandas.to_datetime",
"pandas.DataFrame"
]
] |
Zyun-Y/BiconNets | [
"f5ea85dc58550969b99a2ccccccd8133dda4358c",
"f5ea85dc58550969b99a2ccccccd8133dda4358c",
"f5ea85dc58550969b99a2ccccccd8133dda4358c"
] | [
"paper_result/MINet/bicon/train/network/MINet.py",
"paper_result/PoolNet/bicon/train/train.py",
"paper_result/MINet/bicon/train/utils/tensor_ops.py"
] | [
"import torch\nimport torch.nn as nn\n\nfrom module.BaseBlocks import BasicConv2d\nfrom utils.tensor_ops import cus_sample, upsample_add\nfrom backbone.origin.from_origin import Backbone_ResNet50_in3, Backbone_VGG16_in3\nfrom module.MyModule import AIM, SIM\n\n\nclass MINet_VGG16(nn.Module):\n def __init__(self)... | [
[
"torch.randn",
"torch.nn.Conv2d"
],
[
"torch.device",
"torch.cuda.is_available",
"torch.cuda.set_device",
"torch.zeros"
],
[
"torch.nn.functional.interpolate"
]
] |
casutton/bayes-qnet | [
"0fff4b38394e47b02c0b4f0a4e433049b78fa09c"
] | [
"src/utils.py"
] | [
"import numpy\n\ndef as_str (l):\n return ' '.join (map(str, l))\n\ndef randelt (l):\n return l[numpy.random.randint(len(l))]\n\ndef append (*l):\n result = []\n for x in l: result.append (x)\n return result\n\ndef roll_die (p):\n if sum(p) > 1 + 1e-12:\n raise \"Huh? p: %s\" % (p,) \n #... | [
[
"numpy.random.multinomial",
"numpy.where"
]
] |
vbacher/PYRO-NN | [
"e476024a44802b983c6f2ebd6f4444d9fe54120f",
"e476024a44802b983c6f2ebd6f4444d9fe54120f",
"e476024a44802b983c6f2ebd6f4444d9fe54120f"
] | [
"examples/ct_reconstruction/example_fdk.py",
"gradient_check/gradient_check.py",
"pyronn/ct_reconstruction/layers/projection_3d.py"
] | [
"# Copyright [2019] [Christopher Syben, Markus Michen]\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 ... | [
[
"numpy.radians",
"numpy.expand_dims",
"tensorflow.multiply",
"numpy.arctan",
"numpy.squeeze",
"tensorflow.cast",
"matplotlib.pyplot.get_cmap",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.axis",
"tensorflow.signal.ifft",
"matplotlib.pyplot.figure"
],
[
"numpy... |
yuki-inaho/Open3D | [
"ff7003d542c4fcf88a2d9e7fe08508b3e52dc702",
"cbbee4e19a45551ada223f491e667f1868115ead"
] | [
"examples/Python/Advanced/non_blocking_visualization.py",
"examples/Python/Basic/open3d_tutorial.py"
] | [
"# Open3D: www.open3d.org\n# The MIT License (MIT)\n# See license file or visit www.open3d.org for details\n\n# examples/Python/Advanced/non_blocking_visualization.py\n\nimport open3d as o3d\nimport numpy as np\nimport copy\n\nif __name__ == \"__main__\":\n o3d.utility.set_verbosity_level(o3d.utility.VerbosityLe... | [
[
"numpy.identity"
],
[
"numpy.asarray"
]
] |
51616/split | [
"58b6efa8ab2c24e85c0a14922ee6a2a83aaa7e19",
"58b6efa8ab2c24e85c0a14922ee6a2a83aaa7e19"
] | [
"augmentation.py",
"spair/utils.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport tensorflow_probability as tfp\nimport os \n\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'\n\nwidth = height = 32\nchannel = 3\npatch_size_x = 8 ;patch_size_y = 8\n\nclass Augmentator(object):\n def __init__(self,type,size=1,mean=0,std=1):\n self.size = size... | [
[
"tensorflow.convert_to_tensor",
"tensorflow.concat",
"tensorflow.range",
"numpy.random.choice",
"tensorflow.unstack",
"tensorflow.reduce_sum",
"tensorflow.reshape",
"tensorflow.random.uniform",
"tensorflow.squeeze",
"tensorflow.expand_dims",
"tensorflow.einsum",
"te... |
rasoolims/fairseq | [
"57b6a6dbfb290718eaa25040551d9db8a6b68a9b"
] | [
"fairseq/models/fconv.py"
] | [
"# Copyright (c) 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the license found in the LICENSE file in\n# the root directory of this source tree. An additional grant of patent rights\n# can be found in the PATENTS file in the same directory.\n\nimport math\nimport to... | [
