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# --------------------------------------------------------------------------- #
# Network in Network, ICML2014, https://arxiv.org/abs/1312.4400
# pytorch implementation by Haiyang Liu (haiyangliu1997@gmail.com)
# --------------------------------------------------------------------------- #
import torch
import torch.n... |
import math
n,m=[int(x) for x in raw_input().split(" ")]
listA=[int(x) for x in raw_input().split(" ")]
listM=[]
for i in range(m):
listM.append([int(x) for x in raw_input().split(" ")])
sum=0
Phi=(1+math.sqrt(5))/2.0
phi=(1-math.sqrt(5))/2.0
diff=Phi-phi
def NthFib(x):
return int((math.pow(Phi,x) - math.pow(phi,x))... |
import csv
import re
from Levenshtein import distance
from .itm2utm import itm2geo
L_FACTOR = 3
F_CENTRES = ('datasets/Centres_of_Population_-_OSi_'
'National_Placenames_Gazetteer.csv')
F_TOWNLANDS = ('datasets/Townlands_-_OSi_'
'National_Placenames_Gazetteer.csv')
F_COUNTIES = ('datasets/... |
# 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
# d... |
#!/usr/bin/env python
#-*- coding:utf-8 -*-
import re
# 除外文字列の集合
exclude_words = set()
def split_space(text):
'''
指定したテキストから単語を抽出します
@param text: unicode
@return: iter
'''
words = re.split(u"\s+", text.strip())
for word in words:
if word not in exclude_words:
yiel... |
train_results_root_folder = "/change_this_placeholder_folder" # For example "/Users/your-user/train-results"
trained_using_aws_spot_instance = False |
r"""
Utilities (:mod:`meshless.utils`)
=================================
"""
import numpy as np
def area_of_polygon(x, y):
"""Area of an arbitrary 2D polygon given its vertices
"""
area = 0.0
for i in range(-1, len(x)-1):
area += x[i] * (y[i+1] - y[i-1])
return abs(area) / 2.0
def unitvec... |
import unittest
import json
from .common import ApiTestBase, compat_mock
class CollectionsTests(ApiTestBase):
"""Tests for CollectionsEndpointsMixin."""
@staticmethod
def init_all(api):
return [
{
'name': 'test_create_collection',
'test': CollectionsTe... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
]
operations = [
migrations.CreateModel(
name='Cidade',
fields=[
('id', models.AutoField(verbo... |
#!/usr/bin/env /data/mta/Script/Python3.8/envs/ska3-shiny/bin/python
#################################################################################################
# #
# find_cron_records.py:reads cron job file and find ... |
def bubble(lst):
length = len(lst) - 1
result = []
no_swap = False
while not no_swap:
no_swap = True
for a in range(length):
if lst[a] > lst[a + 1]:
lst[a], lst[a + 1] = lst[a + 1], lst[a]
result.append(list(lst))
no_swap = Fals... |
# Copyright 2022 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from __future__ import annotations
from textwrap import dedent # noqa: PNT20
from pants.backend.helm.util_rules.chart_metadata import DEFAULT_API_VERSION, ChartType
def gen_chart_file... |
name=[]
age=[]
gender=[]
location=[]
flag=0
no= int(input("Enter number of customers :"))
for i in range(no):
n=input("Enter name : ")
name.append(n)
a=input("Enter age : ")
age.append(a)
g=input("Enter gender : ")
gender.append(g)
l=input("Enter location : ")
loc... |
import numpy as np
import tensorflow as tf
from tf_util.tf_util import get_array_str
import dsn.util.tf_integrals as tfi
from dsn.util.tf_langevin import bounded_langevin_dyn, bounded_langevin_dyn_np
import dsn.util.np_integrals as npi
import os
DTYPE = tf.float64
def rank1_spont_static_solve(
mu_init, delta_0_i... |
from city import City
from population import Population
from tour import Tour
from tour_manager import TourManager
import algorithm
def parse_args():
import argparse
parser = argparse.ArgumentParser(description='Using Genetic Algorithm to solve Traveling Salesman Problem.')
