content stringlengths 5 1.05M |
|---|
from django.conf.urls import url, include
# from rest_framework import routers
from nlp_tools import views
# router = routers.DefaultRouter()
# router.register(r'tokenize', views.tokenize)
# Wire up our API using automatic URL routing.
# Additionally, we include login URLs for the browsable API.
urlpatterns = [
#... |
"""
Source: https://github.com/lemariva/uPySensors/blob/19c5e2a21d61dbb50bf3b1c9032789e816291720/hcsr04.py
"""
from machine import Pin, time_pulse_us
from micropython import const
from uasyncio import sleep
import utime
from constants import THOUSAND
from utils.conversions import micro_to_base
_DEFAULT_TIMEOUT = con... |
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the isValid function below.
def isValid(s):
frequency = [s.count(letter) for letter in set(s) ]
if(max(frequency)-min(frequency) == 0):
return('YES')
elif(frequency.count(max(frequency)) == 1 and max(frequency)-min(... |
from csv import DictReader
from io import StringIO
from objectify.encoding import _DEFAULT_ENCODING
# data = DictReader(open(file, encoding='utf-8'))
# for row in data:
# rowmap = dict(row)
# # print(dumps(rowmap, indent=2))
# cidr = rowmap['a_cidr']
# print(cidr)
def objectify_csv(path_buf_stream,
... |
#!/usr/bin/env python
"""
GUI Frame for XRD display
"""
import sys
import os
import time
import copy
from functools import partial
from threading import Thread
import socket
from functools import partial
import wx
import wx.lib.mixins.inspection
import wx.lib.scrolledpanel as scrolled
try:
from wx._core import P... |
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
import tensorflow as tf
tf.get_logger().setLevel('ERROR')
from tensorflow.keras.mixed_precision import experimental as mixed_precision
import numpy as np
import cv2
import shutil
from lr_schedules import WarmupCosineDecay, WarmupPiecewise
import os.path as osp
from uti... |
from pydantic import BaseModel
try:
from bme280 import BME280 as BME280Sensor
from ltr559 import LTR559 as LTR559Sensor
except ImportError:
from mocks import BME280 as BME280Sensor, LTR559 as LTR559Sensor
from models.bme280 import BME280
from models.ltr559 import LTR559
class Enviro(BaseModel):
bme2... |
"""
The prime factors of 13195 are 5, 7, 13 and 29.
What is the largest prime factor of the number 600851475143?
"""
from math import trunc
def largestPrimeFactor(num):
primeFactor = 1
x = 2
while x < num/x + 1:
if num % x == 0:
primeFactor = x
num /= x
else:
... |
import rice_calc.modules as modules
import os
import numpy as np
import datetime
def cacl_rice_dos(list_str_day, day_input, file_list,result_path):
output_img = 'ard_store'
day_in_date = datetime.datetime(int(day_input[0:4]), int(day_input[4:6]), int(day_input[6:8]))
start_day = day_in_date - datetime.time... |
import requests
import os
from flask_rebar import errors
from app.app import registry
from app.app import rebar
from app.schemas.chat import ChatSchema
@registry.handles(rule="/chat", method="POST", request_body_schema=ChatSchema())
def post_chat():
# TODO: Do not use dockers internal host.
chat = rebar.val... |
# coding: utf-8
#
# Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file
# except in compliance with the License. A copy of the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "lice... |
#!/usr/bin/python
import StringIO
import subprocess
import os
import time
#import datetime
from datetime import datetime
from PIL import Image
# Original code written by brainflakes and modified to exit
# image scanning for loop as soon as the sensitivity value is exceeded.
# this can speed taking of larger photo if m... |
from tkinter import ttk, StringVar, colorchooser
import json
from .canvas import SimpleGraph
class SelectorMeta(SimpleGraph):
'''A selection icon that sets the shape and color of the graphic.
Example:
======================
from tkinter import Tk
root = Tk()
select = SelectorMeta(root)
s... |
# Copyright Contributors to the Pyro project.
# SPDX-License-Identifier: Apache-2.0
from collections import OrderedDict
import pytest
import torch
import funsor.ops as ops
import funsor.torch.distributions as dist
from funsor.cnf import Contraction
from funsor.domains import Bint, Reals
from funsor.gaussian import G... |
import sympy.physics.mechanics as _me
import sympy as _sm
import math as m
import numpy as _np
x, y = _me.dynamicsymbols('x y')
a, b = _sm.symbols('a b', real=True)
e = a*(b*x+y)**2
m = _sm.Matrix([e,e]).reshape(2, 1)
e = e.expand()
m = _sm.Matrix([i.expand() for i in m]).reshape((m).shape[0], (m).shape[1])
e = _sm.fa... |
#!/usr/bin/env python3
import sys
if sys.version_info.minor < 6:
raise Exception("Execute this script with at least python 3.6 to ensure all dicts are ordered!")
