repo_name stringlengths 6 130 | hexsha list | file_path list | code list | apis list |
|---|---|---|---|---|
Sondar4/crypto-trends | [
"21c9342e1a38effb65d58760bdd567fa38922b23"
] | [
"visual/graphic.py"
] | [
"from flask import (\n Blueprint, redirect, render_template, request, url_for, send_file\n)\nfrom visual.db import get_db\n\n#--------------------- Imports to generate the plot ---------------------\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport statsmodels.formula.api as smf\n... | [
[
"pandas.to_datetime",
"matplotlib.pyplot.tick_params",
"matplotlib.pyplot.axvline",
"matplotlib.pyplot.savefig",
"pandas.DataFrame",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.fill_between",
"pandas.plotting.register_matplotlib_converters",
"matplotlib.pyplot.axis",
"ma... |
rsd-raul/TF_Yolo_Android | [
"74cfc647346c077e358dee09498dfdc1927e3796"
] | [
"tensorflow/python/framework/constant_op.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.python.framework.ops.device",
"tensorflow.python.eager.execute.args_to_matching_eager",
"tensorflow.python.eager.context.in_graph_mode",
"tensorflow.python.framework.ops.EagerTensor",
"tensorflow.python.framework.ops.register_tensor_conversion_function",
"tensorflow.python.fram... |
lizhengCH/RL2048 | [
"fd5a87d96049c0c5f97148d59cce864f5564e4ca"
] | [
"rl_utils.py"
] | [
"# @Author : Zheng Li\r\n# @Time : 2018/7/25\r\n# @Version : 1.0\r\n# @Document: RL2048.ipynb\r\nimport pickle\r\nimport numpy as np\r\n\r\n\r\ndef reward(state):\r\n table = state.copy().values[1:-1, 1:-1]\r\n\r\n score = np.sum((table // 4) ** 2)\r\n\r\n zero = np.sum(table == 0) * np.mean(table)\r\n... | [
[
"numpy.mean",
"numpy.flipud",
"numpy.argmax",
"numpy.sum"
]
] |
ngroebner/Autoencoders | [
"49105c4aba2959c6973aeba41b9df4eb012f44ac"
] | [
"Autoencoders/losses.py"
] | [
"import torch\nfrom torch import nn\nimport torch.nn.functional as F\n\n# from pytorch examples\n# Reconstruction + KL divergence losses summed over all elements and batch\ndef vae_loss(recon_x, x, mu, logvar):\n MSE = F.binary_cross_entropy_loss(recon_x, x) #, reduction='sum')\n\n # see Appendix B from VAE p... | [
[
"torch.nn.functional.binary_cross_entropy_loss"
]
] |
bjoernmeier/turbodbc | [
"98b0767603b55be7f7c34f18e7bb2e91a7b2e79f"
] | [
"setup.py"
] | [
"from setuptools import setup, Extension, Distribution\nimport setuptools.command.build_ext\n\nimport sys\nimport sysconfig\nimport os\nimport os.path\nimport distutils.sysconfig\n\nimport itertools\nfrom glob import iglob\n\n\ndef _get_turbodbc_libname():\n builder = setuptools.command.build_ext.build_ext(Distr... | [
[
"numpy.get_include"
]
] |
jaycoskey/DancingLinks | [
"24f005d8c5a4166cdb07d447fc351e6d24f77469"
] | [
"block2d.py"
] | [
"#!/usr/bin/env python\n# Copyright (2021) by Jay M. Coskey\n\nimport sys\n\nimport numpy as np\n\n\nclass Block2D:\n def __init__(self, name, reference_layout):\n self.name = name\n self.reference_layout = reference_layout.astype(np.bool)\n self.layouts = self._get_layouts()\n\n def prin... | [
[
"numpy.fliplr",
"numpy.rot90",
"numpy.array",
"numpy.array_equal"
]
] |
saberkia/MLand | [
"49335932b66e4d4c73acecb7bdf46ed7adefe5a6"
] | [
"dc_supervised/sk_multi_knn.py"
] | [
"from sklearn.neighbors import KNeighborsClassifier\nimport numpy as np\nfrom sklearn import datasets\nfrom sklearn.model_selection import train_test_split\nimport matplotlib.pyplot as plt\n\n\ndigits = datasets.load_digits()\nprint(digits.keys())\n# Print the shape of the images and data keys\nprint(digits.images.... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"numpy.arange",
"sklearn.model_selection.train_test_split",
"sklearn.neighbors.KNeighborsClassifier",
"matplotlib.pyplot.plot",
"sklearn.datasets.load_digits",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matp... |
sakshamgulati/MLOps_Workshop | [
"004a1020264a3c84fcc7cdf37ece766b5101000e"
] | [
"training/train.py"
] | [
"import numpy as np\nimport pandas as pd\nfrom sklearn import metrics\nfrom sklearn.model_selection import train_test_split\nimport lightgbm\n\n# Split the dataframe into test and train data\n\n\ndef split_data(data_df):\n \"\"\"Split a dataframe into training and validation datasets\"\"\"\n\n features = data... | [
[
"sklearn.metrics.auc",
"numpy.array",
"sklearn.model_selection.train_test_split",
"sklearn.metrics.roc_curve"
]
] |
gpiantoni/gridgen | [
"975d77a7ee860b1882564724f9f34d2d2801808f"
] | [
"gridgen/matlab/io.py"
] | [
"import scipy.io as spio\nfrom json import load as json_load\nfrom numpy import array, c_, isnan, zeros, genfromtxt, intersect1d, unravel_index\ntry:\n from mat73 import loadmat as load73\nexcept ModuleNotFoundError:\n load73 = None\n\nfrom ..utils import DTYPE, DTYPE_ECOG\n\n\ndef read_ecog2d_matlab(gamma_fi... | [
[
"numpy.isnan",
"scipy.io.loadmat",
"numpy.genfromtxt",
"numpy.intersect1d",
"numpy.array",
"numpy.unravel_index",
"numpy.zeros"
]
] |
sanskar107/Neural-PIL | [
"f34559cf3061c5fd056adc28f8fd47b2501eb842"
] | [
"nn_utils/film_siren_layers.py"
] | [
"import tensorflow as tf\n\n\nclass Sine(tf.keras.layers.Layer):\n def __init__(self, w0: float = 30.0, **kwargs):\n \"\"\"\n Sine activation function with w0 scaling support.\n Args:\n w0: w0 in the activation step `act(x; w0) = sin(w0 * x)`\n \"\"\"\n super(Sine, s... | [
[
"tensorflow.sin"
]
] |
BlueBrain/me-features-to-mo-ID-mapping | [
"15585305c926aef6adfe6027301503c8490097e4"
] | [
"downloader/BBP_downloader.py"
] | [
"# This file is part of me-features-to-mol-ID-mapping.\n#\n#\n# Copyright © 2021-2022 Blue Brain Project/EPFL\n#\n#\n# This program is free software: you can redistribute it and/or modify\n# it under the terms of the APACHE-2 License.\n#\n# This program is distributed in the hope that it will be useful,\n# but WITH... | [
[
"numpy.asarray"
]
] |
AppliedMechanics-EAFIT/Mod_Temporal | [
"6a0506d906ed42b143b773777e8dc0da5af763eb",
"6a0506d906ed42b143b773777e8dc0da5af763eb"
] | [
"codigo/metodos_numericos/raices/roots.py",
"notas_de_clase/img/sympy/sympy_grafico.py"
] | [
"# -*- coding: utf-8 -*-\r\nfrom __future__ import division, print_function\r\nfrom numpy import log2, ceil, abs, zeros\r\n\r\n\r\ndef bracketing(fun, a, b, N):\r\n \"\"\"Estimate the root of a real function using bracketing\r\n\r\n Parameters\r\n ----------\r\n fun : function\r\n Function.\r\n ... | [
[
"numpy.log2",
"numpy.zeros"
],
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.gcf",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.figure"
]
] |
okojoalg/raft-mlp | [
"6060d5d95e142acf80cea6d180adfb075cbe87d0"
] | [
"libs/modules.py"
] | [
"import math\nfrom abc import ABC\nfrom typing import List\n\nimport torch\nfrom einops import rearrange\nfrom einops.layers.torch import Rearrange\nfrom torch import nn\nfrom torch.nn import functional as F\n\nfrom libs.consts import EMB_MIXER, EMB_CROSS_MLP, EMBEDDING_TYPES\nfrom libs.regularizations import DropP... | [
[
"torch.nn.Dropout",
"torch.nn.GELU",
"torch.cat",
"torch.nn.LayerNorm",
"torch.nn.Linear",
"torch.nn.Identity",
"torch.nn.Unfold",
"torch.nn.functional.interpolate"
]
] |
cantbeblank96/kevin_toolbox | [
"a258b2a42c9b4d042decb193354ecb7419bd837c"