[
"torch.nn.functional.glu",
"torch.Tensor",
"torch.nn.functional.dropout",
"torch.nn.init.constant_",
"torch.nn.utils.weight_norm",
"torch.nn.ModuleList",
"torch.nn.Embedding",
"torch.nn.utils.remove_weight_norm",
"torch.nn.Linear",
"torch.nn.init.normal_",
"torch.nn.fun... |
Wanggcong/Spatial-Temporal-Re-identification | [
"6978365af1cdbbbe654002889a4c1574314af861"
] | [
"test_st_duke.py"
] | [
"# -*- coding: utf-8 -*-\n\nfrom __future__ import print_function, division\n\nimport argparse\nimport torch\nimport torch.nn as nn\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torch.autograd import Variable\nimport numpy as np\nimport torchvision\nfrom torchvision import datasets, model... | [
[
"torch.nn.Sequential",
"torch.norm",
"torch.cuda.set_device",
"torch.load",
"torch.cat",
"torch.utils.data.DataLoader",
"torch.FloatTensor",
"torch.cuda.is_available"
]
] |
JeremyBYU/FastGaussianAccumulator | [
"995c1cb53485212bc2c71dad3ed3834caaa1f45b",
"995c1cb53485212bc2c71dad3ed3834caaa1f45b",
"995c1cb53485212bc2c71dad3ed3834caaa1f45b"
] | [
"tests/python/helpers/setup_helper.py",
"examples/python/util/line_mesh.py",
"src/Python/slowga/projections.py"
] | [
"import numpy as np\n\nfrom fastgac import GaussianAccumulatorS2Beta, IcoCharts, MatX3d\n\nfrom scipy.spatial.transform import Rotation as R\n\n \ndef setup_fastgac(normals:np.ndarray, level=4):\n kwargs_s2 = dict(level=level)\n # Create Gaussian Accumulator\n ga_cpp_s2 = GaussianAccumulatorS2Beta(**kwa... | [
[
"numpy.radians",
"numpy.sqrt",
"numpy.power",
"numpy.arccos",
"numpy.cos",
"numpy.sin",
"numpy.arctan2",
"numpy.column_stack",
"numpy.argsort",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros"
],
[
"numpy.dot",
"numpy.expand_dims",
"numpy.array_e... |
jGaboardi/splot | [
"b30f13eed864e237b36d9d678a6a69a0d54f5319"
] | [
"splot/tests/test_viz_esda_mpl.py"
] | [
"import matplotlib.pyplot as plt\nfrom libpysal.weights.contiguity import Queen\nimport libpysal as lp\nfrom libpysal import examples\nimport geopandas as gpd\nimport numpy as np\nfrom pytest import raises, warns\n\nfrom esda.moran import (Moran_Local, Moran, Moran_BV,\n Moran_Local_BV, Moran... | [
[
"numpy.array",
"matplotlib.pyplot.close"
]
] |
marcinz/cunumeric | [
"c40b038d4eb0611f7bb16d5bd11891a633ef7892",
"c40b038d4eb0611f7bb16d5bd11891a633ef7892",
"c40b038d4eb0611f7bb16d5bd11891a633ef7892",
"c40b038d4eb0611f7bb16d5bd11891a633ef7892",
"c40b038d4eb0611f7bb16d5bd11891a633ef7892",
"c40b038d4eb0611f7bb16d5bd11891a633ef7892",
"c40b038d4eb0611f7bb16d5bd11891a633ef789... | [
"tests/universal_functions_tests/true_divide_tests/inplace_broadcast.py",
"tests/universal_functions_tests/tan_tests/scalar.py",
"tests/universal_functions_tests/arcsin_tests/normal.py",
"tests/diag.py",
"tests/universal_functions_tests/add_tests/complex_data.py",
"tests/universal_functions_tests/greater_... | [
"# Copyright 2021 NVIDIA Corporation\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law or ... | [
[
"numpy.true_divide",
"numpy.random.randn",
"numpy.array_equal"
],
[
"numpy.tan"
],
[
"numpy.arcsin"
],
[
"numpy.diag",
"numpy.array",
"numpy.array_equal"
],
[
"numpy.add",
"numpy.random.random"
],
[
"numpy.greater_equal",
"numpy.random.randn"
]... |
BalasaravananB/Visualizer | [
"16451c1be9edcaa5be5303b2b8834ff26012b456",
"16451c1be9edcaa5be5303b2b8834ff26012b456"
] | [
"public/js/ecllipes-detection-test.py",
"public/js/multi-image-circle.py"
] | [
