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from math import sin, cos import pytest import numpy as np from .._esn_online import ESNOnline from reservoirpy.datasets import lorenz @pytest.fixture(scope="session") def matrices(): Win = np.array([[1, -1], [-1, 1], [1, -1], [-1, -1]]) W = np.arr...
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from skimage.transform import resize heatmap_1_r = resize(heatmap_1, (50,80), mode='reflect', preserve_range=True, anti_aliasing=True) heatmap_2_r = resize(heatmap_2, (50,80), mode='reflect', preserve_range=True, anti_aliasing=True) heatmap_3_r = resize(heatmap_3, (50,80), mod...
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import logging import boto3 from botocore.exceptions import ClientError def download_file(dest_bucket_name, dest_file_key): """Fetch an file to an Amazon S3 bucket The src_data argument must be of type bytes or a string that references a file specification. :param dest_bucket_name: string...
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import os import sys sys.path.append(os.path.join(os.path.dirname(__file__), "../../")) import tensorflow as tf import magenta.models.melody_rnn.melody_rnn_create_dataset as md import scripts.target as tgt def main(unused_argv): tf.logging.set_verbosity(md.FLAGS.log) config = md.melody_rnn_config_flags.confi...
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from rest_framework.authentication import SessionAuthentication class CsrfExemptSessionAuthentication(SessionAuthentication): def enforce_csrf(self, request): return
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import json import os import pickle import ulmo import param import pandas as pd import geopandas as gpd from shapely.geometry import box, Point from quest import util reserved_catalog_entry_fields = [ 'name', 'service', 'service_id', 'publisher_id', 'display_name', 'description', 'reser...
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import game_config from game_config import Position import copy class Snake(object): def __init__(self) -> None: self.window_size = Position(game_config.game_sizes["width"], game_config.game_sizes["height"]) self.direction = game_config.D_Down self.body = [] self.last_body = [] ...
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from io import BytesIO from typing import List from lor_deckcodes.utils import next_varint, decode_base32 from lor_deckcodes.constants import faction_mapping, CURRENT_FORMAT_VERSION, SUPPORTED_VERSIONS def _decode_card_block(n: int, data_stream: BytesIO) -> List[str]: card_block_list = [] n_card_copies = ne...
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import os, subprocess, sys, getopt from subprocess import run def find_cppcheck(): drive_letters = ['C', 'D'] for drive_letter in drive_letters: cppcheck_path = drive_letter + r":\Program Files\Cppcheck\cppcheck.exe" if os.path.isfile(cppcheck_path): return cppcheck_path print('Failed to find cp...
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r"""Assorted function for use when computing metrics and evals.""" import collections import os import numpy as np import scipy from scipy import signal from scipy.ndimage.filters import convolve import tensorflow.compat.v1 as tf def _FSpecialGauss(size, sigma): """Function to mimic the 'fspecial' gaussian MATLAB ...
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from sys import platform import sys try: import caffe except ImportError: print("This sample can only be run if Python Caffe if available on your system") print("Currently OpenPose does not compile Python Caffe. This may be supported in the future") sys.exit(-1) import os os.environ["GLOG_minloglev...
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from InstruccionesPL.TablaSimbolosPL.InstruccionPL import InstruccionPL from InstruccionesPL.IndicesPL import IndicePL1, IndicePL7, IndicePL8, IndicePL9, IndicePLUnique, IndicePLUsing, IndicePLUsingNull from InstruccionesPL.Expresiones import PrimitivoPL class AlterIndice(InstruccionPL): def __init__(self, nombre...
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import torch import torch.nn as nn import torch.nn.functional as F import torch.distributions as D from base import BaseModel EPSILON = 1e-30 class GraphVAE(BaseModel): def __init__(self, input_dim, n_nodes, node_dim): super(GraphVAE, self).__init__() # store parameters self.input_dim = in...
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from dse.cqlengine import columns from dse.cqlengine.models import Model from dse.cqlengine.query import LWTException from datetime import datetime import hashlib import validate_email from .user_management_events_kafka import UserManagementPublisher class UserModel(Model): """Model class that maps to the user tab...
