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# vim: tabstop=4 shiftwidth=4 softtabstop=4 # Copyright (c) 2017 <NAME> # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to us...
[ "hyver.command.create.Create" ]
[((1418, 1448), 'hyver.command.create.Create', 'create.Create', (['config_instance'], {}), '(config_instance)\n', (1431, 1448), False, 'from hyver.command import create\n')]
import napari def show_image(im, title, viewer=None, label=False): """ convenience helper function to show image in Napari Args: im (numpy array): image to show title (string): title of image viewer (napari instance, optional): pre-existing Napari label (bool, optional): True ...
[ "napari.Viewer" ]
[((436, 451), 'napari.Viewer', 'napari.Viewer', ([], {}), '()\n', (449, 451), False, 'import napari\n')]
import bpy import numpy as np from smorgasbord.common.decorate import register from smorgasbord.common.io import get_vecs, get_scalars def get_red(arr): return arr[:, 0:1].ravel() def get_green(arr): return arr[:, 1:2].ravel() def get_blue(arr): return arr[:, 2:3].ravel() def avg_rgb(arr): # St...
[ "numpy.unique", "smorgasbord.common.io.get_scalars", "numpy.average", "numpy.where", "bpy.props.EnumProperty", "smorgasbord.common.io.get_vecs" ]
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#!/usr/bin/env python3 import sys import os from scipy.stats import wasserstein_distance from scipy.stats import ks_2samp def compare_fct_mse(input1, input2): fct_dict = dict() with open(input1, "r") as f1: for line in f1: toks = line.split() dst = int(toks[0]) src...
[ "scipy.stats.wasserstein_distance", "os.path.isdir", "os.listdir", "scipy.stats.ks_2samp" ]
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# created by gelearthur # imports import uuid import os import argparse # arguments parser = argparse.ArgumentParser("Script that makes music files for unturned") parser.add_argument('-f','--file',help="A path to the myMusic.content.manifest",required=True) args = parser.parse_args() # a loop thing asse...
[ "argparse.ArgumentParser", "os.path.splitext", "os.path.join", "uuid.uuid4", "os.path.dirname", "os.path.basename" ]
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#! coding:utf-8 """ track_controller.py Created by 0160929 on 2016/09/29 16:38 """ import os from TrackMaster.signalfigureview import WaveViewer __version__ = '0.0' import sys from PySide.QtGui import * from PySide.QtCore import * import iconsloader __all__ = ["TrackController"] class T...
[ "os.path.basename", "TrackMaster.signalfigureview.WaveViewer" ]
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# This is a synthesizer filter for adding sawtooth wave patterns # of a given duration and sample rate from scipy import signal import fileIO import math import numpy as np def sawWav(fileName, fs, freq): t = np.linspace(0, 1, int(fs)) dat = signal.sawtooth(2 * math.pi * freq * t) fileIO.file_output(fil...
[ "scipy.signal.sawtooth" ]
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#!/usr/bin/env python import argparse import sys, subprocess, os import re import datetime import math # Generate customized SLURM submit scripts to run RAxML-ng. # Takes a directory of alignmets, runs the raxml-ng --parse # function to get estimates of RAM and CPU needs for the job. # Then uses a templates sba...
[ "os.listdir", "math.ceil", "argparse.ArgumentParser", "re.compile", "os.makedirs", "subprocess.Popen", "subprocess.run", "os.path.join", "datetime.datetime.now", "os.path.basename", "sys.exit", "os.path.relpath" ]
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from distutils.core import setup from Cython.Build import cythonize setup(ext_modules=cythonize("sieve_module.py"))
[ "Cython.Build.cythonize" ]
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#!/usr/bin/env python # -*- coding: utf-8 -*- import json from alipay.aop.api.response.AlipayResponse import AlipayResponse from alipay.aop.api.domain.RateCurrency import RateCurrency class AlipayOverseasTravelRateCurrencyBatchqueryResponse(AlipayResponse): def __init__(self): super(AlipayOverseasTravel...
[ "alipay.aop.api.domain.RateCurrency.RateCurrency.from_alipay_dict" ]
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import torch import numpy from deep_signature.nn.datasets import DeepSignatureEuclideanArclengthTupletsOnlineDataset from deep_signature.nn.datasets import DeepSignatureEquiaffineArclengthTupletsOnlineDataset from deep_signature.nn.datasets import DeepSignatureAffineArclengthTupletsOnlineDataset from deep_signature.nn....
[ "common.utils.get_latest_subdirectory", "deep_signature.nn.losses.ArcLengthLoss", "deep_signature.nn.trainers.ModelTrainer", "argparse.ArgumentParser", "deep_signature.nn.networks.DeepSignatureArcLengthNet", "torch.set_default_dtype", "numpy.load", "torch.device" ]
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import os import pathlib from click.testing import CliRunner from syncify.core import rsync_to, rsync, store, load, extract_archive import mock settings = {"tarfile_output_path": "$HOME/transfer/syncify.tar.gz"} applications = { "transgui": { "description": "Transmission Remote GUI", "paths": [ { ...
[ "pathlib.Path", "click.testing.CliRunner", "os.path.dirname", "syncify.core.extract_archive", "os.path.expanduser" ]
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import collections import logging import time import itertools import io import subprocess import selectors from typing import Any from typing import Deque, Type, List, Tuple import pytest from .config import SSHConfiguration from .continuous import Action from .continuous import ContinuousSSH @pytest.fixture def c...
[ "pytest.approx", "logging.getLogger", "collections.deque", "selectors.SelectorKey", "itertools.product", "io.BytesIO", "pytest.mark.parametrize", "pytest.raises" ]
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# PROGRAMMER: <NAME> # DATE CREATED: 26/04/2020 # REVISED DATE: # PURPOSE: Classifies flower images using a pretrained deep neural network such as VGG11 and RESNET50 # This Python script is used to build and train a new classifier of the pretrained model (VGG11 as defaut) # # E...
[ "fc_model.train", "fc_model.classifier", "torch.cuda.is_available", "torch.nn.NLLLoss", "torch.save", "torchvision.models.resnet50", "torchvision.models.vgg11", "utility_model.load_data", "utility_model.get_input_arg" ]
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# -*- coding: utf-8 -*- """ Copyright © 2017, <NAME> Contributed by <NAME> (<EMAIL>) This file is part of BSD license <https://opensource.org/licenses/BSD-3-Clause> """ import logging from quest.models import CIQuest class QuestUtility: """ strState route graph: ↓---- all cancel ----↑ ...
[ "quest.models.CIQuest.objects.filter" ]
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"""Work out the optimum mass for maximum cannonball range""" import sympy as sym import numpy as np import matplotlib.pyplot as plt import atmosphere import pycollo from pycollo.functions import cubic_spline # state variables r = sym.Symbol("r") # downrange distance h = sym.Symbol("h") # height (above sea level?) v =...