XRL_FUNCTIONS = {
'AtomicWeight': {'Z': int},
'ElementDensity': {'Z': int},
'CS_Total': {'Z': int, 'E': float},
'CS_Photo': {'Z': int, 'E': float},... |
import os, hashlib
import requests
from tqdm import tqdm
URL_MAP = {
"cifar10": "https://heibox.uni-heidelberg.de/f/869980b53bf5416c8a28/?dl=1",
"ema_cifar10": "https://heibox.uni-heidelberg.de/f/2e4f01e2d9ee49bab1d5/?dl=1",
"lsun_bedroom": "https://heibox.uni-heidelberg.de/f/f179d4f21ebc4d43bbfe/?dl=1",
... |
import arrow
from flask import request, session, url_for
def init_utils(application):
@application.before_request
def before_request():
if request.args.get('css') in ['enable', 'disable']:
session['css_disabled'] = request.args.get('css') == 'disable'
@application.context_processor
... |
import torch
import numpy as np
import readability
from more_itertools import sort_together
from tqdm import tqdm
import pdb
STRIDE = 200
def super_linear_uid_compute(input, k_power):
uid = torch.zeros(1)
for surprisal in input:
uid = uid + torch.pow(surprisal, k_power)
return uid/len(input)
def ... |
import hashlib
from django.utils.crypto import get_random_string
from django.template import Context, Template, TemplateSyntaxError
def get_random_hash(length=32):
return hashlib.sha1(get_random_string().encode("utf8")).hexdigest()[:length]
def string_template_replace(text, context_dict):
try:
t = ... |
# -*- coding:utf-8 -*-
# author: hpf
# create time: 2020/7/14 22:37
# file: select_sort.py
# IDE: PyCharm
# 思路:
# 把一个无序序列看做两部分，前一部分为有序，后一部分为无序
# [ [], 34, 2, 13, 76, 54, 22, 90, 46, 13]
# 从后一部分找出最小值，与第一个元素互换
# 找出次小值，与第二个元素互换，以此类推
def select_sort(alist):
n = len(alist)
# 需要进行n-1次选择操作
for j in range(n-1):
... |
from .minimizer import GeneralizeToRepresentative
from ._version import __version__
__all__ = ['GeneralizeToRepresentative',
'__version__']
|
import discord
from discord import message
from discord.ext import commands
from discord.ext.commands.core import command
from discord.utils import get
from discord.ext import tasks
import ast
import io
import os
import sys
import traceback
import textwrap
import platform
import psutil
import config
from pymongo impor... |
import pandas as pd
import pickledb
db = pickledb.load('cornell_lines_out.db', False)
import json
df = pd.read_csv('./movie_lines.txt', sep = '\+\+\+\$\+\+\+',
engine = 'python', index_col = False)
df.head()
df.drop(df.columns[1:4], axis=1, inplace=True)
for value in df.values.tolist():
db.set(str(va... |
import tornado.web
import tornado.ioloop
from apiApplicationModel import userData
from cleanArray import Label_Correction
import json
import asyncio
import aiohttp
colName=['age', 'resting_blood_pressure', 'cholesterol', 'max_heart_rate_achieved', 'st_depression', 'num_major_vessels', 'st_slope_downsloping', '... |
from .bool_type import BoolType
from .int_type import IntType
from .str_type import StrType
from .float_type import FloatType
|
# -*- coding: utf-8 -*-
import requests
from lxml.html.clean import clean_html
from django.db import transaction
from django.core.management.base import BaseCommand, CommandError
from budget.models import Reply, Keyword
from lxml import etree
from datetime import *
from dateutil.parser import *
from lxml.html.clean imp... |
import json
class Word:
def __init__(self, word, translation=None, phrase=None, synonyms=[],
sound_record_path=None, study_status=0,
last_repeat_date=None, *args, **keywords):
self.word = word.strip()
self.word_lower = self.word.lower()
self.translation = ... |
import multiprocessing
import os
from time import sleep
import boto3
from cloudlift.config import get_account_id, get_cluster_name, \
ServiceConfiguration, get_region_for_environment
from cloudlift.config.logging import log_bold, log_intent, log_warning
from cloudlift.deployment import deployer, ServiceInformatio... |
#!/usr/bin/python
import csv
import sys
import os.path
from . import data_prep_utils
from collections import OrderedDict
