id int64 0 190k | prompt stringlengths 21 13.4M | docstring stringlengths 1 12k ⌀ |
|---|---|---|
141,626 | import os
from natsort import natsorted
from glob import glob
def get_last_path(path, session):
x = natsorted(glob(os.path.join(path,'*%s'%session)))[-1]
return x | null |
141,627 | import torch
import numpy as np
import cv2
def torchPSNR(tar_img, prd_img):
imdff = torch.clamp(prd_img,0,1) - torch.clamp(tar_img,0,1)
rmse = (imdff**2).mean().sqrt()
ps = 20*torch.log10(1/rmse)
return ps | null |
141,628 | import torch
import numpy as np
import cv2
def save_img(filepath, img):
cv2.imwrite(filepath,cv2.cvtColor(img, cv2.COLOR_RGB2BGR)) | null |
141,629 | import torch
import numpy as np
import cv2
def numpyPSNR(tar_img, prd_img):
imdff = np.float32(prd_img) - np.float32(tar_img)
rmse = np.sqrt(np.mean(imdff**2))
ps = 20*np.log10(255/rmse)
return ps | null |
141,630 | import torch
import os
from collections import OrderedDict
def freeze(model):
for p in model.parameters():
p.requires_grad=False | null |
141,631 | import torch
import os
from collections import OrderedDict
def unfreeze(model):
for p in model.parameters():
p.requires_grad=True | null |
141,632 | import torch
import os
from collections import OrderedDict
def is_frozen(model):
x = [p.requires_grad for p in model.parameters()]
return not all(x) | null |
141,633 | import torch
import os
from collections import OrderedDict
def save_checkpoint(model_dir, state, session):
epoch = state['epoch']
model_out_path = os.path.join(model_dir,"model_epoch_{}_{}.pth".format(epoch,session))
torch.save(state, model_out_path) | null |
141,634 | import torch
import os
from collections import OrderedDict
def load_checkpoint(model, weights):
checkpoint = torch.load(weights)
try:
model.load_state_dict(checkpoint["state_dict"])
except:
state_dict = checkpoint["state_dict"]
new_state_dict = OrderedDict()
for k, v in stat... | null |
141,635 | import torch
import os
from collections import OrderedDict
def load_checkpoint_multigpu(model, weights):
checkpoint = torch.load(weights)
state_dict = checkpoint["state_dict"]
new_state_dict = OrderedDict()
for k, v in state_dict.items():
name = k[7:] # remove `module.`
new_state_dict[n... | null |
141,636 | import torch
import os
from collections import OrderedDict
def load_start_epoch(weights):
checkpoint = torch.load(weights)
epoch = checkpoint["epoch"]
return epoch | null |
141,637 | import torch
import os
from collections import OrderedDict
def load_optim(optimizer, weights):
checkpoint = torch.load(weights)
optimizer.load_state_dict(checkpoint['optimizer'])
# for p in optimizer.param_groups: lr = p['lr']
# return lr | null |
141,639 | import os
import numpy as np
from glob import glob
from natsort import natsorted
from skimage import io
import cv2
from skimage.metrics import structural_similarity
from tqdm import tqdm
import concurrent.futures
def image_align(deblurred, gt):
def compute_psnr(image_true, image_test, image_mask, data_range=None):
def ... | null |
141,640 | import os
import numpy as np
from torch.utils.data import Dataset
import torch
from PIL import Image
import torchvision.transforms.functional as TF
from pdb import set_trace as stx
import random
def is_image_file(filename):
return any(filename.endswith(extension) for extension in ['jpeg', 'JPEG', 'jpg', 'png', 'JP... | null |
141,641 | import os
from dataset_RGB import DataLoaderTrain, DataLoaderVal, DataLoaderTest
class DataLoaderTrain(Dataset):
def __init__(self, rgb_dir, img_options=None):
super(DataLoaderTrain, self).__init__()
inp_files = sorted(os.listdir(os.path.join(rgb_dir, 'input')))
tar_files = sorted(os.listd... | null |
141,661 | import os
from dataset_RGB import DataLoaderTrain, DataLoaderVal, DataLoaderTest
class DataLoaderVal(Dataset):
def __init__(self, rgb_dir, img_options=None, rgb_dir2=None):
def __len__(self):
def __getitem__(self, index):
def get_validation_data(rgb_dir, img_options):
assert os.path.exists(rgb_dir)... | null |
141,676 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.transforms.functional as TF
from PIL import Image
import os
from runpy import run_path
from skimage import img_as_ubyte
from collections import OrderedDict
from natsort import natsorted
from glob import glob
import cv2
import argparse... | null |
141,677 | import torch
import torch.nn as nn
import torch.nn.functional as F
import torchvision.transforms.functional as TF
from PIL import Image
import os
from runpy import run_path