] | [
"kevin/machine_learning/patch_for_numpy/axis_and_dim/shuffle/generate_shuffle_index_ls.py"
] | [
"import math\nimport numpy as np\nfrom kevin.machine_learning.patch_for_numpy.axis_and_dim import z_pattern\n\n\ndef generate_shuffle_index_ls(**kwargs):\n \"\"\"\n 生成随机的 index_ls 转置序列\n\n 参数：\n shape: 维度\n 当维度大于1时，仅对最后一个维度进行单位化\n ... | [
[
"numpy.array",
"numpy.random.RandomState",
"numpy.prod"
]
] |
sundogrd/tensorflow_end2end_speech_recognition | [
"65b9728089d5e92b25b92384a67419d970399a64",
"65b9728089d5e92b25b92384a67419d970399a64",
"65b9728089d5e92b25b92384a67419d970399a64",
"65b9728089d5e92b25b92384a67419d970399a64"
] | [
"utils/io/inputs/frame_stacking.py",
"examples/erato/training/train_ctc.py",
"examples/svc/visualization/probs.py",
"models/recurrent/tests/test_tf_qrnn_forward.py"
] | [
"#! /usr/bin/env python\n# -*- coding: utf-8 -*-\n\nfrom __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\n\nimport numpy as np\nimport math\n\nfrom utils.progressbar import wrap_iterator\n\n\ndef stack_frame(input_list, num_stack, num_skip, progressbar=False... | [
[
"numpy.array",
"numpy.zeros"
],
[
"tensorflow.Graph",
"tensorflow.summary.FileWriter",
"tensorflow.placeholder",
"tensorflow.trainable_variables",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.train.Saver",
"tensorflow.summary.merge"
],
... |
lilab-bcb/nmf-torch | [
"acfe548aad950f4aafa17c37a4160209eb919b03"
] | [
"nmf/nmf_models/_nmf_online_hals.py"
] | [
"import torch\n\nfrom typing import Union\nfrom ._nmf_online_base import NMFOnlineBase\n\n\nclass NMFOnlineHALS(NMFOnlineBase):\n def __init__(\n self,\n n_components: int,\n init: str,\n beta_loss: float,\n tol: float,\n random_state: int,\n alpha_W: float,\n ... | [
[
"torch.abs",
"torch.isnan",
"torch.zeros",
"torch.randperm",
"torch.tensor"
]
] |
NSLS-II-OPLS/profile_collection | [
"8c1987fc99a477f21d4e879bbc12a8551788fa4f",
"8c1987fc99a477f21d4e879bbc12a8551788fa4f"
] | [
"startup/13-bimorph.py",
"startup/11-energy.py"
] | [
"bimv0 = [-199.5,-250.6,-51.8,-49.6,-1.5,-35.5,69.1,9,23.1,29.9,-19.2,60.3,-29,-23.6,-203,-303.6]\nbimv1 = [-199.5,-250.6,-51.8,-49.6,-1.5,-35.5,69.1,9,23.1,29.9,-19.2,60.3,-29,-23.6,-203,-303.6]\nbimv2 = [38.3,-102.2,277.5,234.3,325.1,163.2,391.7,280.6,365.3,273.5,196.5,399.9,219.4,304.3,51.5,-327.5]\nbimv3 = [-18... | [
[
"matplotlib.pyplot.plot",
"matplotlib.pyplot.show",
"matplotlib.pyplot.figure"
],
[
"numpy.abs",
"numpy.cos",
"numpy.arcsin"
]
] |
nw2190/ConvPDE | [
"86f3fa67d64a6c56f3dff4d32999fe70db30795e",
"86f3fa67d64a6c56f3dff4d32999fe70db30795e",
"86f3fa67d64a6c56f3dff4d32999fe70db30795e"
] | [
"Poisson_Varying_Domain/Setup/Time_Test/utils/mesh.py",
"Variable_Coefficient/Setup/sample_gaussian.py",
"Poisson_Varying_Domain/Setup/Preprocess_Data.py"
] | [
"from mshr import *\nfrom dolfin import *\n\nimport numpy as np\nfrom scipy import interpolate\nfrom matplotlib import pyplot as plt\n\nimport png\nfrom PIL import Image, ImageFilter\n\n\n# Generates mesh for a polygon with vertex count in specified interval,\n# saves mesh for solver, and saves image file of specif... | [
[
"numpy.random.seed",
"numpy.cumsum",
"numpy.save",
"numpy.cos",
"numpy.sin",
"numpy.max",
"numpy.mod",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros",
"numpy.random.randint"
],
[
"numpy.square",
"numpy.sqrt",
"numpy.random.seed",
"numpy.linspac... |
Mishakolok/Atomize_ITC | [
"7408569e13daa9f7f337cb580947bb3b1f0931ba"
] | [
"atomize/device_modules/PB_ESR_500_pro.py"
] | [
"#!/usr/bin/env python3\r\n# -*- coding: utf-8 -*-\r\n\r\nimport os\r\nimport sys\r\nimport math\r\nfrom copy import deepcopy\r\nfrom operator import iconcat\r\nfrom functools import reduce\r\nfrom itertools import groupby, chain\r\nimport numpy as np\r\nimport atomize.device_modules.config.config_utils as cutil\r\... | [
[
"numpy.split",
"numpy.amax",
"numpy.unique",
"numpy.asarray",
"numpy.amin",
"numpy.argwhere",
"numpy.concatenate",
"numpy.ones",
"numpy.fromstring",
"numpy.diff",
"numpy.transpose",
"numpy.array",
"numpy.zeros",
"numpy.where"
]
] |
CoolProp/CoolPlot | [
"0967e243934c0970ef830b43befeabacc688cdfd"
] | [
"CoolPlot/Util/Quantities.py"
] | [
"# -*- coding: utf-8 -*-\nfrom __future__ import print_function, division\n\nfrom abc import ABCMeta\nfrom six import with_metaclass\nimport warnings\nimport numpy as np\n\nimport CoolProp\n\nfrom . import is_string, _get_index\n\nclass BaseQuantity(object):\n \"\"\"A very basic property that can convert an inpu... | [
[
"numpy.asanyarray"
]
] |
pauldmccarthy/oxford_asl | [
"112ca520e974e6aca74fedf5a4befd1ce8bd6816"
] | [
"python/oxford_asl/gui/preview_mpl.py"
] | [
"\"\"\"\nBASIL GUI for Oxford ASL - Preview widgets\n\nCopyright (C) 2020 University of Oxford\n\"\"\"\nimport os\nimport shutil\nimport tempfile\n\nimport numpy as np\nimport nibabel as nib\n\nimport wx\n\nimport matplotlib\nmatplotlib.use('WXAgg')\nfrom matplotlib.backends.backend_wxagg import FigureCanvasWxAgg a... | [
[
"matplotlib.use",
"matplotlib.backends.backend_wxagg.FigureCanvasWxAgg",
"numpy.mean",
"matplotlib.figure.Figure"
]
] |
nandub/nim-pymod | [
"3e4c49afdfdab2c3325588b6b823c102f22fc588"
] | [
"examples/002-PyArrayIterators-addValToEach/test_addval.py"
] | [
"# Copyright (c) 2015 SnapDisco Pty Ltd, Australia.\n# All rights reserved.\n# \n# This source code is licensed under the terms of the MIT license\n# found in the \"LICENSE\" file in the root directory of this source tree.\n\nimport numpy as np\nimport _addval as av\n\nFUNCS_TO_RUN1 = [\n (\"addVal1\", av.ad... | [
[
"numpy.random.randint"
]
] |
fledge-iot/foglamp-south-human-detector | [
"deaadd512d44a409c8d320e6e843b767de23408d"
] | [
"python/fledge/plugins/south/person_detection/person_detection.py"
] | [
"# -*- coding: utf-8 -*-\n\n# FLEDGE_BEGIN\n# See: http://fledge-iot.readthedocs.io/\n# FLEDGE_END\n\n\"\"\" Human Detector Plugin\n\"\"\"\n__author__ = \"Amandeep Singh Arora, Deepanshu Yadav\"\n__copyright__ = \"Copyright (c) 2020 Dianomic Systems Inc.\"\n__license__ = \"Apache 2.0\"\n__version__ = \"${VERSION}\"... | [
[
"numpy.expand_dims",
"numpy.float32"
]
] |
gawelk/F3DAS | [
"4a4e7233add608820de9ee0fd1c369c2fa1d24c1"
] | [
"gmshModel/Model/RandomInclusionRVE.py"
] | [
"################################################################################\n# CLASS FOR INCLUSION RVE MESHES GENERATED USING THE GMSH-PYTHON-API #\n################################################################################\n# This file provides a class definition for a generation of RVEs with... | [
[
"numpy.sum",
"numpy.asarray",
"numpy.atleast_2d",
"numpy.shape",
"numpy.random.rand",
"numpy.savetxt",
"numpy.zeros",
"numpy.where"
]
] |
BatoolMM/scikit-learn | [
"142e388fa004e3367fdfc0be4a194be0d0c61c8c"
] | [
"sklearn/neighbors/_nearest_centroid.py"
] | [
"\"\"\"\nNearest Centroid Classification\n\"\"\"\n\n# Author: Robert Layton <robertlayton@gmail.com>\n# Olivier Grisel <olivier.grisel@ensta.org>\n#\n# License: BSD 3 clause\n\nimport warnings\nimport numpy as np\nfrom scipy import sparse as sp\n\nfrom ..base import BaseEstimator, ClassifierMixin\nfrom ..me... | [
[
"scipy.sparse.issparse",
"numpy.sqrt",
"numpy.clip",
"numpy.abs",