def consoleLabel(raw_strings, labels, module):
print('\nStart console labeling!\n')
valid_input_tags = OrderedDict([(str(i), label) for i, label in enumerate(labels)])
printHelp(valid_... |
# adapted from https://github.com/facebookresearch/pytorch_GAN_zoo
import torch
import torch.nn as nn
import torch.nn.functional as F
from model.layers import flatten, upscale2d, EqualizedLinear, EqualizedConv2d, NormalizationLayer
from model.network_utils import mini_batch_std_dev
class BasicBlock(nn.Module):
d... |
import FWCore.ParameterSet.Config as cms
from Configuration.EventContent.EventContent_cff import AODSIMEventContent
EXODisappTrkSkimContent = AODSIMEventContent.clone()
EXODisappTrkSkimContent.outputCommands.append('drop *')
EXODisappTrkSkimContent.outputCommands.append('keep *_reducedHcalRecHits_*_*')
EXODisappTrkSki... |
from utils import SYM2ID, ROOT_DIR, IMG_DIR, NULL, IMG_TRANSFORM
from copy import deepcopy
import random
import json
import numpy as np
from PIL import Image
import torch
from torch.utils.data import Dataset, DataLoader
from torch.utils.data.dataloader import default_collate
class HINT(Dataset):
def __init__(self,... |
import sys
sys.path.append('..')
from robot.components import MotorComponent
#from basestation.xbox import Controller
import time
motor = MotorComponent('leftMotor', 'l_stick_vertical', 11, 12)
controllerValue = 0
while True:
controllerValue += 5
print(controllerValue)
time.sleep(.05)
motor.doUpdate(co... |
from turtle import Turtle
WIDTH = 5
HEIGHT = 1
class Paddle(Turtle):
def __init__(self, position):
super().__init__()
self.position = position
self.shape("square")
self.shapesize(WIDTH, HEIGHT)
self.penup()
self.color("white")
self.goto(position)
def up... |
"""Smoke test."""
from . import u
def test_render_no_commands():
t = """aa bb cc dd"""
s = u.render(t, {})
assert s == t
def test_empty():
t = ""
s = u.render(t, {})
assert s == t
def test_strip():
t = '{2+2} xxx {3+3} yyy {4+4}'
s = u.render(t)
assert s == '4 xxx 6 yyy 8'
... |
# -*- test-case-name: twistedcaldav.test.test_upgrade -*-
##
# Copyright (c) 2008-2015 Apple Inc. All rights reserved.
#
# 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.or... |
def corr_gamma(a1,a2,mu1,mu2,rho,N):
"""
Use: X1,X2 = corr_gamma(a1,a2,b1,b2,rho,N)
This function follows an algorithm obtained at
http://web.ics.purdue.edu/~hwan/IE680/Lectures/Chap08Slides.pdf
It generates the two gamma distributed random variables
X1 ~ Gamma(a1,mu1)
X2 ~ Gamma(a2,mu2)
... |
# coding: utf-8
"""
Task Execution Service
No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator) # noqa: E501
The version of the OpenAPI document: v1
Generated by: https://openapi-generator.tech
"""
from __future__ import absolute_import
import... |
import logging
import os
import sys
from pynetdicom.presentation import StoragePresentationContexts
from libs import Database, handle_open, handle_c_store, handle_c_find, handle_close, handle_c_echo, handle_c_get
from pynetdicom import AE, build_context, evt
def main():
"""Main"""
db = Database("config.ini"... |
import warnings
import hashlib
import os
from functools import total_ordering
from lxml import etree
from six import add_metaclass, string_types as basestring
try:
import urlparse
except ImportError:
from urllib import parse as urlparse
try:
from collections.abc import Iterable, Mapping
except ImportErr... |
#!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os.path as osp
import attr
import numba
import numpy as np
from habitat_sim.bindings import cuda_enabled
from h... |
#!/usr/bin/env python
# encoding: utf-8
# This file is part of the quickscons project. This project is used to build
# other software that MAY or MAY NOT be licensed under the same terms as this
# project. This project is licensed under the below:
#
# The MIT License (MIT)
#
# Copyright © 2015 Stephen M Buben <smbuben... |
import os
import re
import sys
import time
