repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
FedeClaudi/vedo | [
"efa0ecc86134e233ba7c9885a7b0cb0f899eb88d"
] | [
"vedo/addons.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\nfrom __future__ import division, print_function\nimport vedo\nfrom vedo.colors import printc, getColor\nfrom vedo.assembly import Assembly\nfrom vedo.mesh import Mesh, merge\nfrom vedo.pointcloud import Points\nfrom vedo.utils import mag, isSequence, make_ticks\nfro... | [
[
"numpy.max",
"numpy.array",
"numpy.dot",
"numpy.zeros",
"numpy.sum",
"numpy.min",
"numpy.sign",
"numpy.sqrt",
"numpy.cross"
]
] |
Euphoria16/GMPQ | [
"f93f8428bc025e01ab01c8f8ffd1d551598f716a"
] | [
"models/mixresnet.py"
] | [
"import torch.nn as nn\nimport math\nfrom . import quant_module as qm\nimport torch.nn.functional as F\nfrom torch.autograd import Variable\nfrom torch import Tensor\nimport torch\n\n__all__ = [\n 'mixres18_w2346a2346', 'mixres50_w234a234','mixres18_w234a234'\n]\n\n\ndef conv3x3(conv_func, in_planes, out_planes,... | [
[
"torch.nn.Linear",
"torch.nn.functional.avg_pool2d",
"torch.nn.Sequential",
"torch.nn.AvgPool2d",
"torch.nn.BatchNorm2d",
"torch.nn.ReLU",
"torch.nn.Conv2d",
"torch.nn.functional.relu",
"torch.sum"
]
] |
TmsRC/TomasRubio_Ejercicio20 | [
"7cd41626ac709211585fe4cfeee8a3b1c8829607"
] | [
"complejo.py"
] | [
"import numpy as np\nimport cmath\n\nclass Complejo:\n def __init__(self,a,b):\n self.imaginario = b\n self.real = a\n self.norma = (a**2 + b**2)**(1/2)\n def conjugado(self):\n self.imaginario = -self.imaginario\n return self\n def calcula_norma(self):\n return se... | [
[
"numpy.power"
]
] |
vasilogi/comf-webapp | [
"d2b1ef5d279eb55ac47722eced013f46c0ac2e2b"
] | [
"modules/arrhenius.py"
] | [
"# Standard library imports\r\nimport sys\r\n\r\n# Third party imports\r\nimport numpy as np\r\n\r\ndef rateConstant(frequency,enthalpy,temperature):\r\n # S.I.\r\n # the units of frequency are identical to those of the rate constant k\r\n # e.g. for a first-order reaction it's s-1\r\n R = 8.31446261... | [
[
"numpy.exp"
]
] |
gasymovdf/pseudo-slit | [
"4cdbef2487f7e4a7eb32ad8dc19f99eba7a7f5b6"
] | [
"pseudoslit/calc.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nfrom mpl_toolkits.axes_grid1 import make_axes_locatable\n\ndef pseudoslit(data, pa, width=1, precision=100, ax=None):\n dims = len(data.shape)\n if dims==2:\n a, b = data.shape\n else:\n a, b, vel_size = data.shape\n data_prec = np.repe... | [
[
"numpy.max",
"numpy.array",
"numpy.sin",
"numpy.zeros",
"numpy.sum",
"numpy.tan",
"numpy.radians",
"numpy.cos",
"numpy.repeat"
]
] |
shearerj/market-sim-close-price | [
"551270fd61d22de166f44d1619490545bf2de355"
] | [
"market-sim/pytorch_ddpg/util.py"
] | [
"\nimport os\nimport torch\nfrom torch.autograd import Variable\n\nUSE_CUDA = torch.cuda.is_available()\nFLOAT = torch.cuda.FloatTensor if USE_CUDA else torch.FloatTensor\n\ndef prRed(prt): print(\"\\033[91m {}\\033[00m\" .format(prt))\ndef prGreen(prt): print(\"\\033[92m {}\\033[00m\" .format(prt))\ndef prYellow(p... | [
[
"torch.cuda.is_available",
"torch.from_numpy"
]
] |
DavidParkes/oggm | [
"e8df785b8c0c6b9ecf3a12ba388d3878035036ec"
] | [
"oggm/cli/prepro_levels.py"
] | [
"\"\"\"Command line arguments to the oggm_prepro command\n\nType `$ oggm_prepro -h` for help\n\n\"\"\"\n\n# External modules\nimport os\nimport sys\nimport argparse\nimport time\nimport logging\nimport numpy as np\nimport geopandas as gpd\n\n# Locals\nimport oggm.cfg as cfg\nfrom oggm import utils, workflow, tasks,... | [
[
"numpy.all",
"numpy.max",
"numpy.min",
"numpy.isfinite"
]
] |
dfalveargOT/CropApp | [
"afa9c19c25ad6433a4bd8fa991abd248fd6b249f"
] | [
"Preprocessing.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\"\"\"\nCreated on Fri May 3 20:18:24 2019\nCopyright © 2019 DataRock S.A.S. All rights reserved.\n@author: DavidFelipe\n\nScript de preprocesamiento de imagenes\n\n\"\"\"\ntry:\n import numpy as np\n from skimage.color import rgb2yiq, rgb2lab, rgb2ycbcr, rgb... | [
[
"numpy.array",
"numpy.fft.fft2",
"numpy.zeros",
"numpy.percentile",
"numpy.copy",
"numpy.abs",
"numpy.fft.fftshift"
]
] |
qSaevar/Qcodes | [
"07b42534855aa545be528859b20a01e157b757ab"
] | [
"qcodes/utils/validators.py"
] | [
"import math\nfrom typing import Union, Tuple, cast, Optional\nimport collections\n\nimport numpy as np\n\nBIGSTRING = 1000000000\nBIGINT = int(1e18)\n\n\ndef validate_all(*args, context=''):\n \"\"\"\n Takes a list of (validator, value) couplets and tests whether they are\n all valid, raising ValueError o... | [
[
"numpy.max",
"numpy.array",
"numpy.empty",
"numpy.min",
"numpy.shape"
]
] |
ahcantao/pyswarms | [
"1422eb7ad3b8641de83b39dc36ce7b09858e2440"
] | [
"tests/optimizers/test_local_best.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Unit testing for pyswarms.single.LocalBestPSO\"\"\"\n\n# Import from __future__\nfrom __future__ import with_statement\nfrom __future__ import absolute_import\nfrom __future__ import print_function\n\n# Import modules\nimport unittest\nimport numpy as np\n\n#... | [
[
"numpy.array"
]
] |
Rainelz/Doc-SR | [
"81443cc83d124bf286ef7d1cefa707ac56c6eed5"
] | [
"codes/models/networks.py"
] | [
"import torch\nimport models.archs.discriminator_vgg_arch as SRGAN_arch\n#import models.archs.EDVR_arch as EDVR_arch\n\n# Generator\ndef define_G(opt):\n opt_net = opt['network_G']\n which_model = opt_net['which_model_G']\n\n # image restoration\n if which_model == 'MSRResNet':\n import models.ar... | [
[
"torch.device"
]
] |
heavenbeing/stock | [
"1bf1e78a96321e2ab8b5505de606878168daa128"
] | [
"web/chartHandler.py"
] | [
"#!/usr/local/bin/python3\n# -*- coding: utf-8 -*-\n\n\nfrom tornado import gen\nimport libs.stock_web_dic as stock_web_dic\nimport web.base as webBase\nimport logging\nimport tornado.web\nimport matplotlib\nmatplotlib.use('Agg')\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport io\n\ndef GenImage(freq):... | [
[
"matplotlib.use",
"numpy.sin",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure",
"numpy.linspace"
]
] |
msr-fiddle/DS-Analyzer | [
"dbdff253b3548a540aaf8766b871db9360083528"
] | [
"tool/image_classification/pytorch-imagenet-dali-mp.py"
] | [
"import argparse\nimport os\nimport shutil\nimport time\nimport math\nimport sys\n\nimport torch\nfrom torch.autograd import Variable\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\nimport torch.distributed as dist\nimport torch.optim\nimport torch.utils.data\nimport torch.ut... | [
[
"torch.distributed.get_world_size",
"torch.cuda.synchronize",
"torch.distributed.init_process_group",
"torch.autograd.Variable",
"torch.save",
"torch.no_grad",
"torch.cuda.device_count",
"torch.manual_seed",
"torch.cuda.set_device",