[ "sympy.sin", "sympy.Symbol", "sympy.cos", "pycollo.functions.cubic_spline", "matplotlib.pyplot.ylabel", "pycollo.OptimalControlProblem", "matplotlib.pyplot.xlabel", "matplotlib.pyplot.plot", "numpy.max", "numpy.rad2deg", "matplotlib.pyplot.show" ]
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import json import os import boto3 import time import uuid from helper import AwsHelper from og import OutputGenerator from trp import Document from decimal import Decimal import datastore import re def getJobResults(api, jobId): pages = [] time.sleep(5) client = AwsHelper().getClient('textract') if...
[ "trp.Document", "datastore.DocumentStore", "json.loads", "helper.AwsHelper", "time.sleep", "boto3.resource" ]
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from django.conf.urls import include, url from django.contrib import admin urlpatterns = [ url(r'^smartling_callback/$', 'mezzanine_smartling.views.smartling_callback', name='smartling_callback'), ]
[ "django.conf.urls.url" ]
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import pytest from selenium import webdriver from selenium.webdriver.support.wait import WebDriverWait from selenium.webdriver.support import expected_conditions as EC import random @pytest.fixture def driver(request): wd = webdriver.Chrome(desired_capabilities={"pageLoadStrategy": "eager"}) # wd = webdriver....
[ "selenium.webdriver.Chrome", "selenium.webdriver.support.wait.WebDriverWait", "selenium.webdriver.support.expected_conditions.number_of_windows_to_be", "selenium.webdriver.support.expected_conditions.title_is", "random.randint" ]
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# Copyright 2019 Open End AB # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, s...
[ "blm.testblm.Sub._query", "blm.testblm.Defaults._query", "bson.objectid.ObjectId", "os.path.dirname", "blm.TO._query", "blm.clear", "blm.testblm.Base._query" ]
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from rpyc.utils.server import ThreadedServer import rpyc import subprocess import os import re from dataclasses import dataclass DOCKER_SWARM_ADDR = os.getenv('DOCKER_SWARM_ADDR') @dataclass class WorkerCXT: host_addr: str username: str password: str key_file: str def __init__(self): pas...
[ "subprocess.run", "re.match", "os.getenv" ]
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import io import os import re import shutil import sys import typing import webbrowser from time import sleep import click import pandas as pd from whylogs.app import SessionConfig, WriterConfig from whylogs.app.session import session_from_config from whylogs.cli import ( OBSERVATORY_EXPLANATION, PIPELINE_DES...
[ "pandas.read_csv", "re.compile", "whylogs.cli.generate_notebooks", "click.File", "webbrowser.open", "time.sleep", "sys.exit", "click.BadParameter", "whylogs.app.WriterConfig", "os.listdir", "click.secho", "click.option", "io.StringIO", "click.command", "click.confirm", "click.prompt", ...
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#!/usr/bin/env python # -*- coding: utf-8 -*- #__author__ = '0xAE' #_name_ = ' drupal full path disclousure' import re def assign(service, arg): if service == "drupal": return True, arg def audit(arg): payload='?q[]=x' verify_url = arg + payload pathinfo = re.compile(r' in <b>...
[ "re.compile" ]
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# -*- coding: UTF-8 -*- """ Based on ``behave tutorial`` Feature: A Step uses a User-Defined Type as Step Parameter (tutorial10) Scenario Outline: Calculator Given I have a calculator When I add "<x>" and "<y>" Then the calculator returns "<sum>" Examples: Add Numbers | x | y | sum | ...
[ "behave.given", "behave.register_type", "behave.when", "calculator.Calculator", "behave.then", "hamcrest.equal_to" ]
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''' Tests the data merge functions and package. .. moduleauthor:: <NAME> <<EMAIL>> ''' from __future__ import absolute_import import unittest import os from segeval.data.tsv import (input_linear_mass_tsv, input_linear_positions_tsv) from segeval.data.samples import HEARST_1997_STARGAZER class TestTsv(unittest.TestCa...
[ "segeval.data.tsv.input_linear_positions_tsv", "os.path.join", "segeval.data.tsv.input_linear_mass_tsv", "os.path.split" ]
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""" :Author: <NAME> :Date: Dec 06, 2019 :Version: 0.0.3 """ import logging import ltn.fol.fol_status as FOL from ltn.fol.constant import constant from ltn.fol.logic import Forall, Not from ltn.fol.predicate import predicate from ltn.fol.variable import variable logging.basicConfig(format='[%(asctime)s] {%(pathname)s:...
[ "logging.basicConfig", "ltn.fol.fol_status.train", "ltn.fol.constant.constant", "matplotlib.pyplot.pcolor", "ltn.fol.predicate.predicate", "matplotlib.pyplot.colorbar", "pandas.set_option", "matplotlib.pyplot.figure", "matplotlib.pyplot.subplot", "matplotlib.pyplot.show" ]
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from ..config.config import LennyBotActionConfig from .iaction import IAction import requests class DownloadResourcesAction(IAction): def __init__(self, name, source_version, target_version, config: LennyBotActionConfig) -> None: self._name = name self._source_version = source_version self...
[ "requests.get" ]
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from safenotes.paths import SAFENOTES_DIR_PATH, PASSWORD_FILE_PATH from safenotes.colors import red, green, yellow, blue from safenotes.helpers import display_colored_text from hmac import compare_digest as compare_hash from os.path import isfile, join from os import listdir, system from getpass import getpass from cry...
[ "safenotes.paths.SAFENOTES_DIR_PATH.mkdir", "os.listdir", "os.getenv", "os.path.join", "getpass.getpass", "os.system", "crypt.crypt", "safenotes.helpers.display_colored_text" ]
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import sys import rospy import signal from geometry_msgs.msg import Twist # AUTONOMOUS MOVEMENT from A_movement.baseline.A_Baseline import A_Baseline from A_movement.ee1.A_EE1 import A_EE1 from A_movement.ee2.A_EE2 import A_EE2 from A_movement.ee3.A_EE3 import A_EE3 from A_movement.ee4.A_EE4 import A_EE4 from A_movem...
[ "signal.signal", "A_movement.baseline.A_Baseline.A_Baseline", "common.recording.MetricsRecorder.MetricsRecorder" ]
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import numpy as np import torch from torchvision import models from utils import process_image import json from torch import nn, optim from collections import OrderedDict #loads a checkpoint and rebuilds the model def load_checkpoint(filepath): checkpoint = torch.load(filepath) if checkpoint['arch'] ==...
[ "torch.nn.ReLU", "torch.nn.Dropout", "torch.load", "torch.topk", "numpy.argmax", "torch.exp", "torchvision.models.vgg11", "utils.process_image", "torch.cuda.is_available", "torch.nn.NLLLoss", "torch.nn.Linear", "torch.nn.LogSoftmax", "json.load", "torch.no_grad", "torchvision.models.vgg1...
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#!/usr/bin/env python # Copyright 2016-2019 Biomedical Imaging Group Rotterdam, Departments of # Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obt...