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import numpy as np from keras import backend as K import os import sys def patch_path(path): return os.path.join(os.path.dirname(__file__), path) def main(): K.set_image_dim_ordering('tf') sys.path.append(patch_path('..')) from keras_video_classifier.library.recurrent_networks import VGG16Bidirecti...
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from concurrent.futures import ThreadPoolExecutor from pprint import pprint from datetime import datetime import time from itertools import repeat import logging import yaml from netmiko import ConnectHandler, NetMikoAuthenticationException logging.getLogger("paramiko").setLevel(logging.WARNING) logging.basicConfig...
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from __future__ import print_function, absolute_import from collections import OrderedDict import numpy as np import tables from six import iteritems from ._result import H5NastranResult from ._bdf import H5NastranBDF class H5Nastran(H5NastranBDF, H5NastranResult): def __init__(self, h5filename, mode='r', nast...
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effects = { # instruction name -> [bytes, newva, contraints, effects] 'rdtsc': ('0f31', None, (), ('edx = TSC_HIGH', 'eax = TSC_LOW')), 'div16': ('66f7f2', None, (), ('eax = (((((edx & 0x0000ffff) << 16) | (eax & 0x0000ffff)) / (edx & 0x0000ffff)) | (eax & 0xffff00...
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import os import unittest from os.path import expanduser from util.Docker import Docker class GoServices(unittest.TestCase): def test_go(self): script_dir = os.path.dirname(os.path.realpath(__file__)) code_dir = script_dir + "/.." home = expanduser("~") goPath = os.environ['GOPATH...
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import numpy as np from axelerate.networks.yolo.backend.utils.box import BoundBox from axelerate.networks.yolo.backend.utils.box import BoundBox, nms_boxes, boxes_to_array class YoloDecoder(object): def __init__(self, anchors = [0.57273, 0.677385, 1.87446, 2.06253, 3.33843, 5.47434, 7....
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import functools import torch class TensorList(list): """Container mainly used for lists of torch tensors. Extends lists with pytorch functionality.""" def __init__(self, list_of_tensors = None): if list_of_tensors is None: list_of_tensors = list() super(TensorList, self).__init__...
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import pytest from ddtrace.internal.sma import SimpleMovingAverage from ddtrace.internal.writer import DEFAULT_SMA_WINDOW def test_min_size(): sma = SimpleMovingAverage(DEFAULT_SMA_WINDOW) assert DEFAULT_SMA_WINDOW == sma.size assert DEFAULT_SMA_WINDOW == len(sma.counts) assert DEFAULT_SMA_WINDOW ==...
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import sys import unittest from linkml_runtime.dumpers import rdf_dumper, json_dumper from linkml_runtime.loaders import yaml_loader from pyshex.evaluate import evaluate from linkml.generators.jsonldcontextgen import ContextGenerator from linkml.generators.shexgen import ShExGenerator from tests.test_generators.envir...
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from __future__ import print_function, unicode_literals import platform import sys info = { 'impl': platform.python_implementation(), 'version': platform.python_version(), 'revision': platform.python_revision(), 'maxunicode': sys.maxunicode, 'maxsize': sys.maxsize } search_modules = ['charade', ...
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class ImageBackgroundSettings(BackgroundSettings,IDisposable): """ Represents the rendering image background settings. """ def Dispose(self): """ Dispose(self: BackgroundSettings,A_0: bool) """ pass def ReleaseUnmanagedResources(self,*args): """ ReleaseUnmanagedResources(self: BackgroundSettings,disposin...
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import json import spacy from collections import defaultdict nlp = spacy.load('en_core_web_sm') def load_json(filename): "Wrapper function to load JSON data." with open(filename) as f: data = json.load(f) return data def save_json(data, filename): "Wrapper function to save the data as JSON....
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import argparse import json import pytest from typing import Dict, List, Tuple, Union NestedDict = Union[Dict[str, float], "NestedDict"] def flatten_nested_dict(nested_dict: NestedDict) -> Dict[Tuple[str, ...], float]: def _recursively_flatten( target: Dict[Tuple[str, ...], float], d: NestedDict, prefix:...
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import argparse import torch from utils.cli import boolean_argument def get_args(rest_args): parser = argparse.ArgumentParser() parser.add_argument("--env-name", default="PointRobotSparse-v0") parser.add_argument("--seed", type=int, default=73) parser.add_argument("--max-rollouts-per-task", default=2)...