"torch.set_printoptions",
"torch.dist... |
MTD-group/Lead-Pourbaix-Diagrams | [
"2387798d949f48d2aa6a64d952aa9ad665d0b4d7"
] | [
"src/makeplot.py"
] | [
"import matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\n\ncolordict = {\n \"Pb\": \"#85807b\",\n \"Pb++\": \"#db653d\",\n \"PbO\": \"#e04a16\",\n \"PbO2\": \"#3ec760\",\n \"Pb3O4\": \"#2a8744\",\n \"Pb++++\": \"#c92840\",\n \"HPbO2-\": \"#db7d42\", \n \"PbO3--\": \"#bf3939... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplots",
"numpy.shape",
"numpy.arange",
"matplotlib.pyplot.ylabel"
]
] |
hunse/nengo | [
"5fcd7b18aa9496e5c47c38c6408430cd9f68a720",
"5fcd7b18aa9496e5c47c38c6408430cd9f68a720"
] | [
"nengo/tests/test_solvers.py",
"nengo/params.py"
] | [
"\"\"\"\nTODO:\n - add a test to test each solver many times on different populations,\n and record the error.\n\"\"\"\nfrom __future__ import print_function\n\nimport numpy as np\nimport pytest\n\nimport nengo\nfrom nengo.dists import UniformHypersphere\nfrom nengo.utils.compat import range\nfrom nengo.utils.n... | [
[
"numpy.array",
"numpy.dot",
"numpy.zeros_like",
"numpy.zeros",
"numpy.random.RandomState",
"numpy.round",
"numpy.interp",
"numpy.allclose",
"numpy.linalg.lstsq",
"numpy.argsort",
"numpy.log10",
"numpy.linspace",
"numpy.meshgrid"
],
[
"numpy.asarray",
... |
hakutyou/justforfun | [
"c51765e990984f40b5f704f714e8f2d944e21c3a"
] | [
"python/opencv/Shi-Tomasi.py"
] | [
"import numpy as np\nimport cv2\nfrom matplotlib import pyplot as plt\n\nimg = cv2.imread('test.jpg')\nif img is None:\n print('No such image.')\nelse:\n gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n\n corners = cv2.goodFeaturesToTrack(gray, 25, 0.01, 10)\n points = np.int0(corners)\n\n... | [
[
"numpy.int0"
]
] |
d-chambers/OpenSarToolkit | [
"0edf4b1e43a66b6d0a675d007c2053a053dc60df"
] | [
"ost/s1/grd_batch.py"
] | [
"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\n\n\"\"\"Batch processing for GRD products\n\n\"\"\"\n\nimport os\nimport json\nimport itertools\nimport logging\nimport pandas as pd\nfrom pathlib import Path\n\nfrom godale._concurrent import Executor\n\nfrom ost import Sentinel1Scene\nfrom ost.s1 import grd_to_ard... | [
[
"pandas.DataFrame.from_dict",
"pandas.DataFrame"
]
] |
MVRonkin/dsatools | [
"5c811838bb3fb8ae00195d5f68e451bd23b3448c"
] | [
"dsatools/utilits/_smooth.py"
] | [
"import numpy as np\n\nfrom ... import operators\n\n__all__=['moving_average',]\n\ndef moving_average(vector,av_cof, mode='postw'):\n '''\n Simple Moving Average or Weighted Moving Average\n \n Parameters\n -------------\n * vector: 1d ndarray,\n input vector.\n * av_cof: int or 1d ndar... | [
[
"numpy.ones",
"numpy.asarray"
]
] |
carolinscholl/boltzmann-machines | [
"c6d3f9051b1cb12eca7a9c6ad540e58ee36f7501"
] | [
"pruning/MNIST_PruneDBM_AntiFI.py"
] | [
"import warnings\nwarnings.filterwarnings(\"ignore\")\n\nimport os\nimport sys\nimport env\nimport tensorflow as tf\nimport numpy as np\nimport pickle\nfrom bm.dbm import DBM\nfrom bm.rbm.rbm import BernoulliRBM, logit_mean\nfrom bm.init_BMs import * # helper functions to initialize, fit and load RBMs and 2 layer D... | [
[
"numpy.array",
"tensorflow.test.gpu_device_name",
"numpy.reshape",
"numpy.zeros",
"numpy.asarray",
"numpy.random.seed",
"numpy.mean",
"tensorflow.compat.v1.Session",
"tensorflow.ConfigProto",
"sklearn.linear_model.LogisticRegression",
"tensorflow.python.client.device_li... |
dreamflasher/client | [
"c8267f1c6b8b6970172d622bb8fbf7cc773d78b2"
] | [
"wandb/tensorflow/__init__.py"
] | [
"from copy import deepcopy\n\nimport tensorflow as tf\n\nfrom wandb import util\nfrom wandb.apis.file_stream import Chunk\nfrom wandb.data_types import history_dict_to_json\nfrom wandb.tensorboard import *\nimport wandb\n\nif hasattr(tf.estimator, 'SessionRunHook'):\n # In tf 1.14 and beyond, SessionRunHook is i... | [
[
"tensorflow.summary.merge_all",
"tensorflow.train.summary_iterator",
"tensorflow.train.SessionRunArgs"
]
] |
AndrewLaird/ChessTutorModels | [
"c4fd960417d5b9918e430d040deb89fed3f4b73b"
] | [
"utils/torch_utils.py"
] | [
"# PyTorch utils\n\nimport logging\nimport math\nimport os\nimport subprocess\nimport time\nfrom contextlib import contextmanager\nfrom copy import deepcopy\nfrom pathlib import Path\n\nimport torch\nimport torch.backends.cudnn as cudnn\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision\n\n... | [
[
"torch.zeros",
"torch.device",
"torch.nn.utils.prune.l1_unstructured",
"torch.sqrt",
"torch.cuda.synchronize",
"torch.nn.functional.interpolate",
"torch.cuda.get_device_properties",
"torch.no_grad",
"torch.nn.utils.prune.remove",
"torch.cuda.device_count",
"torch.manual... |
ivanquirino/gluon-cv | [
"a990c2f148efccd3f7dc0cc0ccd81c03a0f91dd5"
] | [
"gluoncv/data/mscoco/instance.py"
] | [
"\"\"\"MS COCO object detection dataset.\"\"\"\nfrom __future__ import absolute_import\nfrom __future__ import division\nimport os\nimport numpy as np\nimport mxnet as mx\nfrom .utils import try_import_pycocotools\nfrom ..base import VisionDataset\n\n__all__ = ['COCOInstance']\n\n\nclass COCOInstance(VisionDataset)... | [
[
"numpy.asarray",
"numpy.maximum"
]
] |
hzxGoForward/eos-reading | [
"d42928d3c3033962c472f31ed24c20fa92b4590c"
] | [
"tutorials/bios-boot-tutorial/bios-boot-tutorial.py"
] | [
"#!/usr/bin/env python3\r\n\r\nimport argparse\r\nimport json\r\nimport numpy\r\nimport os\r\nimport random\r\nimport re\r\nimport subprocess\r\nimport sys\r\nimport time\r\n\r\nargs = None\r\nlogFile = None\r\n\r\nunlockTimeout = 999999999\r\nfastUnstakeSystem = './fast.refund/eosio.system/eosio.system.wasm'\r\n\r... | [
[
"numpy.random.pareto"
]
] |
szandala/PRISM | [
"7f40e9ebdb5e53c1343cd3d358933861b24573da"
] | [
"torchprism/PRISM.py"
] | [
"from torch.nn import Conv2d, MaxPool2d\nfrom torch import no_grad, round\nfrom torch.nn.functional import interpolate\nfrom itertools import chain\n\n\nclass PRISM:\n _excitations = []\n _hook_handlers = []\n _is_orig_image = True\n\n def _excitation_hook(module, input, output):\n # for better o... | [
[
"torch.round",
"torch.nn.functional.interpolate",
"torch.no_grad"
]
] |
YixuanZheng/Aerosol_Inequality_2019 | [
"029b198311f192dbb98b96053ce0fbc55a3ab392"
] | [
"modules/1.Temperature_ts.py"
] | [
"# -*- coding: utf-8 -*-\n\n'''\nThis code calculate running average of temperature (global mean and gridded results)\nbased on 1850-2019 transient simulation\n\nPreindustrial global mean temperature derived from a 110-year 1850 repeating cycle simulation is also calcualted\n\nby Yixuan Zheng (yxzheng@carnegiescien... | [
[
"pandas.ExcelWriter",
"numpy.zeros",
"pandas.DataFrame",
"numpy.sign",
"numpy.where",
"numpy.arange",
"numpy.append"
]
] |