from skimage import img_as_ubyte
from collections import OrderedDict
from natsort import natsorted
from glob import glob
import cv2
import argparse... | null |
141,678 | import os
import re
import openai
import streamlit as st
from dotenv import load_dotenv
from tempfile import NamedTemporaryFile
import streamlit.components.v1 as components
from streamlit_chat import message
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from ... | null |
141,679 | import os
import re
import openai
import streamlit as st
from dotenv import load_dotenv
from tempfile import NamedTemporaryFile
import streamlit.components.v1 as components
from streamlit_chat import message
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from ... | null |
141,680 | import os
import re
import openai
import streamlit as st
from dotenv import load_dotenv
from tempfile import NamedTemporaryFile
import streamlit.components.v1 as components
from streamlit_chat import message
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from ... | null |
141,681 | import os
import re
import openai
import streamlit as st
from dotenv import load_dotenv
from tempfile import NamedTemporaryFile
import streamlit.components.v1 as components
from streamlit_chat import message
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from ... | null |
141,682 | import os
import re
import openai
import streamlit as st
from dotenv import load_dotenv
from tempfile import NamedTemporaryFile
import streamlit.components.v1 as components
from streamlit_chat import message
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from ... | null |
141,683 | import os
import re
import openai
import streamlit as st
from dotenv import load_dotenv
from tempfile import NamedTemporaryFile
import streamlit.components.v1 as components
from streamlit_chat import message
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferWindowMemory
from ... | null |
141,684 | import os
import webbrowser
import argparse
from langchain.document_loaders.figma import FigmaFileLoader
from langchain.chat_models import ChatOpenAI
from langchain.indexes import VectorstoreIndexCreator
from langchain.prompts.chat import (
ChatPromptTemplate,
SystemMessagePromptTemplate,
HumanMessagePrompt... | null |
141,685 | from dataclasses import dataclass, field
from typing import Optional, Dict, Sequence
import numpy as np
import torch
import transformers
from torch.utils.data import Dataset
from transformers import Trainer
import os
The provided code snippet includes necessary dependencies for implementing the `safe_save_model_for_hf... | Collects the state dict and dump to disk. |
141,686 | from dataclasses import dataclass, field
from typing import Optional, Dict, Sequence
import numpy as np
import torch
import transformers
from torch.utils.data import Dataset
from transformers import Trainer
import os
class ModelArguments:
"""filed的作用：如果有新值就会被替换掉，"""
model_name_or_path: Optional[str] = field(def... | transformers.HfArgumentParser，传入的类必须有@dataclass进行装饰，这样这些参数会被自动添加到命令中 |
141,687 | import torch
import math
import numpy as np
from typing import List, Dict
from torch.utils.data import DataLoader, Dataset
import os
import time
class MyDataset(Dataset):
def __init__(self, data_prefix, seq_length, pad_id):
super(MyDataset, self).__init__()
"""这边要求data_prefix为完整的路径，但不包括后缀"""
... | args: - per_device_train_batch_size: 自带的 - seed: 自带的 - global_batch_distributed: "[1,2,3]" |
141,688 | import copy
import logging
from dataclasses import dataclass, field
from typing import Optional, Dict, Sequence
import numpy as np
import torch
import transformers
from torch.utils.data import Dataset
from transformers import Trainer
import os
from torch.utils.data import DataLoader
from typing import List
import math
... | transformers.HfArgumentParser，传入的类必须有@dataclass进行装饰，这样这些参数会被自动添加到命令中 |
141,689 | import json
import shutil
import numpy as np
import os
from sentencepiece import SentencePieceProcessor
from typing import List
import argparse
import multiprocessing
from tqdm import tqdm
import time
import torch
from torch.utils.data import Dataset
import re
import nltk
def read(args):
ds = MyDataset(args.rea... | null |
141,690 | import json
import shutil
import numpy as np
import os
from sentencepiece import SentencePieceProcessor
from typing import List
import argparse
import multiprocessing
from tqdm import tqdm
import time
import torch
from torch.utils.data import Dataset
import re
import nltk