import urllib2
sys.path.append("../frame/")
from loggingex import LOG_INFO
from loggingex import LOG_ERROR
from loggingex import LOG_WARNING
from singleton import singleton
from mysql_manager import mysql_manager
@singleton
class stock_conn_manager():
def __init__(self)... |
from cdmanager import cd
import os
from pathlib import Path
import pandas as pd
import shutil
import subprocess
from utilpipeline import (
checkMD5isCorrect,
checkFastaQLenght,
performTrimGaloreFourFiles,
qualityCheckTrimGaloreFourFiles,
performBismark
)
ids_file = '../data/commonDa... |
#!/usr/bin/python
# -*- coding: utf-8 -*-
"""
(c) 2017 David Barroso <dbarrosop@dravetech.com>
This file is part of Ansible
Ansible is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the Licens... |
from datetime import datetime, timedelta
import makerbase
from makerbase.models import *
"""
user: {
'id':
'name':
'avatar_url':
'html_url':
<link to person?>
}
maker: {
'name':
'avatar_url':
'html_url':
}
project: {
'name':
'description':
'avatar_url':
'html_url':
}... |
import glob
import json
import os
import torch
class Saver(object):
@staticmethod
def meta_path(dir_):
return os.path.join(dir_, 'meta.json')
@staticmethod
def model_path(dir_, num_step=None, model_name=None):
model_name = model_name or 'model-*.ckpt'
if num_step is not None:... |
from .l2norm import L2Norm
from .multibox_loss import MultiBoxLoss
from .focal_loss import FocalLoss
__all__ = ['L2Norm', 'MultiBoxLoss',"FocalLoss"]
|
import torch
from torch import nn
import torch.nn.functional as F
from models import audio_convnet
from models import image_convnet
from models import base_models
def normalize_img(value, vmax=None, vmin=None):
value1 = value.view(value.size(0), -1)
value1 -= value1.min(1, keepdim=True)[0]
value1 /= value1... |
"""
The ledgerlink module
=====================
This module defines the models allowing to manipulate information regarding links stored in the
NEO blockchain.
"""
def init_app(app, **kwargs):
# Register blueprints.
from . import views
app.register_blueprint(views.ledgerlink_blueprint)
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
__author__ = "Ricardo Ribeiro"
__credits__ = ["Ricardo Ribeiro"]
__license__ = "MIT"
__version__ = "0.0"
__maintainer__ = "Ricardo Ribeiro"
__email__ = "ricardojvr@gmail.com"
__status__ = "Development"
from pyforms.gui.Controls.ControlBase import... |
from sklearn.svm import SVC
from global_constants import TRAIN, TEST, DEV
def train_and_predict(data, labels, kernel='linear', probability=True):
# print "Probability", probability
svc = SVC(kernel=kernel, probability=probability, verbose=False, max_iter=100000)
svc.fit(data[TRAIN], labels[TRAIN])
pre... |
"""Datasets required by pytorch dataloaders for competition data."""
import numpy as np
from torch.utils.data import Dataset
from constants import Mappings, FilePaths
TGT2ERR_COL = {"reactivity": "reactivity_error", "deg_Mg_50C": "deg_error_Mg_50C", "deg_Mg_pH10": "deg_error_Mg_pH10"}
class RNAData(Dataset):
d... |
import os
import os.path
import tempfile
import numpy as np
from magenta.models.rl_tuner import rl_tuner_ops
from magenta.models.rl_tuner import note_rnn_loader
from magenta.models.rl_tuner import rl_tuner
import matplotlib
import matplotlib.pyplot as plt # pylint: disable=unused-import
import tensorflow.compat.v1 as... |
from github import Github, InputGitTreeElement
import re
import datetime
from argparse import ArgumentParser
parser = ArgumentParser()
parser.add_argument("-r", "--release", action="store_true", help="Release only mode")
parser.add_argument("-c", "--commit", action="store_true", help="Commit only mode")
parser.add_ar... |
# -*- coding: utf-8 -*-
import os
import requests
import json
import time
import pathlib
import itertools
import numpy as np
from tqdm import tqdm
from preprocessing import (
read_ts_dataset,
normalize_dataset,
moving_windows_preprocessing,
denormalize,
)