JoeyTeng/Algorithm-Selection-for-Classification-Problems-via-Cluster-based-Meta-features | [
"61fe5a231a0062d9939d1ccdfc0babcbe9562867"
] | [
"utilities/paired_t_test.py"
] | [
"# @Author: Joey Teng\n# @Email: joey.teng.dev@gmail.com\n# @Filename: paired_t_test.py\n# @Last modified by: Joey Teng\n# @Last modified time: 31-Jul-2018\nimport argparse\nimport json\n\nimport numpy\nimport scipy.stats\n\n\ndef main(args):\n pathA, pathB = args.i\n print(pathA, pathB, flush=True)\n\n ... | [
[
"numpy.matrix"
]
] |
JIANG-CX/data_labeling | [
"8d2470bbb537dfc09ed2f7027ed8ee7de6447248",
"8d2470bbb537dfc09ed2f7027ed8ee7de6447248",
"8d2470bbb537dfc09ed2f7027ed8ee7de6447248"
] | [
"venv/lib/python3.8/site-packages/tensorflow/python/keras/api/keras/datasets/reuters/__init__.py",
"venv/lib/python3.8/site-packages/keras/distribute/optimizer_combinations.py",
"venv/lib/python3.8/site-packages/keras/api/_v1/keras/layers/experimental/__init__.py"
] | [
"# This file is MACHINE GENERATED! Do not edit.\n# Generated by: tensorflow/python/tools/api/generator/create_python_api.py script.\n\"\"\"Reuters topic classification dataset.\n\"\"\"\n\nfrom __future__ import print_function as _print_function\n\nimport sys as _sys\n\nfrom tensorflow.python.keras.datasets.reuters ... | [
[
"tensorflow.python.util.module_wrapper.TFModuleWrapper"
],
[
"tensorflow.compat.v2.compat.v1.train.RMSPropOptimizer",
"tensorflow.compat.v2.compat.v1.train.GradientDescentOptimizer",
"tensorflow.compat.v2.compat.v1.train.AdamOptimizer",
"tensorflow.compat.v2.compat.v1.train.FtrlOptimizer",... |
naomi-mcrn/MVTec-Anomaly-Detection | [
"c3d9c84600e27aaa00e1933cb2d1596524687a51",
"c3d9c84600e27aaa00e1933cb2d1596524687a51"
] | [
"autoencoder/models/baselineVAEtiny_base.py",
"autoencoder/models/baselineCAEtiny_unetmodoki.py"
] | [
"\"\"\"\nModel inspired by: https://github.com/natasasdj/anomalyDetection\n\"\"\"\n\nimport tensorflow as tf\nfrom tensorflow.keras.layers import (\n Input,\n Dense,\n Conv2D,\n MaxPooling2D,\n UpSampling2D,\n BatchNormalization,\n GlobalAveragePooling2D,\n LeakyReLU,\n Activation,\n c... | [
[
"tensorflow.exp",
"tensorflow.shape",
"tensorflow.keras.layers.Lambda",
"tensorflow.keras.layers.Input",
"tensorflow.keras.layers.UpSampling2D",
"tensorflow.keras.layers.Flatten",
"tensorflow.GradientTape",
"tensorflow.keras.layers.Activation",
"tensorflow.math.exp",
"tenso... |
stevenjj/PnC | [
"e1e417dbd507f174bb2661247cb4360b6ee0ada7"
] | [
"Addition/PythonPlotter/PlotMultiple.py"
] | [
"import sys\nimport importlib\n\nimport numpy as np\nimport matplotlib\nmatplotlib.use('TkAgg')\nimport matplotlib.pyplot as plt\nimport os\n\n# Plot configuration\nPLOT_VERTICALLY = 0\nPLOT_HORIZONTALLY = 1\nPLOT_CONFIG = PLOT_VERTICALLY\n\n# List of valid figures to plot. Must be the names of the plotting script ... | [
[
"matplotlib.use",
"matplotlib.pyplot.show"
]
] |
laomao0/AIM_DAIN | [
"8322569498d675d3b2c1f35475c1299cad580bde"
] | [
"src/my_args.py"
] | [
"import os\nimport datetime\nimport argparse\nimport numpy\nimport networks\nimport torch\nmodelnames = networks.__all__\nimport datasets\ndatasetNames = datasets.__all__\n\nparser = argparse.ArgumentParser(description='Flow-Directed Interpolation Kernel')\n\nparser.add_argument('--debug',action = 'store_true', h... | [
[
"numpy.random.randint"
]
] |
hardbyte/sorting-gym | [
"22227816207a74f2c061e51d33469c725aaecd11"
] | [
"sorting_gym/envs/basic_neural_sort_interface.py"
] | [
"from collections import OrderedDict\nfrom dataclasses import dataclass\nfrom typing import Callable\n\nfrom gym import Space\nfrom gym.spaces import Discrete, Dict, MultiBinary, Tuple\nimport numpy as np\n\nfrom sorting_gym.envs.sort_interface_base import NeuralSortInterfaceEnv\n\n\n@dataclass(frozen=True)\nclass ... | [
[
"numpy.zeros"
]
] |
montefesp/EPIPPy | [
"7de873cf70d06986e83a434b6ab4b8997694a269"
] | [
"epippy/generation/vres/potentials/glaes/create_priors.py"
] | [
"\"\"\"\nThe functions from this file originate from https://github.com/FZJ-IEK3-VSA/glaes/blob/master/create_prior.py\n\"\"\"\n\nimport geokit as gk\nimport numpy as np\nfrom os.path import join, isdir\nfrom os import mkdir\n\nfrom collections import OrderedDict\nfrom json import dumps\nfrom typing import List\n\n... | [
[
"numpy.ones",
"numpy.logical_and"
]
] |
adi-797/Iris-and-Pupil-detection-using-OpenCV | [
"2421a25ff99ca67f213c05fbf482c49e7c443881"
] | [
"Ocular/webapp-django/Dlib-pack/Eye.py"
] | [
"# import the necessary packages\r\nfrom scipy.spatial import distance as dist\r\nfrom imutils.video import FileVideoStream\r\nfrom imutils.video import VideoStream\r\nfrom imutils import face_utils\r\nimport numpy as np\r\nimport argparse\r\nimport imutils\r\nimport time\r\nimport dlib\r\nimport cv2\r\nimport time... | [
[
"numpy.zeros"
]
] |
xychu/models | [
"0344c5503ee55e24f0de7f37336a6e08f10976fd",
"0344c5503ee55e24f0de7f37336a6e08f10976fd"
] | [
"research/fivo/models/vrnn.py",
"research/object_detection/utils/np_box_mask_list_test.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.zeros_initializer",
"tensorflow.contrib.distributions.kl_divergence",
"tensorflow.zeros",
"tensorflow.concat",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.nn.rnn_cell.LSTMCell",
"tensorflow.contrib.distributions.Normal",
"tensorflow.nn.softplus",
"te... |
KRRVU/kgbench | [
"d70ff8a6f48228f38a4ad3fee8df033050213556"
] | [
"tests/utiltest.py"
] | [
"import unittest\nimport torch\nfrom torch import nn\n\nimport sys\n\nimport kgbench as kg\nfrom kgbench import tic, toc\n\nimport torch\nimport numpy as np\n\nclass TestUtil(unittest.TestCase):\n\n def test_batching(self):\n\n amplus = kg.load('amplus')\n\n batched = kg.to_tensorbatches(amplus.get... | [
[
"numpy.array"
]
] |
eridgd/finetune | [
"92b28ecc1db0e33838995ea792b5d3b6f3dd7686"
] | [
"finetune/datasets/stanford_sentiment_treebank.py"
] | [
"import os\nimport logging\nfrom pathlib import Path\n\nimport numpy as np\n\nfrom sklearn.model_selection import train_test_split\n\nfrom finetune import Classifier\nfrom finetune.datasets import Dataset, generic_download\n\nlogging.basicConfig(level=logging.DEBUG)\n\nSST_FILENAME = \"SST-binary.csv\"\nDATA_PATH =... | [
[
"sklearn.model_selection.train_test_split"
]
] |
Angramme/pseudospectra | [
"f2fe924ab74479b18579406d4f6a0afa8372d51a"
] | [
"lib/algo/grid.py"
] | [
"import numpy as np\nimport math\nimport matplotlib.pyplot as plt\nfrom lib.math import gershgorin_norm, ssvd_min\n\n\ndef main(\n plot, \n matrix: np.matrix, \n eps: np.array, \n step: float =0.5, \n update = lambda: True, \n progresstick =.01):\n\n \n A = matrix\n n, _ = A.shape\n \n... | [
[
"numpy.max",
"numpy.eye",
"numpy.linalg.eig",
"matplotlib.pyplot.Rectangle",
"numpy.linspace",
