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import time, os import numpy as np import json
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import carpeta8 # bloque principal lista=carpeta8.cargar() carpeta8.imprimir(lista) carpeta8.ordenar(lista) carpeta8.imprimir(lista)
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import re from mediaRename.constants import constants as CONST def cleanReplace(data): """ Takes each dict object and clean :param data: dict object :return: none """ dataIn = data["files"] # (regX, replaceSTR) cleanPasses = [(CONST.CLEAN_PASSONE, ""), (CONST.CLEAN_PASSTWO, ""), ...
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# Copyright (c) 2019 MindAffect B.V. # Author: Jason Farquhar <jason@mindaffect.nl> # This file is part of pymindaffectBCI <https://github.com/mindaffect/pymindaffectBCI>. # # pymindaffectBCI is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published b...
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a = [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] b = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13] c = [] for x in a: if x in b: c.append(x) print(c)
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from tensorflow import keras import os import numpy as np import sys import json sys.path.append("/".join(os.path.abspath(__file__).split("/")[:-2])) from model.dataset import utils, test_sampler summary, all_predictions = estimate_model_accuracy( keras.models.load_model("./RMS_model/model.h5") ) print(summary)...
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import torch import torch.nn as nn import torch.nn.functional as F import os import numpy as np from Layer import FeedForwardNetwork from Layer import MultiHeadAttention __author__ = "Serena Khoo"
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import requests import urllib.request import os import pickle import argparse # file read folder path = 'http://db.itkc.or.kr//data/imagedb/BOOK/ITKC_{0}/ITKC_{0}_{1}A/ITKC_{0}_{1}A_{2}{5}_{3}{4}.JPG' # Manual label = ['BT', 'MO'] middle = 1400 last = ['A', 'V'] # A ~400 V ~009 num = 10 num1 = 400 fin = ['A', 'B',...
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"""This module holds the Symbol, ComputationalGraph, and ComputationalGraphNode classes and methods to help construct a computational graph.""" from typing import Optional from .operators import Add, Subtract, Multiply, Divide, Grad, Div, Curl, Laplacian
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# Copyright (c) Microsoft. All rights reserved. # Licensed under the MIT license. See LICENSE file in the project root for # full license information. import datetime import threading import contextlib
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import tkinter as tk from tkinter import messagebox import json # Constants FONT_NAME = "Open Sans" BG_COLOR = "#f9f7f7" FONT_COLOR = "#112d4e" ACCENT = "#dbe2ef" root = tk.Tk() root.title("Money Tracker") root.config(bg=BG_COLOR) root.resizable(0, 0) root.iconbitmap("C:\\Users\\ASUA\\Desktop\\Tests\\MoneyTransactio...
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import requests
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import json import matplotlib import matplotlib.pyplot as plt import numpy as np import os import time if __name__ == "__main__": for directory in os.listdir('./datasets'): if "example" not in directory: save_figs(directory) print("creating statistics done")
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from __future__ import unicode_literals import frappe
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# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed u...
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from PIL import Image import numpy as np # Works when launched from terminal # noinspection PyUnresolvedReferences from k_means import k_means input_image_file = 'lena.jpg' output_image_prefix = 'out_lena' n_clusters = [2, 3, 5] max_iterations = 100 launch_count = 3 main()
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from __future__ import absolute_import from __future__ import division from __future__ import print_function import argparse import tensorflow as tf import yaml from model.dcrnn_supervisor import DCRNNSupervisor if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--confi...
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import torch.optim as optim from torch import nn from data.match_dataset import MatchDataset from torch.utils.data import DataLoader from models.lol_result_model import LOLResultModel import torch if __name__ == '__main__': EPOCH = 50 BATCH_SIZE = 32 loader = DataLoader(MatchDataset('dataset/train_data....
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#!/usr/bin/env python import libtripled, logging, sys, os # CONSTANTS log = logging.getLogger('tripled.cpfromddd') if __name__ == '__main__': logging.basicConfig(level=logging.DEBUG) if len(sys.argv) < 4: print '%s <master> <tripled src> <local dst>' % (sys.argv[0]) exit(-1) tripled = l...
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#!/usr/bin/env python3 # Copyright (c) Meta Platforms, Inc. and affiliates. # All rights reserved. # # This source code is licensed under the BSD-style license found in the # LICENSE file in the root directory of this source tree. from enum import Enum from typing import cast, Dict, List, Optional, Tuple, Union impor...