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from builtins import str from django.contrib import messages from django.urls import reverse from django.shortcuts import redirect from django.contrib.auth.decorators import login_required from django.shortcuts import render from pykeg.web.decorators import staff_member_required from pykeg.util import kbjson from . i...
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import sys from ._C import mecab_cost_train, mecab_dict_gen, mecab_dict_index, mecab_main, mecab_system_eval, mecab_test_gen def run_mecab_main(argv=sys.argv): mecab_main(argv) def run_mecab_dict_index(argv=sys.argv): mecab_dict_index(argv) def run_mecab_dict_gen(argv=sys.argv): mecab_dict_gen(argv) ...
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from PyFlow.UI.Canvas.UINodeBase import UINodeBase from PyFlow.Packages.PyFlowOpenCv.UI.UIOpenCvBaseNode import UIOpenCvBaseNode from PyFlow.Packages.PyFlowOpenCv.UI.UICv_TransformNode import UICv_TransformNode def createUINode(raw_instance): if raw_instance.__class__.__name__ == "cv_Transform": return UICv_Transf...
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from datetime import date from decimal import Decimal from django.db.models.fields.files import ImageFieldFile, FileField class BaseSerializer(object): def serialize(self, value): return value class DateSerializer(BaseSerializer): def serialize(self, value): return str(value) class Decimal...
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import multiprocessing import os import pickle import tempfile import time import unittest import uuid from hypothesis import given from hypothesis.strategies import text try: import pymongo except ImportError: pymongo = None from chocolate import SQLiteConnection, MongoDBConnection, DataFrameConnection, Spa...
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class CandidateDescriptor(object): """ Descriptor that defines an candidate the solver wants to be checked. It is used to lable/identify the candidates and their results in the case of batch processing. """ def __init__(self, **definingValues): """ @param definingValues Class assume...
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from asgiref.sync import async_to_sync from channels.layers import get_channel_layer def sysMsg(channel_name, msg_type, not_level, content={}): """ Notify system message to channel """ channel_layer = get_channel_layer() async_to_sync(channel_layer.group_send)( channel_name, { ...
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from numba import njit, boolean, int64, float64 from numba.experimental import jitclass import numpy as np from .utils import isin @jitclass([ ('value', float64[:]), ('sign', float64[:]), ('size', int64) ]) class signed: def __init__(self, value, sign=None): """ If sign is None, init from val...
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from creme import stream from . import base class ChickWeights(base.FileDataset): """Chick weights along time. The stream contains 578 items and 3 features. The goal is to predict the weight of each chick along time, according to the diet the chick is on. The data is ordered by time and then by chic...
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from zope.interface import implements from twisted.plugin import IPlugin from twisted.application.service import IServiceMaker from twisted.application import internet from oauth_proxy import oauth_proxy class OAuthProxyServiceMaker(object): implements(IServiceMaker, IPlugin) tapname = "oauth_proxy" desc...
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import tensorflow as tf import copy from icecaps.estimators.estimator_chain import EstimatorChain from icecaps.estimators.seq2seq_encoder_estimator import Seq2SeqEncoderEstimator from icecaps.estimators.seq2seq_decoder_estimator import Seq2SeqDecoderEstimator class Seq2SeqEstimator(EstimatorChain): def __init__...
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import ConfigParser import string _ConfigDefault = { "database.dbms": "mysql", "database.name": "", "database.user": "root", "database.password": "", "database.host": "127.0.0.1" } def LoadConfig(file, config={}): """ returns a diction...
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from paddleflow.pipeline import Pipeline from paddleflow.pipeline import ContainerStep from paddleflow.pipeline import Parameter from paddleflow.pipeline import Artifact from paddleflow.pipeline import CacheOptions from paddleflow.pipeline import PF_USER_NAME def job_info(): return { "PF_JOB_TYPE": "vcjob"...
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import configs_and_settings import csv import os # C:\Users\Xavier\LSTMforSHM\data\time_series_datasets\csv_data_test_file.csv # csv_file_path = r"C:\Users\Xavier\LSTMforSHM\data\time_series_datasets\csv_data_test_file.csv" csv_file_path = r"C:\Users\Xavier\LSTMforSHM\data\csv_data\csv_data_test_file123.csv" def re...