"numpy.median",
"numpy.ptp",
"numpy.sign",
"numpy.mean",
"numpy.where",
"numpy.zeros",
"numpy.sum",
"numpy.empty"
]
] |
eyaler/impersonator | [
"6843fb21197bc5a32c8189c8d8cbd880c5b71249",
"6843fb21197bc5a32c8189c8d8cbd880c5b71249",
"6843fb21197bc5a32c8189c8d8cbd880c5b71249"
] | [
"thirdparty/neural_renderer/neural_renderer/renderer.py",
"thirdparty/neural_renderer/tests/test_save_obj.py",
"networks/discriminator.py"
] | [
"from __future__ import division\nimport math\n\nimport torch\nimport torch.nn as nn\nimport numpy\n\nimport neural_renderer as nr\n\n\nclass Renderer(nn.Module):\n def __init__(self, image_size=256, anti_aliasing=True, background_color=[0, 0, 0],\n fill_back=True, camera_mode='projection',\n ... | [
[
"torch.cuda.FloatTensor",
"torch.from_numpy"
],
[
"numpy.allclose"
],
[
"torch.nn.Sequential",
"torch.cat",
"torch.nn.ModuleList",
"torch.nn.Conv2d",
"torch.nn.Sigmoid",
"torch.nn.LeakyReLU",
"torch.nn.functional.interpolate"
]
] |
lordzohar/ga-learner-dsmp-repo | [
"53e9e7fe450f8b6a8ff0ac837477e652f64f4420"
] | [
"Inferential-Statistics/code.py"
] | [
"# --------------\nimport pandas as pd\r\nimport scipy.stats as stats\r\nimport math\r\nimport numpy as np\r\nimport warnings\r\n\r\nwarnings.filterwarnings('ignore')\r\n#Sample_Size\r\nsample_size=2000\r\n\r\n#Z_Critical Score\r\nz_critical = stats.norm.ppf(q = 0.95) \r\n\r\n\r\n# path [File location varia... | [
[
"scipy.stats.chi2.ppf",
"scipy.stats.norm.ppf",
"pandas.read_csv",
"pandas.Series",
"scipy.stats.chi2_contingency",
"numpy.sqrt",
"matplotlib.pyplot.subplots",
"numpy.array",
"matplotlib.pyplot.show"
]
] |
mginesi/sds | [
"c0ce8fbf931996622d0c50a074073d280e37d508"
] | [
"sds/envs/quanser/qube/qube_rr.py"
] | [
"import numpy as np\n\nfrom sds.envs.quanser.common import QSocket, VelocityFilter\nfrom sds.envs.quanser.qube.base import QubeBase\nfrom sds.envs.quanser.qube.ctrl import CalibrCtrl\n\n\nclass QubeRR(QubeBase):\n def __init__(self, ip, fs_ctrl):\n super(QubeRR, self).__init__(fs=500.0, fs_ctrl=fs_ctrl)\n... | [
[
"numpy.array",
"numpy.zeros",
"numpy.abs",
"numpy.linalg.norm"
]
] |
nspotrepka/deeptone | [
"bdceff6678fbb757930053b474d89edb12add434"
] | [
"deeptone/setup.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.utils.data import DataLoader\n\ndef torch_version():\n return torch.__version__\n\ndef cuda_is_available():\n return torch.cuda.is_available()\n\ndef cuda_device_count():\n return torch.cuda.device_count()\n\ndef device():\n return torch.device('cuda:0' i... | [
[
"torch.cuda.device_count",
"torch.utils.data.DataLoader",
"torch.nn.DataParallel",
"torch.cuda.is_available"
]
] |
radiasoft/rsbeams | [
"1a35c9222ee727a580d626b1791b2c29c1215346",
"1a35c9222ee727a580d626b1791b2c29c1215346"
] | [
"rsbeams/rsptcls/RsPhaseSpace6D.py",
"rsbeams/rsdata/switchyard.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Data holding class for 6D phase space distributions.\n\nOriginal code taken from RadTrack project, https://github.com/radiasoft/radtrack\n:copyright: Copyright (c) 2013 RadiaBeam Technologies, LLC. All Rights Reserved.\n\nSubsequent mods are due to RadiaSoft,\n:copyright: Copyright (... | [
[
"numpy.load",
"numpy.savez",
"numpy.shape",
"numpy.zeros"
],
[
"pandas.DataFrame",
"numpy.max",
"numpy.average",
"numpy.zeros",
"numpy.empty"
]
] |
adisam007/Vehicle-Counting-Application | [
"c5ffbf0e17fc78fff4e9aae8e63fab28b636b385"
] | [
"deep_sort/generate_detections.py"
] | [
"# vim: expandtab:ts=4:sw=4\nimport os\nimport errno\nimport argparse\nimport numpy as np\nimport cv2\nimport tensorflow.compat.v1 as tf\n \nphysical_devices = tf.config.experimental.list_physical_devices('GPU')\nprint(physical_devices)\nif len(physical_devices) > 0:\n tf.config.experimental.set_memory_growth... | [
[
"tensorflow.compat.v1.get_default_graph",
"numpy.maximum",
"tensorflow.compat.v1.import_graph_def",
"tensorflow.compat.v1.config.experimental.list_physical_devices",
"numpy.asarray",
"tensorflow.compat.v1.config.experimental.set_memory_growth",
"tensorflow.compat.v1.Session",
"nump... |
CrtomirJuren/pyfirmata-arduino | [
"020873972d119955e80387f44bcc193ad0b460a6"
] | [
"old-version/pyfirmata2-realtime_scope.py"
] | [
"#!/usr/bin/python3\n\nfrom pyfirmata2 import Arduino\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.animation as animation\n\n# Realtime oscilloscope at a sampling rate of 100Hz\n# It displays analog channel 0.\n# You can plot multiple chnannels just by instantiating\n# more RealtimePlotWi... | [
[
"matplotlib.pyplot.subplots",
"numpy.append",
"matplotlib.animation.FuncAnimation",
"matplotlib.pyplot.show",
"numpy.zeros"
]
] |
onnx/onnx-converters | [
"f9ebc35dba8a9555112a8d0b84f5a3d51278cca9"
] | [
"test/backend/test_node.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport math\nimport unittest\n\nfrom onnx import defs\nfrom onnx import helper\nfrom onnx import TensorProto\nfrom onnx.backend.test.case.node import hardmax\nf... | [
[
"numpy.minimum",
"numpy.sqrt",
"numpy.cumsum",
"numpy.all",
"numpy.exp",
"numpy.where",
"numpy.complex64",
"numpy.square",
"numpy.matmul",
"numpy.ceil",
"numpy.less_equal",
"numpy.zeros",
"numpy.log",
"numpy.multiply",
"numpy.power",
"numpy.testing.a... |
zhanhuadong/gatk-master | [
"667fa62a0a65270a822f56160e50702129a4fcd8"
] | [
"src/main/python/org/broadinstitute/hellbender/gcnvkernel/io/io_denoising_calling.py"
] | [
"import logging\n\nimport numpy as np\nimport pymc3 as pm\nimport pandas as pd\nimport os\nimport json\nfrom typing import List, Optional\n\nfrom .. import config\nfrom ..models.model_denoising_calling import DenoisingCallingWorkspace, DenoisingModel\nfrom ..models.model_denoising_calling import CopyNumberCallingCo... | [
[
"pandas.read_csv"
]
] |
cvamateur/SimDet | [
"aa9bd4d3a34ecf6b882f5f8bba4bb565b747eaac"
] | [
"src/solver.py"
] | [
"import time\nimport torch\nimport matplotlib.pyplot as plt\n\nfrom utils.bbox_utils import coord_trans\n\n\ndef detection_solver(detector: torch.nn.Module, data_loader, cfg):\n \"\"\"\n Optimize detector.\n \"\"\"\n detector = detector.to(cfg.device)\n\n # optimizer\n optimizer = torch.optim.SGD(... | [
[
"torch.optim.lr_scheduler.LambdaLR",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
tslaton/cross-section-viewer | [
"8b966786bc6cd3d36ae9569ad7d0484448b044f8"
] | [
"ipysliceviewer/sliceviewer.py"
] | [
"# Standard lib\nimport os\n# Third party\nfrom PIL import Image\nfrom bqplot import (\n LinearScale, Figure, PanZoom,\n Toolbar, Image as BQImage,\n)\nfrom ipywidgets import (\n VBox, HBox, Layout, GridBox,\n Button, ToggleButton, ToggleButtons,\n IntSlider, FloatRangeSlider,\n Play, Output, jsli... | [
[
"numpy.clip"
]
] |
avoll/zipline-crypto | [
"5cc586fa0396d7ffce78b70cf66ac5a020b9a4e4"
] | [
"zipline_poloniex/bundle.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"\nZipline bundle for Poloniex exchange\n\"\"\"\nimport logging\nfrom datetime import time, timedelta, datetime\n\nfrom pytz import timezone\nimport numpy as np\nimport pandas as pd\nfrom pandas.tseries.offsets import CustomBusinessDay\nfrom zipline.utils.calendars import (\n Tradi... | [
[
"pandas.tseries.offsets.CustomBusinessDay",
"pandas.Timestamp",