The provided code snippet includes necessa... | 下面这个暂时先取消掉自动合并的功能，必须要指定，也就是写入到新的文件 |
141,691 | import json
import shutil
import numpy as np
import os
from sentencepiece import SentencePieceProcessor
from typing import List
import argparse
import multiprocessing
from tqdm import tqdm
import time
import torch
from torch.utils.data import Dataset
import re
import nltk
def collate_fn_from_text(text: str):
r... | null |
141,692 | import json
import shutil
import numpy as np
import os
from sentencepiece import SentencePieceProcessor
from typing import List
import argparse
import multiprocessing
from tqdm import tqdm
import time
import torch
from torch.utils.data import Dataset
import re
import nltk
class Tokenizer:
def __init__(self, mod... | 打开文本文件 |
141,693 | import json
import shutil
import numpy as np
import os
from sentencepiece import SentencePieceProcessor
from typing import List
import argparse
import multiprocessing
from tqdm import tqdm
import time
import torch
from torch.utils.data import Dataset
import re
import nltk
def write(args):
"""这个函数用于处理我们爬取的文件"""
... | 不支持一个数据集中有不同类型的数据进行混合 |
141,694 | import copy
import logging
from dataclasses import dataclass, field
from typing import Optional, Dict, Sequence
import numpy as np
import torch
import transformers
from torch.utils.data import Dataset
from transformers import Trainer
import os
from torch.utils.data.distributed import DistributedSampler
class args:
... | null |
141,695 | from torch.utils.data import Dataset
import numpy as np
import os
import torch
import argparse
import time
from tqdm import tqdm
from sentencepiece import SentencePieceProcessor
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--read_data_path_prefix", default=None, type=str, help="会自动在结... | null |
141,696 | from torch.utils.data import Dataset
import numpy as np
import os
import torch
import argparse
import time
from tqdm import tqdm
from sentencepiece import SentencePieceProcessor
class MyDataset(Dataset):
def __init__(self, data_prefix, seq_length, pad_id):
super(MyDataset, self).__init__()
"""这边要求da... | 只保留中文，而在之前的版本中，中文是在前面的 |
141,697 | from torch.utils.data import Dataset
import numpy as np
import os
import torch
import argparse
import time
from tqdm import tqdm
from sentencepiece import SentencePieceProcessor
class MyDataset(Dataset):
def __init__(self, data_prefix, seq_length, pad_id):
super(MyDataset, self).__init__()
"""这边要求da... | 加载待删除的索引 |
141,698 | from torch.utils.data import Dataset
import numpy as np
import os
import torch
import argparse
import time
from tqdm import tqdm
from sentencepiece import SentencePieceProcessor
class MyDataset(Dataset):
def __init__(self, data_prefix, seq_length, pad_id):
def _check(self):
def _load_index(self):
de... | null |
141,699 | import os
import logging
import bitsandbytes as bnb
import torch
import transformers
import argparse
from transformers import (
AutoTokenizer,
AutoModelForCausalLM,
set_seed,
Trainer,
BitsAndBytesConfig,
)
from peft import (
prepare_model_for_kbit_training,
LoraConfig,
get_peft_model,
... | null |
141,700 | import os
import sys
from typing import List
import fire
import torch
import transformers
from datasets import load_dataset
from peft import (
LoraConfig,
get_peft_model,
get_peft_model_state_dict,
prepare_model_for_kbit_training,
set_peft_model_state_dict,
TaskType,
)
from transformers import A... | (1) ChatGLM3 uses <unk> as padding token (2) Qwen uses <|endoftext|> as padding token |
141,701 | import os
import sys
from typing import List
import fire
import torch
import transformers
from datasets import load_dataset
from peft import (
LoraConfig,
get_peft_model,
get_peft_model_state_dict,
prepare_model_for_int8_training,
set_peft_model_state_dict,
)
from transformers import AutoModelForCau... | null |
141,702 | import os
import sys
from typing import List
import fire
import torch
import transformers
from datasets import load_dataset
from peft import (
LoraConfig,
get_peft_model,
get_peft_model_state_dict,
prepare_model_for_int8_training,
set_peft_model_state_dict,
)
from transformers import LlamaForCausalL... | null |
141,703 | import json
from fastapi import FastAPI, Request
import uvicorn
import datetime
import torch
from transformers import LlamaTokenizer
from transformers import GenerationConfig
from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig
from utils import Prompter
async def complement(request: Request):
global mode... | null |