"import cv2 \nimport numpy as np \n \n# Load image \nimage = cv2.imread('/bala/projects/inoru/WheelVisualizer/storage/app/public/demo_cars/0777_cc1280_032_KH3.jpg', 0) \n \n# Set our filtering parameters \n# Initialize parameter settiing using cv2.SimpleBlobDetector \nparams = cv2.SimpleBlobDetector_Params() \n ... | [
[
"numpy.zeros"
],
[
"numpy.around"
]
] |
yaoxingcheng/cogdl | [
"fad95b189207f78fce720383584da52b14a9850e",
"fad95b189207f78fce720383584da52b14a9850e"
] | [
"examples/gcn.py",
"cogdl/models/nn/gat.py"
] | [
"import torch\nfrom cogdl.tasks import build_task\nfrom cogdl.datasets import build_dataset\nfrom cogdl.models import build_model\nfrom cogdl.utils import build_args_from_dict\n\n\ndef get_default_args():\n cuda_available = torch.cuda.is_available()\n default_dict = {'hidden_size': 16,\n 'd... | [
[
"torch.cuda.is_available"
],
[
"torch.nn.functional.softmax",
"torch.mm",
"torch.nn.Dropout",
"torch.Size",
"torch.nn.functional.log_softmax",
"torch.nn.functional.dropout",
"torch.zeros",
"torch.cat",
"torch.isnan",
"torch.ones",
"torch.nn.init.xavier_normal_",... |
jammerware/pandashape | [
"37e45e830cf71b28486aa4949f1ba7106ae6ed56"
] | [
"src/pandashape/internal/TransformerExecutor.py"
] | [
"import pandas as pd\nfrom pandas import DataFrame\nfrom ..transformers import Transformer\nfrom ..internal import ColumnResolver, listify\n\n\nclass TransformerExecutor:\n def validate(self, df, columnDefinitions):\n for columnDef in columnDefinitions:\n for transformer in listify(columnDef['t... | [
[
"pandas.concat",
"pandas.DataFrame"
]
] |
Beerend/TReNDS | [
"3cbd954881fe0b992e93e1b65d54cf3c9f7f05e3"
] | [
"notebooks/models/resnet.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nimport math\nfrom functools import partial\n\n__all__ = [\n 'resnet10', 'resnet18', 'resnet34', 'resnet50', 'resnet101',\n 'resnet152', 'resnet200'\n]\n\ndef conv3x3x3(in_planes, out_planes, stride=1, d... | [
[
"torch.nn.Sequential",
"torch.cat",
"torch.nn.functional.adaptive_avg_pool3d",
"torch.nn.MaxPool3d",
"torch.nn.Conv3d",
"torch.nn.Linear",
"torch.nn.functional.avg_pool3d",
"torch.nn.ReLU",
"torch.nn.BatchNorm3d",
"torch.nn.init.kaiming_normal_"
]
] |
Data-is-life/lots-of-data | [
"932e605ca2b880c7aa9e23e3ea0861c802d00b80",
"932e605ca2b880c7aa9e23e3ea0861c802d00b80",
"932e605ca2b880c7aa9e23e3ea0861c802d00b80"
] | [
"src/old_files/dummies_bins_test_train_cv.py",
"src/old_files/tf_model.py",
"src/old_files/keras_grid_search_dtw.py"
] | [
"# Author: Mohit Gangwani\n# Date: 11/05/2018\n# Git-Hub: Data-is-Life\n\nimport pandas as pd\nimport os\nimport pickle\n# import numpy as np\nfrom random import randint\nfrom sklearn.preprocessing import PolynomialFeatures as MMXs\nfrom sklearn.model_selection import train_test_split\n\n\ndef save_pickle(something... | [
[
"sklearn.preprocessing.PolynomialFeatures",
"pandas.read_csv",
"sklearn.model_selection.train_test_split"
],
[
"torch.nn.Dropout",
"sklearn.preprocessing.MaxAbsScaler",
"torch.sum",
"torch.autograd.Variable",
"torch.nn.Linear",
"torch.nn.BCEWithLogitsLoss",
"torch.Float... |
tracysaber/terngrad | [
"cd7e5f1c59e87712a208fc1351defa029a340146",
"cd7e5f1c59e87712a208fc1351defa029a340146"
] | [
"slim/datasets/download_convert_and_shard_cifar10.py",
"terngrad/inception/inception_distributed_train.py"
] | [
"# Copyright 2016 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.Graph",
"tensorflow.gfile.DeleteRecursively",
"tensorflow.gfile.Open",
"tensorflow.gfile.Exists",
"numpy.squeeze",
"tensorflow.app.flags.DEFINE_integer",
"tensorflow.placeholder",
"tensorflow.python_io.TFRecordWriter",
"tensorflow.image.encode_png",
"tensorflow.... |
LeonidBeynenson/nncf_pytorch | [
"f8ded2752aded28d3559308c354235e5011ccbe0"
] | [
"tests/quantization/test_algo_quantization.py"