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import fileinput from itertools import count def slice_to_str(slice): return ''.join(str(n) for n in slice) INPUT = int(fileinput.input()[0]) input_str = str(INPUT) input_len = len(input_str) recipes = [3, 7] recipes_len = 2 elf_1 = 0 elf_2 = 1 part_1 = None part_2 = None while part_1 is None or part_2 is No...
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import bpy import os import math import json from copy import deepcopy from . import DataBase from . import Versions from . import Util bUsePrincipledMat = True isHighHeel = False bRotationLimit = False bLimitOnTwist = True bUseCustomBone = False bUseDrivers = False #remove shape key from all wearable things, not just...
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import math import time import os import PyQt5.QtWidgets as QtWidgets import PyQt5.QtCore as Qt from vtk.qt.QVTKRenderWindowInteractor import QVTKRenderWindowInteractor from vtkUtils import * from config import * class MainWindow(QtWidgets.QMainWindow, QtWidgets.QApplication): def __init__(self, app): se...
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from PIL import Image import argparse import os import mimetypes from utils.transforms import get_no_aug_transform import torch from models.generator import Generator import numpy as np import torchvision.transforms.functional as TF import torch.nn.functional as F from torchvision import transforms import cv2 from torc...
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import math from mks.models import Member from persons.models import Person, PersonAlias # from: http://www.cs.princeton.edu/introcs/21function/ErrorFunction.java.html # Implements the Gauss error function. # erf(z) = 2 / sqrt(pi) * integral(exp(-t*t), t = 0..z) # # fractional error in math formula less than 1.2 * 1...
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import elasticsearch import argparse import re def parse_rule_line(rule_line): """ Parse each rule line and return a dict representation of a rule :param rule_line: :return: rule dict """ rule_dict = {} rule_info = re.search("\((.*)\)", rule_line).group(1) msg_sections = rule_info.spli...
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import cympy import pandas class Substation(object): """""" def __init__(self, model_filename): """""" # Open the model self.model_filename = model_filename cympy.study.Open(self.model_filename) def baseload_allocation(self, feeder_loads): """Allocate lo...
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from abc import ABC, abstractmethod from pathlib import Path from typing import List from novelsave.core.entities.novel import Novel class BasePackager(ABC): @property @abstractmethod def priority(self): """Determines the order in which the packager must be called. Lowest first""" @abstract...
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import os import utils import config import traceback import argparse import logging.config from luna import LunaExcepion logging.config.fileConfig("logging.conf") logger = logging.getLogger() os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' def parse_args(): parser = argparse.ArgumentParser() parser.add_argument('-...
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import logging from telegram import Update from telegram.ext import CommandHandler, Updater, CallbackContext logger = logging.getLogger(__name__) def add_core(upd: Updater, core_handlers_group: int): logger.info("register smile-mode handlers") dp = upd.dispatcher dp.add_handler(CommandHandler("start", s...
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import warnings from types import FrameType from typing import Optional, Dict, Any, cast __all__ = ["make_step"] import inspect from baikal.steps import Step def make_step( base_class: type, attr_dict: Dict[str, Any] = None, class_name: Optional[str] = None ) -> type: """Creates a step subclass from the gi...
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import webview import pytest from .util import run_test def test_bg_color(): window = webview.create_window('Background color test', 'https://www.example.org', background_color='#0000FF') run_test(webview, window) def test_invalid_bg_color(): with pytest.raises(ValueError): webview.create_window...
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import hoki.age_utils as au import hoki.load as load import pkg_resources import numpy as np import pandas as pd import pytest from hoki.utils.exceptions import HokiFatalError, HokiUserWarning, HokiFormatError # Loading Data data_path = pkg_resources.resource_filename('hoki', 'data') hr_file = data_path + '/hrs-sin-i...
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import requests # Vuln Base Info def info(): return { "author": "cckuailong", "name": '''Wordpress Profile Builder Plugin Cross-Site Scripting''', "description": '''The Profile Builder User Profile & User Registration Forms WordPress plugin is vulnerable to cross-site scripting due to insu...
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from blesuite.connection_manager import BLEConnectionManager from blesuite.event_handler import ATTEventHook from blesuite.entities.gatt_device import BLEDevice from blesuite.entities.permissions import Permissions import blesuite.utils.att_utils as att_utils from scapy.layers.bluetooth import ATT_Read_Request, ATT_Rea...