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from .plugin_loader import manifest from .plugin_manager import PluginManager
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from opytimizer.optimizers.science import HGSO # One should declare a hyperparameters object based # on the desired algorithm that will be used params = { 'n_clusters': 2, 'l1': 0.0005, 'l2': 100, 'l3': 0.001, 'alpha': 1.0, 'beta': 1.0, 'K': 1.0 } # Creates an HGSO optimizer o = HGSO(param...
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"""Image generating architectures. Kyle Roth. 2019-07-10. """
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from django.conf.urls import url from .views import (EmergencyContactCreateView, EmergencyContactUpdateView, EmergencyContactDeleteView, EmergencyContactDetailView, EmergencyContactListView, AdverseEventTypeUpdateView, AdverseEventTypeCreateView, AdverseEventTypeDeleteView, Adve...
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#!/usr/bin/python3 '''Handles all database interactions for qbootstrapper ''' from flask import g from qbflask import app import sqlite3 def connect_db(): '''Connects to the database and returns the connection ''' conn = sqlite3.connect(app.config['DATABASE']) conn.row_factory = sqlite3.Row retur...
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"""Interprets each AST node""" import ast import textwrap from typing import Any, Dict, List def extract_fields(code: str) -> Dict[str, Any]: """Extracts data from code block searching for variables Args: code: the code block to parse """ # Parsing expects that the code have no indentation ...
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#!/usr/bin/env python # -*- coding: utf-8 -*- from runner.koan import *
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params = [int(x) for x in input().split()] point = params[-1] card_numbers = sorted([int(i) for i in input().split()]) max_sum = 0 for i in range(len(card_numbers)): for j in range(i+1, len(card_numbers)): for k in range(j+1, len(card_numbers)): if card_numbers[i] + card_numbers[j] + card_numbe...
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import os import re # from .m.red import readInput data = open("2\\input.txt").read().split('\n') parsedData = [] for x in data: parsedData.append(list(filter(None, re.split("[- :]", x)))) parsedData.pop() count = 0 for x in parsedData: print(x) if(x[3][int(x[0])-1] != x[3][int(x[1])-1] and (...
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#!/usr/bin/env python2.4 """ """ obj = MyClass(6, 7)
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from django.shortcuts import render from django.http import JsonResponse from django.db import connections from django.db.models import Count from django.contrib import admin from visitor.models import Apache import json admin.site.register(Apache) # Create your views here.
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# --- # jupyter: # jupytext: # formats: ipynb,py:percent # text_representation: # extension: .py # format_name: percent # format_version: '1.3' # jupytext_version: 1.13.7 # kernelspec: # display_name: Python 2 # language: python # name: python2 # --- # %% import pandas a...
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import pytest import pyhomogenize as pyh from . import has_dask, requires_dask from . import has_xarray, requires_xarray from . import has_numpy, requires_numpy
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from behave import * from hamcrest import assert_that, equal_to from vec3 import Vec3, vec3 from vec4 import Vec4, point, vector from base import equal, normalize, transform, ray, lighting import numpy as np from shape import material, sphere, test_shape, normal_at, set_transform, intersect, glass_sphere, point_light f...
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#!/usr/bin/env python # 'wordfrequencies.py'. # Chris Shiels. import re import sys if __name__ == "__main__": sys.exit(main(sys.stdin, sys.stdout, sys.stderr, sys.argv[1:]))
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import threading import time import numpy as np from collections import deque
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from django.apps import AppConfig
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""" fetch historical stocks prices """ from tqdm import tqdm import pandas as pd import pandas_datareader as pdr from .base import DataFetcher def get_stock_price(symbol, start, end): """get stock price of a company over a time range Args: symbol (str): ticker symbol of a stock start (datetime...
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from .instruccionAbstracta import InstruccionAbstracta
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# Copyright 2018 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://www.apache.org/licenses/LICENSE-2.0 # # or in the "license...
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# uncompyle6 version 3.7.4 # Python bytecode 3.7 (3394) # Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)] # Embedded file name: T:\InGame\Gameplay\Scripts\Server\postures\posture_tunables.py # Compiled at: 2016-02-19 01:17:07 # Size of source mod 2**32: 2003 byt...
