instruction stringclasses 100
values | code stringlengths 78 193k | response stringlengths 259 170k | file stringlengths 59 203 |
|---|---|---|---|
Create Google-style docstrings for my code | import csv
import dataclasses
import json
import html
import os
from contextlib import nullcontext
import gradio as gr
from modules import call_queue, shared, ui_tempdir, util
import modules.images
from modules.ui_components import ToolButton
import modules.infotext_utils as parameters_copypaste
folder_symbol = '\U0... | --- +++ @@ -1,319 +1,322 @@-import csv
-import dataclasses
-import json
-import html
-import os
-from contextlib import nullcontext
-
-import gradio as gr
-
-from modules import call_queue, shared, ui_tempdir, util
-import modules.images
-from modules.ui_components import ToolButton
-import modules.infotext_utils as pa... | https://raw.githubusercontent.com/lllyasviel/stable-diffusion-webui-forge/HEAD/modules/ui_common.py |
Can you add docstrings to this Python file? | import os
import torch
import gradio as gr
from gradio.context import Context
from modules import shared_items, shared, ui_common, sd_models, processing, infotext_utils, paths, ui_loadsave
from backend import memory_management, stream
from backend.args import dynamic_args
from modules.shared import cmd_opts
total_vr... | --- +++ @@ -165,6 +165,7 @@
def ui_refresh_memory_management_settings(model_memory, async_loading, pin_shared_memory):
+ """ Passes precalculated 'model_memory' from "GPU Weights" UI slider (skip redundant calculation) """
refresh_memory_management_settings(
async_loading=async_loading,
pi... | https://raw.githubusercontent.com/lllyasviel/stable-diffusion-webui-forge/HEAD/modules_forge/main_entry.py |
Please document this code using docstrings |
import torch
import math
import struct
import numpy as np
from PIL import Image
import itertools
def calculate_parameters(sd, prefix=""):
params = 0
for k in sd.keys():
if k.startswith(prefix):
w = sd[k]
params += w.nelement()
return params
def weight_dtype(sd, prefix=""... | --- +++ @@ -1,3 +1,20 @@+"""
+ This file is part of ComfyUI.
+ Copyright (C) 2024 Comfy
+
+ This program is free software: you can redistribute it and/or modify
+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ ... | https://raw.githubusercontent.com/lllyasviel/stable-diffusion-webui-forge/HEAD/packages_3rdparty/comfyui_lora_collection/utils.py |
Add docstrings to clarify complex logic | import os
import tempfile
from collections import namedtuple
from pathlib import Path
import gradio.components
import gradio as gr
from PIL import PngImagePlugin
from modules import shared
Savedfile = namedtuple("Savedfile", ["name"])
def register_tmp_file(gradio_app, filename):
if hasattr(gradio_app, 'temp_... | --- +++ @@ -1,178 +1,199 @@-import os
-import tempfile
-from collections import namedtuple
-from pathlib import Path
-
-import gradio.components
-import gradio as gr
-
-from PIL import PngImagePlugin
-
-from modules import shared
-
-
-Savedfile = namedtuple("Savedfile", ["name"])
-
-
-def register_tmp_file(gradio_app, ... | https://raw.githubusercontent.com/lllyasviel/stable-diffusion-webui-forge/HEAD/modules/ui_tempdir.py |
Add docstrings that explain inputs and outputs | import os
import re
from modules import shared
from modules.paths_internal import script_path, cwd
def natural_sort_key(s, regex=re.compile('([0-9]+)')):
return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)]
def listfiles(dirname):
filenames = [os.path.join(dirname, x) for x in ... | --- +++ @@ -1,244 +1,276 @@-import os
-import re
-
-from modules import shared
-from modules.paths_internal import script_path, cwd
-
-
-def natural_sort_key(s, regex=re.compile('([0-9]+)')):
- return [int(text) if text.isdigit() else text.lower() for text in regex.split(s)]
-
-
-def listfiles(dirname):
- filenam... | https://raw.githubusercontent.com/lllyasviel/stable-diffusion-webui-forge/HEAD/modules/util.py |
Write Python docstrings for this snippet | from collections import namedtuple
from copy import copy
from itertools import permutations, chain
import random
import csv
import os.path
from io import StringIO
from PIL import Image
import numpy as np
import modules.scripts as scripts
import gradio as gr
from modules import images, sd_samplers, processing, sd_mode... | --- +++ @@ -1,838 +1,844 @@-from collections import namedtuple
-from copy import copy
-from itertools import permutations, chain
-import random
-import csv
-import os.path
-from io import StringIO
-from PIL import Image
-import numpy as np
-
-import modules.scripts as scripts
-import gradio as gr
-