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import numpy as np import matplotlib.pyplot as plt import afterglowpy as grb Z = {'jetType': grb.jet.TopHat, # Top-Hat jet 'specType': 0, # Basic Synchrotron Emission Spectrum 'thetaObs': 0.05, # Viewing angle in radians 'E0': 1.0e53, # Isotropic-equivalent ene...
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import FWCore.ParameterSet.Config as cms # Set the HLT paths import HLTrigger.HLTfilters.hltHighLevel_cfi ALCARECOSiStripCalMinBiasAAGHLT = HLTrigger.HLTfilters.hltHighLevel_cfi.hltHighLevel.clone( andOr = True, ## choose logical OR between Triggerbits ## HLTPaths = [ ## #Minimum Bias ## "HLT_MinBias*"...
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from setuptools import setup, find_packages setup( name='mkdocs-pdf-export-plugin', version='0.5.10', description='An MkDocs plugin to export content pages as PDF files', long_description='The pdf-export plugin will export all markdown pages in your MkDocs repository as PDF files' ...
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import random from six import string_types import frappe import jwt from frappe import _ from frappe.auth import LoginManager from frappe.utils import cint, get_url, get_datetime from frappe.utils.password import check_password, passlibctx, update_password from renovation_core.utils import update_http_response from ...
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import idc import ida_enum from bip.py3compat.py3compat import * from .bipelt import BipRefElt class BipEnum(object): """ Class for representing and manipulating an enum in IDA. Class method :meth:`~BipEnum.get` and :meth:`~BipEnum.create` allows to easily create and recuperate a :class:...
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import sys import subprocess import re from tabulate import tabulate import textwrap import warnings import datetime as dt import numpy as np from scipy.interpolate import interp1d from ._exceptions import InterfaceError, AdapterUnaccessibleError from .utils import db2dbm, RealTimePlot, spin, rssi_to_colour_str from ....
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import pytest pytestmark = [ pytest.mark.django_db, pytest.mark.freeze_time('2032-12-01 16:20'), ] @pytest.fixture(autouse=True) def material(course, mixer): return mixer.blend('notion.Material', course=course, is_home_page=True, page_id='deadbeef') @pytest.fixture def another_material(course, mixer, f...
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import alarm import board import time import digitalio import neopixel ## WAKING PINS - uncomment appropriate pin per microcontroller wake_pin = board.X1 # STM32F4 Pyboard # wake_pin = board.GP0 # RP2040 Pico # wake_pin = board.A4 # NRF52840 Feather # wake_pin = board.IO5 ...
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import sys import os import dk import gc from .mainframe import MainFrame class App(dk.App): ''' 응용 프로그램 인스턴스 (dk.App)''' def onInit(self): self.resourceDir = os.path.abspath(os.path.join( os.path.dirname(__file__), 'resources' )) print('resourceDir: ', self.resourceDir) displayBound...
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from utils.basic_utils import load_json, save_json def combine(video_name_split_path, video_duration_path, save_path): video_name_split = load_json(video_name_split_path) video_duration_dict = load_json(video_duration_path) combined_dict = {} for split_name, split_video_names in video_name_split.item...
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from navycut.utils.server import create_asgi_app from os import environ # Asynchronus server gateway interface # use uvicorn asgi server to run this app #define your default settings file here: environ.setdefault("NAVYCUT_SETTINGS_MODULE", "check1.settings") application = create_asgi_app()
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import os from argparse import ArgumentParser import random def read_ner(path): data = [[]] with open(path, encoding='ISO-8859-1') as f: for line in f: line = line.strip() # New sentence if len(line) == 0: if len(data[-1]) > 0: d...
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import json from os.path import expanduser class RenderEnvironment(): def __init__(self): self.queueName = None self.largeDiskQueueName = None self.jobDefinition = None self.sourceBucket = None self.resultsBucket = None def validate(self): if self.queueName is ...
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import pytest from cx_const import Number, StepperDir from cx_core.stepper import MinMax, Stepper, StepperOutput class FakeStepper(Stepper): def __init__(self) -> None: super().__init__(MinMax(0, 1), 1) def step(self, value: Number, direction: str) -> StepperOutput: return StepperOutput(next_...