] | [
"\"\"\"\n Copyright (c) 2019-2020 Intel Corporation\n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n http://www.apache.org/licenses/LICENSE-2.0\n Unless required by applicable law o... | [
[
"torch.ones",
"torch.multiprocessing.spawn",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.tensor",
"torch.nn.Linear",
"torch.cuda.is_available",
"torch.cuda.device_count",
"torch.nn.functional.max_pool2d",
"torch.ones_like"
]
] |
qadmus/panda | [
"fd4751c77b84a531ba2d6812d7eeb31823db93e5"
] | [
"tests/safety/test_volkswagen_pq.py"
] | [
"#!/usr/bin/env python3\nimport unittest\nimport numpy as np\nfrom panda import Panda\nfrom panda.tests.safety import libpandasafety_py\nimport panda.tests.safety.common as common\nfrom panda.tests.safety.common import make_msg, MAX_WRONG_COUNTERS\n\nMAX_RATE_UP = 4\nMAX_RATE_DOWN = 10\nMAX_STEER = 300\nMAX_RT_DELT... | [
[
"numpy.arange"
]
] |
Pandinosaurus/pyLiDAR-SLAM | [
"1baa21a67bd32f144f8e17583251ac777f81345e",
"1baa21a67bd32f144f8e17583251ac777f81345e",
"1baa21a67bd32f144f8e17583251ac777f81345e"
] | [
"slam/common/projection.py",
"slam/dataset/rosbag_dataset.py",
"slam/initialization.py"
] | [
"from typing import Optional, Any\n\nimport torch\nimport numpy as np\nfrom abc import ABC, abstractmethod\n\nfrom functools import lru_cache\nfrom slam.common.utils import check_tensor, assert_debug\n\n\ndef torch__spherical_projection(t_pointcloud: torch.Tensor,\n height: int,\n ... | [
[
"torch.norm",
"torch.ones",
"torch.floor",
"numpy.linalg.norm",
"torch.asin",
"torch.arange",
"torch.argsort",
"torch.atan2"
],
[
"numpy.concatenate",
"numpy.ones"
],
[
"numpy.eye"
]
] |
liuzhenhai/numba | [
"a41c85fdd7d6abf8ea1ebe9116939ddc2217193b",
"a41c85fdd7d6abf8ea1ebe9116939ddc2217193b",
"a41c85fdd7d6abf8ea1ebe9116939ddc2217193b",
"a41c85fdd7d6abf8ea1ebe9116939ddc2217193b",
"a41c85fdd7d6abf8ea1ebe9116939ddc2217193b"
] | [
"numba/tests/test_diffusion.py",
"numba/tests/issues/test_issue_50.py",
"numba/tests/test_mandelbrot_2.py",
"numba/tests/issues/test_issue_164.py",
"numba/tests/broken_issues/test_log1p_vectorize.py"
] | [
"import unittest\n\nimport numpy as np\nfrom numba import autojit \n\nmu = 0.1\nLx, Ly = 101, 101\n\n@autojit \ndef diffusionObstacleStep(u,tempU,iterNum):\n for n in range(iterNum):\n for i in range(1, Lx - 1):\n for j in range(1, Ly - 1):\n u[i,j] = mu * (tempU[i+1,j]-2*tempU[i... | [
[
"numpy.zeros",
"numpy.allclose"
],
[
"numpy.zeros"
],
[
"numpy.arange",
"numpy.array",
"numpy.zeros",
"numpy.zeros_like"
],
[
"numpy.random.rand",
"numpy.empty"
],
[
"numpy.array"
]
] |
samuelpucek/ep-stats | [
"040ac2038f086e03c7c95596cba2ce9cca1382b6",
"040ac2038f086e03c7c95596cba2ce9cca1382b6"
] | [
"src/epstats/toolkit/check.py",
"src/epstats/toolkit/experiment.py"
] | [
"from typing import List\nimport pandas as pd\nimport numpy as np\nfrom scipy.stats import chisquare\n\nfrom .parser import Parser\n\n\nclass Check:\n \"\"\"\n Perform data quality check that accompanies metric evaluation in the experiment.\n\n See [Data Quality Checks](../stats/basics.md#data-quality-chec... | [
[
"numpy.errstate",
"pandas.DataFrame",
"scipy.stats.chisquare"
],
[
"pandas.concat",
"numpy.sqrt",
"numpy.tile",
"numpy.ones",
"numpy.append",
"numpy.errstate",
"numpy.repeat",
"numpy.array",
"numpy.zeros",
"pandas.pivot_table"
]
] |
ynysjtu/Adversarial_Invariant_Learning | [
"fccabab643853d1bf34410e0fc185706093e04c3"
] | [
"domainbed/hparams_registry.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\r\n\r\nimport numpy as np\r\n\r\ndef _hparams(algorithm, dataset, random_state):\r\n \"\"\"\r\n Global registry of hyperparams. Each entry is a (default, random) tuple.\r\n New algorithms / networks / etc. should add entries here.\r\n ... | [