141,704 | import time
from typing import Any, List, Optional, Union
from transformers import PreTrainedTokenizer, PreTrainedTokenizerFast
from transformers import LlamaTokenizer
from vllm.config import (CacheConfig, ModelConfig, ParallelConfig,
SchedulerConfig)
from vllm.core.scheduler import Scheduler
f... | Gets a tokenizer for the given model name via Huggingface. |
141,705 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,706 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,707 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,708 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,709 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,710 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,711 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,712 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,713 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,714 | import os
import torch
import uvicorn
from fastapi.responses import StreamingResponse
from fastapi import FastAPI, Request
from transformers import AutoTokenizer, AutoConfig, AutoModelForCausalLM, pipeline
from queue import Queue
import json
from typing import List, Dict, Optional
import time
import asyncio
import argp... | null |
141,715 | import torch
from accelerate import init_empty_weights, infer_auto_device_map, load_checkpoint_and_dispatch
from transformers import GenerationConfig, LlamaForCausalLM, LlamaTokenizer, LlamaConfig, AutoModelForCausalLM, AutoConfig, AutoTokenizer
from typing import List
def set_limit(allocate:List[int]=None):
if al... | null |
141,716 | import torch
from accelerate import init_empty_weights, infer_auto_device_map, load_checkpoint_and_dispatch
from transformers import GenerationConfig, LlamaForCausalLM, LlamaTokenizer, LlamaConfig, AutoModelForCausalLM, AutoConfig, AutoTokenizer
from typing import List
def get_tokenizer_and_model(base_model:str, dtype... | null |
141,717 | from typing import Optional
import fire
import torch
import tqdm
import transformers
from peft import PeftModel
The provided code snippet includes necessary dependencies for implementing the `make_diff` function. Write a Python function `def make_diff( path_raw: str, path_tuned: str, path_diff: str, device="cpu", ... | Make the weight diff. This function is given to present full transparency of how the weight diff was created. Run: python weight_diff.py make_diff --path_raw <your_path_raw> --path_tuned <your_path_tuned> --path_diff <your_path_diff> |
141,718 | from typing import Optional
import fire
import torch
import tqdm
import transformers
from peft import PeftModel
The provided code snippet includes necessary dependencies for implementing the `recover` function. Write a Python function `def recover( path_raw, path_diff, path_tuned: Optional[str] = None, ... | Recover the original weights from the released weight diff. This function is given for you to run. Things to do before running this: 1. Convert Meta's released weights into huggingface format. Follow this guide: https://huggingface.co/docs/transformers/main/model_doc/llama 2. Make sure you cloned the released weight di... |
141,719 | from typing import Optional
import fire
import torch
import tqdm
import transformers
from peft import PeftModel
The provided code snippet includes necessary dependencies for implementing the `merge` function. Write a Python function `def merge( path_zhixi, path_lora, path_sfted: Optional[str] = None, i... | Merge the released lora weight with the pretrained zhixi to be a single hf format model for further lora training or full-finetuning This function is given for you to run. Things to do before running this: 1. Getting the pretrained zhixi model. Follow this guide: https://github.com/zjunlp/KnowLM 2. Make sure you cloned... |
141,720 | import argparse
from huggingface_hub import snapshot_download
import time
def _print(message):
print(f"[{time.ctime()}] {message}") | null |
141,721 | import argparse
from huggingface_hub import snapshot_download
import time
def add_argument():
parser = argparse.ArgumentParser(description="download")
parser.add_argument('--download_path', type=str, default='./CaMA', help="storage directory")
parser.add_argument('--only_lora', action='store_true', default... | null |
141,722 | import argparse
from huggingface_hub import snapshot_download
import time
def check_args(args):
assert args.only_lora or args.only_base or args.both, \
"Please select the file to download."