[ "numpy.mean", "argparse.ArgumentParser", "matplotlib.use", "collections.Counter", "numpy.random.seed", "tikzplotlib.save", "matplotlib.pyplot.rcdefaults", "matplotlib.pyplot.subplots", "pandas.read_hdf" ]
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# Generated by Django 2.2.24 on 2021-11-04 08:51 from django.db import migrations, models def update_stood_down(self, schema_editor): "Set is_stood_down value depending on molnix_status for existing records" SurgeAlert = self.get_model('notifications', 'surgealert') for record in SurgeAlert.objects.all():...
[ "django.db.migrations.RunPython", "django.db.models.BooleanField" ]
[((805, 884), 'django.db.migrations.RunPython', 'migrations.RunPython', (['update_stood_down'], {'reverse_code': 'migrations.RunPython.noop'}), '(update_stood_down, reverse_code=migrations.RunPython.noop)\n', (825, 884), False, 'from django.db import migrations, models\n'), ((719, 784), 'django.db.models.BooleanField',...
# Generated by Django 2.2.2 on 2019-07-03 13:16 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('radio', '0004_new_song_path_structure'), ] operations = [ migrations.AddField( model_name='store', name='track_gain'...
[ "django.db.models.DecimalField" ]
[((340, 468), 'django.db.models.DecimalField', 'models.DecimalField', ([], {'blank': '(True)', 'decimal_places': '(2)', 'max_digits': '(6)', 'null': '(True)', 'verbose_name': '"""recommended replaygain adjustment"""'}), "(blank=True, decimal_places=2, max_digits=6, null=True,\n verbose_name='recommended replaygain a...
import eel import numpy as np import datetime def rotate(arr, x, y, z): cos_z, sin_z, cos_y = np.cos(z), np.sin(z), np.cos(y) sin_y, cos_x, sin_x = np.sin(y), np.cos(x), np.sin(x) rot_mat = [[cos_z*cos_y, cos_z*sin_y*sin_x - sin_z*cos_x, cos_z*sin_y*cos_x + sin_z*sin_x], [sin_z*cos_y, sin_z*sin_y*sin_x + cos_z...
[ "numpy.random.normal", "eel.sleep", "eel.start", "eel.init", "numpy.array", "numpy.zeros", "datetime.datetime.now", "numpy.dot", "numpy.cos", "numpy.sin", "eel.drawLines" ]
[((957, 1043), 'numpy.array', 'np.array', (['[0, 1, 0, 2, 0, 4, 1, 3, 1, 5, 2, 3, 2, 6, 3, 7, 4, 5, 4, 6, 5, 7, 6, 7]'], {}), '([0, 1, 0, 2, 0, 4, 1, 3, 1, 5, 2, 3, 2, 6, 3, 7, 4, 5, 4, 6, 5, 7,\n 6, 7])\n', (965, 1043), True, 'import numpy as np\n'), ((1022, 1039), 'numpy.zeros', 'np.zeros', (['(3, 24)'], {}), '((3...
from utils import escape_text, make_fake_message def test_template_basis(): from nonebot.adapters import MessageTemplate template = MessageTemplate("{key:.3%}") formatted = template.format(key=0.123456789) assert formatted == "12.346%" def test_template_message(): Message = make_fake_message() ...
[ "nonebot.adapters.MessageTemplate", "utils.escape_text", "utils.make_fake_message" ]
[((143, 171), 'nonebot.adapters.MessageTemplate', 'MessageTemplate', (['"""{key:.3%}"""'], {}), "('{key:.3%}')\n", (158, 171), False, 'from nonebot.adapters import MessageTemplate\n'), ((300, 319), 'utils.make_fake_message', 'make_fake_message', ([], {}), '()\n', (317, 319), False, 'from utils import escape_text, make_...
import socket from contextlib import closing from typing import cast from .logging import LoggingDescriptor _logger = LoggingDescriptor(name=__name__) def find_free_port() -> int: with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s: s.bind(("127.0.0.1", 0)) s.setsockopt(socket.S...
[ "socket.socket" ]
[((201, 250), 'socket.socket', 'socket.socket', (['socket.AF_INET', 'socket.SOCK_STREAM'], {}), '(socket.AF_INET, socket.SOCK_STREAM)\n', (214, 250), False, 'import socket\n'), ((458, 507), 'socket.socket', 'socket.socket', (['socket.AF_INET', 'socket.SOCK_STREAM'], {}), '(socket.AF_INET, socket.SOCK_STREAM)\n', (471, ...
# -*- coding: utf-8 -*- import os import distutils.util try: from config import * except ImportError: from config_example import * def env_bool(env, default): if os.environ.get(env): return distutils.util.strtobool(os.environ.get(env)) else: return default def env_str(env, default)...
[ "os.environ.get", "os.getenv" ]
[((178, 197), 'os.environ.get', 'os.environ.get', (['env'], {}), '(env)\n', (192, 197), False, 'import os\n'), ((333, 356), 'os.getenv', 'os.getenv', (['env', 'default'], {}), '(env, default)\n', (342, 356), False, 'import os\n'), ((393, 412), 'os.environ.get', 'os.environ.get', (['env'], {}), '(env)\n', (407, 412), Fa...
#!/usr/local/bin/python3 import sys import serial #SERIAL_DEVICE = "/dev/tty.SLAB_USBtoUART" SERIAL_DEVICE = "/dev/tty.usbserial-1410" MY_AXIS = 'X' DISABLE_MOSFETS_COMMAND = 0 ENABLE_MOSFETS_COMMAND = 1 SET_POSITION_AND_MOVE_COMMAND = 2 SET_VELOCITY_COMMAND = 3 SET_POSITION_AND_FINISH_TIME_COMMAND = 4 SET_ACCELERA...
[ "serial.Serial" ]
[((939, 988), 'serial.Serial', 'serial.Serial', (['SERIAL_DEVICE', '(230400)'], {'timeout': '(0.5)'}), '(SERIAL_DEVICE, 230400, timeout=0.5)\n', (952, 988), False, 'import serial\n')]
#!/usr/bin/env python ##################################### # Sense temperature from SenseHat # Send data to third party api. ##################################### from subprocess import call import os, sys, json, time, urllib2, getopt sys.path.append('../lib') import osutils as utils try: from sense_hat import ...
[ "getopt.getopt", "urllib2.urlopen", "sense_hat.SenseHat", "osutils.install_pkg", "time.sleep", "os.path.basename", "sys.exit", "sys.path.append" ]
[((238, 263), 'sys.path.append', 'sys.path.append', (['"""../lib"""'], {}), "('../lib')\n", (253, 263), False, 'import os, sys, json, time, urllib2, getopt\n'), ((477, 519), 'urllib2.urlopen', 'urllib2.urlopen', (["(url + '&field1=%s' % temp)"], {}), "(url + '&field1=%s' % temp)\n", (492, 519), False, 'import os, sys, ...
#!/usr/bin/env python2 import urllib.request import cv2 import os import random import json cap=cv2.VideoCapture(0) while cap.isOpened(): status,img=cap.read() cv2.imshow("Press C for 2 sec to capture the photo",img) if cv2.waitKey(1) & 0xff==ord('c'): cv2.imshow("Capture Image",img) num=s...