[
"numpy.random.RandomState"
]
] |
catalinnega/Cryptocurrencies-TA-on-Dash | [
"498f152e06fe959e2c9672bd4d862820e6155884"
] | [
"indicators/rsi/rsi_db.py"
] | [
"import indicators.rsi.rsi_settings as rsi_settings\nfrom indicators.rsi.rsi_obj import RSI\nimport ochlv_db.db_settings as db_settings\nimport sqlite3\nimport pandas as pd\nfrom tqdm import tqdm\nimport time\nfrom datetime import datetime\n\nstop_streaming = False\n\ndef rsi_fn(n = '-------rsi_idle-------'):\n ... | [
[
"pandas.read_sql_query"
]
] |
ZhengRanran/motion_imitation | [
"246b2e786ccb2033cf0f4eff6fe6c62dbfb51eee"
] | [
"motion_imitation/envs/sensors/sensor.py"
] | [
"# coding=utf-8\n# Copyright 2020 The Google Research Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.array",
"numpy.full"
]
] |
Khoale1096/stupidNMT | [
"894536c16dc7ff958aa5571828a89ecabfcb72d7"
] | [
"models/new_transformer.py"
] | [
"'''\nA module which implements the basic Transformer\n'''\nimport uuid\nimport threading\nimport pdb\nimport torch\nfrom torch import nn\n\nfrom models.new_attention import NewAttention\nfrom models.attention import MultiHeadedAttention\nfrom models.embeddings import PositionEmbedding, TokenEmbedding\nfrom models.... | [
[
"torch.nn.init.calculate_gain",
"torch.nn.Dropout",
"torch.nn.CrossEntropyLoss",
"torch.cat",
"torch.nn.init.constant_",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.init.xavier_uniform_",
"torch.nn.ReLU"
]
] |
Mo5mami/retinanet-examples | [
"f7ad4ff6a99fe3e66f8a9c8e8a6e03b870f84700"
] | [
"odtk/backbones/resnet.py"
] | [
"import torchvision\nfrom torchvision.models import resnet as vrn\nimport torch.utils.model_zoo as model_zoo\n\nfrom .utils import register\n\nclass ResNet(vrn.ResNet):\n 'Deep Residual Network - https://arxiv.org/abs/1512.03385'\n\n def __init__(self, layers=[3, 4, 6, 3], bottleneck=vrn.Bottleneck, outputs=[... | [
[
"torch.utils.model_zoo.load_url"
]
] |
markliou/tool_scripts | [
"d9f7d8f23edeb294dac1c9d29a2d7358751922b7"
] | [
"python/tensorflow/BatchNorm_SELU/convolutional_network_SELU.py"
] | [
"'''\nA Convolutional Network implementation example using TensorFlow library.\nThis example is using the MNIST database of handwritten digits\n(http://yann.lecun.com/exdb/mnist/)\n\nAuthor: Aymeric Damien\nProject: https://github.com/aymericdamien/TensorFlow-Examples/\n'''\n\nfrom __future__ import print_function\... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.zeros",
"tensorflow.nn.max_pool",
"tensorflow.cast",
"tensorflow.train.AdamOptimizer",
"tensorflow.nn.conv2d",
"tensorflow.layers.batch_normalization",
"tensorflow.nn.moments",
"tensorflow.ConfigProto",
"tensorf... |
mfaytak/ultramisc | [
"1701cfaa37b05897c2946b4a292c5269bac75f2a"
] | [
"scripts/dim-reduction/punjabi-cache-frames.py"
] | [
"\"\"\"\npunjabi-cache-frames: frame caching method used in Punjabi dental/retroflex project (Kochetov, Faytak, Nara)\n\"\"\"\n\n# TODO: actually using?\nfrom __future__ import absolute_import, division, print_function\n\nimport argparse\nimport glob\nimport numpy as np\nimport os\nimport pandas as pd\nimport re\ni... | [
[
"numpy.expand_dims",
"numpy.save"
]
] |
peterhan91/Medical-Robust-Training | [
"02928666ddca6803ae6df8169c291d3f427c2970",
"02928666ddca6803ae6df8169c291d3f427c2970"
] | [
"visualization/visualize_attack.py",
"visualization/visualize.py"
] | [
"\nimport os\nimport torch\nimport torchvision as tv\nfrom torchvision import models\nimport torch.nn as nn\nimport numpy as np\nfrom torch.utils.data import DataLoader\nfrom utils import makedirs, tensor2cuda, load_model, LabelDict\nfrom argument import parser\nfrom visualization import VanillaBackprop\nfrom attac... | [