parser.add_argument('... |
import cv2 as cv
import numpy as np
def nothing(position):
print(position)
img = np.zeros((300, 512, 3), np.uint8)
cv.namedWindow('image')
cv.createTrackbar('B', 'image', 0, 255, nothing)
cv.createTrackbar('G', 'image', 0, 255, nothing)
cv.createTrackbar('R', 'image', 0, 255, nothing)
switch = '0 : OFF\n 1 : ... |
from flask import render_template, request
from app import app
import flask_mobility.decorators as mobdec
from scriptMaps import n1_MapaclassMaxPB
from scriptDivCompare import Compareclass
from scriptPacotes import n1_PacotesclassMaxPB
from pprint import pprint
from dbmongo import *
from datetime import *
import time
... |
import solver
from ..translators.caesartranslator import *
from ..keygenerators.numberkeygenerator import *
from ..keygenerators.keygenerator import *
from ..scorers.czechscorer import *
class BruteForceSolver(solver.Solver):
"""Tries out all possible solutions"""
def __init__(self, keyGenerator=NumberKeyGenerator(... |
# -*- coding: utf-8 -*-
#
# Copyright (c) 2012, Clément MATHIEU
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, thi... |
# -*- encoding:utf-8 -*-
# __author__=='Gan'
# In a forest, each rabbit has some color. Some subset of rabbits (possibly all of them) tell you how many other
# rabbits have the same color as them. Those answers are placed in an array.
# Return the minimum number of rabbits that could be in the forest.
# Examples:
# In... |
name =1
age =1
name = 2
age =2
|
import torch
from torch import nn
from torch.nn import functional as F
class ResBlk(nn.Module):
"""
resnet block
"""
def __init__(self, ch_in, ch_out, stride=1):
super(ResBlk, self).__init__()
self.conv1 = nn.Conv2d(ch_in, ch_out, kernel_size=3, stride=stride, padding=1)
self... |
import unittest
import best_travel as b
class BestTravelTest(unittest.TestCase):
def test_best_sum(self):
self.assertEqual(b.choose_best_sum([50, 55, 57, 58, 60], 3, 174), [55,58,60])
|
#!/usr/bin/env python3
# Copyright (c) 2021 Mahdi Biparva, mahdi.biparva@gmail.com
# miTorch: Medical Imaging with PyTorch
# Deep Learning Package for 3D medical imaging in PyTorch
# Implemented by Mahdi Biparva, April 2021
# Brain Imaging Lab, Sunnybrook Research Institute (SRI)
import os
import time
... |
import os
import re
dirpath = os.getcwd()
dirpath+='/'
chr_names=['chr1','chr2','chr3','chr4',
'chr5','chr6','chr7','chr8',
'chr9','chr10','chr11','chr12',
'chr13','chr14','chr15','chr16',
'chr17','chr18','chr19','chr20',
'chr21','chr22','chrX','chrY']
outp=open(... |
#!/usr/bin/env python
import re
import os
import time
import hashlib
orig_text = open('pf.scala').read()
def compute_tempvalue(prog_text):
digest = hashlib.sha1(prog_text).hexdigest()
tempvalue = hashlib.sha1('42' + digest).hexdigest()
return tempvalue
for x in range(10000, 99999):
new_text = re.su... |
from itertools import combinations
import pandas as pd
from sklearn.preprocessing import (PolynomialFeatures, OneHotEncoder,
StandardScaler)
def onehot_conversion(X_cat, model=None):
if model:
X_onehot = pd.DataFrame(model.transform(X_cat),
... |
from . import inline
|
EnsureSConsVersion(1,2)
import os
import sys
import inspect
import platform
import re
import subprocess
from SCons import SConf
def getTools():
result = []
if os.name == 'nt':
result = ['nvcc', 'default', 'msvc']
elif os.name == 'posix':
result = [ 'nvcc', 'default','g++']
else:
... |
from django.core.cache import cache, get_cache
cachekey_usr_session_profix = 'usr_session_'#roleid
class cache:
@staticmethod
def loc_setValue(key, val):
"""
set local memery cache.
"""
c = get_cache('in_memery')
c.set(key, val)
@staticmethod
def loc_getValue(key):
"""
get local memery cache.