[ "cv2.imwrite", "cv2.imshow", "cv2.destroyAllWindows", "cv2.VideoCapture", "os.system", "random.random", "cv2.waitKey" ]
[((97, 116), 'cv2.VideoCapture', 'cv2.VideoCapture', (['(0)'], {}), '(0)\n', (113, 116), False, 'import cv2\n'), ((1206, 1229), 'cv2.destroyAllWindows', 'cv2.destroyAllWindows', ([], {}), '()\n', (1227, 1229), False, 'import cv2\n'), ((169, 226), 'cv2.imshow', 'cv2.imshow', (['"""Press C for 2 sec to capture the photo"...
# coding: utf-8 """ Author @NirajDevPandey Purpose = Passage search for a given query using Doc2Vec algorithm. this will train your own text passages and return the most similar paragraph from the corpus. The more passages you have the better it works. I would recommend to use pre trained model if you have less data...
[ "gensim.models.doc2vec.Doc2Vec", "smart_open.smart_open", "warnings.filterwarnings", "gensim.utils.simple_preprocess" ]
[((632, 665), 'warnings.filterwarnings', 'warnings.filterwarnings', (['"""ignore"""'], {}), "('ignore')\n", (655, 665), False, 'import warnings\n'), ((1245, 1314), 'gensim.models.doc2vec.Doc2Vec', 'gensim.models.doc2vec.Doc2Vec', ([], {'vector_size': '(50)', 'min_count': '(2)', 'epochs': '(50)'}), '(vector_size=50, min...
"""End-to-end test for templar/cli/templar.py""" from templar.api.config import ConfigBuilderError from templar.cli import templar import io import mock import os.path import shutil import unittest STAGING_DIR = os.path.join('tests', 'cli', 'staging') TEST_DATA = os.path.join('tests', 'cli', 'test_data') class Temp...
[ "mock.patch", "shutil.rmtree" ]
[((432, 458), 'shutil.rmtree', 'shutil.rmtree', (['STAGING_DIR'], {}), '(STAGING_DIR)\n', (445, 458), False, 'import shutil\n'), ((2726, 2776), 'mock.patch', 'mock.patch', (['"""sys.stdout"""'], {'new_callable': 'io.StringIO'}), "('sys.stdout', new_callable=io.StringIO)\n", (2736, 2776), False, 'import mock\n'), ((3604...
"""Test embedding different file formats and different encodings within the <Data> tag.""" import unittest import os from pywps import get_ElementMakerForVersion from pywps.app.basic import get_xpath_ns from pywps import Service, Process, ComplexInput, ComplexOutput, FORMATS from pywps.tests import client_for, assert_...
[ "pywps.get_ElementMakerForVersion", "owslib.wps.WPSExecution", "pywps.app.basic.get_xpath_ns", "pywps.ComplexInput", "base64.b64encode", "pywps.tests.assert_response_success", "owslib.wps.ComplexDataInput", "os.path.dirname", "pywps.ComplexOutput" ]
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import os import glob import random class PairGenerator(object): person1 = 'person1' person2 = 'person2' label = 'same_person' def __init__(self, lfw_path='./tf_dataset/resources' + os.path.sep + 'lfw'): self.all_people = self.generate_all_people_dict(lfw_path) def generate_all_people_di...
[ "random.choice", "random.random", "os.listdir", "glob.glob" ]
[((477, 497), 'os.listdir', 'os.listdir', (['lfw_path'], {}), '(lfw_path)\n', (487, 497), False, 'import os\n'), ((527, 600), 'glob.glob', 'glob.glob', (["(lfw_path + os.path.sep + person_folder + os.path.sep + '*.jpg')"], {}), "(lfw_path + os.path.sep + person_folder + os.path.sep + '*.jpg')\n", (536, 600), False, 'im...
"""Added a type for processes Revision ID: eadce7fbbf49 Revises: <PASSWORD> Create Date: 2018-08-31 13:24:22.009338 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '<KEY>' down_revision = '<PASSWORD>' branch_labels = None depends_on = None def upgrade(): ...
[ "sqlalchemy.String", "alembic.op.drop_column" ]
[((425, 462), 'alembic.op.drop_column', 'op.drop_column', (['"""processes"""', '"""p_type"""'], {}), "('processes', 'p_type')\n", (439, 462), False, 'from alembic import op\n'), ((367, 378), 'sqlalchemy.String', 'sa.String', ([], {}), '()\n', (376, 378), True, 'import sqlalchemy as sa\n')]
# -*- coding: utf-8 -*- from __future__ import unicode_literals import os import pytz import datetime BASEDIR = os.path.realpath(os.path.dirname(__file__)) ### Core Settings DB_URL = 'postgresql+psycopg2://compiler2017:mypassword@localhost/compiler2017' # DB_URL = 'sqlite:///data/compiler.db' TIMEZONE = pytz.timezone(...
[ "os.path.dirname", "pytz.timezone", "os.path.join" ]
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import matplotlib.pyplot as plt import cv2 import numpy as np def plot_imgs(imgs, titles=None, cmap='brg', ylabel='', normalize=True, ax=None, r=(0, 1), dpi=100): n = len(imgs) if not isinstance(cmap, list): cmap = [cmap]*n if ax is None: _, ax = plt.subplots(1, n, figsize=(6...
[ "cv2.line", "numpy.array", "cv2.circle", "numpy.random.randint", "matplotlib.pyplot.tight_layout", "matplotlib.pyplot.subplots", "numpy.round", "matplotlib.pyplot.get_cmap" ]
[((1245, 1263), 'matplotlib.pyplot.tight_layout', 'plt.tight_layout', ([], {}), '()\n', (1261, 1263), True, 'import matplotlib.pyplot as plt\n'), ((291, 338), 'matplotlib.pyplot.subplots', 'plt.subplots', (['(1)', 'n'], {'figsize': '(6 * n, 6)', 'dpi': 'dpi'}), '(1, n, figsize=(6 * n, 6), dpi=dpi)\n', (303, 338), True,...
import typing as tp import pydantic import yaml from loguru import logger from .config_models import GlobalConfig, CameraConfigSection @logger.catch(reraise=True) @tp.no_type_check def _load_config(config_path: str, model) -> tp.Any: logger.debug(f"Looking for config in {config_path}") with open(config_pat...
[ "loguru.logger.catch", "loguru.logger.debug", "pydantic.parse_obj_as" ]
[((140, 166), 'loguru.logger.catch', 'logger.catch', ([], {'reraise': '(True)'}), '(reraise=True)\n', (152, 166), False, 'from loguru import logger\n'), ((242, 294), 'loguru.logger.debug', 'logger.debug', (['f"""Looking for config in {config_path}"""'], {}), "(f'Looking for config in {config_path}')\n", (254, 294), Fal...
import json import networkx as nx def createGraphs(data): graphs=[] for timeIdx,window in enumerate(data['windows']): interval_graphs=[] for com_index,community in enumerate(window['communities']): com_id = 'TF'+str(timeIdx)+'_c'+str(com_index) G = nx.MultiDiGraph(cid=com_id) G.add_edges_from(community...