-from modules import... | https://raw.githubusercontent.com/lllyasviel/stable-diffusion-webui-forge/HEAD/scripts/xyz_grid.py |
Create structured documentation for my script | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import re
from typing import Any, Dict, List, Union
from mvt.android.utils import ROOT_PACKAGES
from .artifact import AndroidAr... | --- +++ @@ -56,6 +56,9 @@
@staticmethod
def parse_dumpsys_package_for_details(output: str) -> Dict[str, Any]:
+ """
+ Parse one entry of a dumpsys package information
+ """
details = {
"uid": "",
"version_name": "",
@@ -134,6 +137,9 @@ return de... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/artifacts/dumpsys_packages.py |
Add verbose docstrings with examples | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
from typing import Any
from .artifact import AndroidArtifact
SUSPICIOUS_MOUNT_POINTS = [
"/system",
"/vendor",
"/pr... | --- +++ @@ -31,8 +31,20 @@
class Mounts(AndroidArtifact):
+ """
+ This artifact parses mount information from /proc/mounts or similar mount data.
+ It can detect potentially suspicious mount configurations that may indicate
+ a rooted or compromised device.
+ """
def parse(self, entry: str) ->... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/artifacts/mounts.py |
Add docstrings explaining edge cases | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import json
import logging
import os
from typing import Callable, Optional, Union
from rich.progress import track
from mvt.comm... | --- +++ @@ -19,6 +19,9 @@
class DownloadAPKs(AndroidExtraction):
+ """DownloadAPKs is the main class operating the download of APKs
+ from the device.
+ """
def __init__(
self,
@@ -26,6 +29,12 @@ all_apks: bool = False,
packages: Optional[list] = None,
) -> None:
+ ... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/cmd_download_apks.py |
Document helper functions with docstrings | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import logging
import os
from pathlib import Path
from typing import List, Optional
from zipfile import ZipFile
from mvt.android... | --- +++ @@ -56,6 +56,9 @@ self.__files: List[str] = []
def from_dir(self, dir_path: str) -> None:
+ """This method is used to initialize the bug report analysis from an
+ uncompressed directory.
+ """
self.__format = "dir"
self.target_path = dir_path
parent... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/cmd_check_bugreport.py |
Add docstrings to improve readability | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import datetime
from typing import List, Optional, Union
import pydantic
import betterproto
from dateutil import parser
from mv... | --- +++ @@ -44,6 +44,11 @@
class TombstoneCrashResult(pydantic.BaseModel):
+ """
+ MVT Result model for a tombstone crash result.
+
+ Needed for validation and serialization, and consistency between text and protobuf tombstones.
+ """
file_name: str
file_timestamp: str # We store the timest... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/artifacts/tombstone_crashes.py |
Fully document this Python code with docstrings | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import logging
import os
import sqlite3
from typing import Optional, Union
from mvt.common.utils import convert_chrometime_to_da... | --- +++ @@ -16,6 +16,7 @@
class ChromeHistory(AndroidExtraction):
+ """This module extracts records from Android's Chrome browsing history."""
def __init__(
self,
@@ -55,6 +56,11 @@ continue
def _parse_db(self, db_path: str) -> None:
+ """Parse a Chrome History datab... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/adb/chrome_history.py |
Auto-generate documentation strings for this file | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import base64
import logging
import os
import random
import string
import sys
import tempfile
import time
from typing import Call... | --- +++ @@ -37,6 +37,7 @@
class AndroidExtraction(MVTModule):
+ """This class provides a base for all Android extraction modules."""
def __init__(
self,
@@ -61,6 +62,7 @@
@staticmethod
def _adb_check_keys() -> None:
+ """Make sure Android adb keys exist."""
if not os.pa... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/adb/base.py |
Create documentation strings for testing functions | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import logging
import os
import sqlite3
from typing import Optional, Union
from mvt.android.parsers.backup import AndroidBackupP... | --- +++ @@ -42,6 +42,7 @@
class SMS(AndroidExtraction):
+ """This module extracts all SMS messages."""
def __init__(
self,
@@ -89,6 +90,11 @@ continue
def _parse_db(self, db_path: str) -> None:
+ """Parse an Android bugle_db SMS database file.