[
"torch.max",
"torch.utils.data.DataLoader",
"torch.nn.Linear",
"torch.no_grad",
"torch.cuda.is_available",
"numpy.array"
],
[
"torch.min",
"torch.utils.data.DataLoader",
"torch.nn.Linear",
"torch.cuda.is_available",
"numpy.array"
]
] |
ZhenghengLi/lcls2 | [
"94e75c6536954a58c8937595dcac295163aa1cdf",
"94e75c6536954a58c8937595dcac295163aa1cdf",
"94e75c6536954a58c8937595dcac295163aa1cdf",
"94e75c6536954a58c8937595dcac295163aa1cdf"
] | [
"psana/psana/graphqt/CMWDBDocEditor.py",
"psana/psana/tests/det.py",
"psana/psana/detector/test_detectors.py",
"psana/psana/app/epix10ka_calib_components.py"
] | [
"#------------------------------\n\"\"\"Class :py:class:`CMWDBDocEditor` implementation for CMWDBDocsBase\n====================================================================\n\nUsage ::\n #### Test: python lcls2/psana/psana/graphqt/CMWDBDocEditor.py\n\n # Import\n from psana.graphqt.CMWDBDocEditor import... | [
[
"numpy.load"
],
[
"numpy.vstack",
"numpy.stack"
],
[
"numpy.zeros"
],
[
"numpy.ones_like",
"numpy.where",
"numpy.zeros_like",
"numpy.stack"
]
] |
brettkoonce/nlp-architect | [
"29b72c39b28dbd8ca8d341075b82a2cdc396e8f8",
"b8c56b8b542ec9cda5db00323f7fa729cf2928ea"
] | [
"nlp_architect/data/cdc_resources/relations/word_embedding_relation_extraction.py",
"nlp_architect/models/gnmt_model.py"
] | [
"# ******************************************************************************\n# Copyright 2017-2018 Intel Corporation\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# ... | [
[
"scipy.spatial.distance.cosine"
],
[
"tensorflow.nn.dynamic_rnn",
"tensorflow.transpose",
"tensorflow.concat",
"tensorflow.contrib.framework.nest.is_sequence",
"tensorflow.contrib.framework.nest.map_structure",
"tensorflow.no_op",
"tensorflow.contrib.seq2seq.AttentionWrapper",
... |
roliveira/pyxel | [
"7725639172cf29861b6e924a5b0103d66277086f"
] | [
"pyxel/app.py"
] | [
"import datetime\nimport gzip\nimport inspect\nimport math\nimport os\nimport pickle\nimport time\n\nimport glfw\nimport numpy as np\nimport PIL.Image\n\nfrom . import utilities\nfrom .audio_player import AudioPlayer\nfrom .constants import (\n APP_GIF_CAPTURE_COUNT,\n APP_GIF_CAPTURE_SCALE,\n APP_MEASURE_... | [
[
"numpy.loads"
]
] |
ASUPychron/pychron | [
"f21b79f4592a9fb9dc9a4cb2e4e943a3885ededc",
"f21b79f4592a9fb9dc9a4cb2e4e943a3885ededc"
] | [
"pychron/core/geometry/centroid_pyx/setup.py",
"pychron/core/tests/curvature.py"
] | [
"# ===============================================================================\n# Copyright 2011 Jake Ross\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.apa... | [
[
"numpy.get_include"
],
[
"numpy.linspace"
]
] |
maharshi-neu/disease-simulation-team-18 | [
"f20c2dc7ff08f7660159d5e8dd593def3dc16649"
] | [
"src/main/Simulator.py"
] | [
"import pygame\nimport numpy as np\nfrom collections import deque\nimport logging\nimport os\n\nfrom . import (Particle, cfg, calculate_r_naught,\n bounce_wall, build_walls, random_coord, draw_walls,\n draw_line, display_text, euclidean_distance, bounce_particle,\n uniform_probability, bar_char... | [
[
"numpy.round",
"numpy.average",
"numpy.random.randint"
]
] |
wookayin/tensorflow-agents | [
"a0f25a4b44d4fc844c9b804bab60af2167f8d2bb",
"ae3751dfeed52422a350227047648dd82297960b",
"1455410dffed3cfdede793b87c179965cdd27d22",
"ae3751dfeed52422a350227047648dd82297960b"
] | [
"tf_agents/environments/tf_py_environment_test.py",
"tf_agents/specs/array_spec.py",
"tf_agents/environments/atari_preprocessing.py",
"tf_agents/networks/value_network.py"