NUM_CORES = 7
def notify_slack(msg, webhook=N... |
#!/usr/bin/env python
# -*- coding:UTF-8 -*-
#
# follow.py
#
# 无限数据流
# Follow a file like tail -f.
import time
def follow(thefile):
thefile.seek(0,2)
try:
while True:
line = thefile.readline()
if not line:
time.sleep(0.1)
continue
yi... |
from .nms import SingleLabelNMS, MultiLabelNMS
POSTPROCESSES = {
'SingleLabelNMS': SingleLabelNMS,
'MultiLabelNMS': MultiLabelNMS
}
def build_postprocess(postprocess: dict):
return POSTPROCESSES[postprocess.pop('type')](**postprocess)
|
def calculateNetIncome(gross, state):
state_tax = {'NY': 10, 'LA': 12, 'CA': 2, 'SF': 0, 'HI': 15}
net = gross - (gross * 0.10)
if state in state_tax:
net = net - (gross * state_tax[state]/100)
print("The calculated Net income after deduction is: " + str(net))
return net
else:
... |
##Write code to rearrange the strings in the list winners so that they are in alphabetical order from A to Z.
winners = ['Kazuo Ishiguro', 'Rainer Weiss', 'Youyou Tu', 'Malala Yousafzai', 'Alice Munro', 'Alvin E. Roth']
winners.sort()
|
from .test_utils import TempDirectoryTestCase
from pulsar.managers.base import JobDirectory
import os
TEST_JOB_ID = "1234"
class JobDirectoryTestCase(TempDirectoryTestCase):
def setUp(self):
super().setUp()
self.job_directory = JobDirectory(self.temp_directory, TEST_JOB_ID)
def test_setup(s... |
import json
from config import db
# Insert into 'catalogs'
with open('./assets/seller_catalogs_extra_fake_data_cambo.json') as json_file:
fake_catalogs = json.load(json_file)
batch = db.batch()
for catalog in fake_catalogs:
docRef = db.document(f'sellers/{catalog["seller_id"]}/catalogs/{catalog["i... |
#from django.http import HttpResponse, JsonResponse
import requests
from requests.auth import HTTPBasicAuth
import json
#from . mpesa_credentials import MpesaAccessToken, LipanaMpesaPpassword
#from django.views.decorators.csrf import csrf_exempt
#from .models import MpesaPayment
from keys import MpesaAccessToken,Lipana... |
# flake8: noqa
from codewars.meeting import meeting
# pylint: disable=line-too-long
def test_meeting() -> None:
cases = [
(
"Alexis:Wahl;John:Bell;Victoria:Schwarz;Abba:Dorny;Grace:Meta;Ann:Arno;Madison:STAN;Alex:Cornwell;Lewis:Kern;Megan:Stan;Alex:Korn",
"(ARNO, ANN)(BELL, JOHN)(... |
import sys
from typing import Dict
import numpy as np
from pso.strategy import OptimizationStrategy, MultiParticle
from pso.swarm import Swarm, SwarmConfig
class MultiSwarm:
def __init__(self, outer_swarm_config: SwarmConfig, strategy: OptimizationStrategy):
self.__strategy = strategy
self.__num... |
import pygame
pygame.init()
pantalla=pygame.display.set_mode((480,300))
salir=False
reloj1= pygame.time.Clock()
imagen1=pygame.image.load("alienr.png").convert_alpha()
(x,y)= (100,100)
vx=0
r1=pygame.Rect(250,70,25,500)
sprite1= pygame.sprite.Sprite()
sprite1.image=imagen1
sprite1.rect=imagen1.get_rect()
sprite1.rect.... |
import os
import py
import pytest
import time
from lektor.builder import Builder
from lektor.db import Database
from lektor.project import Project
from lektor.environment import Environment
from lektor_npm_support import NPMSupportPlugin
@pytest.fixture(scope='function')
def project():
return Project.from_path(o... |
from django.urls import path, register_converter
from orders import views
from .converters import ShiftConverter, OrderVenueConverter, OrderConverter
register_converter(ShiftConverter, "shift")
register_converter(OrderVenueConverter, "order_venue")
register_converter(OrderConverter, "order")
urlpatterns = [
path... |
#!/usr/bin/env python
import mock
import pytest
import requests
import requests_mock
from yaml import load, SafeLoader
import cachet_url_monitor.exceptions
import cachet_url_monitor.status
from cachet_url_monitor.webhook import Webhook
from cachet_url_monitor.configuration import Configuration
import os
@pytest.fix... |
# Author: hys
import math
import torch
from torch import nn
import torch.nn.functional as F
class Conv1dStaticSamePadding(nn.Module):
"""
modified by hys