+
+ :param db_pa... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/adb/sms.py |
Generate docstrings with parameter types | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import base64
import logging
import os
import sqlite3
from typing import Optional, Union
from mvt.common.utils import check_for_... | --- +++ @@ -17,6 +17,7 @@
class Whatsapp(AndroidExtraction):
+ """This module extracts all WhatsApp messages containing links."""
def __init__(
self,
@@ -59,6 +60,11 @@ continue
def _parse_db(self, db_path: str) -> None:
+ """Parse an Android msgstore.db WhatsApp dat... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/adb/whatsapp.py |
Write reusable docstrings |
from collections.abc import Hashable
import datetime
import functools
import logging
import random
import re
import time
from typing import Set, List, Optional, Callable, Union
logger = logging.getLogger("schedule")
class ScheduleError(Exception):
pass
class ScheduleValueError(ScheduleError):
pass
cla... | --- +++ @@ -1,3 +1,42 @@+"""
+Python job scheduling for humans.
+
+github.com/dbader/schedule
+
+An in-process scheduler for periodic jobs that uses the builder pattern
+for configuration. Schedule lets you run Python functions (or any other
+callable) periodically at pre-determined intervals using a simple,
+human-fri... | https://raw.githubusercontent.com/dbader/schedule/HEAD/schedule/__init__.py |
Add docstrings to improve code quality | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import fnmatch
import logging
import os
import zipfile
from typing import Any, Dict, List, Optional, Union
from mvt.common.modul... | --- +++ @@ -13,6 +13,7 @@
class AndroidQFModule(MVTModule):
+ """This class provides a base for all Android Data analysis modules."""
def __init__(
self,
@@ -48,6 +49,12 @@ return fnmatch.filter(self.files, pattern)
def _get_device_timezone(self):
+ """
+ Get the devi... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/androidqf/base.py |
Generate docstrings for script automation | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import json
import logging
from typing import Optional
from .base import AndroidQFModule
class RootBinaries(AndroidQFModule):
... | --- +++ @@ -11,6 +11,7 @@
class RootBinaries(AndroidQFModule):
+ """This module analyzes root_binaries.json for root binaries found by androidqf."""
def __init__(
self,
@@ -39,6 +40,7 @@ }
def check_indicators(self) -> None:
+ """Check for indicators of device rooting."""
... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/androidqf/root_binaries.py |
Write docstrings for data processing functions | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
from rich.prompt import Prompt
from mvt.common.config import settings
MVT_ANDROID_BACKUP_PASSWORD = "MVT_ANDROID_BACKUP_PASSWO... | --- +++ @@ -12,6 +12,11 @@
def cli_load_android_backup_password(log, backup_password):
+ """
+ Helper to load a backup password from CLI argument or environment variable
+
+ Used in MVT CLI command parsers.
+ """
password_from_env_or_config = settings.ANDROID_BACKUP_PASSWORD
if backup_password... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/backup/helpers.py |
Document functions with clear intent | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import logging
import json
from typing import Optional
from mvt.android.artifacts.mounts import Mounts as MountsArtifact
from .... | --- +++ @@ -13,6 +13,7 @@
class Mounts(MountsArtifact, AndroidQFModule):
+ """This module extracts and analyzes mount information from AndroidQF acquisitions."""
def __init__(
self,
@@ -34,6 +35,13 @@ self.results = []
def run(self) -> None:
+ """
+ Run the mounts ana... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/modules/androidqf/mounts.py |
Generate docstrings for this script | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import logging
import os
from datetime import datetime
from typing import Optional, Tuple
import requests
import yaml
from packa... | --- +++ @@ -74,6 +74,10 @@ handle.write(str(timestamp))
def get_latest_update(self) -> int:
+ """
+ Check the time of the latest indicator update.
+ Returns 0 if this file doesn't exists.
+ """
if not os.path.exists(self.latest_update_path):
return 0
... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/updates.py |
Add docstrings for better understanding | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
from typing import Optional
import requests
from tld import get_tld
SHORTENER_DOMAINS = [
"0rz.tw",
"1drv.ms",
"1li... | --- +++ @@ -332,6 +332,12 @@ self.is_shortened = False
def get_domain(self) -> str:
+ """Get the domain from a URL.