] | [
"# coding=utf-8\n# Copyright 2018 The TF-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 b... | [
[
"tensorflow.TensorShape",
"tensorflow.constant",
"tensorflow.control_dependencies",
"tensorflow.test.main",
"numpy.array"
],
[
"tensorflow.as_dtype",
"numpy.issubdtype",
"numpy.dtype",
"numpy.all",
"numpy.any",
"numpy.broadcast_to",
"numpy.array",
"numpy.isi... |
temcdrm/dynonet | [
"7c197c0912686111617667fe318fa848b9dde90e"
] | [
"test_code/stable_ocs_param.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef sigmoid(val):\n return 1/(1 + np.exp(-val))\n\ndef stable_coeff(rho, psi):\n r = sigmoid(rho)\n theta = np.pi * sigmoid(psi)\n\n a_1 = -2*r*np.cos(theta)\n a_2 = r**2\n return a_1, a_2\n\ndef roots_polynomial(a_1, a_2):\n delta = a_1... | [
[
"numpy.imag",
"numpy.sqrt",
"numpy.cos",
"matplotlib.pyplot.subplots",
"numpy.real",
"numpy.random.randn",
"numpy.exp",
"numpy.sum"
]
] |
eera-l/ML-KWS-for-MCU | [
"1109fc9f675afa9940cb910559114570be1290fa"
] | [
"models.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.get_variable",
"tensorflow.nn.dynamic_rnn",
"tensorflow.concat",
"tensorflow.count_nonzero",
"tensorflow.zeros",
"tensorflow.nn.max_pool",
"tensorflow.reduce_sum",
"tensorflow.python.ops.array_ops.split",
"tensorflow.global_variables",
"tensorflow.contrib.rnn.GR... |
yongjie-lin/open-sesame | [
"4b4d3691dfbba00601db205dda7f5f9d907dda37"
] | [
"bertviz/bertviz/attention.py"
] | [
"# coding=utf-8\n# Copyright 2018 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... | [
[
"numpy.log",
"numpy.max",
"numpy.mean",
"numpy.transpose",
"numpy.array",
"numpy.exp"
]
] |
shyam196/egc | [
"43ddb88e82b6e2e3ac7c9a3736a8e55954168f5e",
"43ddb88e82b6e2e3ac7c9a3736a8e55954168f5e"
] | [
"experiments/utils.py",
"kernels/test.py"
] | [
"import os\nimport random\nfrom pathlib import Path\n\nimport numpy as np\nimport requests\nimport torch\nimport torch.nn as nn\n\n\ndef seed_all(seed):\n print(f\"Setting seed: {seed}\")\n random.seed(seed)\n np.random.seed(seed)\n torch.manual_seed(seed)\n torch.cuda.manual_seed_all(seed)\n\n\nDATA... | [
[
"torch.nn.Sequential",
"torch.nn.BatchNorm1d",
"torch.nn.Dropout",
"numpy.random.seed",
"torch.manual_seed",
"torch.nn.Linear",
"torch.cuda.manual_seed_all",
"torch.device"
],
[
"torch.cuda.synchronize",
"numpy.expand_dims",
"torch.ones",
"scipy.sparse.rand",
... |
mihirp1998/blender_emblang | [
"4b7092b8f4dfdc5240ed8ecf8e18ec75b9e0141c"
] | [
"image_generation/render_images.py"
] | [
"\n# Copyright 2017-present, Facebook, Inc.\n# All rights reserved.\n#\n# This source code is licensed under the BSD-style license found in the\n# LICENSE file in the root directory of this source tree. An additional grant\n# of patent rights can be found in the PATENTS file in the same directory.\n\nfrom __future_... | [
[
"numpy.load",
"numpy.random.uniform",
"numpy.random.randint"
]
] |
potpath/simpletransformers | [
"76f1df524c046760fd2938839f014e88678b2a27"
] | [
"simpletransformers/question_answering/question_answering_model.py"
] | [
"from __future__ import absolute_import, division, print_function\n\nimport json\nimport logging\nimport math\nimport os\nimport random\nimport warnings\nfrom dataclasses import asdict\nfrom multiprocessing import cpu_count\n\nimport numpy as np\nimport pandas as pd\nimport torch\nfrom scipy.stats import pearsonr\n... | [
[
"numpy.random.seed",
"torch.load",
"torch.manual_seed",
"torch.utils.data.SequentialSampler",
"torch.utils.data.TensorDataset",
"torch.utils.data.DataLoader",
"torch.utils.data.RandomSampler",
"pandas.DataFrame",
"torch.tensor",
"torch.cuda.amp.autocast",
"torch.cuda.am... |