[ "json.load", "networkx.MultiDiGraph" ]
[((263, 290), 'networkx.MultiDiGraph', 'nx.MultiDiGraph', ([], {'cid': 'com_id'}), '(cid=com_id)\n', (278, 290), True, 'import networkx as nx\n'), ((485, 497), 'json.load', 'json.load', (['f'], {}), '(f)\n', (494, 497), False, 'import json\n')]
#!/usr/bin/python # -*- encoding: utf-8 -*- import math from bisect import bisect_right import torch class WarmupLrScheduler(torch.optim.lr_scheduler._LRScheduler): def __init__( self, optimizer, warmup_iter, warmup_ratio=5e-4, warmup='exp', ...
[ "matplotlib.pyplot.grid", "torch.nn.Conv2d", "math.cos", "numpy.array", "bisect.bisect_right", "numpy.arange", "matplotlib.pyplot.show" ]
[((4201, 4232), 'torch.nn.Conv2d', 'torch.nn.Conv2d', (['(3)', '(16)', '(3)', '(1)', '(1)'], {}), '(3, 16, 3, 1, 1)\n', (4216, 4232), False, 'import torch\n'), ((4640, 4653), 'numpy.array', 'np.array', (['lrs'], {}), '(lrs)\n', (4648, 4653), True, 'import numpy as np\n'), ((4715, 4725), 'matplotlib.pyplot.grid', 'plt.g...
import pandas as pd import numpy as np project_directory = '/Users/etiennelenaour/Desktop/Stage/' sentiment_score = pd.read_excel(project_directory + "csv_files/" +'inquirerbasic.xls') df_true = pd.read_csv(project_directory + 'csv_files/final_df_v3.csv') def creation_list(df, cate): final_list = list() fo...
[ "pandas.read_csv", "pandas.read_excel" ]
[((122, 191), 'pandas.read_excel', 'pd.read_excel', (["(project_directory + 'csv_files/' + 'inquirerbasic.xls')"], {}), "(project_directory + 'csv_files/' + 'inquirerbasic.xls')\n", (135, 191), True, 'import pandas as pd\n'), ((201, 261), 'pandas.read_csv', 'pd.read_csv', (["(project_directory + 'csv_files/final_df_v3....
from abc import ABC from pathlib import Path from typing import List, Union import pytest from pydantic import BaseModel from yaml import load from auto_optional.file_handling import convert_file try: from yaml import CLoader as YamlLoader except ImportError: from yaml import YamlLoader # type: ignore cla...
[ "pytest.mark.parametrize", "auto_optional.file_handling.convert_file", "yaml.load", "pathlib.Path" ]
[((894, 1002), 'pytest.mark.parametrize', 'pytest.mark.parametrize', (['"""test_config"""', 'SINGLE_FILE_TESTS'], {'ids': '[test.name for test in SINGLE_FILE_TESTS]'}), "('test_config', SINGLE_FILE_TESTS, ids=[test.name for\n test in SINGLE_FILE_TESTS])\n", (917, 1002), False, 'import pytest\n'), ((1183, 1215), 'aut...
# The MIT License (MIT) # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, subl...
[ "data_utils.get_batch", "data_utils.add_padding", "random.shuffle" ]
[((2515, 2534), 'random.shuffle', 'random.shuffle', (['qna'], {}), '(qna)\n', (2529, 2534), False, 'import random\n'), ((2056, 2111), 'data_utils.get_batch', 'data_gen.get_batch', (['length', 'batch_size', '(False)', 'cnf.task'], {}), '(length, batch_size, False, cnf.task)\n', (2074, 2111), True, 'import data_utils as ...
from .helper import parse_rule_list, inherit_json from .exceptions import VersionNotFound from .utils import get_library_version from typing import Dict, List, Any from .natives import get_natives import platform import json import copy import os __all__ = ["get_minecraft_command"] def get_libraries(data: Dict[str,A...
[ "os.path.join", "json.load", "copy.copy", "platform.system" ]
[((5133, 5151), 'copy.copy', 'copy.copy', (['options'], {}), '(options)\n', (5142, 5151), False, 'import copy\n'), ((425, 442), 'platform.system', 'platform.system', ([], {}), '()\n', (440, 442), False, 'import platform\n'), ((672, 703), 'os.path.join', 'os.path.join', (['path', '"""libraries"""'], {}), "(path, 'librar...
# crossvalidation evaluation script import datetime import itertools import os import sys from ginipls.__main__ import train_on_vectors, apply_on_vectors, evaluate, f1_score_on_prediction_file, \ accuracy_score_on_prediction_file from ginipls.models.ginipls import PLS_VARIANT from ginipls.config import GLOBAL_LOGGE...
[ "ginipls.__main__.accuracy_score_on_prediction_file", "ginipls.config.GLOBAL_LOGGER.info", "os.makedirs", "ginipls.__main__.f1_score_on_prediction_file", "itertools.product", "os.path.join", "ginipls.config.GLOBAL_LOGGER.debug", "os.path.isfile", "os.path.isdir", "ginipls.__main__.apply_on_vectors...
[((396, 425), 'os.path.join', 'os.path.join', (['wd', '"""processed"""'], {}), "(wd, 'processed')\n", (408, 425), False, 'import os\n'), ((477, 504), 'os.path.isdir', 'os.path.isdir', (['matrices_dir'], {}), '(matrices_dir)\n', (490, 504), False, 'import os\n'), ((522, 548), 'os.path.join', 'os.path.join', (['wd', '"""...
import requests base = "https://danbot.host/nodeStatus" sysinfo = 'https://danbot.host/sysinfo' leaderboard = "https://api.danbot.host/leaderboard" ###################################### ##### GETTING ALL STATUS ##### ###################################### def getallstats(): r = requests.get(base) if r...
[ "requests.get" ]
[((293, 311), 'requests.get', 'requests.get', (['base'], {}), '(base)\n', (305, 311), False, 'import requests\n'), ((679, 697), 'requests.get', 'requests.get', (['base'], {}), '(base)\n', (691, 697), False, 'import requests\n'), ((2082, 2100), 'requests.get', 'requests.get', (['base'], {}), '(base)\n', (2094, 2100), Fa...
#!/usr/bin/env python3 import pandas as pd import numpy as np def last_week(): # Create the dataframe df = pd.read_csv("src/UK-top40-1964-1-2.tsv", sep="\t") # Replace songs that weren't on the last week's list with nulls. cond = (df["LW"] != "New") & (df["LW"] != "Re") df = df.where(cond, ot...
[ "pandas.isna", "pandas.notna", "pandas.read_csv" ]
[((117, 167), 'pandas.read_csv', 'pd.read_csv', (['"""src/UK-top40-1964-1-2.tsv"""'], {'sep': '"""\t"""'}), "('src/UK-top40-1964-1-2.tsv', sep='\\t')\n", (128, 167), True, 'import pandas as pd\n'), ((974, 989), 'pandas.isna', 'pd.isna', (['df.Pos'], {}), '(df.Pos)\n', (981, 989), True, 'import pandas as pd\n'), ((833, ...
from __future__ import unicode_literals, print_function import io import json from snips_nlu import SnipsNLUEngine from snips_nlu.default_configs import CONFIG_EN import glob class IntentRecognition: def __init__(self, name=''): self.name = name def loadntrain(self, rootpath = './datasets/*.json'): ...