"""
def __init__(self, in_channels, out_channels, kernel_size, stride=1, bias=False, groups=1, dilation=1, **kwargs):
super().__init__()
... |
'''https://practice.geeksforgeeks.org/problems/largest-number-in-k-swaps-1587115620/1
Largest number in K swaps
Medium Accuracy: 46.92% Submissions: 26080 Points: 4
Given a number K and string str of digits denoting a positive integer, build the largest number possible by performing swap operations on the digits of st... |
from subprocess import PIPE, run as s_run
from time import sleep
from panel.models import Messages, GeneralSettings
from datetime import datetime
from re import search as search_regex
from django.contrib import messages
from os import remove
from paramiko import RSAKey
from io import StringIO
from django.conf import se... |
import unittest
from logger import Logger, SeverityType
from test import TestPolicy
class TestLoggerMethods(unittest.TestCase):
def test_logger_init(self):
print("TEST_LOGGER_INIT Unit Test")
print("\tAssert Logger.__init__ functions.")
try:
logger = Logger(TestPolicy())
... |
import ctypes
import os.path as osp
import numpy as np
import tensorrt as trt
from .globals import dir_path
ctypes.CDLL(osp.join(dir_path, 'libamirstan_plugin.so'))
def create_batchednms_plugin(layer_name,
scoreThreshold,
iouThreshold,
... |
from typing import List
class Solution:
def minimumTotal(self, triangle: List[List[int]]) -> int:
if not triangle:
return 0
dp = [0 for _ in triangle[-1]]
dp[0] = triangle[0][0]
print(dp)
for level in triangle[1:]:
dp[len(level) - 1] = dp[len(level)... |
import os
def insert_ones(y, segment_end_ms, Ty=1375):
"""
Update the label vector y. The labels of the 50 output steps strictly after the end of the segment
should be set to 1. By strictly we mean that the label of segment_end_y should be 0 while, the
50 followinf labels should be ones.
Argumen... |
from ..remote import RemoteModel
class DeviceViewerBridgeDomainsGridRemote(RemoteModel):
"""
| ``id:`` none
| ``attribute type:`` string
| ``tenant_name:`` none
| ``attribute type:`` string
| ``tenant_dn:`` none
| ``attribute type:`` string
| ``bridge_domain:`` none
| ... |
import socket
import select
import errno
class SerialTCPConnection:
"""
A TCP socket API to match the pyserial API
"""
def __init__(self, address, port, timeout=None):
self._recvBuffer = []
self._port = port
self._recvTimeout = timeout
self._in_waiting = 0
self... |
# Copyright (c) 2016-2017 Enproduktion GmbH & Laber's Lab e.U. (FN 394440i, Austria)
# 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 rig... |
# -*- coding: utf-8 -*-
"""Generating Keywords for Google Ads.ipynb
Automatically generated by Colaboratory.
Original file is located at
https://colab.research.google.com/github/Suraj-Patro/ads_keywords_generator/blob/main/Generating_Keywords_for_Google_Ads.ipynb
## 1. The brief
<p>Imagine working for a digital ... |
# Copyright 2015 Hewlett-Packard Corporation
# All Rights Reserved.
#
# 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
#
# Unle... |
# Copyright (c) 2019 Tradeshift
# Copyright (c) 2020 Fellow Consulting AG
#
# 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 u... |
from pydantic import BaseModel
from typing import Optional
from ..helpers import ModificationContext
from .pose import Pose
from .velocity import Velocity
class RobotShape(BaseModel):
outline: list[tuple[float, float]] = [(-0.5, -0.5), (0.5, -0.5), (0.75, 0), (0.5, 0.5), (-0.5, 0.5)]
height: float = 0.5
cla... |
import sys
import time
from scapy.all import *
sendp(Ether(dst='08:00:27:00:44:72')/IP(dst='192.168.33.10')/TCP(dport=8888), iface='eth1')
def receive(packet):
p = packet[0][1]
if p.src == '192.168.33.10' and p.load == 'expired':
sys.exit(1)
sniff(filter='tcp', prn=receive, timeout=12, iface='eth1')
... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('api', '0098_userpreferences_default_tab'),
]
operations = [
migrations.AddField(
... |
# encoding: utf-8
"""Polynomial networks for regression and classification."""