... |
# I pledge my honor that I have abided by the Stevens Honor System.
# Jeffrey Eng
def sum(p):
total = 0
for i in p:
total += float(i)
return total
def main():
numbers = input("Enter a list of numbers separated by spaces: ")
x = numbers.split()
print("The sum is", sum(x))
main()
|
import os
import math
from work.models import Site, ShiftedQty, ProgressQty, SurveyQty, ShiftedQtyExtra, ProgressQtyExtra, SiteExtra, DprQty, Log, Resolution, ResolutionLink, Log, Loa
import pandas as pd
from work.data import DISTRICTS_ALLOWED, DIVISIONS_ALLOWED, PROGRESS_QFIELDS, SURVEY_QFIELDS, REVIEW_QFIELDS, DPR_IN... |
from itertools import groupby
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 15 12:04:27 2019
@author: CNEA
"""
class MATERIAL(object):
_KEY__ = ''
_NUM__ = None
_TYPE__ = 'MATERIAL'
def __init__(self, *args, **kwargs):
self._NUM__ = args
self._KEY__ = kwargs['KEY']
def string(... |
#### Class 03
#### Reading and writing files
## Reading text files ------------------------------------------------
import sys
import os
os.chdir("C:/Users/wooki/Documents/GitHub/pythoncourse2018/day04")
## Read all lines as one string
with open('test_readfile.txt') as f:
the_whole_thing = f.read()
print the_who... |
import numpy as np
import math
class Pegasos(object):
"""docstring for Pegasos"""
def __init__(self, reg, k, maxiter = 1000000, X=None, Y=None, check = False ):
super(Pegasos, self).__init__()
self.reg = reg
self.k = k
self.W = None
self.iteration = 2
self.maxiter = maxiter
self.X = X
self.Y = Y
s... |
import time
x=int(input("Please enter the first number :"))
y=int(input("Please enter the second number :"))
i=1
factorsof_x=set()
factorsof_y=set()
for i in range(1,x+1):
if x%i==0:
factorsof_x.add(i)
print("Calculating factors of",x,"...")
time.sleep(1)
print(factorsof_x)
for i in range(1,y+1):
if y... |
import numpy as np
import logging
from omegaconf import DictConfig
import torch
import torch.nn.functional as F
from torch.utils.data import IterableDataset
from torch.nn.utils.rnn import pad_sequence
from transformers import AutoTokenizer
from typing import Dict, Tuple
logger = logging.getLogger(__name__)
# pylint:d... |
import pandas as pd
import numpy as np
df = pd.read_csv('../dataset/googleplaystore.csv')
df['new'] = pd.to_datetime(df['Last Updated'])
df['lastupdate'] = (df['new'] - df['new'].max()).dt.days
df.to_csv('../dataset/pre-processed/lastUpdated.csv') |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
__mtime__ = '2019/5/5'
from selenium import webdriver
from time import sleep
import unittest
class Login(unittest.TestCase):
'''
禅道登录
'''
@classmethod
def setUpClass(cls):
cls.driver = webdriver.Firefox()
def setUp(self):
self.dri... |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.contrib import admin
from models import *
# Register your models here.
admin.site.register(Movie)
admin.site.register(Keyword)
admin.site.register(Actor)
admin.site.register(UserMovie)
|
from Pyskell.Language.PyskellTypeSystem.TypeSignature import *
from Pyskell.Language.PyskellTypeSystem.TypedFunction import *
from Pyskell.Language.PyskellTypeSystem.AlgebraicDataType import *
from Pyskell.Language.PyskellTypeSystem.TypeClass import *
from Pyskell.Language.PyskellTypeSystem.PatternMatching import *
|
from app.models.article import Tags
async def create_tag(name: str):
return await Tags.objects.create(name=name)
async def get_tags():
return await Tags.objects.all()
|
#!/usr/bin/env python
"""
This uses the spotify web API to get analysis data for the track.
The analysis is used to create a "smart fast forward" that advances
to sections of the song (n-key).