[ "json.load", "snips_nlu.SnipsNLUEngine", "glob.glob", "io.open" ]
[((340, 359), 'glob.glob', 'glob.glob', (['rootpath'], {}), '(rootpath)\n', (349, 359), False, 'import glob\n'), ((522, 554), 'snips_nlu.SnipsNLUEngine', 'SnipsNLUEngine', ([], {'config': 'CONFIG_EN'}), '(config=CONFIG_EN)\n', (536, 554), False, 'from snips_nlu import SnipsNLUEngine\n'), ((443, 456), 'io.open', 'io.ope...
import numpy as np import utils from dataset_specifications.dataset import Dataset class ConstNoiseSet(Dataset): def __init__(self): super().__init__() self.name = "const_noise" self.std_dev = np.sqrt(0.25) def get_support(self, x): return (x-2*self.std_dev, x+2*self.std_dev)...
[ "numpy.random.normal", "utils.get_gaussian_pdf", "numpy.sqrt", "numpy.stack", "numpy.random.uniform" ]
[((224, 237), 'numpy.sqrt', 'np.sqrt', (['(0.25)'], {}), '(0.25)\n', (231, 237), True, 'import numpy as np\n'), ((360, 405), 'numpy.random.uniform', 'np.random.uniform', ([], {'low': '(-1.0)', 'high': '(1.0)', 'size': 'n'}), '(low=-1.0, high=1.0, size=n)\n', (377, 405), True, 'import numpy as np\n'), ((420, 473), 'nump...
import sys import json import time import pexpect import pexpect.replwrap import subprocess with open(sys.argv[1], 'r') as f: log = json.load(f) tidal_startup = subprocess.check_output('bash -c "ghc-pkg field -f ~/.cabal/store/ghc-$(ghc --numeric-version)/package.db tidal data-dir --simple-output"', shell=True)....
[ "subprocess.check_output", "pexpect.replwrap.REPLWrapper", "subprocess.Popen", "time.sleep", "json.load" ]
[((369, 426), 'subprocess.Popen', 'subprocess.Popen', (["['ghci', '-ghci-script', tidal_startup]"], {}), "(['ghci', '-ghci-script', tidal_startup])\n", (385, 426), False, 'import subprocess\n'), ((435, 551), 'pexpect.replwrap.REPLWrapper', 'pexpect.replwrap.REPLWrapper', (['f"""ghci -ghci-script {tidal_startup}"""', '"...
# -*- coding: utf-8 -*- """ Copyright (c) Microsoft Corporation. All Rights Reserved. Licensed under the MIT license. See LICENSE file on the project webpage for details. XBlock to allow for video playback from Azure Media Services Built using documentation from: http://amp.azure.net/libs/amp/latest/docs/index.html "...
[ "logging.getLogger", "azure_video_pipeline.utils.get_video_info", "edxval.models.Video.objects.filter", "xblock.core.XBlock.needs", "django.http.HttpResponseBadRequest", "xmodule.modulestore.django.modulestore", "xblock.fragment.Fragment", "edxval.models.Video.objects.get", "requests.get", "lms.dj...
[((1300, 1327), 'logging.getLogger', 'logging.getLogger', (['__name__'], {}), '(__name__)\n', (1317, 1327), False, 'import logging\n'), ((1337, 1361), 'xblockutils.resources.ResourceLoader', 'ResourceLoader', (['__name__'], {}), '(__name__)\n', (1351, 1361), False, 'from xblockutils.resources import ResourceLoader\n'),...
#!/usr/bin/python from getpass import getpass from os import system system('clear') # colors red = "\033[91;1m" green = "\033[92;1m" yellow = "\033[93;1m" blue = "\033[94;1m" # banner print(green + ''' ┌───────────────────────────────┐ │╻ ╻┏━┓┏━┓╻ ╻ ┏┓ ╻ ╻┏━┓╺┳╸┏━╸┏━┓│ │┣━┫┣━┫┗━┓┣━┫ ┣┻┓┃ ┃┗━┓ ┃ ┣╸ ┣┳┛│ │╹ ╹╹ ╹┗━┛╹...
[ "os.system" ]
[((69, 84), 'os.system', 'system', (['"""clear"""'], {}), "('clear')\n", (75, 84), False, 'from os import system\n'), ((746, 780), 'os.system', 'system', (['"""python modules/hasher.py"""'], {}), "('python modules/hasher.py')\n", (752, 780), False, 'from os import system\n'), ((821, 858), 'os.system', 'system', (['"""p...
# Copyright (c) 2021, NVIDIA CORPORATION. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to i...
[ "cugraph.utilities.check_nx_graph", "cudf.Series", "collections.defaultdict", "cudf.DataFrame", "cugraph.sampling.random_walks_wrapper.random_walks" ]
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#!/usr/bin/env python from __future__ import print_function # Core import collections from functools import wraps import logging import pprint import random import re import time import ConfigParser from decimal import * # Third-Party import argh from clint.textui import progress import html2text from PIL import Ima...
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from collections import OrderedDict, defaultdict import numpy as np import torch.nn as nn import torch.nn.functional as F import time import torch from FClip.line_parsing import OneStageLineParsing from FClip.config import M from FClip.losses import ce_loss, sigmoid_l1_loss, focal_loss, l12loss from FClip.nms import ...
[ "FClip.losses.l12loss", "collections.OrderedDict", "FClip.nms.structure_nms_torch", "FClip.losses.ce_loss", "FClip.line_parsing.OneStageLineParsing.fclip_torch", "FClip.losses.sigmoid_l1_loss", "time.time", "FClip.config.M.to_dict", "FClip.losses.focal_loss", "torch.cat", "torch.nn.functional.bi...
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import os import sys import json import logging import numpy as np logging.basicConfig(level=logging.INFO) from robo.solver.hyperband_datasets_size import HyperBand_DataSubsets from hpolib.benchmarks.ml.surrogate_svm import SurrogateSVM run_id = int(sys.argv[1]) seed = int(sys.argv[2]) rng = np.random.RandomState(...
[ "logging.basicConfig", "os.makedirs", "json.dump", "numpy.log", "os.path.join", "hpolib.benchmarks.ml.surrogate_svm.SurrogateSVM", "robo.solver.hyperband_datasets_size.HyperBand_DataSubsets", "numpy.random.RandomState" ]
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import numpy as np from slugnet.activation import ReLU, Softmax from slugnet.layers import Convolution, Dense, MeanPooling, Flatten from slugnet.loss import SoftmaxCategoricalCrossEntropy as SCCE from slugnet.model import Model from slugnet.optimizers import SGD from slugnet.data.mnist import get_mnist X, y = get_mn...