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import os import json import copy import subprocess from dotenv import load_dotenv, find_dotenv import yaml import logging import argparse import requests # grafana api host grafana_api_host = "https://monitor.harmony.one/api/" # set shard count shard_count = 4 # min storage space for alerting min_storage_space = 5 # ...
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import warnings from collections import OrderedDict, defaultdict from typing import ( Any, Callable, Collection, DefaultDict, Dict, Iterable, List, Optional, Sequence, Set, Tuple, cast, ) import torch from torch import nn import pystiche from ..misc import build_deprec...
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from deficrawler.lending import Lending def test_liquidation_aave_2_eth(): aave = Lending(protocol="Aave", chain="Ethereum", version=2) liquidations = aave.get_data_from_date_range( '21/04/2021 05:20:01', '22/04/2021 06:22:01', "liquidation") assert(liquidations[0]['tx_id'] != "") assert(liqui...
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from utils import registry DATASETS = registry.Registry('dataset') def build_dataset_from_cfg(cfg, default_args = None): """ Build a dataset, defined by `dataset_name`. Args: cfg (eDICT): Returns: Dataset: a constructed dataset specified by dataset_name. """ return DATASETS....
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import tuned.logs log = tuned.logs.get() __all__ = ["Monitor"] class Monitor(object): """ Base class for all monitors. Monitors provide data about the running system to Plugin objects, which use the data to tune system parameters. Following methods require reimplementation: - _init_available_devices(cls) ...
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import warnings from typing import Dict, Type from ..core.builder import DatasetBuilder from ...serializers.event import EventDataSerializer, StatsBombSerializer # 3749133 / 38412 class Statsbomb(DatasetBuilder): def get_dataset_urls(self, **kwargs) -> Dict[str, str]: warnings.warn( "\n\nYou ...
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import numpy as np import numpy.random as rnd from libtlda.rba import RobustBiasAwareClassifier def test_init(): """Test for object type.""" clf = RobustBiasAwareClassifier() assert type(clf) == RobustBiasAwareClassifier assert not clf.is_trained def test_fit(): """Test for fitting the model."""...
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myvar = {1:10,2:20} class myclass(): def __init__(self): myvar[1]=100 print myvar self.printvar() def printvar(self): print myvar k = myclass()
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import logging from django_elasticsearch_dsl.registries import registry from django.apps import apps from froide.celery import app as celery_app logger = logging.getLogger(__name__) def get_instance(model_name, pk): model = apps.get_model(model_name) try: return model._default_manager.get(pk=pk) ...
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import os, urllib, sys, getopt class Renamer: input_encoding = "" output_encoding = "" path = "" is_url = False def __init__(self, input, output, path, is_url): self.input_encoding = input self.output_encoding = output self.path = path self.is_url = is_url def...
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from behave import given, when, then from hamcrest import * empty_database = '' one_user_registered = 'alice <PASSWORD>' URL = 'http://localhost:8080/demo/library.html' DEFAULT_USERNAME = 'alice' DEFAULT_PASSWORD = '<PASSWORD>' @given('I am not registered') def step_impl(context): pass @when('I register with a...
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from __future__ import print_function import numpy as np import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt import h5py import tensorflow as tf from tensorflow.keras import backend as K from tensorflow.keras.layers import Input, Dense, Dropout from tensorflow.keras.models import Model, model_fro...
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from typing import Iterable, Callable, TypeVar from .config import CacheType from .foreach_recipe import ForeachRecipe from .recipe import Recipe R = TypeVar("R") # The return type of the bound function def recipe(ingredients: Iterable[Recipe] = (), transient: bool = False, cache: CacheType = CacheType.Auto) -> \ ...
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import supriya.realtime def test_01(server): control_bus = supriya.realtime.Bus.control() control_bus.allocate() assert control_bus.is_allocated result = control_bus.get() assert result == 0.0 assert control_bus.value == result control_bus.set(0.5) result = control_bus.get() as...
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from __future__ import absolute_import, division, print_function # svn co https://cbflib.svn.sourceforge.net/svnroot/cbflib/trunk/CBFlib_bleeding_edge sourceforge_cbflib class info_counters(object): def __init__(O): O.mkdir = 0 O.copied = 0 O.updated = 0 O.already_up_to_date = 0 def report(O): ...