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from . import Log, Move
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from Musician import Musician
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import unittest import numpy as np import fastpli.objects import fastpli.tools if __name__ == '__main__': unittest.main()
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import tensorflow as tf from kerascv.layers.iou_similarity import IOUSimilarity iou_layer = IOUSimilarity()
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import socket import struct IP_BACKUP = '127.0.0.1' PORTA_BACKUP = 5000 ARQUIVO_BACKUP = "/home/aluno-uffs/Documentos/Trab_Final/Atv1-Distribuida/cliente_BACKUP.c" #Recebe o arquivo. sockReceber = socket.socket(socket.AF_INET, socket.SOCK_DGRAM, socket.IPPROTO_UDP) sockReceber.setsockopt(socket.SOL_SOCKET, socket.SO_...
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import numpy as np from matplotlib import pyplot as plt from localpoly.base import LocalPolynomialRegression # simulate data np.random.seed(1) X = np.linspace(-np.pi, np.pi, num=150) y_real = np.sin(X) y = np.random.normal(0, 0.3, len(X)) + y_real # local polynomial regression model = LocalPolynomialRegression(X=X, ...
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## Activation functions from .module import Module from ..utils import functional as F
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from . import spec from typing import ( # noqa: F401 Any, Callable, List, NewType, Tuple, ) from .spec import ( BeaconState, BeaconBlock, )
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""" Copyright 2010 Jason Chu, Dusty Phillips, and Phil Schalm 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 agre...
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import os import sys import boto3 from github import Github SSM_CLIENT = boto3.client("ssm") GITHUB_REPO_NAME = os.environ.get("GITHUB_REPO_NAME", "") PR_NUMBER = os.environ.get("PR_NUMBER", "") FAILED = bool(int(sys.argv[2])) GITHUB_TOKEN = os.environ.get("GITHUB_TOKEN", "") if __name__ == "__main__": repo =...
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from __future__ import annotations from typing import TYPE_CHECKING, Dict, List, Optional, Union from Acquire.Client import Wallet if TYPE_CHECKING: from openghg.dataobjects import SearchResults __all__ = ["Search"]
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# -*- coding: utf-8 -*- """ Copyright 2019 CS Systmes d'Information 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 ...
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import numpy as np from scipy.stats import bernoulli import heapq
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3
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from driver_53x5 import main main(0x5395)
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# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: v2ray.com/core/proxy/vmess/inbound/config.proto from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf i...
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import logging import csv import time from bs4 import BeautifulSoup import requests logging.basicConfig( format='%(asctime)s %(levelname)s:%(message)s', level=logging.INFO) if __name__ == '__main__': print('start up') main() print('all done')
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from asteroid.interp import interp from asteroid.version import VERSION from asteroid.state import state from asteroid.globals import ExpectationError from asteroid.walk import function_return_value from asteroid.support import term2string from sys import stdin import readline
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"""API for eeadm file state.""" from http import HTTPStatus from flask import request from flask_restx import Namespace, Resource, fields from core.eeadm.file_state import EEADM_File_State from ltfsee_globus.auth import token_required api = Namespace( "file_state", description="Get state of a file in archive eea...
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from numpy import sort from src.helpers.dataframe_helper import df_get, write_to_csv def __copy_random_record_of_class(from_df, from_file_path, to_df, to_file_path, classes=None): """ TODO if we want to be more precise, we have to move the row, not just copy it """ if classes is None or len(classes)...
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''' BOAT_RACE_DB2 140_mkcsv_t_info_d.py HTMLt_info_dCSV macOS 11.1/Raspbian OS 10.4/python 3.9.1/sqlite3 3.32.3 2021.02.01 ver 1.00 ''' import os import datetime from bs4 import BeautifulSoup # BASE_DIR = '/home/pi/BOAT_RACE_DB' ''' mkcsv_t_info_d HTMLt_info_dCSV ''' # mkcsv_t_info_d() #t_info_dCSV
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#!/usr/bin/env python3 import numpy as np B = np.reshape(np.genfromtxt("data/b_nmc.txt"), (40, 40)) import matplotlib.pyplot as plt plt.contourf(B) plt.colorbar() plt.show()
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#!/usr/bin/env python3 import os, json print("Content-type:text/html\r\n\r\n") print print("<title>Test CGI</title>") print("<p>Hello World!</>") # #Q1 # print(os.environ) # json_object = json.dumps(dict(os.environ), indent=4) # #print(json_object) #Q2 # for param in os.environ.keys(): # if (param=="QUERY_STRING"...