"numpy.meshgrid"
]
] |
juliaviolet/Python_Bootcamp_Jos-_Padilla | [
"0a061283edcb7b33d5a7e165e8811ee61d694515"
] | [
"2D_Numpy_Arrays.py"
] | [
"import numpy as np\n\nnp_2D = np.array([[1.73,1.68,1.71,1.89,1.79],[65.4,59.2,63.6,88.4,68.7]])\n\nprint(np_2D)\n\nprint(np_2D.shape)\n\nprint(np_2D[0][2])\n\nprint(np_2D[0,2])\n\nprint(np_2D[:,1:3])\n\nprint(np_2D[1,:])\n"
] | [
[
"numpy.array"
]
] |
ziimiin14/crazyflie-kratos-ros | [
"f626217131bbf63bb25aa2118f76ff7d98b25298"
] | [
"scripts/rosbag_readEventStruct.py"
] | [
"import rosbag\nimport numpy as np\nimport argparse\nimport os\n\n\nif __name__ == \"__main__\":\n\n\n parser = argparse.ArgumentParser()\n parser.add_argument(\"bag\",help = \"ROS bag file to extract\")\n\n parser.add_argument(\"--time_output_file\",default=\"time_extracted_data\",help=\"binary file to ex... | [
[
"numpy.array"
]
] |
Lynda-Starkus/DeepvisionAI_Backend | [
"f3637ef173ed1af6cffd1bf98357e581d785fb88"
] | [
"yolov5/utils/plots.py"
] | [
"# Plotting utils\n\nimport glob\nimport math\nimport os\nfrom copy import copy\nfrom pathlib import Path\n\nimport cv2\nimport matplotlib\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nimport seaborn as sn\nimport torch\nimport yaml\nfrom PIL import Image, ImageDraw, ImageFont\n\nfrom y... | [
[
"matplotlib.pyplot.xlim",
"numpy.exp",
"scipy.signal.filtfilt",
"numpy.max",
"numpy.log",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.subplots",
"numpy.arange",
"matplotlib.pyplot.subplot",
"matplotlib.use",
"numpy.array",
"matplotlib.pyplot.title",
"matplot... |
eteq/astropy-benchmarks | [
"a8d5b3f30b2f1d7252d450aad53bb0572e44a1e8"
] | [
"benchmarks/coordinates.py"
] | [
"import numpy as np\nfrom astropy.coordinates import SkyCoord, FK5, Latitude, Angle\nfrom astropy import units as u\n\n\ndef time_latitude():\n Latitude(3.2, u.degree)\n\n\nANGLES = Angle(np.ones(10000), u.deg)\n\n\ndef time_angle_array_repr():\n # Prior to Astropy 3.0, this was very inefficient\n repr(ANG... | [
[
"numpy.linspace",
"numpy.ones"
]
] |
magalhaesdavi/ai-chatbot | [
"810740fbbd694539d6fd4ddc6f482e5d8f26b52d"
] | [
"model.py"
] | [
"import torch.nn as nn\n\n\n# Fully connected neural network with one hidden layer\nclass NeuralNet(nn.Module):\n def __init__(self, input_size, hidden_size, num_classes):\n super(NeuralNet, self).__init__()\n self.fc1 = nn.Linear(input_size, hidden_size)\n self.fc2 = nn.Linear(hidden_size, ... | [
[
"torch.nn.Linear",
"torch.nn.ReLU"
]
] |
ostfor/tf-adain | [
"5fec895470f8518742b9a057b79f62597f06a99d"
] | [
"adain/nn.py"
] | [
"import tensorflow as tf\n\nfrom adain.layer import upsample_nearest, vgg_preprocess\n\n\n_VGG19 = [\n ('prep', 'prep', {}),\n ('conv', 'conv1_1', {'filters': 64}),\n ('conv', 'conv1_2', {'filters': 64}),\n ('pool', 'pool1', {}),\n ('conv', 'conv2_1', {'filters': 128}),\n ('conv', 'conv2_2', ... | [
[
"tensorflow.zeros_initializer",
"tensorflow.constant_initializer",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.layers.max_pooling2d",
"tensorflow.variable_scope",
"tensorflow.layers.conv2d",
"tensorflow.pad"
]
] |
sunxiaobing1999/spartan2 | [
"95e80fce52c7c9274e7424fb4d9c6511b128b4c4"
] | [
"spartan/model/eaglemine/desc/dtmnorm.py"
] | [
"#!/usr/bin/python2.7\n# -*- coding=utf-8 -*-\n\n# # Describe hypercubes (in high dimensional) with DTM Gaussian distribution\n# DTM Gaussian: Discrete Truncate Multivariate Normal Gaussian.\n# Author: wenchieh\n#\n# Project: eaglemine\n# dtmnorm.py\n# Version: 1.0\n# Date: December 1 2017\n... | [
[
"numpy.array",
"numpy.asarray",
"numpy.zeros",
"numpy.log",
"numpy.sum",
"numpy.linalg.det",
"numpy.diag",
"scipy.optimize.minimize"
]
] |
muxuezi/jupyterworkflow | [
"65699416edfcbfdc206941e85345b9a2db9cd65e"
] | [
"103bestpractice/jupyterworkflow/data.py"
] | [
"import os\nfrom urllib.request import urlretrieve\nimport pandas as pd\n\nFREMONT_URL = 'https://data.seattle.gov/api/views/65db-xm6k/rows.csv?accessType=DOWNLOAD'\n\n\ndef get_fremont_data(filename='Fremont.csv', url=FREMONT_URL, force_download=False):\n \"\"\"Download and cache the fremont data\n\n Paramet... | [
[
"pandas.to_datetime",
"pandas.read_csv"
]
] |
rickead/DeepLearningBook | [
"5250ed7838a169ad34d6d141bacf8c3b4a13d26b"
] | [
"example5-3.py"
] | [
"\"\"\"\r\nExample 5-3, pg 191 - Generating Shakespeare via LSTMs\r\n\r\nThe training dataset for this example is provided by the Complete Works of\r\nWilliam Shakespear (http://www.gutenbarg.org/ebooks/100)\r\n\r\nAll code is written to run on Tensorflow 2 using the embedded Keras API.\r\n\r\nThe original Java cod... | [
[
"tensorflow.data.Dataset.from_tensor_slices",
"tensorflow.keras.utils.get_file",
"tensorflow.keras.callbacks.ModelCheckpoint",
"tensorflow.keras.layers.Dense",
"tensorflow.keras.layers.LSTM",
"tensorflow.train.latest_checkpoint",
"tensorflow.TensorShape",
"tensorflow.keras.losses.s... |
alex-w/vplanet | [
"e901ac08208f7fd5edb30677f32f36619eb8ca8c"
] | [
"examples/CassiniStates/makeplot.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport vplot\nimport sys\nimport scipy.signal as sig\n#plt.rcParams[\"text.usetex\"]=True\n#plt.rcParams[\"text.latex.unicode\"]=True\n\n# Check correct number of arguments\nif (len(sys.argv) != 2):\n print('ERROR: Incorrect number of arguments.')\n print(... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.arrow",
"numpy.mean",
"numpy.where",
"numpy.cos",
"numpy.imag",
"numpy.sin",
"numpy.sqrt",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.close",
"numpy.real",
"matplotlib.pyplot.figure",
... |
cyun-404/Bicubic-interpolation | [
"0b3d806228aabdaeb9ce59b1a38e1026b1c0a6e4"
] | [
"bicubic_.py"
] | [
"import cv2\nimport numpy as np\nimport math\nimport sys, time\n\n# Interpolation kernel\ndef u(s,a):\n if (abs(s) >=0) & (abs(s) <=1):\n return (a+2)*(abs(s)**3)-(a+3)*(abs(s)**2)+1\n elif (abs(s) > 1) & (abs(s) <= 2):\n return a*(abs(s)**3)-(5*a)*(abs(s)**2)+(8*a)*abs(s)-4*a\n return 0\n\n#... | [
[
"numpy.dot",
"numpy.zeros"
]
] |
Dou-Yu-xuan/pytorch-cnn-finetune | [
"92ead74d5dbfbaa695c27cc5ddf7bccce4a5fb6e"
] | [
"tests/test_pretrained_models.py"
] | [
"import types\n\nimport pytest\nimport torch.nn as nn\nimport pretrainedmodels\n\nfrom cnn_finetune import make_model\nfrom cnn_finetune.utils import default\nfrom .utils import (\n assert_equal_model_outputs,\n assert_almost_equal_model_outputs,\n copy_module_weights\n)\n\n\n@pytest.mark.parametrize('mode... | [
[
"torch.nn.AvgPool2d"
]
] |
kamko/lnu_ht19_4ME310_assignment2 | [
"d1287b898bb371f27739700ccd629fcbc315648a"
] | [
"src/clustering/pam.py"
] | [
"import itertools\n\nimport numpy as np\n\nfrom src.log_util import log\nfrom src.numpy_util import np_rows\nfrom src.numpy_util import random_from_range\nfrom src.numpy_util import to_numpy\n\n\nclass PAM:\n\n def __init__(self,\n n_clusters,\n distance,\n max_ite... | [