It also uses the analysis data to send note data over OSC to a synthesizer
creating a very strange sort of automatic accompian... |
# -*- coding: utf-8 -*-
class Solution:
def wordBreak(self, s, wordDict):
if not s:
return True
wordSet = set(wordDict)
result = [False] * (len(s) + 1)
for i in range(len(s) + 1):
if not result[i] and s[: i + 1] in wordSet:
result[i] = True... |
# Copyright 2021 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).
from pants.backend.python.target_types import (
PythonRequirementFindLinksField,
PythonRequirementModulesField,
PythonRequirementResolveField,
PythonRequirementsField,
... |
import gpt_2_simple as gpt2
import pandas as pd
from tqdm import tqdm
import os
input_data_file = './data/2-quotes_filtered.csv'
output_folder = "output/"
split_quotes = pd.read_csv(input_data_file)
print(split_quotes.head())
## These were the top 20 most common topics in the dataset
topics_to_keep = ['life', 'love'... |
# -*-coding: utf-8-*-
import numpy as np
'''将文件中的数据读取至矩阵'''
def openFile(filename):
file_object = open(filename)
fileContext = file_object.readlines()
tempData = np.array(fileContext)
# print tempData
size = tempData.size
# print size
data = np.zeros([size, 5], dtype=basestring)
for i ... |
import pyrealsense2 as rs
import numpy as np
import cv2
import open3d as o3d
from floodfill import Grid
import scipy
import matplotlib.pyplot as plt
import time
from tracking import processObjects
NUMBER_OF_OBJECTS = 100
MAX_DIST = 0.5
config_perception = {
"IMAGE_WIDTH":640,
"IMAGE_HEIGHT":480,
... |
# -*- coding: utf-8 -*-
A=int(input())
list=['программист','программиста', 'программистов']
iA = A % 100
if iA >=9 and iA <=20:
print(str(A) + " " + list[2])
else:
iA = iA % 10
if iA == 1:
print(str(A) + " " + list[0])
elif iA > 1 and iA < 5:
print(str(A) + " " + list[1])
else:
... |
import unittest
from expense import Expense
class TestCategoryIncome(unittest.TestCase):
def setUp(self):
self.expense = Expense(10, 'Food', '12-12-1234')
def test_str(self):
self.assertEqual(str(self.expense), '10$ - Food - 12-12-1234 - Expense')
def test_repr(self):
self.assert... |
from xml.etree import ElementTree as et
import os
from sys import exit
from time import sleep
import traceback as trace
def main():
for filename in os.listdir(path=os.getcwd() + "\\xml"):
if filename.endswith(".xml"):
root = et.parse("xml/" + filename).getroot()
for elemen... |
# -*- coding: utf-8 -*-
import math
import numpy as np
from numpy import array
from operator import add
from regions import *
################################################################################
############################### Vertices buffer ################################
############################... |
from waitress import serve
from newProject.wsgi import application
if __name__ == '__main__':
serve(application, host = 'localhost', port='8080') |
"""This contains all of the model filters for the Ghostwriter application."""
import django_filters
from django import forms
from .models import Client
class ClientFilter(django_filters.FilterSet):
"""Filter used to search the `Client` model."""
name = django_filters.CharFilter(lookup_expr='icontains')
... |
# preprocessing for machine learning
import numpy as np
import pandas as pd
import pickle
def process_data_for_labels(ticker):
hm_days = 7
df = pd.read_csv('sp500_joined_closes.csv', index_col=0)
tickers = df.columns.values.tolist()
df.fillna(0, inplace=True)
for i in range(1, hm_days+1):
... |
import numpy as np
import h5py
input_lm_files = ['_prerun_result.lm']
output_figfile_prefix = "Pre"
output_figfile_dir = 'figs'
## Offscreen rendering
# mlab.options.offscreen = True
## Define molecules and volume
cyt = 1
NA = 6.022e23
f = h5py.File(input_lm_files[0],'r')