"pandas.date_range"
]
] |
Paddle-Team-7/PiT-Paddle-master | [
"125268471ca34be3161cce5364c728341c3711e0"
] | [
"try.py"
] | [
"import numpy as np\n\nimport paddle\nimport paddle.static as static\nimport paddle.nn.functional as F\n\npaddle.enable_static()\ndata = static.data(name=\"input\", shape=[-1, 32, 32], dtype=\"float32\")\nlabel = static.data(name=\"label\", shape=[-1,1], dtype=\"int\")\nfc_out = static.nn.fc(x=data, size=10)\npredi... | [
[
"numpy.array",
"numpy.random.rand"
]
] |
kyper999/caffe2-2 | [
"7c10b470de8d19261f10e958846d7efcfd751a09"
] | [
"caffe2/python/predictor/predictor_exporter_test.py"
] | [
"from __future__ import absolute_import\nfrom __future__ import division\nfrom __future__ import print_function\nfrom __future__ import unicode_literals\n\nimport tempfile\nimport unittest\nimport numpy as np\nfrom caffe2.python import cnn, workspace, core\n\nfrom caffe2.python.predictor_constants import predictor_... | [
[
"numpy.random.randn",
"numpy.zeros",
"numpy.random.seed",
"numpy.ones"
]
] |
laochanlam/loglizer | [
"d0cab2c7993f5a47bf8b2e5031f2dcc89f620fcf"
] | [
"models/log_clustering.py"
] | [
"#!/usr/bin/env python\n# -*- coding: utf-8 -*-\n__author__ = 'Shilin He'\n\nimport sys\nsys.path.append('../utils')\n\nimport numpy as np\nimport math\nfrom scipy.special import expit\nfrom numpy import linalg as LA\nfrom scipy.cluster.hierarchy import linkage\nfrom scipy.cluster.hierarchy import fcluster\nfrom sc... | [
[
"numpy.dot",
"numpy.allclose",
"numpy.nonzero",
"numpy.squeeze",
"numpy.linalg.norm",
"numpy.ones",
"scipy.spatial.distance.pdist",
"numpy.argmin",
"numpy.count_nonzero",
"scipy.cluster.hierarchy.linkage",
"numpy.array",
"numpy.zeros",
"numpy.sum",
"scipy.cl... |
christopher-schroeder/dna-seq-strling | [
"d813fac0560721c08e9971a8a66f5ce6f396e1f0"
] | [
"workflow/scripts/create_catalogue.py"
] | [
"import pandas as pd\nimport json\n\ndata = pd.read_csv(snakemake.input.regions, sep=\"\\t\")\nret = []\n\nfor i, row in data.iterrows():\n entry = dict()\n entry[\"LocusId\"] = row[\"region_name\"]\n entry[\"LocusStructure\"] = f'({row[\"motif\"]})*'\n entry[\"ReferenceRegion\"] = f'{row[\"chrom\"]}:{r... | [
[
"pandas.read_csv"
]
] |
okadalabipr/Shinohara_et_al_2014 | [
"c73b242ecdf500ed4c10aeb9ded5f1f452f9f22d"
] | [
"plot_func.py"
] | [
"from matplotlib import pyplot as plt\n\nfrom model.name2idx import V\n\n\ndef timecourse(sim):\n plt.figure(figsize=(16, 12))\n plt.rcParams['font.size'] = 18\n plt.rcParams['axes.linewidth'] = 1\n plt.rcParams['lines.linewidth'] = 2\n\n plt.subplots_adjust(wspace=0.4, hspace=0.5)\n\n # IKK activ... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.yticks",
"matplotlib.pyplot.ylim",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlim",
"matplotlib.pyplot.subplot",
"matplotlib.pyplot.ylabel",
"matplotlib.pyplot.subplots_adjust",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot... |
wandb/fairing | [
"7e0529d065130e5af22c068312fa20fe61e5705f"
] | [
"examples/kubeflow/main.py"
] | [
"# Copyright 2015 The TensorFlow Authors. All Rights Reserved.\n#\n# Licensed under the Apache License, Version 2.0 (the \"License\");\n# you may not use this file except in compliance with the License.\n# You may obtain a copy of the License at\n#\n# http://www.apache.org/licenses/LICENSE-2.0\n#\n# Unless requ... | [
[
"tensorflow.summary.FileWriter",
"tensorflow.examples.tutorials.mnist.mnist.inference",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.summary.merge_all",
"tensorflow.logging.set_verbosity",
"tensorflow.examples.tutorials.mnist.mnist.loss",
"tensor... |
jamesj-jiao/aim | [
"452380368f76ff441b2ff3a51029f4ad43a9d902"
] | [
"examples/tf_profiler_while_loop.py"
] | [
"import time\nimport tensorflow as tf\n\n# Import MNIST data\nfrom tensorflow.examples.tutorials.mnist import input_data\n\nimport aim\naim.init(overwrite=True)\n\nfrom aim import Profiler\nProfiler.init(auto_detect_cycles=False, aggregate=Profiler.MEAN)\n\nmnist = input_data.read_data_sets('/tmp/data/', one_hot=Tr... | [
[
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.matmul",
"tensorflow.while_loop",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.train.AdamOptimizer",
"tensorflow.Session",
"tensorflow.argmax",
"tensorflow.... |
Bartiik/action-hypergraph-networks | [
"3d4dfddfacaaea36667fe752b0cb7f22608d75ee"
] | [
"hyperdopamine/interfaces/train.py"
] | [
"# This script modifies Dopamine with the original copyright note:\n# \n# Copyright 2018 The Dopamine 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.... | [
[
"tensorflow.compat.v1.logging.set_verbosity"
]
] |
AldenJurling/webbpsf | [
"9d368ab988a600047f5476020a38c682f59cca6a"
] | [
"webbpsf/jupyter_gui.py"
] | [
"import logging\nimport matplotlib\nimport astropy.io.fits as fits\n\nimport poppy\nfrom . import webbpsf_core\nfrom . import wfirst\n\n_log = logging.getLogger('webbpsf')\n\n\n\ndef show_notebook_interface(instrumentname):\n \"\"\"\n Show Jupyter notebook widget interface\n\n Parameters\n -----------\n... | [
[
"matplotlib.pyplot.subplots",
"matplotlib.pyplot.figure"
]
] |
KhaledSharif/winton-stock-market | [
"78340264dd6e6a91b83a6b989494635a7a16f5c5"
] | [
"submission.py"
] | [
"import xgboost as xgb\nimport numpy as np\nimport pandas\n\nmajor_list = []\n\ntraining_csv = pandas.read_csv('./train.csv', index_col=0)\ntesting_csv = pandas.read_csv('./test_2.csv', index_col=0)\n\nfor Number in range(1,62+1): # From 1 to 62\n\n if Number == 61:\n name_of_column = 'Ret_PlusOne'\n ... | [
[
"pandas.read_csv",
"pandas.DataFrame"
]
] |
hepengli/multiagent-particle-envs | [
"8c8da62be162c813632c1736f57bfaa75d7e107e"
] | [
"multiagent/new_core.py"
] | [
"import numpy as np\r\nimport seaborn as sns\r\n\r\n# physical/external base state of all entites\r\nclass EntityState(object):\r\n def __init__(self):\r\n # physical position\r\n self.p_pos = None\r\n # physical velocity\r\n self.p_vel = None\r\n\r\n# state of agents (including commu... | [
[
"numpy.square",
"numpy.abs",
"numpy.arcsin",
"numpy.vstack",
"numpy.linalg.norm",
"numpy.cos",
"numpy.sin",
"numpy.random.randn",
"numpy.array",
"numpy.zeros",
"numpy.logaddexp"
]
] |
MonikaLamba/Microarray | [
"eee7627bf763faf100c5e509620c1b64c0378ea1"
] | [
"pipeline.py"
] | [
"import logging\n\nimport numpy as np\nimport pandas as pd\nfrom sklearn.model_selection import StratifiedKFold\n\nfrom utils import features_utils, nn_utils\nfrom utils.data_params import DataParams as dp\nfrom utils.hyperparams import Hyperparameters as hp\n\nlogger = logging.getLogger(__name__)\nlogger.setLevel(... | [
[
"numpy.random.permutation",
"numpy.array",
"pandas.read_csv",
"sklearn.model_selection.StratifiedKFold"
]
] |
jacekdobrowolski/regression_forest | [
"7eb6de444d5abc625a91c055141bc8524e0f12f0"
] | [
"plots/plot6.py"
] | [
"import matplotlib.pyplot as plt\n\nimport random_forest\nimport preparedata\n\ndf = preparedata.load()\ndelayed_df = preparedata.delay(df, 2)\nforest_result = list()\nnaive_result = list()\n\niterations = 10\nx_axis = range(10, 130, 20)\nfor x in x_axis:\n random_forest.tree.config.create_config(\n min_s... | [
[
"matplotlib.pyplot.legend",