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from __future__ import absolute_import from past.builtins import basestring import re from ckan.common import _ import ckan.lib.navl.dictization_functions as df from ckanext.fluent.validators import fluent_text from ckan.common import config import ckan.plugins.toolkit as toolkit import ckan.logic.validators as validat...
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import json import pytest from graphene.test import Client from main.schema import schema @pytest.mark.django_db def test_municipalities_exists(): client = Client(schema) result = client.execute(''' query { municipalities { edges { node { id name bfsNumber } } } ...
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import logging import re import secrets import django from django.contrib.auth import authenticate from django.core.mail import send_mail from django.http import HttpResponse from django.shortcuts import render, redirect from app.views import validate_user_email from .models import CustomUser def get_logger(): ...
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from __future__ import division, print_function import numpy as np import plyades.util as util def precession(date): ''' Vallado 2nd Edition p.215 ''' # Julian centuries since the epoch t = (date - 2451545)/36525 zeta = util.dms2rad(0, 0, 2306.2181*t + 0.30188*t**2 + 0.017998*t**3) theta = util...
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from ..factory import Type class callStateReady(Type): protocol = None # type: "callProtocol" connections = None # type: "vector<callConnection>" config = None # type: "string" encryption_key = None # type: "bytes" emojis = None # type: "vector<string>" allow_p2p = None # type: "Bool"
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from __future__ import absolute_import import time from flexmock import flexmock import pony.tasks from tests.test_base import BaseTest class SendMessageTest(BaseTest): def test_execute(self): task = pony.tasks.SendMessage('_to', '_text', [1, 2, 3]) (flexmock(self.bot.slack_client.server) ...
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import info class subinfo(info.infoclass): def setTargets( self ): self.svnTargets[ "master"] = f"https://github.com/hunspell/hunspell.git" for ver in ["1.6.2"]: self.targets[ver] = f"https://github.com/hunspell/hunspell/archive/v1.6.2.tar.gz" self.archiveNames[ver] = f"hun...
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import pickle import torch import math import time def to_cuda(x): use_gpu = torch.cuda.is_available() if use_gpu: x = x.cuda() return x def time_since(since): now = time.time() s = now - since m = math.floor(s / 60) s -= m * 60 return '%dm %ds' % (m, s) def save_checkpoint...
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import torch import torch.nn as nn import torch.nn.functional as F from .fusion import AsymBiChaFuseReduce, BiLocalChaFuseReduce, BiGlobalChaFuseReduce class ResidualBlock(nn.Module): def __init__(self, in_channels, out_channels, stride, downsample): super(ResidualBlock, self).__init__() self.bod...
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import discord from discord.ext import commands class Help(commands.Cog): """Displays the message you are currently viewing!""" def __init__(self,bot): self.bot = bot @commands.command() @commands.has_permissions(add_reactions=True,embed_links=True) async def help(self,ctx,*cog): "...
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import rclpy from rclpy.node import Node from rclpy.exceptions import ParameterNotDeclaredException from rcl_interfaces.msg import ParameterType class MyPythonNode(Node): def __init__(self): super().__init__("dummy_node") self.get_logger().info("This node just says 'Hello'") timer_period ...
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from numpy import inf, nan from sklearn.gaussian_process import GaussianProcessClassifier as Op from lale.docstrings import set_docstrings from lale.operators import make_operator class _GaussianProcessClassifierImpl: def __init__(self, **hyperparams): self._hyperparams = hyperparams self._wrappe...
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import cv2 import numpy as np def draw_rectangle(event, x, y, flags, params): global x_init, y_init, drawing def update_pts(): params["top_left_pt"] = (min(x_init, x), min(y_init, y)) params["bottom_right_pt"] = (max(x_init, x), max(y_init, y)) img[y_init:y, x_init:x] = 255 - img[y_...
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import rdkit.Chem as Chem import rdkit.Chem.AllChem as AllChem from rdkit.Chem.rdchem import ChiralType, BondType, BondDir from rdchiral.chiral import template_atom_could_have_been_tetra from rdchiral.utils import vprint class rdchiralReaction(): ''' Class to store everything that should be pre-computed for a...