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#!/usr/local/bin/python3 from subprocess import Popen, PIPE from urllib.parse import quote import sqlite3, datetime, sys, re # Global Variables removeCheckedItems = True # Set to false if you want to keep "completed" to-do items when this is run bearDbFile = str(sys.argv[3]) oneTabID = str(sys.argv[4]) # Methods de...
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import sys from time import perf_counter from command import CommandList from errors import DppArgparseError, DppDockerError, DppError from message import message if __name__ == "__main__": from multiprocessing import freeze_support freeze_support() main()
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# -*- coding: utf-8 -*- """ ui/choice_grid.py Last updated: 2021-05-04 Manage the grid for the puil-subject-choice-editor. =+LICENCE============================= Copyright 2021 Michael Towers Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with ...
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import math result=(math.pow(3,2)+1)*(math.fmod(16,7))/7 print(result)
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# -*- coding: utf-8 -*- """ Created on Tue Feb 5 16:25:45 2019 @author: polsterc16 ============================================================================== LICENCE INFORMATION ============================================================================== This Software uses Code (spg4) provided by "Brandon Rho...
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from autostat.run_settings import RunSettings, Backend from autostat.kernel_search import kernel_search, get_best_kernel_info from autostat.dataset_adapters import Dataset from autostat.utils.test_data_loader import load_test_dataset from html_reports import Report from markdown import markdown import matplotlib.py...
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# -*- coding: utf-8 -*- """ @Remark: """ from django.urls import path, re_path from rest_framework import routers from apps.lyusers.views import UserManageViewSet system_url = routers.SimpleRouter() system_url.register(r'users', UserManageViewSet) urlpatterns = [ re_path('users/disableuser/(?P<pk>.*?)/',Use...
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# -*- coding: utf-8 -*- ''' Texas A&M University Sounding Rocketry Team SRT-6 | 2018-2019 SRT-9 | 2021-2022 %-------------------------------------------------------------% TAMU SRT _____ __ _____ __ __ / ___/______ __ _____ ___/ / / ___...
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#/usr/bin/env python import sys from setuptools import setup from cricket import VERSION try: readme = open('README.rst') long_description = str(readme.read()) finally: readme.close() required_pkgs = [ 'tkreadonly', ] if sys.version_info < (2, 7): required_pkgs.extend(['argparse', 'unittest2', 'p...
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import requests; import json; from collections import Counter # Counts and orders the list of violations import sys; from urllib.parse import quote_plus # Make sysarg url-safe # List of Apache Commons libraries which I know can be analyzed (without crashing/failing their tests) commonsList = ["bcel", "beanutils", ...
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n = int(input('Qual tabuada deseja ver: ')) c=1 print(11*'=') while c <= 10: print('{} x {:2} = {}'.format(n,c,c*n)) c += 1 print(11*'=')
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import argparse import json import os import matplotlib.pyplot as plt import numpy as np import tensorflow as tf import tqdm from config import Config from dataset import LJSpeech from model import DiffWave if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument('--config', default...
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# boudoir - chuchotement pantophobique # https://www.youtube.com/watch?v=KL2zW6Q5hWs # https://gist.github.com/jf-parent/c8ea7e54e30593af01512f4e21b54670 Scale.default = Scale.major Root.default = 0 Clock.bpm = 120 b1.reset() >> glass( [0], dur = 16, ).after(16, 'stop') Clock.set_time(0) Clock.future(0, pla...
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import random import urllib.parse import sqlite3 import asyncio import aiohttp import discord from discord.ext import commands import loadconfig
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# !/usr/bin/env python # -*- coding: utf-8 -*- import base64 import json import copy import socket import subprocess import six
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"""Build beta detail models for the API""" import enum from typing import Dict, Optional import deserialize from asconnect.models.common import BaseAttributes, Links, Relationship, Resource
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import math from plotter import Plotter from plots import LinePlot import board import digitalio import busio import adafruit_sdcard import storage from adafruit_bitmapsaver import save_pixels plot() #save() print('done') #import jax.numpy as np # #def periodic_spikes(firing_periods, duration: in...