"matplotlib.pyplot.title",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.show",
"matplotlib.pyplot.ylabel"
]
] |
cvillacampa/GPInputNoise | [
"0e9268a7dec7920bff5219b083793ad1e7633a54",
"0e9268a7dec7920bff5219b083793ad1e7633a54"
] | [
"experiments/synthetic/noise_0.5/NIMGPC_NN/test_toy.py",
"experiments/active_learning/0.25/NIMGPC/test_real.py"
] | [
"import numpy as np\nimport tensorflow as tf\nimport sys\nsys.path.append(\"../../../..\")\nfrom gp_input_noise.nimgpc_nn import NIMGPC_NN\nfrom gp_input_noise.data import load_object\nfrom gp_input_noise.rbf_ard import RBF_ARD\n\nnp.random.seed(0)\n\nfold = int(sys.argv[1])\ndata = load_object(\"../data/dataset_no... | [
[
"numpy.dot",
"numpy.random.seed",
"numpy.triu_indices",
"numpy.arange",
"numpy.ones",
"numpy.max",
"numpy.mean",
"numpy.zeros_like",
"tensorflow.train.AdamOptimizer",
"numpy.sum"
],
[
"numpy.dot",
"numpy.log",
"numpy.random.seed",
"numpy.random.choice",
... |
5l1v3r1/pyannote-audio | [
"23b4f548c5d1deedb5383799d17bbb24628ca54b"
] | [
"pyannote/audio/train/trainer.py"
] | [
"#!/usr/bin/env python\n# encoding: utf-8\n\n# The MIT License (MIT)\n\n# Copyright (c) 2018-2020 CNRS\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, includin... | [
[
"torch.device",
"torch.utils.tensorboard.SummaryWriter",
"torch.load"
]
] |
brad903/Inflearn-DeepLearningZeroToAll | [
"dc0d79fb61c7d93a2f0fa2066a08434e765b4712"
] | [
"lab-10-5-mnist_nn_dropout.py"
] | [
"# Lab 10 MNIST and Dropout\nimport tensorflow as tf\nimport random\n# import matplotlib.pyplot as plt\n\nfrom tensorflow.examples.tutorials.mnist import input_data\n\ntf.set_random_seed(777) # reproducibility\n\nmnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\n# Check out https://www.tensorflow.o... | [
[
"tensorflow.matmul",
"tensorflow.nn.softmax_cross_entropy_with_logits",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.random_normal",
"tensorflow.contrib.layers.xavier_initializer",
"tensorflow.Session",
"tensorflow.train.Ad... |
richardSHkim/FairMOT | [
"e32e49022a212ada9edf30a9d58ef3a664ca6442"
] | [
"src/lib/tracking_utils/visualization.py"
] | [
"import numpy as np\nimport cv2\n\n\ndef tlwhs_to_tlbrs(tlwhs):\n tlbrs = np.copy(tlwhs)\n if len(tlbrs) == 0:\n return tlbrs\n tlbrs[:, 2] += tlwhs[:, 0]\n tlbrs[:, 3] += tlwhs[:, 1]\n return tlbrs\n\n\ndef get_color(idx):\n idx = idx * 3\n color = ((37 * idx) % 255, (17 * idx) % 255, (... | [
[
"numpy.asarray",
"numpy.copy",
"numpy.zeros"
]
] |
NLP-RL/A-SIDDS | [
"86f1f4387cf3809106b14043aebe2571e8174654"
] | [
"Code/log/run_for_test.py"
] | [
"# -*- coding:utf-8 -*-\n\nimport time\nimport argparse\nimport pickle\nimport sys, os\nimport random\nimport json\nimport torch\nsys.path.append(os.getcwd().replace(\"src/dialogue_system/run\",\"\"))\n\nfrom src.dialogue_system.agent import AgentRandom\nfrom src.dialogue_system.agent import AgentDQN\nfrom src.dial... | [
[
"torch.manual_seed",
"torch.cuda.manual_seed"
]
] |
megvii-research/SOLQ | [
"058dd08959f2f80619c92cb341b6bccba5a20127"
] | [
"util/tool.py"
] | [
"# ------------------------------------------------------------------------\n# Copyright (c) 2021 megvii-model. All Rights Reserved.\n# ------------------------------------------------------------------------\n# Modified from Deformable DETR (https://github.com/fundamentalvision/Deformable-DETR)\n# Copyright (c) 20... | [
[
"torch.load"
]
] |
ronaldseoh/ecco | [
"52e7014fb3c2cf4a68590dd479ac65ee0cc38fd4"
] | [
"src/ecco/lm.py"
] | [
"from collections import defaultdict\nimport inspect\nimport json\nimport os\nimport random\nimport torch\nimport transformers\nfrom transformers import BatchEncoding\n\nimport ecco\nimport numpy as np\nfrom IPython import display as d\nfrom torch.nn import functional as F\nfrom ecco.attribution import compute_prim... | [
[
"numpy.swapaxes",
"torch.nn.functional.softmax",
"torch.zeros",
"torch.cat",
"torch.multinomial",
"torch.tensor",
"torch.matmul",
"numpy.zeros_like",
"torch.cuda.is_available",
"numpy.array",
"torch.argmax"
]
] |
frysee/jesse | [
"07b4ce0427d6aed5c1de2b5faa9307c8cab18250"
] | [
"jesse/utils.py"
] | [
"import math\nfrom decimal import Decimal\nfrom typing import Union\n\nimport numpy as np\nimport pandas as pd\nfrom talib import MA\n\nimport jesse.helpers as jh\nfrom jesse.enums import timeframes\n\n\ndef anchor_timeframe(timeframe: str) -> str:\n \"\"\"\n Returns the anchor timeframe. Useful for writing\n... | [
[
"pandas.to_datetime",
"numpy.clip",
"numpy.full",
"numpy.all",
"numpy.logical_or",
"numpy.diff",
"numpy.array",
"numpy.logical_and",
"numpy.where"
]
] |
xuanxu/intergalactic | [
"09e158243e1c119d7b3c06fcbb009572081994c1"
] | [
"src/starmatrix/tests/test_matrix.py"
] | [
"import pytest\nfrom pytest_mock import mocker\nimport numpy as np\nimport starmatrix.constants as constants\nimport starmatrix.settings as settings\nimport starmatrix.elements as elements\nimport starmatrix.abundances as abundances\nimport starmatrix.matrix as matrix\n\n\ndef test_q_index():\n assert matrix.q_i... | [
[
"numpy.all",
"numpy.zeros",
"numpy.random.rand",
"numpy.random.choice"
]
] |
vahidmoeinifar/ndlib | [
"c55a65b4f0ed2928cf36f4e2b33d872d33e734ba"
] | [
"ndlib/models/dynamic/DynSISModel.py"
] | [
"from ..DynamicDiffusionModel import DynamicDiffusionModel\nimport numpy as np\nimport networkx as nx\nimport future.utils\n\n__author__ = \"Giulio Rossetti\"\n__license__ = \"BSD-2-Clause\"\n__email__ = \"giulio.rossetti@gmail.com\"\n\n\nclass DynSISModel(DynamicDiffusionModel):\n \"\"\"\n Model Parameter... | [
[
"numpy.random.random_sample"
]
] |
Ganeshrockz/ML-Project | [
"d212257b38da5c2ea48cacb6ba8c018a9a84a1f0"
] | [
"prediction/svm.py"
] | [
"\r\n\r\n#You do not talk about Fight Club\r\nimport os\r\nos.chdir('....\\\\data\\\\input.csv')\r\n\r\n#You DO NOT talk about Fight Club\r\nimport pandas as pd\r\nfrom sklearn.preprocessing import LabelEncoder\r\nfrom fancyimpute import KNN\r\nfrom sklearn import svm\r\n\r\n#Only two guys to a fight\r\ntrain = pd.... | [
[
"sklearn.preprocessing.LabelEncoder",
"pandas.read_csv",
"pandas.DataFrame"
]
] |
LuckyDC/generalizing-reid | [
"c77cb7a8317408e632a1e435d9ab533170bdb37d"
] | [
"train.py"
] | [
"import logging\nimport os\nimport pprint\n\nimport torch\nimport torch.distributed as dist\nimport yaml\nfrom apex import amp\nfrom apex import parallel\nfrom tensorboardX import SummaryWriter\nfrom torch import optim\n\nfrom data import get_cross_domain_train_loader\nfrom data import get_test_loader\nfrom data im... | [
[
"torch.optim.lr_scheduler.MultiStepLR",
"torch.distributed.init_process_group",
"torch.cuda.set_device",
"torch.distributed.is_initialized",
"torch.distributed.destroy_process_group",
"torch.optim.SGD",
"torch.distributed.get_rank",
"torch.cuda.device_count"
]
] |
alpkn/open_model_zoo | [
"15230340eea7677ea457560a3b3e16baedf4be8f"
] | [
"demos/action_recognition_demo/python/action_recognition_demo/steps.py"
] | [
"\"\"\"\n Copyright (c) 2020 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 http://www.apache.org/licenses/LICENSE-2.0\n\n Unless required by applicable law ... | [
[
"numpy.expand_dims",
"numpy.concatenate",
"numpy.max",
"numpy.exp",
