text stringlengths 1 93.6k |
|---|
conn.execute('''CREATE TABLE accounts
|
(
|
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
accountId INTEGER NOT NULL,
|
ownerId INTEGER NOT NULL,
|
userName TEXT NOT NULL,
|
token TEXT NOT NULL,
|
email TEXT,
|
password TEXT,
|
cookie TEXT,
|
isPremium INTEGERL,
|
invitesRemaining INTEGER,
|
timestamp INTEGER
|
);''')
|
print('[+] Table accounts created successfully.')
|
conn.execute('''CREATE TABLE flood
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(ownerId INTEGER PRIMARY KEY,
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warned INTEGER DEFAULT 0,
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lastMessage INTEGER DEFAULT 0,
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blockTill INTEGER DEFAULT 0
|
);''')
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print('[+] Table flood created successfully.')
|
# <FILESEP>
|
import multiprocessing as mp
|
if mp.get_start_method(allow_none=True) != 'spawn':
|
mp.set_start_method('spawn')
|
import argparse
|
import os
|
import time
|
import torch
|
import torch.nn as nn
|
import torch.nn.parallel
|
import torch.backends.cudnn as cudnn
|
import torch.optim
|
import torch.utils.data
|
import torch.utils.data.distributed
|
import torchvision.transforms as transforms
|
from tensorboardX import SummaryWriter
|
import models
|
from models import ParameterClient
|
from logger import create_logger
|
from datasets import FileListDataset, DistSequentialSampler
|
from utils import *
|
model_names = sorted(name for name in models.__dict__
|
if name.islower() and not name.startswith("__")
|
and callable(models.__dict__[name]))
|
classifier_types = sorted(name for name in models.__factory_classifier__)
|
parser = argparse.ArgumentParser(
|
description='PyTorch Face Classification Training')
|
parser.add_argument('--arch',
|
'-a',
|
metavar='ARCH',
|
default='resnet50',
|
choices=model_names,
|
help='model architecture: ' + ' | '.join(model_names) +
|
' (default: resnet18)')
|
parser.add_argument('--train-filelist', type=str)
|
parser.add_argument('--train-prefix', type=str)
|
parser.add_argument('--val-filelist', type=str)
|
parser.add_argument('--val-prefix', type=str)
|
parser.add_argument('-j',
|
'--workers',
|
default=0,
|
type=int,
|
metavar='N',
|
help='number of data loading workers (default: 0)')
|
parser.add_argument('--epochs',
|
default=30,
|
type=int,
|
metavar='N',
|
help='number of total epochs to run')
|
parser.add_argument('--start-epoch',
|
default=0,
|
type=int,
|
metavar='N',
|
help='manual epoch number (useful on restarts)')
|
parser.add_argument('--batch-size', default=256, type=int)
|
parser.add_argument('--test-batch-size', default=None, type=int)
|
parser.add_argument('--lr',
|
'--learning-rate',
|
default=0.01,
|
type=float,
|
metavar='LR',
|
help='initial learning rate')
|
parser.add_argument('--lr-steps',
|
default=[21, 27],
|
type=list,
|
help='stpes to change lr')
|
parser.add_argument('--momentum', default=0.9, type=float)
|
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