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from os import listdir import subprocess for f in listdir("tests/vulkan"): if f.endswith(".spv"): continue print(f"-- compiling test {f}") p = subprocess.run(["glslangValidator", f"tests/vulkan/{f}", "-H", "-o", f"tests/vulkan/{f}.spv"], shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)...
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# Taken straight from Patter https://github.com/ryanleary/patter # TODO: review, and copyright and fix/add comments import torch from torch.utils.data import Dataset from .manifest import Manifest def audio_seq_collate_fn(batch): """ collate a batch (iterable of (sample tensor, label tensor) tuples) into ...
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""" ~~~ IMPORT EXPERIMENTAL DATA, PROCESS, AND NONDIMENSIONALIZE ~~~ This code reads in the rescaled Snodgrass data and compares parameters to known parameters found in the Henderson and Segur paper. 1. Get distances 2. Read in the gauge data for each event (get frequencies and Fourier magnitudes) 3. Adjust the y ax...
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from .rip import *
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# -*- coding: utf-8 -*- # Time : 2022/1/17 15:20 # Author : QIN2DIM # Github : https://github.com/QIN2DIM # Description: import os.path import time from hashlib import sha256 from typing import List, Optional, Union, Dict import cloudscraper import yaml from lxml import etree # skipcq: BAN-B410 - Ignore...
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import torch import torch.nn as nn from torch.nn import functional as F
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# Copyright 2020 Google LLC # # 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, ...
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from enum import Enum from typing import ( Any, Dict, ) from galaxy import ( exceptions, model, ) from galaxy.managers import hdas from galaxy.managers.context import ProvidesUserContext from galaxy.managers.jobs import ( JobManager, JobSearch, view_show_job, ) from galaxy.schema.fields imp...
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import pytest import numpy as np from deephub.models.registry.toy import DebugToyModel from deephub.models.feeders import MemorySamplesFeeder from deephub.trainer import Trainer
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from typing import TYPE_CHECKING import pytest from . import CapturedOutput from utsc.switchconfig import config from prompt_toolkit.application import create_app_session from prompt_toolkit.input import create_pipe_input if TYPE_CHECKING: from .. import MockedUtil from pytest_mock import MockerFixture ...
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# Copyright (c) 2014, HashFast Technologies LLC # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # 1. Redistributions of source code must retain the above copyright # notice, this list of...
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from django.db import models from django.conf import settings from courses.models import Course # Create your models here.
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import argparse import os import re import sys from operator import itemgetter from typing import Optional import sentry_sdk import youtube_dl from selenium.common.exceptions import SessionNotCreatedException from cmd_tool import ( get_execution_path, exit_enter, get_input_path_or_exit, get_chrome_dri...
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# -*- coding: utf-8 -*- import os import io import urllib2 import string from BeautifulSoup import BeautifulSoup import pandas as pd import sys city_url = 'http://twblg.dict.edu.tw/holodict_new/index/xiangzhen_level1.jsp?county=1' if __name__=='__main__': # data = extract_items(city_url) data...
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import csv #global variables for teams: sharks = [] dragons = [] raptors = [] #read the csv file with the player info and create a player dictionary: #distribute kids based on experience: #finalize teams: #update the player dictionary to include the assigned teams: #write the league info into the text file: #gene...
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import wpilib import wpilib.drive import ctre import robotmap from wpilib.interfaces import GenericHID RIGHT_HAND = GenericHID.Hand.kRight LEFT_HAND = GenericHID.Hand.kLeft if __name__ == "__main__": wpilib.run(Robot,physics_enabled=True)
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from django.contrib import admin from django.urls import path from .views import blog urlpatterns = [ path('', blog, name='blog'), ]
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#!/usr/bin/env python from iris_sdk.models.maps.base_map import BaseMap
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import re import traceback import urllib2 import pandas as pd import json,random,time,datetime from bs4 import BeautifulSoup from pandas.tseries.offsets import YearEnd from sqlalchemy import text from webapp import db, app from webapp.models import FinanceBasic headers = {'User-Agent':'Mozilla/5.0 (Windows; U; Wind...
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import tensorflow as tf from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets('MNIST_data', one_hot = True) # Network hyperparameters learning_rate = 0.0001 # 1.95 for sigmoid activation function batch_size = 10 update_step = 10 input_nodes = 784 # 28x38 images as input layer_1_...
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