data = f['Model']['Diffusion']['Latti... |
# coding: utf-8
# Part of PIT Solutions AG. See LICENSE file for full copyright and licensing details.
import datetime
import logging
from odoo import fields, models, api, _
from odoo.tools import DEFAULT_SERVER_DATETIME_FORMAT
_logger = logging.getLogger(__name__)
EXCEPTION_LOG_TYPE = {
('red', _("Danger")),
... |
# Generated by Django 3.1.3 on 2021-01-04 14:30
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('users', '0011_booking_service'),
]
operations = [
migrations.AlterField(
model_name='booking',
name='date',
... |
# _______________________________________________
## Introduction
# _______________________________________________
# Creating a prognostic model from Wisconsin Breast Cancer Data
# by Victor Wan
# Desc: Visualising Breast Cancer Wisconsin data and creating a predictive model based on nuclear features
# Importing lib... |
#__init__ constructor yapıcı metot
class Personel:
isim = ""
soyisim = ""
yas = 0
def __str__(self):
return "{} {}".format(self.isim,self.soyisim)
def __init__(self, firstname, lastname, age):
self.isim = firstname
self.soyisim = lastname
self.yas = age
# ... |
import tkinter as tk
from tkinter import messagebox
class Application(tk.Frame):
def __init__(self,master=None):
super().__init__(master)
self.master=master
self.pack()
self.createWidget()
def createWidget(self):
self.btn01= tk.Button(self,text='insert point',command=self... |
import os
import math
import logging
import time
import pickle
import pandas as pd
import numpy as np
import datetime
from pygooglenews import GoogleNews
import nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
def tanh(x):
t=(np.exp(x)-np.exp(-x))/(np.exp(x)+np.exp(-x))
return t
def get_sta... |
def sort_me(lst):
lst.sort(key=lambda a: str(a)[-1])
return lst
# return sorted(key=lambda a: str(a)[-1])
|
import sys
import requests
from datetime import datetime
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.ext.automap import automap_base
from sqlalchemy.orm import sessionmaker
engine = create_engine('postgresql+psycopg2://likit@localhost/research_dev')
Base... |
"""
orignal author: Andreas Rene Geist
email: andreas.geist@tuhh.de
website: https://github.com/AndReGeist
license: BSD
addition and modification of file by Patrick Phillips summer 2019
email: pphill10@u.rochester.edu
website: https://github.com/peweetheman
"""
import time
# import resource
import os
import numpy as n... |
from django.db import models
from django.urls import reverse
class Roaster(models.Model):
name = models.CharField(max_length=120)
city = models.CharField(max_length=120)
country = models.CharField(max_length=120)
website = models.CharField(max_length=120)
def get_absolute_url(self):
return reverse("roasters:ro... |
def reverse(self):
llist = self.__reverse_recursive(self.begin)
llist.next = None
self.begin, self.tail = self.tail, llist
def __reverse_recursive(self, curr):
if curr.next == None:
return curr
else:
node = self.__reverse_recursive(curr.next)
... |
# /*
# Copyright 2011, Lightbox Technologies, Inc
#
# 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 b... |
t = int(input())
while t > 0:
a,b,c,d = map(int,input().split())
x,y,x1,y1,x2,y2 = map(int,input().split())
x = x + (b - a)
y = y + (d - c)
if abs(a + b) > 0 and x1 == x2:
print("NO")
elif abs(c + d) > 0 and y1 == y2:
print("NO")
elif x1 <= x <= x2 and y1 <= y <= y2... |
import sqlite3
conexion = sqlite3.connect("Tienda de mascotas")
puntero = conexion.cursor()
###########################################
"""
puntero.execute('''
CREATE TABLE MASCOTA(
ID_MASCOTA INTEGER PRIMARY KEY AUTOINCREMENT,
NOMBRE VARCHAR(10),
PESO INTEGER)
''')
"""
"""
puntero.execute('INSERT INTO MASCOTA VA... |
#modified maka package from https://github.com/gfhuertac/maka
import os
import sys
import json
from os.path import join, dirname
from random import randint
from queue import Queue
from threading import Thread
from time import sleep
from dotenv import load_dotenv
from optparse import IndentedHelpFormatter, OptionGroup,... |
#!/usr/bin/env python3
import hanlp, re #, pdb
from .ret_semantics import analyze_ret