[
"numpy.delete",
"numpy.min",
"numpy.argmin"
]
] |
alexprz/NHIS_analyse | [
"466e944ed1002bf227cb1522d91daf9b80c7d7d5"
] | [
"pvals/sort.py"
] | [
"\"\"\"Sort pvals.\"\"\"\nimport os\nimport pandas as pd\n\n\npvals_dirs = []\nfor db_dir in next(os.walk('.'))[1]:\n pvals_dirs += [f'{db_dir}/{d}' for d in next(os.walk(db_dir))[1]]\n\nfor pvals_dir in pvals_dirs:\n for filename in next(os.walk(pvals_dir))[2]:\n if 'pvals.csv' not in filename:\n ... | [
[
"pandas.read_csv"
]
] |
pedrofreitascampospro/locintel | [
"eb9c56cdc308660c31d90abe9fe62bd3634ba273"
] | [
"locintel/routes/plotting/routes.py"
] | [
"import matplotlib.pyplot as plt\n\n\ndef plot_test(test_result, kwargs=None):\n plt.title(f\"{test_result.identifier}\")\n for provider, result in test_result.routes.items():\n plt.scatter(\n *zip(*result.route.geometry.to_lng_lat_tuples()),\n label=provider,\n **kwarg... | [
[
"matplotlib.pyplot.text",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.tight_layout"
]
] |
ryz1g/Tic-Tac-Toe-using-AI-ML | [
"0df91f75fcce20f6e36aae6132747a87038622f3"
] | [
"helping_functions.py"
] | [
"from os import system\nimport numpy as np\nimport math\nfrom tensorflow.keras.models import model_from_json\nimport tensorflow as tf\nfrom tensorflow import keras\n\n#loading of pretrained model and weights starts\njson_file = open('model.json', 'r')\nloaded_model_json = json_file.read()\njson_file.close()\nloaded... | [
[
"numpy.array",
"numpy.amax",
"numpy.random.rand",
"tensorflow.keras.models.model_from_json"
]
] |
cosmozhang/autoencoding_parsing | [
"2e8f4811ca6032f4f89195cd019a4fce4b399dcc"
] | [
"lap/src/decoder.py"
] | [
"# This file contains routines from Lisbon Machine Learning summer school.\n# The code is freely distributed under a MIT license. https://github.com/LxMLS/lxmls-toolkit/\n\nimport torch\nimport numpy as np\nimport pdb\n\ndef log_add_exp(a, b):\n max_ab = torch.max(a, b)\n # max_ab[~isfinite(max_ab)] = 0\n ... | [
[
"numpy.max",
"torch.zeros",
"numpy.zeros",
"torch.max",
"numpy.ones",
"numpy.shape",
"torch.logsumexp",
"torch.cuda.is_available",
"numpy.argmax",
"numpy.size",
"torch.exp"
]
] |
tkerola/chainer | [
"572f6eef2c3f1470911ac08332c2b5c3440edf44"
] | [
"chainer/iterators/multiprocess_iterator.py"
] | [
"from __future__ import division\nimport datetime\nimport multiprocessing\nfrom multiprocessing import sharedctypes # type: ignore\nimport signal\nimport sys\nimport threading\nimport warnings\n\nimport numpy\nimport six\n\nfrom chainer.dataset import iterator\nfrom chainer.iterators import _statemachine\nfrom cha... | [
[
"numpy.frombuffer"
]
] |
abulatek/pyspeckit | [
"862b946027c2f562602347a1bfe0635c7f9f0021"
] | [
"pyspeckit/spectrum/models/h2co_mm.py"
] | [
"\"\"\"\n===========================\nFormaldehyde mm-line fitter\n===========================\n\nThis is a formaldehyde 3_03-2_02 / 3_22-221 and 3_03-2_02/3_21-2_20 fitter.\nIt is based entirely on RADEX models.\n\nThis is the EWR fork of the fitter in pyspeckit.\n\nModule API\n^^^^^^^^^^\n\"\"\"\nfrom __future__ ... | [
[
"numpy.array",
"numpy.isnan",
"numpy.abs"
]
] |
unoebauer/public-astro-tools | [
"765efd02a595fa42a0692114fe448f2457674828"
] | [
"radiative_shock/radiative_shock_calculator.py"
] | [
"#!/usr/bin/env python\n# MIT License\n#\n# Copyright (c) 2018 Ulrich Noebauer\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\"), to deal\n# in the Software without restriction, including without limitation th... | [
[
"matplotlib.use",
"numpy.array",
"numpy.isnan",
"numpy.zeros",
"numpy.ones",
"matplotlib.pyplot.figure",
"numpy.sign",
"numpy.fabs",
"numpy.sqrt",
"numpy.append",
"numpy.log10",
"numpy.linspace",
"numpy.meshgrid",
"numpy.insert"
]
] |
tarrou/probability | [
"d4d80a1c04ad0b3e98758ebc3f7f82887274384d",
"d4d80a1c04ad0b3e98758ebc3f7f82887274384d"
] | [
"tensorflow_probability/python/math/psd_kernels/hypothesis_testlib.py",
"tensorflow_probability/python/mcmc/transformed_kernel.py"
] | [
"# Copyright 2019 The TensorFlow Probability 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 a... | [
[
"tensorflow.compat.v2.math.sigmoid",
"tensorflow.compat.v2.math.tanh",
"tensorflow.compat.v2.Variable"
],
[
"tensorflow.python.util.deprecation.silence",
"tensorflow.compat.v2.identity",
"tensorflow.compat.v2.convert_to_tensor"
]
] |
marvinzh/ConvLab | [
"45ac46b805e064f783b3a1a409b0902ac81da661"
] | [
"convlab/evaluator/multiwoz.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport re\nimport numpy as np\nfrom copy import deepcopy\n\nfrom convlab.evaluator.evaluator import Evaluator\nfrom convlab.modules.util.multiwoz.dbquery import dbs\n\nrequestable = \\\n{'attraction': ['post', 'phone', 'addr', 'fee', 'area', 'type'],\n 'restaurant': ['addr', 'phone', 'po... | [
[
"numpy.mean"
]
] |
xavierbellagamba/4_RuptureRecognition | [
"18e41f6a5a677862bb6d7d0c9adf27271c7b59fe"
] | [
"4_DiscriminatorTraining/4_trainDiscriminator_BoostedTree.py"
] | [
"import numpy as np\nimport matplotlib.pyplot as plt\nimport os\nfrom sklearn.ensemble import GradientBoostingClassifier\nimport GMCluster as gml\nimport discr_utils as du\nfrom matplotlib import cm\nfrom operator import add, sub\nimport pickle\nfrom matplotlib import rc\n\ndef cm2inch(value):\n\treturn value/2.54\... | [
[
"matplotlib.cm.get_cmap",
"numpy.load",
"numpy.save",
"matplotlib.rc",
"matplotlib.pyplot.subplots",
"numpy.mean",
"numpy.std",
"numpy.arange",
"sklearn.ensemble.GradientBoostingClassifier"
]
] |
fischersean/project-euler | [
"1c2f4c5dfa390f971e1eb19b3a5760f3c9340e5c"
] | [
"scripts/analyze_tri_gaps.py"
] | [
"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport os\n\nfile = os.path.join(os.path.realpath('../..'), 'tmp', 'p12out')\ndf = pd.read_csv(file, header=None)\n\nprint(df[0].value_counts())\n\ndef is_prime(n):\n if n<=3: \n return n > 1\n elif n%2==0 or n%3==0:\n return Fa... | [
[
"pandas.read_csv",
"pandas.Series"
]
] |
hanrthu/SimCLR | [
"096aab29984e2761615758dec5377abef42cbad3"
] | [
"resnet-18_80-epochs/checkpoints/resnet_simclr.py"
] | [
"import torch.nn as nn\nimport torch.nn.functional as F\nimport torchvision.models as models\n\n\nclass ResNetSimCLR(nn.Module):\n\n def __init__(self, base_model, out_dim):\n super(ResNetSimCLR, self).__init__()\n self.resnet_dict = {\"resnet18\": models.resnet18(pretrained=False),\n ... | [
[
"torch.nn.Linear",
"torch.nn.functional.relu"
]
] |
amitrai1998/complex--number-calculator | [
"014ea2af6e7f62c2e4a763159b8de6d1d5dd5562"
] | [
"code.py"
] | [