"numpy.array",
"numpy.sum"
]
] |
gilsaia/BERT-NER-Pytorch | [
"a45d0a64cbef254af7174c21e4c58eb8afa70931"
] | [
"callback/optimizater/adabound.py"
] | [
"import torch\r\nimport math\r\nfrom torch.optim.optimizer import Optimizer\r\n\r\nclass AdaBound(Optimizer):\r\n \"\"\"Implements AdaBound algorithm.\r\n It has been proposed in `Adaptive Gradient Methods with Dynamic Bound of Learning Rate`_.\r\n Arguments:\r\n params (iterable): iterable of param... | [
[
"torch.full_like",
"torch.zeros_like",
"torch.max"
]
] |
ajaybiswas22/Distance-Based-Classifier | [
"f3c56ae6f12fc59fe1c3178515dd0980435e7ba3"
] | [
"src/distance_based_classifier.py"
] | [
"# Distance Based Classification\n\"\"\"\n@author: Ajay Biswas\n220CS2184\nM.Tech Information Security \nNational Institute of Technology, Rourkela\n\"\"\"\n\nfrom sklearn import datasets\nimport statistics as st\nimport numpy as np\nimport pandas as pd\nfrom sklearn.metrics import mean_squared_error as mse\nfrom s... | [
[
"sklearn.metrics.mean_absolute_error",
"sklearn.datasets.load_iris",
"numpy.zeros",
"sklearn.metrics.mean_squared_error"
]
] |
NouamaneTazi/conv-emotion | [
"0c9dcb9cc5234a7ca8cf6af81aabe28ef3814d0e"
] | [
"emotion-cause-extraction/ECPE-2D/main.py"
] | [
"import numpy as np\r\nimport tensorflow.compat.v1 as tf\r\ntf.disable_v2_behavior()\r\ntf.enable_eager_execution()\r\nfrom sklearn.model_selection import KFold\r\nimport sys, os, time, codecs\r\n\r\nsys.path.append('./utils')\r\nsys.path.append('./bert')\r\nfrom tf_funcs import *\r\nfrom prepare_data import *\r\ni... | [
[
"tensorflow.compat.v1.nn.dropout",
"tensorflow.compat.v1.app.flags.DEFINE_bool",
"tensorflow.compat.v1.concat",
"tensorflow.compat.v1.enable_eager_execution",
"tensorflow.compat.v1.shape",
"tensorflow.compat.v1.config.set_soft_device_placement",
"tensorflow.compat.v1.constant",
"te... |
chengzimo/PedestrianDetection | [
"643b07e87595b480eed6b28058ffbb5845f09f53"
] | [
"PedestrianDetectionFunc/PedestrianDetectionModel.py"
] | [
"#encoding: utf-8\nimport numpy as np\nfrom PedestrianDetectionFunc.Utils.utils import letterbox_image\nfrom PedestrianDetectionFunc.Model.model import yolo_eval\nimport os\nfrom keras import backend as K\nfrom keras.models import load_model\n\nclass PedestrianModel(object):\n def __init__(self):\n self.i... | [
[
"numpy.array",
"numpy.expand_dims"
]
] |
ouyangksoc/urbanpy | [
"ef8b74560a7aa95d33db71ccd345169eadf85bd2"
] | [
"UrbanPy/layers.py"
] | [
"import torch.nn as nn\nimport torch\nimport torch.nn.functional as F\ncuda = True if torch.cuda.is_available() else False\nTensor = torch.cuda.FloatTensor if cuda else torch.FloatTensor\nimport numpy as np\n\nclass LocalConv(nn.Module):\n def __init__(self, width, block_size, in_chn, out_chn):\n super(Lo... | [
[
"torch.nn.functional.kl_div",
"torch.nn.functional.upsample",
"numpy.isnan",
"torch.randn",
"torch.eye",
"torch.log",
"torch.cuda.is_available",
"torch.stack",
"numpy.zeros"
]
] |
lorenzob123/HMLF | [
"3577c61b8f2bae7959de81dfd3981c3a8e26d8b6",
"3577c61b8f2bae7959de81dfd3981c3a8e26d8b6"
] | [
"tests/utils.py",
"hmlf/environments/vec_env/subproc_vec_env.py"
] | [
"from typing import List, Optional, Tuple\n\nimport numpy as np\n\nfrom hmlf.spaces import Box\n\n\ndef make_box(low: Optional[List] = None, high: Optional[List] = None, shape: Optional[Tuple] = None) -> Box:\n if shape is None:\n if (low is None) and (high is None):\n raise ValueError(\"Some v... | [
[
"numpy.array"
],
[
"numpy.stack"
]
] |
kibernetika-ai/demo-zoo | [
"e3ff6010dc2636a44beff2a0333270a824996ed0"
] | [
"heartbeat/heartbeat_hook.py"
] | [
"import numpy as np\nimport pandas as pd\nimport logging\nimport matplotlib.pyplot as plt\nimport io\n\nLOG = logging.getLogger(__name__)\n\nCLASSES = [\"Cat. N\",\"Cat. S\",\"Cat. V\",\"Cat. F\",\"Cat. Q\"]\n\ndef init_hook(**kwargs):\n LOG.info('init: {}'.format(kwargs))\n\ndef process(inputs, ctx, **kwargs):\... | [
[
"pandas.read_csv",
"numpy.expand_dims",
"matplotlib.pyplot.figure",
"numpy.arange",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.ylabel"
]
] |
combra-lab/NALSM | [
"d2d303eea01657770feb9fac775fa925d4d70c6e",
"d2d303eea01657770feb9fac775fa925d4d70c6e"
] | [
"LSM_APSTDP_CONSTRUCTOR_MNIST.py",
"NALSM_OUTPUT_LAYER.py"
] | [
"import numpy as np\r\nimport time\r\nimport NALSM_LIF_v1 as neuron\r\nimport LSM_APSTDP_STDP as plasticity\r\nimport NALSM_SIM_SUPPORT as runSupport\r\nimport NALSM_OUTPUT_LAYER as out_lin_csfr\r\nimport NALSM_GEN_SUPPORT as sup\r\n\r\nclass simulation_constructor:\r\n def __init__(self\r\n , ne... | [
[
"numpy.asarray",
"numpy.arange",
"numpy.shape",
"numpy.floor",
"numpy.mod",
"numpy.average",
"numpy.where",
"numpy.vstack"
],
[
"tensorflow.compat.v1.nn.softmax",
"tensorflow.compat.v1.disable_v2_behavior",
"tensorflow.compat.v1.reduce_mean",
"tensorflow.compat.... |
scienceopen/pyoptflow | [
"4485da929c5567470d821c3f2a23e3bccc7f768e"
] | [
"src/pyoptflow/lucaskanade.py"
] | [
"\"\"\"\nThis function isn't working yet.\n\"\"\"\nimport numpy as np\n\n\ndef LucasKanade(im1, im2, kernel, poi, W):\n # %% evaluate every POI\n V = np.zeros((poi.shape[0], 2))\n for i in range(len(poi)):\n A = buildA(im2, poi[i][0][1], poi[i][0][0], kernel)\n B = buildB(im2, im1, poi[i][0][... | [
[
"numpy.diag",
"numpy.linalg.inv",
"numpy.ones",
"numpy.exp",
"numpy.array",
"numpy.zeros"
]
] |
MTG/asteroid | [
"850109d87872a2ed0676a4abe890c023b2e00dc0"
] | [
"asteroid/losses/pmsqe.py"
] | [
"import numpy as np\nimport torch\nfrom torch import tensor\nimport torch.nn as nn\nfrom scipy.io import loadmat\nimport pathlib\nimport os\n\n\nclass SingleSrcPMSQE(nn.Module):\n \"\"\"Computes the Perceptual Metric for Speech Quality Evaluation (PMSQE)\n as described in [1].\n This version is only design... | [
[
"torch.mean",
"torch.abs",
"torch.ones_like",
"torch.ones",
"torch.sqrt",
"torch.min",
"torch.sum",
"torch.zeros_like",
"scipy.io.loadmat",
"torch.tensor",
"torch.matmul",
"numpy.zeros",
"torch.pow"
]
] |
kaushikmupadhya/Natural-Language-Processing | [
"58f1f2793d2d455223a1d2f3fb790c57a1c98c0c"
] | [
"basics_nlp.py"
] | [
"# -*- coding: utf-8 -*-\n\"\"\"Basics_NLP.ipynb\n\nAutomatically generated by Colaboratory.\n\nOriginal file is located at\n https://colab.research.google.com/drive/1AEnGCBRsmDwBl_02BdnnYnUZN6zxlOb_\n\"\"\"\n\nfrom google.colab import drive\ndrive.mount('/content/drive')\n\n\"\"\"# NLP Basics: What is Natural L... | [
[
"pandas.set_option",
"pandas.read_csv",
"pandas.DataFrame"
]
] |
ZhuoranYu/TorchSSL | [
"c318dda792a94b41e86593c36a0ffb70cb2f15df"
] | [
"energymatch.py"
] | [
"# import needed library\nimport os\nimport logging\nimport random\nimport warnings\n\nimport numpy as np\nimport torch\nimport torch.nn as nn\nimport torch.nn.parallel\nimport torch.backends.cudnn as cudnn\nimport torch.distributed as dist\nimport torch.multiprocessing as mp\n\nfrom utils import net_builder, get_l... | [
[
"torch.distributed.init_process_group",
"torch.multiprocessing.spawn",
"numpy.random.seed",
"torch.cuda.set_device",
"torch.manual_seed",
"torch.distributed.barrier",
"torch.nn.SyncBatchNorm.convert_sync_batchnorm",
"torch.nn.DataParallel",
"torch.cuda.is_available",
"torch... |