from .causal_semantics import analyze_causal
from .arg_semantics import analyze_arg_pre, analyze_arg_post
'''
dependency labels: https://universaldependencies.org/u/dep/
pos labels: https://universaldependencies.org/u/pos/
'''
HanLP... |
from appium.webdriver.webdriver import WebDriver
class Page(object):
""" Base Class for all pageobject classes. """
def __init__(self, driver: WebDriver):
self.driver = driver
def set_driver(self, driver: WebDriver):
""" Set class attribute driver with the input WebDriver element
... |
from pandac.PandaModules import loadPrcFileData # loading prc files
loadPrcFileData("", "framebuffer-multisample 1")
loadPrcFileData("", "multisamples 1")
#loadPrcFileData("", "fullscreen #t")
#loadPrcFileData("", "window-resolution x y")
# global python imports
import math, sys, random
#------------------------... |
from django.shortcuts import get_object_or_404, render
from django.http import HttpResponseRedirect
from django.template import loader
from django.urls import reverse
from django.views import generic
class IndexView(generic.ListView):
template_name = 'typo/index.html'
def get_queryset(self):
... |
import tensorflow.keras as keras
import tensorflow as tf
import pandas
tf.random.set_seed(1)
dataframe = pandas.read_csv("data/breast-cancer/data.csv", index_col="id")
y = dataframe.diagnosis
x = dataframe.drop("diagnosis", 1)
print(x.shape)
model = keras.Sequential([
keras.layers.Dense(25, input_shape=(x.shape... |
#!/usr/bin/env pybricks-micropython
from pybricks.hubs import EV3Brick
from pybricks.ev3devices import ColorSensor
from pybricks.parameters import Port, Color
ev3 = EV3Brick()
colourLeft = ColorSensor(Port.S2)
steering_drive = steering.drive(Motor(Port.B), Motor(Port.C))
def testing_blackline (correction, speed):
... |
import jsonfield
from django.utils import timezone
from django.utils.translation import ugettext_lazy as _
from django.db import models
# Create your models here.
TIME_UNIT_SELECTION = (
('0', 'Hours'),
('1', 'Days')
)
# COMPLEXITY_SELECTION = (
# ('0', '1'),
# ('1', '2'),
# ('2', '3'),
# ... |
#coding:utf-8
#!/usr/bin/env python
from gclib.facility import facility
from gclib.utility import currentTime, is_same_day, randint
from game.utility.config import config
from game.utility.email import email
class infection_arena(facility):
def __init__(self):
"""
初始化
"""
facility.__init__(self)
self.b... |
locators= {
'url':'https://qa-pro.domclick.ru/',
'Шапка':{'Войти в шапке': ['[class^="js-topline-auth-button-text topline__icon-link__text"]', 0]
},
'Лендинг':{
'Кнопка Зарегистрироваться': ['[class^="ui bulky green button head-button js-signup"]', 0],
'Смотреть видео': ['... |
# -*- coding: utf-8 -*-
# flake8: noqa
# Model changes with django-simple-history 1.5.4
from __future__ import unicode_literals
from django.db import models, migrations
import django.db.models.deletion
from django.conf import settings
class Migration(migrations.Migration):
dependencies = [
('webplatform... |
from django.contrib import admin
from .models import Stock, Company, Excel # .models is models file in current directory
# Register your models here.
admin.site.register(Excel)
admin.site.register(Company)
admin.site.register(Stock)
|
import numpy as np
# シグモイド関数
def sigmoid(x):
return 1.0/(1.0+np.exp(-x))
# シグモイド関数の微分形
def sigmoid_grad(x):
return (1.0 - sigmoid(x)) * sigmoid(x)
# ステップ関数
def step(x):
y = x > 0
return y.astype(np.int)
# Relu関数
def relu(x):
return np.max(0, x)
# 恒等関数
def identity(x):
return x
# オーバーフロー... |
"""
CCT 建模优化代码
GPU 加速示例(3)
作者：赵润晓
日期：2021年5月6日
"""
# 因为要使用父目录的 cctpy 所以加入
from os import error, path
import sys
sys.path.append(path.dirname(path.abspath(path.dirname(__file__))))
from hust_sc_gantry import HUST_SC_GANTRY
from cctpy import *
ga32 = GPU_ACCELERATOR(float_number_type=GPU_ACCELERATOR.FLOAT32)
ga64 = GP... |
import wx, yaml
import wx.lib.scrolledpanel as scrolled
from passlib.hash import sha256_crypt
import collections
from collections import OrderedDict
import serial, glob, sys
import time
import struct
class PasswordSettings(wx.Frame):
def __init__(self, config, config_file_name):