assert (args.only_lora and not args.only_base and not args.both) \
or (not args.only_lora and args.onl... | null |
141,723 | import logging
import sys
from pathlib import Path
import atheris
import structlog
def set_unblob_log_level(level=logging.CRITICAL):
logger = logging.getLogger("unblob")
def logger_factory():
return logger
structlog.configure(logger_factory=logger_factory)
logger.setLevel(level) | null |
141,724 | import logging
import sys
from pathlib import Path
import atheris
import structlog
def extract(inpath: Path, outpath: Path): # noqa: ARG001
return | null |
141,725 | import logging
import sys
from pathlib import Path
import atheris
import structlog
class File(mmap.mmap):
access: int
def from_bytes(cls, content: bytes):
if not content:
raise ValueError("Can't create File from empty bytes.")
m = cls(-1, len(content))
m.write(content)
... | null |
141,726 | import os
from threading import Lock
__last_id = 0
__last_id_lock = Lock()
def new_id():
# NOTE, that uuid4 can not be used, as there are multiple processes at run time,
# and as subprocesses inherit the random number state, so uuid4 would generate colliding ids
# another option that would not work is to u... | null |
141,727 | from typing import Optional
from pyfatfs._exceptions import PyFATException
from pyfatfs.PyFat import PyFat
from structlog import get_logger
from unblob.extractors.command import Command
from unblob.file_utils import InvalidInputFormat
from ...models import File, Handler, HexString, ValidChunk
def get_max_offset(fs: Py... | null |
141,728 | import binascii
import struct
from typing import Optional
from dissect.cstruct import Instance
from unblob.extractors import Command
from ...file_utils import Endian, convert_int32, get_endian
from ...models import File, HexString, StructHandler, ValidChunk
def swap_int32(i):
return struct.unpack("<I", struct.pack... | null |
141,729 | import io
import itertools
from collections import defaultdict
from enum import IntEnum
from pathlib import Path
from typing import Iterable, List, Optional, Tuple
import attr
from dissect.cstruct import Instance
from structlog import get_logger
from treelib import Tree
from treelib.exceptions import NodeIDAbsentError
... | null |
141,730 | import io
import itertools
from collections import defaultdict
from enum import IntEnum
from pathlib import Path
from typing import Iterable, List, Optional, Tuple
import attr
from dissect.cstruct import Instance
from structlog import get_logger
from treelib import Tree
from treelib.exceptions import NodeIDAbsentError
... | File size can be encoded as 64 bits or 32 bits values. If upper 32 bits are set, it's a 64 bits integer value. Otherwise it's a 32 bits value. 0xFFFFFFFF means zero. |
141,731 | import io
import itertools
from collections import defaultdict
from enum import IntEnum
from pathlib import Path
from typing import Iterable, List, Optional, Tuple
import attr
from dissect.cstruct import Instance
from structlog import get_logger
from treelib import Tree
from treelib.exceptions import NodeIDAbsentError
... | null |
141,732 | import io
import itertools
from collections import defaultdict
from enum import IntEnum
from pathlib import Path
from typing import Iterable, List, Optional, Tuple
import attr
from dissect.cstruct import Instance
from structlog import get_logger
from treelib import Tree
from treelib.exceptions import NodeIDAbsentError
... | null |
141,733 | from typing import Optional
from structlog import get_logger
from unblob.extractors import Command
from unblob.file_utils import Endian
from ...models import File, HexString, StructHandler, ValidChunk
The provided code snippet includes necessary dependencies for implementing the `from_733` function. Write a Python fun... | Convert from ISO 9660 7.3.3 format to uint32_t. Return the little-endian part always, to handle non-specs-compliant images. |
141,734 | from typing import Optional
from structlog import get_logger
from unblob.extractors import Command
from unblob.file_utils import Endian
from ...models import File, HexString, StructHandler, ValidChunk
The provided code snippet includes necessary dependencies for implementing the `from_723` function. Write a Python fun... | Convert from ISO 9660 7.2.3 format to uint16_t. Return the little-endian part always, to handle non-specs-compliant images. |