robsteneha/detr_modified | [
"f97838a55702ee690a8d10f2c273bb50a0fe25a8"
] | [
"models/detr.py"
] | [
"# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved\n\"\"\"\nDETR model and criterion classes.\n\"\"\"\nimport torch\nimport torch.nn.functional as F\nfrom torch import nn\n\nfrom util import box_ops\nfrom util.misc import (NestedTensor, nested_tensor_from_tensor_list,\n ac... | [
[
"torch.nn.functional.softmax",
"torch.ones",
"torch.full",
"torch.nn.functional.l1_loss",
"torch.cat",
"torch.nn.Conv2d",
"torch.nn.Embedding",
"torch.nn.Linear",
"torch.full_like",
"torch.no_grad",
"torch.device",
"torch.distributed.all_reduce",
"torch.stack"
... |
parkerzf/nowinteract | [
"e1119aed4f010261b111b048628f40bc9945ea95"
] | [
"notebooks/scores_analyzer/metrics_visualizer.py"
] | [
"import matplotlib\nmatplotlib.use('Agg')\n\nimport matplotlib.pyplot as plt\nimport matplotlib.ticker as mtick\nimport numpy as np\nimport metrics_analyzer\n\ndef init_figure():\n \"\"\"\n Initialize the figure with the configuration of text and format\n \"\"\"\n plt.xlabel('Score threshold')\n plt.... | [
[
"matplotlib.pyplot.gca",
"matplotlib.pyplot.title",
"matplotlib.use",
"numpy.arange",
"matplotlib.pyplot.savefig",
"matplotlib.pyplot.plot",
"matplotlib.pyplot.xlabel",
"matplotlib.pyplot.grid",
"matplotlib.pyplot.axis",
"matplotlib.pyplot.close",
"matplotlib.ticker.For... |
RuthAngus/aviary | [
"73c11348b32c29ffb0bd3d1d6179df95e89c3121"
] | [
"aviary/avr.py"
] | [
"import numpy as np\nimport pandas as pd\n\nimport pkg_resources\nmpf = pkg_resources.resource_filename(__name__,\n '../data/metal_poor_avr.csv')\nmrf = pkg_resources.resource_filename(__name__,\n '../data/metal_rich_avr.csv')\naf = pkg_resou... | [
[
"numpy.exp",
"numpy.log",
"pandas.read_csv"
]
] |
shshnk94/etm | [
"dbc0db1bcc04c4e039855c38f6be41c64d020ad6"
] | [
"metrics.py"
] | [
"import numpy as np\nimport torch\nfrom sklearn.metrics import pairwise_distances\n\ndef get_topic_diversity(beta):\n\n logits = 1 - torch.mm(beta, beta.transpose(0, 1)) / (torch.norm(beta, 2, 1) * torch.norm(beta, 2, 1))\n TD = logits[np.triu_indices(logits.shape[0], k = 1)].mean()\n print('Topic diverist... | [
[
"numpy.log",
"torch.mm",
"torch.norm",
"numpy.triu_indices",
"numpy.mean"
]
] |
CARLAlover/OpenCOOD | [
"dd42cc7a31bc261ea2461b3068ed6111f13ff437",
"dd42cc7a31bc261ea2461b3068ed6111f13ff437"
] | [
"opencood/utils/eval_utils.py",
"opencood/hypes_yaml/yaml_utils.py"
] | [
"import os\n\nimport numpy as np\nimport torch\n\nfrom opencood.utils import common_utils\nfrom opencood.hypes_yaml import yaml_utils\n\n\ndef voc_ap(rec, prec):\n \"\"\"\n VOC 2010 Average Precision.\n \"\"\"\n rec.insert(0, 0.0)\n rec.append(1.0)\n mrec = rec[:]\n\n prec.insert(0, 0.0)\n p... | [
[
"numpy.argsort",
"numpy.max",
"numpy.argmax"
],
[
"numpy.round",
"numpy.array"
]
] |
arjunakula/ai2thor | [
"a4435886b0916fadb8b42989f6f60542d5d04aaa"
] | [
"tasks.py"
] | [
"import os\nimport sys\nimport datetime\nimport json\nimport re\nimport time\nimport zipfile\nimport threading\nimport hashlib\nimport shutil\nimport subprocess\nimport pprint\nfrom invoke import task\nimport boto3\nimport botocore.exceptions\nimport multiprocessing\nimport io\nimport ai2thor.build\nimport logging\... | [
[
"numpy.ones_like",
"numpy.unique",
"numpy.min",
"numpy.save",
"numpy.argwhere",
"numpy.max",
"numpy.frombuffer",
"numpy.load",
"numpy.where",
"numpy.zeros"
]
] |
XuhuiZhou/kb | [
"4c37bbccd6c871828aceb24b342841825d86df14"
] | [
"tests/test_wordnet.py"
] | [
"\nimport unittest\nimport numpy as np\n\nimport torch\n\nfrom kb.wordnet import WordNetFineGrainedSenseDisambiguationReader\nfrom kb.wordnet import WordNetSpacyPreprocessor, \\\n WordNetCandidateMentionGenerator\nfrom kb.wordnet import unpack_wsd_training_instance\nfrom kb.wordnet... | [
[
"torch.tensor"
]
] |
YaadLuria/IML.HUJI | [
"d5cea7671009d14a37ebf9a308f16c2ca0087c92"
] | [
"exercises/city_temperature_prediction.py"
] | [
"import numpy as np\nimport pandas as pd\nimport plotly.express as px\nimport plotly.graph_objects as go\nimport plotly.io as pio\n\nfrom IMLearn.learners.regressors.polynomial_fitting import PolynomialFitting\nfrom IMLearn.utils import utils\n\npio.templates.default = \"simple_white\"\n\n\ndef load_data(filename: ... | [
[
"pandas.NamedAgg",
"pandas.read_csv",
"numpy.random.seed"
]
] |
ganeshgore/spydrnet-physical | [
"c41d7b928d3a24b9e33c5bb996fde313b09fffd2"
] | [
"examples/OpenFPGA_tiling/02_switch_partition_01.py"
] | [
"\"\"\"\n============================================\nLogical/Pre-techmapped Partition Conn Box 01\n============================================\n\nThis example demonstrates partitioning based on logical connectivity.\nThis example partitions a pre-tech mapped netlist of the connection box based on mux connection ... | [
[
"numpy.set_printoptions",
"numpy.vstack"
]
] |
FogDong/seldon-core | [
"1da1b720f2ba5757ed6cad112459284c2572ad1c"
] | [
"components/alibi-detect-server/adserver/cd_model.py"
] | [
"import json\nfrom typing import List, Dict, Optional\nimport logging\nimport numpy as np\nfrom .numpy_encoder import NumpyEncoder\nfrom alibi_detect.utils.saving import load_detector, Data\nfrom adserver.base import AlibiDetectModel\nfrom seldon_core.user_model import SeldonResponse\n\n\ndef _drift_to_metrics(drif... | [
[
"numpy.array",
"numpy.vstack"
]
] |
wuyx/multiagent-particle-envs | [
"17fd2f7ad3425d53c571718a17fb6597b0647cec"
] | [
"multiagent/scenarios/simple_push.py"
] | [
"import numpy as np\nfrom multiagent.core import World, Agent, Landmark\nfrom multiagent.scenario import BaseScenario\nimport random\n\n#\n# # the non-ensemble version of <ensemble_push>\n#\n#\n\nclass Scenario(BaseScenario):\n def make_world(self):\n world = World()\n # set any world propertie... | [
[
"numpy.square",
"numpy.random.choice",
"numpy.concatenate",
"numpy.random.uniform",
"numpy.array",
"numpy.zeros"
]
] |
cinastanbean/pytorch-CycleGAN-and-pix2pix | [
"cbbb6f79295e7c0116a860ce469a16ebabe032f7"
] | [
"models/networks.py"
] | [
"import torch\nimport torch.nn as nn\nfrom torch.nn import init\nimport functools\nfrom torch.optim import lr_scheduler\n\n\n###############################################################################\n# Helper Functions\n###############################################################################\ndef get_n... | [
[
"torch.optim.lr_scheduler.LambdaLR",
"torch.optim.lr_scheduler.CosineAnnealingLR",
"torch.nn.BCEWithLogitsLoss",
"torch.cuda.is_available",
"torch.nn.ReplicationPad2d",
"torch.nn.Dropout",
"torch.optim.lr_scheduler.ReduceLROnPlateau",
"torch.tensor",
"torch.rand",
"torch.op... |
anthony-walker/pysweep | [
"56167929cccf1d6f0dc3f1385912020840905c43"
] | [
"pysweep/core/solver.py"
] | [
"import sys, os, yaml, numpy, warnings, time, h5py, importlib.util\nimport GPUtil\nimport pysweep.core.io as io\nimport pysweep.core.process as process\nimport pysweep.core.functions as functions\nimport pysweep.core.block as block\nfrom itertools import cycle\n\nclass Solver(object):\n \"\"\"docstring for Solve... | [
[
"numpy.shape"
]
] |
WenmuZhou/pytorch-deeplab-xception | [
"3e952e2e120326a0c2eda9a7c5f380568a46febb"
] | [