"# --------------\n#Code starts here\r\nimport pandas as pd\r\nimport numpy as np\r\nimport math\r\nclass complex_numbers:\r\n \r\n\r\n def __init__(self,real,imag):\r\n \r\n self.real=real\r\n self.imag=imag\r\n \r\n \r\n def __repr__(self):\r\n\r\n if self.real == 0.... | [
[
"numpy.angle"
]
] |
Tikiten/DeepTreeAttention | [
"63c3b6214231ad32c7748cdac84efead386ea750"
] | [
"DeepTreeAttention/generators/create_training_shp.py"
] | [
"import geopandas as gpd\nimport glob\nimport numpy as np\nimport pandas as pd\nimport rasterstats\n\nfrom shapely.geometry import Point\nfrom DeepTreeAttention.utils.paths import find_sensor_path\n\ndef non_zero_99_quantile(x):\n \"\"\"Get height quantile of all cells that are no zero\"\"\"\n mdata = np.ma.m... | [
[
"numpy.nanpercentile",
"numpy.ma.filled",
"numpy.unique",
"pandas.concat",
"pandas.read_csv",
"numpy.ma.masked_where"
]
] |
johli/aparent | [
"69ad29791709b48689ff5d9e3a3daefc568de9ce"
] | [
"aparent/predictor/aparent_predictor.py"
] | [
"import keras\nfrom keras.models import Sequential, Model, load_model\nfrom keras import backend as K\n\nimport tensorflow as tf\n\nimport os\n\nimport numpy as np\n\nfrom scipy.signal import convolve as sp_conv\nfrom scipy.signal import correlate as sp_corr\nfrom scipy.signal import find_peaks\n\nclass OneHotEncod... | [
[
"numpy.concatenate",
"numpy.max",
"numpy.array",
"numpy.zeros",
"numpy.log",
"numpy.median",
"numpy.sum",
"numpy.ones",
"scipy.signal.correlate",
"numpy.mean",
"numpy.ravel",
"scipy.signal.find_peaks",
"numpy.expand_dims"
]
] |
nachewigkeit/CropDefender | [
"e78fc48f720367ca94033f6263eb1e4a9c6b7858"
] | [
"encode_image.py"
] | [
"import os\nimport glob\nimport bchlib\nimport numpy as np\nfrom PIL import Image, ImageOps\nimport torch\nfrom tqdm import tqdm\n\nBCH_POLYNOMIAL = 137\nBCH_BITS = 5\n\n\ndef main():\n import argparse\n parser = argparse.ArgumentParser()\n parser.add_argument('--model', type=str, default=r\"saved_models/c... | [
[
"torch.nn.Sigmoid",
"torch.no_grad",
"torch.from_numpy",
"torch.tensor",
"torch.load"
]
] |
haihabi/py-research-utils | [
"59ba7c9d24e88324b1d17fea57808136be3033cf",
"59ba7c9d24e88324b1d17fea57808136be3033cf"
] | [
"pyresearchutils/signal_processing/metric.py",
"pyresearchutils/torch/tensor_helpers.py"
] | [
"import numpy as np\nimport torch\n\n\ndef db(x):\n if isinstance(x, np.ndarray): # TODO:make a function\n return 10 * np.log10(x)\n elif isinstance(x, torch.Tensor): # TODO:make a function\n return 10 * torch.log10(x)\n else:\n # TODO:change to logger\n raise Exception(\"AA\"... | [
[
"numpy.log10",
"torch.log10"
],
[
"torch.Tensor"
]
] |
ashiq24/BEENE | [
"fc3be30137e3c748a81118cba603ef004f7a4ae3"
] | [
"beene/getBeeneEmbedding.py"
] | [
"# Importing necessery packages\n\nfrom beene import beene_model\nfrom numpy import random\nfrom sklearn.preprocessing import OneHotEncoder\nimport numpy as np\nfrom sklearn.model_selection import train_test_split\n\n\n\n# creating Random data with 3000 sample and 100 genes per sample.\nXt = random.uniform(-1,1,(30... | [
[
"numpy.savetxt",
"numpy.reshape",
"numpy.random.uniform",
"numpy.random.randint",
"numpy.loadtxt",
"sklearn.model_selection.train_test_split",
"sklearn.preprocessing.OneHotEncoder"
]
] |
elsuizo/abr_control | [
"d7d47a1c152dfcb8d1a3093083d53f19cc4922d6",
"d7d47a1c152dfcb8d1a3093083d53f19cc4922d6"
] | [
"examples/timing_plots.py",
"examples/PyGame/path_planning_linear_filter.py"
] | [
"import timeit\n\nimport matplotlib.pyplot as plt\nimport numpy as np\n\nfrom abr_control.arms import twojoint, ur5, jaco2\nfrom abr_control.controllers import OSC\n\n\ndef test_timing(arm, config_params, osc_params, use_cython):\n robot_config = arm.Config(use_cython=use_cython, **config_params)\n ctrlr = OS... | [
[
"numpy.array",
"numpy.zeros",
"numpy.sum",
"matplotlib.pyplot.title",
"matplotlib.pyplot.legend",
"numpy.random.random",
"numpy.arange",
"matplotlib.pyplot.tight_layout",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.xticks",
"matplotlib.p... |
Nirvanall/Attention-Gated-Networks | [
"8619b63edb31da8e255e50149edf63256e65ccc4"
] | [
"models/utils.py"
] | [
"'''\nMisc Utility functions\n'''\n\nimport os\nimport numpy as np\nimport torch.optim as optim\nfrom torch.nn import CrossEntropyLoss, BCELoss\nfrom utils.metrics import segmentation_scores, dice_score_list\nfrom sklearn import metrics\nfrom .layers.loss import *\n\ndef get_optimizer(option, params):\n opt_alg ... | [
[
"numpy.array",
"sklearn.metrics.confusion_matrix",
"torch.optim.SGD",
"torch.optim.Adam",
"sklearn.metrics.accuracy_score",
"torch.nn.BCELoss",
"sklearn.metrics.precision_score",
"sklearn.metrics.f1_score",
"torch.nn.CrossEntropyLoss",
"sklearn.metrics.recall_score"
]
] |
thb1314/mqbench-openvino | [
"476d64a18a009fa5c001895343929c0332224e1a"
] | [
"mqbench/observer.py"
] | [
"import math\nfrom functools import partial\nfrom typing import Tuple\n\nimport torch\nfrom torch.quantization.observer import _ObserverBase\n\nfrom mqbench.utils import sync_tensor, pot_quantization, is_symmetric_quant\nfrom mqbench.utils.logger import logger\n\n\nclass ObserverBase(_ObserverBase):\n '''\n ... | [
[
"torch.round",
"torch.min",
"torch.max",
"torch.maximum",
"torch.minimum",
"torch.clamp",
"torch.abs",
"torch.tensor",
"torch._aminmax",
"torch.ones_like",
"torch.zeros_like",
"torch.flatten"
]
] |
capitancambio/brainz | [
"97a83e2c0cdfdfa646b8c830d12d0cf318fe2f67"
] | [
"brainz/conn/biosemi.py"
] | [
"import socket\nimport threading\nimport numpy as np\nimport logging\nfrom data.bus import DataChunk\n\n\"\"\" Client for biosemi \"\"\"\nclass BiosemiClient(object):\n \"\"\"docstring for BioClient\"\"\"\n def __init__(self, host,port,dataBuilder):\n self.host=host\n self.port=port\n sel... | [
[
"numpy.reshape",
"numpy.frombuffer"
]
] |
morgen-stern/squeezeDet | [
"e7758bf61f9814a23701746f27728044f250a8a0"
] | [
"src/dataset/kitti.py"
] | [
"# Author: Bichen Wu (bichen@berkeley.edu) 08/25/2016\n\n\"\"\"Image data base class for kitti\"\"\"\n\nimport cv2\nimport os \nimport numpy as np\nimport subprocess\n\nfrom dataset.imdb import imdb\nfrom utils.util import bbox_transform_inv, batch_iou\n\nclass kitti(imdb):\n def __init__(self, image_set, data_pat... | [
[
"numpy.max",
"numpy.array",
"numpy.argmax"
]
] |
GairuiBai/unet-self-anomaly | [
"341390dddea438f904b97d23406cf62fede7a26f"
] | [
"lib/visualizer.py"
] | [
"\"\"\" This file contains Visualizer class based on Facebook's visdom.\n\nReturns:\n Visualizer(): Visualizer class to display plots and images\n\"\"\"\n\n##\nimport os\nimport time\nimport numpy as np\nimport torchvision.utils as vutils\n\n##\nclass Visualizer():\n \"\"\" Visualizer wrapper based on Visdom.... | [
[
"numpy.array"
]
] |
lior1990/taming-transformers | [
"504841cc735133d0b1e8da6b7ce8a7a831e4e937"