Global19/onnxconverter-common | [
"09827b56c0d4f359952aac8e0160ff6290ac37f2"
] | [
"onnxconverter_common/float16.py"
] | [
"# Copyright (c) Microsoft Corporation. All rights reserved.\n# Licensed under the MIT License. See License.txt in the project root for\n# license information.\n###########################################################################\n\nimport itertools\nimport numpy as np\nimport onnx\nfrom onnx import helper, ... | [
[
"numpy.array",
"numpy.float16",
"numpy.logical_and",
"numpy.fromstring"
]
] |
KendallPark/struct2tensor | [
"1b9ada0c4018323a0549cc13437c561d39a46a05",
"7e42ed9938dfb88aa451f07b943b6308cd758411"
] | [
"struct2tensor/expression_impl/proto_test_util.py",
"struct2tensor/expression_impl/reroot.py"
] | [
"# Copyright 2019 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 applicable law or agreed ... | [
[
"tensorflow.constant"
],
[
"tensorflow.gather",
"tensorflow.size",
"tensorflow.range"
]
] |
NakedKoala/CenterTrack | [
"6b5e2ccfa9e6975892bf0cd6fae1d51086a25b58"
] | [
"src/lib/dataset/generic_dataset.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nimport math\nimport json\nimport cv2\nimport os\nfrom collections import defaultdict\n\nimport pycocotools.coco as coco\nimport torch\nimport torch.utils.data as data\n\nfrom utils.... | [
[
"numpy.maximum",
"numpy.random.random",
"numpy.clip",
"numpy.arange",
"numpy.cos",
"numpy.sin",
"numpy.random.randn",
"numpy.array",
"numpy.zeros",
"numpy.random.RandomState",
"numpy.random.randint"
]
] |
abhinavchawla/no-save-rrt | [
"dc5e5c37aa6ca1de6459a7676a49d211e63cff0e"
] | [
"rrt-online.py"
] | [
"'''\nMIT License\nCopyright (c) 2019 Fanjin Zeng\nThis work is licensed under the terms of the MIT license, see <https://opensource.org/licenses/MIT>. \n'''\n\nimport numpy as np\nfrom random import random\nimport matplotlib.pyplot as plt\nfrom matplotlib import collections as mc\nfrom collections import deque\n... | [
[
"numpy.dot",
"numpy.sqrt",
"matplotlib.collections.LineCollection",
"matplotlib.pyplot.subplots",
"numpy.linalg.norm",
"matplotlib.pyplot.Circle",
"numpy.array",
"matplotlib.pyplot.show"
]
] |
Fanxingye/TsFormer | [
"da6e7eee1bddb44e2e98f07c9f0d374793e80da6"
] | [
"run_autoformer.py"
] | [
"import argparse\nimport random\n\nimport numpy as np\nimport torch\n\nfrom tsformer.exp_autoformer import Exp_Main\n\nfix_seed = 2021\nrandom.seed(fix_seed)\ntorch.manual_seed(fix_seed)\nnp.random.seed(fix_seed)\n\nparser = argparse.ArgumentParser(\n description='Autoformer & Transformer family for Time Series ... | [
[
"torch.manual_seed",
"torch.cuda.is_available",
"torch.cuda.empty_cache",
"numpy.random.seed"
]
] |
OneDirection9/foundation | [
"a43a568b5d062d80cf3ce5777d0ab3f14147a8f2"
] | [
"foundation/visualization/colormap.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.\n#\n# Modified by: Zhipeng Han\n\"\"\"\nAn awesome colormap for really neat visualizations.\nCopied from Detectron, and removed gray colors.\n\"\"\"\nfrom __future__ import absolute_import, division, print_function\n\nimport numpy as np\n\n__a... | [
[
"numpy.array",
"numpy.random.rand"
]
] |
pushpendradahiya/pegasus | [
"8290444441d187d48082a4034a3ba3182f7b5946"
] | [
"pegasus/eval/estimator_metrics.py"
] | [
"# Copyright 2020 The PEGASUS Authors..\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless required by applicable law ... | [
[
"tensorflow.compat.v1.metrics.mean",
"tensorflow.compat.v1.metrics.accuracy",
"tensorflow.cast",
"tensorflow.equal",
"tensorflow.argmax",
"tensorflow.compat.v1.losses.sparse_softmax_cross_entropy"
]
] |
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