wx.Frame.__init__(sel... |
#! -*- coding: utf-8 -*-
from libs.pontovitoria import PontoVitoria
from linhas import Linha
class RotaIndireta():
def __init__(self, p1,p2, l1,l2, pontos_intersecao):
self.l1 = l1
self.l2 = l2
self.p1 = p1
self.p2 = p2
self.pontos_intersecao = pontos_intersecao
self... |
"""
Pooja would like to withdraw X $US from an ATM. The cash machine will only accept the transaction if X is a multiple of 5, and Pooja's account balance has enough cash to perform the withdrawal transaction (including bank charges). For each successful withdrawal the bank charges 0.50 $US. Calculate Pooja's account b... |
import os
def repo_exists(repo):
os.chdir(f"D:\\MyProjects\\Python Projects")
return os.path.isdir(repo)
def check_status(repo):
os.chdir(f"D:\\MyProjects\\Python Projects\\{repo}")
os.system("git status")
os.chdir(f"D:\\MyProjects\\Python Projects")
def delete_local_repo(repo):
os.chdir("... |
# -*- coding: utf-8 -*-
import json, base64, traceback, logging
import inject, psycopg2
import pytz, datetime
import dateutil.parser
import uuid
import pytz
from model.systems.assistance.date import Date
from model.systems.issue.issue import Issue
class IssueModel:
issue = inject.attr(Issue)
'''
'... |
'''
Given a string, compute recursively (no loops) a new string where all the lowercase 'x' chars have been changed to 'y' chars.
'''
def replaceX (str):
print 'input:',str
if len(str) == 0:
return str
if len(str) == 1 and str == 'x':
return 'y'
elif len(str) == 1 and str != 'x':
return ... |
#!/usr/bin/env python2
#
# Copyright 2017-present Open Networking Foundation
#
# 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 requi... |
from django.shortcuts import render, redirect,HttpResponseRedirect
from .forms import RegisterForm
from users.models import Resulttable,Insertposter
from django.db import models
def register(request):
# 只有当请求为 POST 时，才表示用户提交了注册信息
if request.method == 'POST':
form = RegisterForm(request.POST)
#... |
"""
https://leetcode.com/problems/jump-game-vi/
You are given a 0-indexed integer array nums and an integer k.
You are initially standing at index 0. In one move, you can jump at most k steps forward without going outside the boundaries of the array. That is, you can jump from index i to any index in the range [i + 1... |
import math
import os
import random
import re
import sys
#
# Complete the 'nonDivisibleSubset' function below.
#
# The function is expected to return an INTEGER.
# The function accepts following parameters:
# 1. INTEGER k
# 2. INTEGER_ARRAY s
#
def nonDivisibleSubset(k, s):
# Write your code here
# Cre... |
from re import compile, match
REGEX = compile(r'((25[0-5]|2[0-4]\d|1\d\d|[1-9]\d|\d)\.){3}'
r'(25[0-5]|2[0-4]\d|1\d\d|[1-9]\d|\d)$')
def is_valid_IP(strng):
""" is_valid_ip == PEP8 (forced mixedCase by CodeWars) """
return bool(match(REGEX, strng))
|
#
# Copyright © 2021 Uncharted Software Inc.
#
# 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 l... |
from baselines import main
from dp_utils import get_noise_mul, get_renyi_divergence
MAX_GRAD_NORM = 0.1
MAX_EPS = 5
BATCH_SIZES = [512, 1024, 2048, 4096, 8192, 16384]
BASE_LRS = [0.125, 0.25, 0.5, 1.0]
TARGET_EPS = 3
TARGET_EPOCHS = [30, 60, 120]
BN_MULS = [6, 8]
GROUPS = [9, 27, 81]
for target_epoch in TARGET_EP... |
# Generated by Django 2.0.3 on 2018-04-08 10:41
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('recipes', '0004_auto_20180407_1005'),
]
operations = [
migrations.AlterField(
model_name='medic... |
#!/usr/bin/env python
# coding: utf-8
import os
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import torch
import core.transforms as T
from utils.plot_utils import plot_single_image
from datasets.coco_to_pd import read_coco_classes
from torchvision.models.detection.faster_rcnn import fast... |
import multiprocessing
import argparse
import pprint
import sys
#=========1=========2=========3=========4=========5=========6=========7=
def load_arguments():
argparser = argparse.ArgumentParser(sys.argv[0])
argparser.add_argument('--dataset_path',
type=str,
default='')
argparser.... |
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