] | [
"taming/data/custom_images.py"
] | [
"from typing import Optional\n\nfrom torch.utils.data import Dataset, DataLoader\nimport imageio\nfrom torchvision.transforms import transforms\n\nimport os\nimport pytorch_lightning as pl\n\n\nclass MultipleImageDataset(Dataset):\n def __init__(self, image_path, data_rep):\n transform = transforms.Compos... | [
[
"torch.utils.data.DataLoader"
]
] |
engsoares/mars-gym | [
"c58605180a3f5fb16edbe8bd8954095b9f00a446"
] | [
"src/mars_gym/model/base_model.py"
] | [
"from typing import Tuple, Callable, Union, Type, List, Dict, Any\nfrom itertools import combinations\n\nimport torch\nimport torch.nn as nn\nimport torch.nn.functional as F\nfrom mars_gym.torch.init import lecun_normal_init\nfrom mars_gym.model.abstract import RecommenderModule\nimport numpy as np\nfrom mars_gym.m... | [
[
"torch.nn.Linear",
"torch.cat",
"torch.nn.Embedding"
]
] |
samuelgarcia/ephyviewer | [
"469770eb7b5840523102b72e62f2d4fbe2bcc2ca"
] | [
"ephyviewer/datasource/spikeinterfacesources.py"
] | [
"\"\"\"\nIntegrate\n\"\"\"\n\nfrom .sourcebase import BaseDataSource\nimport sys\nimport logging\n\nimport numpy as np\n\ntry:\n from distutils.version import LooseVersion as V\n import spikeinterface\n if V(spikeinterface.__version__)>='0.90.0':\n HAVE_SI = True\n from neo.rawio.baserawio im... | [
[
"numpy.searchsorted"
]
] |
Jeffkang-94/BDD100k-object-detection | [
"07df20371807f372ad84d41440199989eb20a947"
] | [
"mmdet/datasets/bdd100k.py"
] | [
"import os.path as osp\nimport warnings\nfrom collections import OrderedDict\n\nimport mmcv\nimport numpy as np\nfrom mmcv.utils import print_log\nfrom torch.utils.data import Dataset\n\nfrom mmdet.core import eval_map, eval_recalls\nfrom .builder import DATASETS\nfrom .pipelines import Compose\nfrom .coco import C... | [
[
"numpy.where",
"numpy.random.choice"
]
] |
rohit0906/Monk_Object_Detection | [
"aa96f0fa4629e12e2730164a571ea41aa0ee2278"
] | [
"17_retinaface/lib/train.py"
] | [
"from __future__ import print_function\nimport os\nimport torch\nimport torch.optim as optim\nimport torch.backends.cudnn as cudnn\nimport argparse\nimport torch.utils.data as data\nfrom data import WiderFaceDetection, detection_collate, preproc, cfg_mnet, cfg_re50\nfrom layers.modules import MultiBoxLoss\nfrom lay... | [
[
"torch.no_grad",
"torch.utils.data.DataLoader",
"torch.load",
"torch.nn.DataParallel"
]
] |
mukangt/crnn_ctc_ocr.pytorch | [
"c18582d6f13a47abf2514cc0833166a771192926"
] | [
"src/utils.py"
] | [
"'''\n@Author: Tao Hang\n@Date: 2019-10-17 14:43:52\n@LastEditors : Tao Hang\n@LastEditTime : 2019-12-19 02:16:10\n@Description: \n'''\nimport torch.nn as nn\nimport torch\nfrom torch.autograd import Variable\n\n\ndef weights_init(model):\n for m in model.modules():\n if isinstance(m, nn.Conv2d):\n ... | [
[
"torch.no_grad",
"torch.nn.init.kaiming_normal_",
"torch.nn.init.constant_"
]
] |
adarshchbs/disentanglement | [
"77e74409cd0220dbfd9e2809688500dcb2ecf5a5"
] | [
"load_data.py"
] | [
"import numpy as np\n\nsketch_x_train = np.load('/home/adarsh/project/disentanglement/saved_features/da_sketchy_feature_train.npy',allow_pickle=True)\nsketch_y_train = np.load('/home/adarsh/project/disentanglement/saved_features/da_sketchy_label_train.npy',allow_pickle=True)\nprint('1')\n\nsketch_x_val = np.load('/... | [
[
"numpy.load"
]
] |
spillai/ray | [
"107001d8b8bea0672d5e987341bd6bfcc4a1420e"
] | [
"rllib/models/catalog.py"
] | [
"from functools import partial\nimport gym\nfrom gym.spaces import Box, Dict, Discrete, MultiDiscrete, Tuple\nimport logging\nimport numpy as np\nimport tree # pip install dm_tree\nfrom typing import List, Optional, Type, Union\n\nfrom ray.tune.registry import RLLIB_MODEL, RLLIB_PREPROCESSOR, \\\n RLLIB_ACTION_... | [
[
"numpy.max",
"numpy.product",
"numpy.issubdtype",
"numpy.min"
]
] |
nourshorbagy/MazeSolver | [
"f2b110a2e4522a97d321823b2b176c453411ad71"
] | [
"AI-Package/DBSCAN/DBSCAN.py"
] | [
"# -*- coding: utf-8 -*-\n\nimport numpy\nfrom sklearn.datasets.samples_generator import make_blobs\nfrom sklearn.cluster import DBSCAN\nfrom sklearn.preprocessing import StandardScaler\n\n\n#for making density data \ncenters = [[1, 1], [-1, -1], [1, -1]]\nX, labels_true = make_blobs(n_samples=750, centers=centers,... | [
[
"sklearn.cluster.DBSCAN",
"sklearn.preprocessing.StandardScaler",
"sklearn.datasets.samples_generator.make_blobs"
]
] |
CODEJIN/GAN_based_Vocoders | [
"59eeeacaf9bc9b6743e451dd3b143ebc9ddae3bb"
] | [
"Pattern_Generator.py"
] | [
"import numpy as np\nimport yaml, os, time, pickle, librosa, re, argparse\nfrom concurrent.futures import ThreadPoolExecutor as PE\nfrom collections import deque\nfrom threading import Thread\nfrom random import shuffle\nfrom tqdm import tqdm\n\nfrom Audio import Audio_Prep, Mel_Generate\nfrom yin import pitch_calc... | [
[
"numpy.max",
"numpy.min"
]
] |
ochurlaud/MSc_simulation-fofb | [
"dc9a43f54bf7e570915d0360d102ad04f3cb761d"
] | [
"mysignal/bessy.py"
] | [
"#!/usr/bin/env python3\n# -*- coding: utf-8 -*-\n\n\"\"\" Bessy Signal module\n\n@author: Olivier CHURLAUD <olivier.churlaud@helmholtz-berlin.de>\n\"\"\"\nfrom __future__ import division, print_function\n\nimport math\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport scipy.linalg\nimport scipy.signal as... | [
[
"numpy.linalg.norm",
"scipy.signal.cont2discrete",
"numpy.zeros",
"numpy.fft.ifft",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"numpy.ones",
"matplotlib.pyplot.figure",
"numpy.exp",
"numpy.eye",
"numpy.arange",
"numpy.abs",
... |
ihumphrey/Xi-cam.SAXS | [
"ef71a9e61a0cb277f0a5df3c4b2d907f1154ab4c"
] | [
"xicam/SAXS/operations/onetime.py"
] | [
"import numpy as np\nfrom dask import array as da\nfrom typing import Tuple, List, Iterable\nimport pyqtgraph as pg\n\nimport skbeam.core.correlation as corr\nfrom xicam.SAXS.patches.pyFAI import AzimuthalIntegrator\nfrom xicam.core.intents import PlotIntent\nfrom xicam.core import msg\n\nfrom xicam.plugins.operati... | [
[
"numpy.flipud",
"numpy.min"
]
] |
waleedalzoghby/yolo_caffe | [
"89b101e08dc522131a86bc4808838f25ad44ab8d"
] | [
"valid.py"
] | [
"from darknet import Darknet\nimport dataset\nimport torch\nfrom torch.autograd import Variable\nfrom torchvision import datasets, transforms\nfrom utils import *\nimport os\n\ndef valid(datacfg, cfgfile, weightfile, outfile):\n options = read_data_cfg(datacfg)\n valid_images = options['valid']\n name_list... | [
[
"torch.autograd.Variable",
"torch.utils.data.DataLoader"
]
] |
youchangxin/DeepLabV3Plus | [
"2ee1495b7140a4dc3494e9d4b3557640e380d7b6"
] | [
"train.py"
] | [