[ "slugnet.activation.Softmax", "slugnet.layers.Convolution", "slugnet.optimizers.SGD", "slugnet.layers.Flatten", "slugnet.data.mnist.get_mnist", "numpy.random.seed", "slugnet.loss.SoftmaxCategoricalCrossEntropy", "slugnet.layers.MeanPooling", "numpy.random.permutation" ]
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#!/usr/bin/env python from __future__ import print_function import MV2 import cdms2 import vcs import genutil import glob import numpy # import time import datetime from genutil import StringConstructor import os import pkg_resources pmp_egg_path = pkg_resources.resource_filename( pkg_resources.Requirement.parse("...
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from rest_framework.views import APIView from rest_framework.response import Response from rest_framework import status from . import models, serializers class Notifys(APIView): def get(self, request, format=None): user = request.user notifys = models.Notify.objects.filter(to=user) seri...
[ "rest_framework.response.Response" ]
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import random import numpy as np def divided_training_test(examples_matrix, lbls, train_prec): concatenated_examples_lbs = np.concatenate((examples_matrix, lbls), axis=1) np.random.shuffle(concatenated_examples_lbs) size_of_vector = np.shape(concatenated_examples_lbs)[1] size_of_matrix = len(concaten...
[ "numpy.shape", "numpy.concatenate", "numpy.random.shuffle" ]
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""" Prepare Tests Script generating and a set of parameters for simulations. Parameters are saved as set in `parameters/test_set` To use just run python test_set script does not take any command line arguments or flags. The script is intended to provide a simple way to describe what experiments to perform. ""...
[ "numpy.linspace", "sortedcontainers.SortedSet", "numpy.random.randn" ]
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from django.shortcuts import render from .models import Osoba def poosobama(request): svao = Osoba.objects.all() return render(request, "pitanja/index.html", {'svao' : svao}) # Create your views here.
[ "django.shortcuts.render" ]
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""" Copyright (c) 2021 Graphcore Ltd. All rights reserved. """ """ # Efficient data loading with PopTorch """ """ This tutorial will present how PopTorch could help to efficiently load data to your model and how to avoid common sources of performance loss from the host. This will also cover the more general notion of...
[ "torch.nn.GroupNorm", "torch.nn.ReLU", "time.time", "torch.utils.data.TensorDataset", "torch.nn.Conv2d", "poptorch.DataLoader", "torch.nn.MaxPool2d", "torch.nn.NLLLoss", "torch.nn.Linear", "sys.exit", "torch.nn.LogSoftmax", "poptorch.Options", "torch.empty", "torch.randn", "torch.flatten...
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################################################################################################## # Copyright (c) 2012 <NAME> # # Permission is hereby granted, free of charge, to any person obtaining a copy of # this software and associated documentation files (the "Software"), to deal in # the Software without restri...
[ "frog.models.Video.objects.all", "frog.models.Image.objects.all" ]
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import binascii import os from django.contrib.auth.models import AbstractUser from django.db import models from django.utils.translation import ugettext_lazy as _ from project.apps.user.managers import UserManager, ActionTokenManager from rest_framework.authtoken.models import Token from django.utils import timezone...
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"""Dummy DIMSE-C SCPs for use in unit tests""" from copy import deepcopy import logging import os import socket import time import threading from pydicom import read_file from pydicom.dataset import Dataset from pydicom.uid import UID, ImplicitVRLittleEndian, JPEG2000Lossless from pynetdicom import ( AE, Ass...
[ "logging.getLogger", "pynetdicom.Association", "threading.Thread.__init__", "os.path.join", "pynetdicom.AE", "time.sleep", "pynetdicom.transport.AssociationSocket", "os.path.dirname", "copy.deepcopy", "pydicom.dataset.Dataset" ]
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from __future__ import absolute_import from ..coordinate import Coordinate from ..roi import Roi from .shared_graph_provider import\ SharedGraphProvider, SharedSubGraph from ..graph import Graph, DiGraph from pymongo import MongoClient, ASCENDING, ReplaceOne, UpdateOne from pymongo.errors import BulkWriteError, Wri...
[ "logging.getLogger", "numpy.int64", "networkx.DiGraph", "networkx.Graph", "networkx.connected_components", "pymongo.UpdateOne", "numpy.uint64", "networkx.weakly_connected_components", "pymongo.ReplaceOne", "pymongo.MongoClient", "pymongo.errors.WriteError" ]
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#!BPY """ Name: 'Clean Weight...' Blender: 245 Group: 'WeightPaint' Tooltip: 'Removed verts from groups below a weight limit.' """ __author__ = "<NAME> aka ideasman42" __url__ = ["www.blender.org", "blenderartists.org", "www.python.org"] __version__ = "0.1" __bpydoc__ = """\ Clean Weight This Script is to be used on...
[ "BPyMesh.dict2MeshWeight", "Blender.Draw.PupBlock", "Blender.Draw.Create", "Blender.Draw.PupMenu", "Blender.Scene.GetCurrent", "BPyMesh.meshWeight2Dict" ]
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#!/usr/bin/python import sys import astor from CodeRunner import runCode from CustomExceptions import * class DistanceCalculator(): def normalise_branch_distance(self, branch_distance): try: return 1 - pow(1.001, -branch_distance) except OverflowError as e: print(branch_distance) raise e def calc_bran...
[ "CodeRunner.runCode" ]
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import csv import json #jsonfile = open('nuts.json', 'w') # # # # # # reader = csv.DictReader(csvfile, delimiter='|', quotechar='"') # for row in reader: # json.dump(row, jsonfile) # jsonfile.write('\n') #jsonfile.write('[') #with open('nuts3-qgis.csv', mode="r", encoding="utf-8") as csv_file: globallist = [...
[ "json.dumps", "csv.DictReader" ]
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import json import jydoop import telemetryutils setupjob = telemetryutils.setupjob """ Example job to read the SECURITY_UI histogram and output one row for each entry in the "values" map. Rows are of the form: YYYYMMDD<uuid>, bucket, count, channel, os, os_version """ def map(key, value, cx): try: j = js...
[ "json.loads" ]
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import time def robo_sleep(duration, get_now=time.perf_counter): now = get_now() end = now + duration while now < end: now = get_now() def check_time_sleep(amount): start = time.perf_counter() time.sleep(amount) end = time.perf_counter() return end-start def check_robo_sleep(am...
[ "time.perf_counter", "time.sleep" ]
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import json from lints.vim import VimVint, VimLParserLint def test_vint_undefined_variable(): msg = ['t.vim:3:6: Undefined variable: s:test (see :help E738)'] res = VimVint().parse_loclist(msg, 1) assert json.loads(res)[0] == { "lnum": "3", "col": "6", "text": "[vint]Undefined var...
[ "lints.vim.VimLParserLint", "json.loads", "lints.vim.VimVint" ]
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# Licensed under the Apache License, Version 2.0 (the "License"); you # may not use this file except in compliance with the License. You may # obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under th...