# Author: Vlad Niculae <vlad@vene.ro>
# License: Simplified BSD
import warnings
from abc import ABCMeta, abstractmethod
import numpy as np
from sklearn.preprocessing import add_dummy_feature
from sklearn.utils import check_random_state
f... |
from sklearn.metrics import roc_auc_score, roc_curve, confusion_matrix, average_precision_score, auc, accuracy_score
import numpy as np
import torch
import pandas as pd
from datetime import datetime
import matplotlib.pyplot as plt
import seaborn as sn
import os.path as path
def l1_regularizer(model, lambda_l1=0.01):
... |
import dearpygui.dearpygui as dpg
import os
from Waypoints import Waypoints
from modules import *
from modules.CaveBot import CaveBot
from modules.Healing import Healing
from modules.Utils import Utils
import asyncio
from modules.AttackSpells import AttackSpells
# Create Objects
healing = Healing()
utils = Utils()
cav... |
import re
import serial
import glob
from warnings import warn
from panoptes.pocs.focuser.serial import AbstractSerialFocuser
from panoptes.utils import error
# Birger adaptor serial numbers should be 5 digits
serial_number_pattern = re.compile(r'^\d{5}$')
# Error codes should be 'ERR' followed by 1-2 digits
error_pa... |
"""Presets for end-to-end model training for special tasks."""
__all__ = [
"common_metric_gpu",
"utils_gpu"
]
|
from __future__ import absolute_import
import os
from zope import interface
from twisted.python import usage, reflect, threadpool, filepath
from twisted import plugin
from twisted.application import service, strports, internet
from twisted.web import wsgi, server, static, resource
from twisted.internet import reacto... |
import autoarray.plot as aplt
import numpy as np
aplt.line(
y=np.array([1.0, 2.0, 3.0]), x=np.array([0.5, 1.0, 1.5]), vertical_lines=[1.0, 2.0]
)
aplt.line(
y=np.array([1.0, 2.0, 3.0]),
x=np.array([0.5, 1.0, 1.5]),
vertical_lines=[1.0, 2.0],
vertical_line_labels=["line1", "line2"],
)
aplt.line(
... |
import io
from . import chunked_data_stream as chunky
from splunklib.searchcommands import StreamingCommand, Configuration
def test_simple_streaming_command():
@Configuration()
class TestStreamingCommand(StreamingCommand):
def stream(self, records):
for record in records:
... |
import setuptools
with open("README.md", "r") as fh:
long_description = fh.read()
setuptools.setup(
name="pyconquest", # This is the name of the package
version="0.0.7", # The release version
author="René Monshouwer", # Full name of the a... |
#Copyright ReportLab Europe Ltd. 2000-2004
#see license.txt for license details
#history http://www.reportlab.co.uk/cgi-bin/viewcvs.cgi/public/reportlab/trunk/reportlab/pdfbase/cidfonts.py
#$Header $
__version__=''' $Id: cidfonts.py 3710 2010-05-14 16:00:58Z rgbecker $ '''
__doc__="""CID (Asian multi-byte) font su... |
# -*- coding: utf-8 -*-
import logging
import numpy as np
import math
from sklearn.neighbors import KernelDensity
from sklearn.metrics import roc_auc_score
from sklearn.ensemble import RandomForestClassifier, RandomForestRegressor
from dku_data_drift.preprocessing import Preprocessor
from dku_data_drift.model_drift_con... |
#!/usr/bin/python
# -*- coding:utf-8 -*-
import telnetlib
def do_telnet(Host, username, password, finish, commands):
tn = telnetlib.Telnet(Host, port=23, timeout=10)
tn.set_debuglevel(2)
tn.read_until('login:')
tn.write(username + '\n')
tn.read_until('password:')
tn.write(password + '\n')
... |
print("фыввфыфыв")
#здесь был я (Nikikita62344)
#здесь был алмазик |
import argparse
import os
import random
import sys
import time
from datetime import timedelta
import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim
from torchvision import datasets, transforms
from model import PipelineParallelResNet50
from schedule import (initialize_global_args, is_pipel... |
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