"modeling/backbone/resnet.py"
] | [
"import math\nimport torch.nn as nn\nimport torch.utils.model_zoo as model_zoo\nfrom modeling.sync_batchnorm.batchnorm import SynchronizedBatchNorm2d\n\nclass Bottleneck(nn.Module):\n expansion = 4\n\n def __init__(self, inplanes, planes, stride=1, dilation=1, downsample=None, BatchNorm=None):\n super(... | [
[
"torch.nn.Sequential",
"torch.nn.Conv2d",
"torch.nn.MaxPool2d",
"torch.rand",
"torch.nn.ReLU",
"torch.utils.model_zoo.load_url"
]
] |
yashkant/concat-vqa | [
"6a7fdac8e7c0e26be6b2407bc474237dff26bfe2"
] | [
"evaluator.py"
] | [
"import json\nimport logging\nimport os\nfrom copy import deepcopy\nfrom io import open\n\nimport numpy as np\nimport torch\nfrom tqdm import tqdm\n\nfrom tools.registry import registry\n\nlogging.basicConfig(\n format=\"%(asctime)s - %(levelname)s - %(name)s - %(message)s\",\n datefmt=\"%m/%d/%Y %H:%M:%S\"... | [
[
"numpy.round",
"torch.no_grad",
"torch.max",
"torch.load"
]
] |
aws-samples/bioimage-search | [
"7acdeb8e24c31ff7302563df60f9b65a522dd834"
] | [
"datasets/bbbc-021/scripts/bbbc021-1-train-script.py"
] | [
"import argparse\nimport logging\nimport torch\nimport torchvision\nimport torchvision.transforms as transforms\nimport numpy as np\nimport os as os\nimport torch.nn as nn\nimport torch.nn.functional as F\nimport torch.optim as optim\nfrom torch.utils.data import TensorDataset, DataLoader\nimport random\nfrom colle... | [
[
"torch.nn.Dropout2d",
"torch.zeros",
"torch.load",
"numpy.concatenate",
"torch.cuda.is_available",
"torch.distributed.get_rank",
"torch.nn.CrossEntropyLoss",
"torch.nn.Dropout",
"torch.distributed.init_process_group",
"torch.einsum",
"torch.tensor",
"torch.nn.functi... |
donutloop/machine_learning_examples | [
"46192a57e2dd194925ae76d6bfb169cd2af142dd"
] | [
"tensorflow/deep_learning_mnist/main.py"
] | [
"\n'''\ninput > weiht > hidden layer 1 (activation function) > weights > hidden layer 2 (activation function) > weights > output layer\n\ncompare output to intended output > cost function (cross entropy) > optimization function (optimizer) > minimze cost (AdamOptimizer, SGG, AdaGrad) \n\nbackpropagation \n\nfeed fo... | [
[
"tensorflow.nn.relu",
"tensorflow.matmul",
"tensorflow.contrib.learn.python.learn.datasets.mnist.read_data_sets",
"tensorflow.cast",
"tensorflow.placeholder",
"tensorflow.global_variables_initializer",
"tensorflow.Session",
"tensorflow.nn.softmax_cross_entropy_with_logits_v2",
... |
peterbhase/ExplanationSearch | [
"faeaf72b41b9edf9f13f7a04eda35109758ea275",
"faeaf72b41b9edf9f13f7a04eda35109758ea275"
] | [
"explanation_methods_and_eval/src/models/gradient_search_model.py",
"explanation_methods_and_eval/transformers/src/transformers/modeling_bert.py"
] | [
"from typing import Optional, Dict, Any, List\r\nimport math\r\nimport numpy as np\r\nimport torch\r\nimport torch.nn.functional as F\r\n\r\nfrom allennlp.data.vocabulary import Vocabulary\r\nfrom allennlp.models.model import Model\r\nfrom allennlp.nn import InitializerApplicator, RegularizerApplicator\r\nfrom alle... | [
[
"torch.mean",
"torch.softmax",
"torch.nn.Parameter",
"torch.sum",
"torch.zeros_like",
"torch.tensor",
"torch.square",
"torch.no_grad",
"torch.log",
"torch.topk"
],
[
"torch.nn.Softmax",
"torch.cat",
"torch.zeros",
"torch.nn.Embedding",
"torch.nn.Drop... |
IRMVLab/PWCLONet | [
"165149f84dad3ed6a869e44e41b239ff166d75a1"
] | [
"main.py"
] | [
"'''\n Single-GPU training code\n'''\n\nimport argparse\nfrom datetime import datetime\nimport numpy as np\nimport tensorflow as tf\nimport importlib\nimport os\nimport sys\nimport kitti_dataset\n\n\nBASE_DIR = os.path.dirname(os.path.abspath(__file__))\nsys.path.append(BASE_DIR)\n\nparser = argparse.ArgumentPar... | [
[
"numpy.expand_dims",
"tensorflow.minimum",
"numpy.concatenate",
"tensorflow.train.AdamOptimizer",
"tensorflow.summary.scalar",
"tensorflow.Graph",
"tensorflow.Variable",
"numpy.reshape",
"numpy.arange",
"numpy.eye",
"numpy.matmul",
"tensorflow.train.exponential_deca... |
CharyS117/FGO-py | [
"3bf3bc32998c19728831f14afc7251411b7afbbe"
] | [
"FGO-py/fgoAndroid.py"
] | [
"import re\nimport threading\nimport time\n\nimport cv2\nimport numpy\nfrom airtest.core.android.adb import ADB\nfrom airtest.core.android.android import Android as Airtest\nfrom airtest.core.android.constant import CAP_METHOD\n\nfrom fgoControl import control\nfrom fgoLogging import getLogger\n\nlogger=getLogger('... | [
[
"numpy.array",
"numpy.linalg.norm"
]
] |
beandkay/pytorch-image-models | [
"4513b183352ea4af01553f15bb0cb6ad6dc0bc76"
] | [
"timm/models/inception_v3.py"
] | [
"import torch\nimport torch.nn as nn\nimport torch.nn.functional as F\n\nfrom .registry import register_model\nfrom .helpers import load_pretrained\nfrom .layers import trunc_normal_, SelectAdaptivePool2d\nfrom timm.data import IMAGENET_DEFAULT_STD, IMAGENET_DEFAULT_MEAN, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION... | [
[
"torch.cat",
"torch.nn.functional.dropout",
"torch.nn.init.constant_",
"torch.nn.functional.avg_pool2d",
"torch.nn.Conv2d",
"torch.nn.functional.adaptive_avg_pool2d",
"torch.nn.Linear",
"torch.nn.Identity",
"torch.nn.functional.relu",
"torch.nn.BatchNorm2d",
"torch.flat... |
AbbasMZ/jittor | [
"fcec57f70422b52d6b8d0235e29f91fd2212f559"
] | [
"python/jittor/__init__.py"
] | [
"# ***************************************************************\n# Copyright (c) 2021 Jittor. All Rights Reserved. \n# Maintainers:\n# Dun Liang <randonlang@gmail.com>.\n# Meng-Hao Guo <guomenghao1997@gmail.com>\n#\n# \n# This file is subject to the terms and conditions defined in\n# file 'LICENSE.txt', whic... | [
[
"torch.device",
"numpy.array"
]
] |
samuelgarcia/spikeinterface-gui | [
"1c312db58575e2f4d7c35fceec14b930b1abcc34"
] | [
"spikeinterface_gui/similarityview.py"
] | [
"from .myqt import QT\nimport pyqtgraph as pg\n\nimport numpy as np\nimport matplotlib.cm\nimport matplotlib.colors\n\nfrom .base import WidgetBase\nfrom .tools import ParamDialog\n\n\nclass MyViewBox(pg.ViewBox):\n clicked = QT.pyqtSignal(float, float)\n doubleclicked = QT.pyqtSignal()\n def mouseClickEve... | [
[
"numpy.max",
"numpy.array",
"numpy.any",
"numpy.floor"
]
] |
hy310/intel-object-detection | [
"abe2b29e0c97fc19bd9286c52f12c35564df927f"
] | [
"utils/object_detection_sample_ssd_realtime.py"
] | [
"import cv2\nimport numpy as np\nimport os, sys\nfrom time import strftime, localtime\nimport random\nfrom openvino.inference_engine import IENetwork, IEPlugin\n\n# plugin = IEPlugin(\"MYRIAD\", \"/opt/intel/openvino/deployment_tools/inference_engine/lib/intel64\")\nplugin = IEPlugin(\"GPU\", \"/opt/intel/openvino/... | [
[
"numpy.ndarray"
]
] |
rahulyesantharao/tuplex | [
"03733a57ccb5a3770eecaf1c3adcfb520ed82138"
] | [
"benchmarks/tpch/Q06/tpch6-pandas.py"
] | [
"import pandas as pd\nimport numpy as np\nimport time\nimport datetime\nimport argparse\n\n\nparser = argparse.ArgumentParser(description=\"TPC-H query using Hyper API\")\nparser.add_argument(\n \"--path\",\n type=str,\n dest=\"data_path\",\n default=\"data/lineitem.tbl\",\n help=\"path to lineitem.t... | [
[
"pandas.read_csv"
]
] |
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