"# -*- coding: utf-8 -*-\nimport os\nimport tensorflow as tf\nimport shutil\nfrom deeplabv3plus import model\nfrom dataset import Dataset\nfrom config import cfg\n\n\nos.environ['CUDA_VISIBLE_DEVICES'] = '0'\n\nlog = cfg.TRAIN.LOGDIR\nEPOCHS = cfg.TRAIN.EPOCHS\nsave_every_n_epoch = cfg.TRAIN.SAVE_EPOCH\n\nif os.pat... | [
[
"tensorflow.keras.metrics.Mean",
"tensorflow.train.latest_checkpoint",
"tensorflow.summary.trace_on",
"tensorflow.GradientTape",
"tensorflow.keras.metrics.MeanIoU",
"tensorflow.argmax",
"tensorflow.config.experimental.set_memory_growth",
"tensorflow.keras.metrics.SparseCategoricalA... |
szutenberg/addons | [
"50530e87e827274844a80df1ccadb89423ea119a"
] | [
"tensorflow_addons/optimizers/tests/cyclical_learning_rate_test.py"
] | [
"# Copyright 2019 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"numpy.testing.assert_allclose",
"numpy.abs",
"numpy.floor",
"numpy.linspace",
"numpy.maximum"
]
] |
andersbogsnes/ml_utils | [
"5419a0db4f057b353e37ddee5d1feeb9e2a9680a"
] | [
"src/ml_tooling/plots/viz/regression_viz.py"
] | [
"from matplotlib import pyplot as plt\n\nfrom ml_tooling.plots import plot_residuals, plot_prediction_error\nfrom ml_tooling.plots.viz.baseviz import BaseVisualize\nfrom ml_tooling.config import config\n\n\nclass RegressionVisualize(BaseVisualize):\n \"\"\"\n Visualization class for Regression models\n \"\... | [
[
"matplotlib.pyplot.style.context"
]
] |
tahashmi/arrow | [
"575430d3d74a7a1f5056d5f168ee6d37877635a1"
] | [
"python/pyarrow/tests/test_table.py"
] | [
"# -*- coding: utf-8 -*-\n# Licensed to the Apache Software Foundation (ASF) under one\n# or more contributor license agreements. See the NOTICE file\n# distributed with this work for additional information\n# regarding copyright ownership. The ASF licenses this file\n# to you under the Apache License, Version 2.... | [
[
"numpy.array",
"numpy.isnan",
"numpy.asarray",
"pandas.DataFrame",
"pandas.concat",
"numpy.dtype"
]
] |
IvDmNe/core50 | [
"2497727c2a3dc76d1f383ae368cd587730d062f0"
] | [
"test_metric_learning.py"
] | [
"from scripts.python.data_loader import CORE50\n\nimport torch\nfrom tqdm import tqdm\nfrom faiss_knn import knn\nimport cv2 as cv\nimport numpy as np\nfrom torchvision import transforms\nfrom sklearn.metrics import confusion_matrix\nimport os\nimport pathlib\nimport wandb\nfrom umap import UMAP\n\nimport matplotli... | [
[
"numpy.concatenate",
"torch.cat",
"sklearn.metrics.confusion_matrix",
"torch.stack",
"numpy.empty",
"matplotlib.pyplot.savefig",
"torch.save",
"matplotlib.pyplot.figure",
"torch.load",
"torch.empty",
"torch.set_grad_enabled",
"torch.hub.load"
]
] |
jankukacka/image_viewer_mk2 | [
"38d42eacf2b6ce9a1003b4d9da0f0198cd5bf696"
] | [
"src/image_viewer_mk2/app.py"
] | [
"# ------------------------------------------------------------------------------\n# File: app.py\n# Author: Jan Kukacka\n# Date: 3/2021\n# ------------------------------------------------------------------------------\n# App interface - processes inputs, starts GUI, returns output\n# --------------------------... | [
[
"numpy.array"
]
] |
aislyn/Houston_Redlining | [
"668ce5dd5a0cde8d9440bb92d3175aea127b624b"
] | [
"final_project.py"
] | [
"\n# coding: utf-8\n\n# # Redlining, Race-Exclusive Deed Restriction Language, and Neighborhood Racial Composition in Houston\n# ## 2202PHW Final Project\n# ### Aislyn Schalck, 08-12-2020\n# # \n# Note that this isn't the only explainatory text. This project has text commentary interspaced throughout the code/graph... | [
[
"pandas.DataFrame",
"matplotlib.colors.ListedColormap",
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.show",
"pandas.read_csv",
"matplotlib.colors.LinearSegmentedColormap.from_list"
]
] |
fadybaly/BERT_multilabel | [
"ff88ac35a064e258a574e580f5759807a7f13771"
] | [
"modeling.py"
] | [
"# coding=utf-8\n# Copyright 2018 The Google AI Language Team Authors.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unl... | [
[
"tensorflow.ones",
"tensorflow.matmul",
"tensorflow.reshape",
"tensorflow.control_dependencies",
"tensorflow.nn.softmax",
"tensorflow.one_hot",
"tensorflow.cast",
"tensorflow.shape",
"tensorflow.concat",
"tensorflow.transpose",
"tensorflow.train.list_variables",
"te... |
DATA602/jh-kaggle-util | [
"10cea2b52ccb7bee9d33c9e9330ba24fecda7dce"
] | [
"jhkaggle/jhkaggle/perturb_importance.py"
] | [
"# Jeff Heaton's Kaggle Utilities\n# Copyright 2019 by Jeff Heaton, Open Source, Released under the Apache License\n# For more information: https://github.com/jeffheaton/jh-kaggle-util\n# \n# This is used to determine feature importance using the feature perturb algorithm\nimport jhkaggle\nimport jhkaggle.util\nimp... | [
[
"numpy.max",
"numpy.array",
"sklearn.metrics.mean_squared_error",
"pandas.DataFrame",
"numpy.random.shuffle",
"sklearn.metrics.log_loss"
]
] |
aidanbharath/dolfyn | [
"7c8c62a780ae310b1ffdf04592fa77f400b04334"
] | [
"scripts/motcorrect_vector.py"
] | [
"#!/usr/bin/python\n\nimport argparse\nimport os\nimport numpy as np\nfrom dolfyn.adv.rotate import orient2euler\nimport dolfyn.adv.api as avm\nfrom dolfyn.adv.motion import correct_motion\n\n# TODO: add option to rotate into earth or principal frame (include\n# principal_angle_True in output).\n\nscript_dir = os.p... | [
[
"numpy.array"
]
] |
Gekneusdebips/wradlib | [
"6680d357dd6b19511f687727020fc37bc47c968d"
] | [
"wradlib/io/radolan.py"
] | [
"#!/usr/bin/env python\n# Copyright (c) 2011-2020, wradlib developers.\n# Distributed under the MIT License. See LICENSE.txt for more info.\n\n\"\"\"\nRead RADOLAN and DX\n^^^^^^^^^^^^^^^^^^^\nReading DX and RADOLAN data from German Weather Service\n\n.. autosummary::\n :nosignatures:\n :toctree: generated/\n\n... | [
[
"numpy.array",
"numpy.int",
"numpy.float",
"numpy.ones",
"numpy.flipud",
"numpy.where",
"numpy.float32",
"numpy.frombuffer",
"numpy.int32",
"numpy.vstack"
]
] |
crowther15/Selenium-Youtube-Scraper | [
"916763c7d169b51b78acd1c20a85a1d75e48c29c"
] | [
"scraper.py"
] | [
"import pandas as pd\nfrom selenium import webdriver\nfrom selenium.webdriver.chrome.options import Options\nfrom selenium.webdriver.common.by import By\n\n\nYOUTUBE_TRENDING_URL = 'https://www.youtube.com/feed/trending'\n\ndef get_driver ():\n chrome_options = Options ()\n chrome_options.add_argument ('--no-sand... | [
[
"pandas.DataFrame"
]
] |
divyanshu092/Photorealistic_Style_Transfer | [
"157d391a25e1225ab0830d9fb78bb773459aad94"
] | [
"Code/utils.py"
] | [
"import torch\r\nimport numpy as np\r\nfrom PIL import Image\r\nfrom torchvision import transforms\r\n\r\n\r\ndef load_image(img_path, img_size=None):\r\n '''\r\n Resize the input image so we can make content image and style image have same size, \r\n change image into tensor and normalize it\r\n ... | [
[
"numpy.array"
]
] |
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