[ "logging.getLogger", "logging.basicConfig", "httpexceptor.HTTP302", "datetime.datetime.utcnow", "httpexceptor.HTTP404", "purpler.store.Store", "os.environ.get", "selector.Selector", "iso8601.parse_date", "datetime.timedelta", "jinja2.FileSystemLoader", "httpexceptor.HTTP400", "bleach.linkify...
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import unittest import numpy as np import pytest from audiomentations import TanhDistortion from audiomentations.core.utils import calculate_rms class TestTanhDistortion(unittest.TestCase): def test_single_channel(self): samples = np.random.normal(0, 0.1, size=(2048,)).astype(np.float32) sample_...
[ "numpy.random.normal", "numpy.allclose", "audiomentations.core.utils.calculate_rms", "audiomentations.TanhDistortion", "numpy.amax" ]
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import json import time import traceback from components.registrators.aws_iot.generic import AwsIoTGenericRegistrator from handlers.utils import Logger, base_response # Import Project Logger project_logger = Logger() logger = project_logger.get_logger() # Set the Registration Class handler from the import to keep La...
[ "traceback.format_exc", "json.loads", "handlers.utils.Logger", "handlers.utils.base_response", "time.time" ]
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### basic modules import numpy as np import time, pickle, os, sys, json, PIL, tempfile, warnings, importlib, math, copy, shutil, setproctitle ### torch modules import torch import torch.nn as nn import torch.optim as optim from torch.autograd import Variable from torchvision import datasets, transforms from torch.opti...
[ "os.path.exists", "os.makedirs", "torch.utils.data.DataLoader", "torchvision.transforms.RandomHorizontalFlip", "torchvision.transforms.RandomCrop", "torchvision.datasets.ImageFolder", "torch.utils.data.distributed.DistributedSampler", "torchvision.transforms.Normalize", "torchvision.datasets.CIFAR10...
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import os from ray.tune.logger import DEFAULT_LOGGERS, CSVLogger from ray.tune.result import EXPR_PROGRESS_FILE class PathmindCSVLogger(CSVLogger): def _init(self): """CSV outputted with Headers as first set of results.""" progress_file = os.path.join(self.logdir, EXPR_PROGRESS_FILE) self...
[ "os.path.exists", "os.path.getsize", "os.path.join" ]
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import os import urllib.request import csv import yaml from flask import Flask, request, jsonify import numpy as np from package.preprocessing import read_data, preprocess from package.model_utils import train_model from package.app_util import json_to_row app = Flask(__name__) # read in configuration with open('....
[ "os.path.exists", "flask.Flask", "flask.request.get_data", "package.preprocessing.read_data", "yaml.safe_load", "package.app_util.json_to_row", "os.mkdir", "numpy.random.RandomState", "flask.jsonify" ]
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""" support.py Convenience and utility methods. """ import time class Timer: """ Context manager which measures elapsed time """ def __enter__(self): self.start = time.time() return self def __exit__(self, *args): self.end = time.time() self.elapsed_time = self.en...
[ "time.time" ]
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import re, os, glob def CollectData(N, mem): for fn in glob.glob("search_tmp.*"): os.remove(fn) with open("search.cpp", "rt") as f: src = f.read() ints = mem / 8 src = re.sub(r"const int SIZE = (\d*);", r"const int SIZE = %d;" % N, src) src = re.sub(r"const int ARR_SAMPLE...
[ "re.sub", "os.system", "glob.glob", "os.remove" ]
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import collections import multiprocessing import threading from tkinter import * import evolution_render from ea.store import Store from game.simulation import dnn_to_handler from render import App load_cromosomes = [] ins_cromosomes = [] max_generation = 10 global curr_case curr_case = 1 def CurSelect(evt): val...
[ "render.App", "ea.store.Store.load_gen" ]
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# -*- coding: utf-8 -*- import datetime import urllib from django.shortcuts import render_to_response from django.template import RequestContext from django.contrib.contenttypes.models import ContentType from django.shortcuts import get_object_or_404 from django.utils import timezone from .models import * from .help...
[ "django.contrib.contenttypes.models.ContentType.objects.get_for_model", "urllib.unquote", "django.shortcuts.get_object_or_404", "django.template.RequestContext", "django.utils.timezone.now" ]
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# © BugHunterCodeLabs ™ # © bughunter0 # 2021 # Copyright - https://en.m.wikipedia.org/wiki/Fair_use import os from os import error import pyrogram from pyrogram import Client, filters from pyrogram.types import InlineKeyboardMarkup, InlineKeyboardButton from pyrogram.types import User, Message from bs4 import Beauti...
[ "pyrogram.filters.command", "requests.get", "bs4.BeautifulSoup", "pyrogram.filters.regex", "os.remove" ]
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"Example substitution; adapted from t_sub.py/t_NomialSubs /test_Basic" from gpkit import Variable x = Variable("x") p = x**2 assert p.sub({x: 3}) == 9 assert p.sub({x.key: 3}) == 9 assert p.sub({"x": 3}) == 9
[ "gpkit.Variable" ]
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import urllib.request import re import argparse import sys import os from time import sleep __version__ = "1.0" banner = """ \033[1m\033[91m .d888888b. d88888888b 8888 8888 8888 8888 ...
[ "os.getcwd", "argparse.ArgumentParser", "re.search" ]
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from collections import deque n, Q = map(int, input().split()) graph = [[] for _ in range(n)] for i in range(n - 1): a, b = map(int, input().split()) a -= 1 b -= 1 graph[a].append(b) graph[b].append(a) # print(graph) dist = [-1] * n q = deque() q.append(0) dist[0] = 0 while q: v = q.popleft() ...
[ "collections.deque" ]
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import pytest from tests.communication.test_FileComm import TestFileComm as base_class class TestAsciiFileComm(base_class): r"""Test for AsciiFileComm communication class.""" @pytest.fixture(scope="class", autouse=True) def filetype(self): r"""Communicator type being tested.""" return "as...
[ "pytest.fixture" ]
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import unittest import numpy from chainer import cuda from chainer import functions from chainer import gradient_check from chainer import testing from chainer.testing import attr from chainer.testing import condition @testing.parameterize(*testing.product({ 'in_shape': [(2, 3, 8, 6), (2, 1, 4, 6)], })) class T...
[ "chainer.functions.ResizeImages", "chainer.testing.condition.retry", "chainer.testing.run_module", "chainer.testing.product", "numpy.zeros", "numpy.array", "chainer.functions.resize_images", "numpy.random.uniform", "chainer.testing.assert_allclose", "chainer.cuda.to_gpu" ]
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#third party imports import traceback from tqdm import tqdm #progress bar from github #std imports import os import threading import json import re import time #local imports from . import helpers class Ufc_Data_Scraper: #Constants DEFAULT_DIRECTORY ="UFC_Data_Scraper" SAVE_FIGHT_DIR = "fight_history" ...
[ "traceback.format_exc", "os.listdir", "tqdm.tqdm", "time.sleep", "os.getcwd", "os.chdir", "os.remove", "os.path.isdir", "os.mkdir", "threading.Thread", "json.dump", "re.search" ]
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