141,735 | import io
import os
import stat
import struct
from enum import IntEnum, unique
from pathlib import Path
from typing import Dict, Optional
from structlog import get_logger
from ...file_utils import (
Endian,
FileSystem,
InvalidInputFormat,
read_until_past,
round_up,
)
from ...models import (
Extr... | Apply a RomFS checksum and returns whether it's valid or not. |
141,736 | import io
import os
import stat
import struct
from enum import IntEnum, unique
from pathlib import Path
from typing import Dict, Optional
from structlog import get_logger
from ...file_utils import (
Endian,
FileSystem,
InvalidInputFormat,
read_until_past,
round_up,
)
from ...models import (
Extr... | Read a 16 bytes aligned, null terminated string. |
141,737 | import io
import shutil
from pathlib import Path
from typing import Optional
import attr
import lief
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.extractor import carve_chunk_to_file
from unblob.file_utils import (
Endian,
File,
convert_int8,
convert_int32,
conve... | Extract the initramfs part, with a potentially 4 extra bytes. Due to alignment definition of initramfs the start-end offsets can not be exactly calculated, so the output could have a 4 extra bytes before or after the initramfs. |
141,738 | import io
from pathlib import Path
from typing import Optional
import attr
from dissect.cstruct import Instance
from pyperscan import Flag, Pattern, Scan, StreamDatabase
from structlog import get_logger
from unblob.file_utils import File, iterate_file, stream_scan
from unblob.models import (
Endian,
Extractor,
... | null |
141,739 | import io
from pathlib import Path
from typing import Optional
import attr
from dissect.cstruct import Instance
from pyperscan import Flag, Pattern, Scan, StreamDatabase
from structlog import get_logger
from unblob.file_utils import File, iterate_file, stream_scan
from unblob.models import (
Endian,
Extractor,
... | null |
141,740 | import contextlib
import os
import tarfile
from pathlib import Path
from typing import Optional
from structlog import get_logger
from ...file_utils import OffsetFile, SeekError, decode_int, round_up, snull
from ...models import (
Extractor,
ExtractResult,
File,
HexString,
Regex,
StructHandler,
... | null |
141,741 | import contextlib
import os
import tarfile
from pathlib import Path
from typing import Optional
from structlog import get_logger
from ...file_utils import OffsetFile, SeekError, decode_int, round_up, snull
from ...models import (
Extractor,
ExtractResult,
File,
HexString,
Regex,
StructHandler,
... | null |
141,742 | import binascii
from pathlib import Path
from typing import Optional
from structlog import get_logger
from unblob.extractors import Command
from ...extractors.command import MultiFileCommand
from ...file_utils import Endian, InvalidInputFormat, StructParser
from ...models import (
DirectoryHandler,
File,
Gl... | null |
141,743 | import binascii
from pathlib import Path
from typing import Optional
from structlog import get_logger
from unblob.extractors import Command
from ...extractors.command import MultiFileCommand
from ...file_utils import Endian, InvalidInputFormat, StructParser
from ...models import (
DirectoryHandler,
File,
Gl... | null |
141,744 | import binascii
import io
from pathlib import Path
from typing import Iterable, Optional, Tuple, cast
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.file_utils import (
File,
FileSystem,
InvalidInputFormat,
iterate_file,
snull,
)
from unblob.models import (
End... | null |
141,745 | import binascii
import io
from pathlib import Path
from typing import Iterable, Optional, Tuple, cast
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.file_utils import (
File,
FileSystem,
InvalidInputFormat,
iterate_file,
snull,
)
from unblob.models import (
End... | null |
141,746 | import binascii
import io
from pathlib import Path
from typing import Iterable, Optional, Tuple, cast
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.file_utils import (
File,
FileSystem,
InvalidInputFormat,
iterate_file,
snull,
)
from unblob.models import (
End... | null |
141,747 | from pathlib import Path
from typing import Optional
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.file_utils import Endian, File, InvalidInputFormat, StructParser
from unblob.models import Extractor, HexString, StructHandler, ValidChunk
XOR_KEY = b"\xac\x78\x3c\x9e\xcf\x67\xb3\x59"
... | null |
141,748 | import io
from pathlib import Path
from typing import Optional
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.file_utils import (
Endian,
File,
FileSystem,
InvalidInputFormat,
StructParser,
snull,
)
from unblob.models import (
Extractor,
ExtractResult,
... | null |
141,749 | import io
from pathlib import Path
from typing import Optional
from dissect.cstruct import Instance
from structlog import get_logger
from unblob.extractor import carve_chunk_to_file
from unblob.file_utils import Endian, File, InvalidInputFormat, StructParser, snull
from unblob.models import Chunk, Extractor, HexString,... | null |
141,750 | import gzip
import io
import struct
import zlib
from pathlib import Path
from typing import List, Optional
from structlog import get_logger
from unblob.extractors import Command
from unblob.extractors.command import MultiFileCommand
from unblob.models import Extractor
from ...file_utils import InvalidInputFormat
from .... | null |
141,751 | import io
from typing import Optional, Tuple
import attr
from pyperscan import Flag, Pattern, Scan, StreamDatabase
from structlog import get_logger
from unblob.extractors import Command
from ...file_utils import (
Endian,
convert_int8,
convert_int16,
convert_int32,
decode_multibyte_integer,
read... | null |
141,752 | import io
from typing import Optional, Tuple
import attr
from pyperscan import Flag, Pattern, Scan, StreamDatabase
from structlog import get_logger
from unblob.extractors import Command
from ...file_utils import (
Endian,
convert_int8,
convert_int16,
convert_int32,
decode_multibyte_integer,
read... | null |
141,753 | from typing import Optional
import attr
from pyperscan import Flag, Pattern, Scan, StreamDatabase
from structlog import get_logger
from unblob.extractors import Command
from ...file_utils import InvalidInputFormat, SeekError, StructParser, stream_scan
from ...models import File, Handler, HexString, Regex, ValidChunk
d... | null |
141,754 | from typing import Optional
import attr
from pyperscan import Flag, Pattern, Scan, StreamDatabase
from structlog import get_logger
from unblob.extractors import Command
from ...file_utils import InvalidInputFormat, SeekError, StructParser, stream_scan
from ...models import File, Handler, HexString, Regex, ValidChunk
ST... | null |
141,755 | import atexit
import sys
from importlib.metadata import version
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
import click
from rich.console import Console
from rich.panel import Panel
from rich.style import Style
from rich.table import Table
from structlog import get_logger
from unb... | null |
141,756 | import atexit
import sys
from importlib.metadata import version
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
import click
from rich.console import Console
from rich.panel import Panel
from rich.style import Style
from rich.table import Table
from structlog import get_logger
from unb... | null |
141,757 | import atexit
import sys
from importlib.metadata import version
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
import click
from rich.console import Console
from rich.panel import Panel
from rich.style import Style
from rich.table import Table
from structlog import get_logger
from unb... | null |
141,758 | import atexit
import sys
from importlib.metadata import version
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
import click
from rich.console import Console
from rich.panel import Panel
from rich.style import Style
from rich.table import Table
from structlog import get_logger
from unb... | null |
141,759 | import atexit
import sys
from importlib.metadata import version
from pathlib import Path
from typing import Dict, Iterable, List, Optional, Tuple
import click
from rich.console import Console
from rich.panel import Panel
from rich.style import Style
from rich.table import Table
from structlog import get_logger
from unb... | null |
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