+
+ :returns: Domain name extracted from URL
+ :rtype: str
+
+ """
return (
get_tld(self.url, as_object=True, fix_protocol=True)
... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/url.py |
Create documentation for each function signature | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
class Artifact:
def __init__(self, *args, **kwargs):
self.results = []
self.detected = []
self.indi... | --- +++ @@ -5,6 +5,9 @@
class Artifact:
+ """
+ Main artifact class
+ """
def __init__(self, *args, **kwargs):
self.results = []
@@ -13,7 +16,13 @@ super().__init__(*args, **kwargs)
def parse(self, entry: str):
+ """
+ Parse the artifact, adds the parsed informa... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/artifact.py |
Write clean docstrings for readability | import os
import yaml
import json
from typing import Tuple, Type, Optional
from appdirs import user_config_dir
from pydantic import AnyHttpUrl, Field
from pydantic_settings import (
BaseSettings,
InitSettingsSource,
PydanticBaseSettingsSource,
SettingsConfigDict,
YamlConfigSettingsSource,
)
MVT_CO... | --- +++ @@ -72,6 +72,9 @@ def save_settings(
self,
) -> None:
+ """
+ Save the current settings to a file.
+ """
if not os.path.isdir(MVT_CONFIG_FOLDER):
os.makedirs(MVT_CONFIG_FOLDER)
@@ -82,6 +85,14 @@
@classmethod
def initialise(cls) -> "MVTSe... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/config.py |
Write clean docstrings for readability | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import glob
import json
import logging
import os
from functools import lru_cache
from typing import Any, Dict, Iterator, List, Op... | --- +++ @@ -23,6 +23,9 @@
class Indicators:
+ """This class is used to parse indicators from a STIX2 file and provide
+ functions to compare extracted artifacts to the indicators.
+ """
def __init__(self, log=logger) -> None:
self.log = log
@@ -38,6 +41,9 @@ self.parse_stix2... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/indicators.py |
Auto-generate documentation strings for this file | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import base64
import binascii
import hashlib
from .artifact import AndroidArtifact
class DumpsysADBArtifact(AndroidArtifact):
... | --- +++ @@ -14,6 +14,9 @@ multiline_fields = ["user_keys", "keystore"]
def indented_dump_parser(self, dump_data):
+ """
+ Parse the indented dumpsys output, generated by DualDumpOutputStream in Android.
+ """
res = {}
stack = [res]
cur_indent = 0
@@ -66,6 +69,9... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/artifacts/dumpsys_adb.py |
Help me add docstrings to my project | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import csv
import json
import logging
import os
import re
from typing import Any, Dict, List, Optional, Union
from .utils import... | --- +++ @@ -26,6 +26,7 @@
class MVTModule:
+ """This class provides a base for all extraction modules."""
enabled = True
slug: Optional[str] = None
@@ -39,6 +40,21 @@ log: logging.Logger = logging.getLogger(__name__),
results: Union[List[Dict[str, Any]], Dict[str, Any], None] = None,... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/module.py |
Add docstrings to improve readability | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import cProfile
import datetime
import hashlib
import json
import logging
import os
import re
from typing import Any, Iterator, U... | --- +++ @@ -17,6 +17,17 @@
class CustomJSONEncoder(json.JSONEncoder):
+ """
+ Custom JSON encoder to handle non-standard types.
+
+ Some modules are storing non-UTF-8 bytes in their results dictionaries.
+ This causes exceptions when the results are being encoded as JSON.
+
+ Of course this means tha... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/common/utils.py |
Add docstrings for production code | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import binascii
import glob
import logging
import multiprocessing
import os
import os.path
import shutil
import sqlite3
from typi... | --- +++ @@ -19,8 +19,17 @@
class DecryptBackup:
+ """This class provides functions to decrypt an encrypted iTunes backup
+ using either a password or a key file.
+
+
+ """
def __init__(self, backup_path: str, dest_path: Optional[str] = None) -> None:
+ """Decrypts an encrypted iOS backup.
+ ... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/ios/decrypt.py |
Add docstrings to make code maintainable | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import hashlib
import logging
import os
import plistlib
from datetime import datetime, timezone
from typing import Any, Dict, Opt... | --- +++ @@ -26,6 +26,7 @@
class Applications(IOSExtraction):
+ """Extract information from accounts installed on the phone."""
def __init__(
self,
@@ -96,6 +97,9 @@ self.detected.append(result)
def _parse_itunes_timestamp(self, entry: Dict[str, Any]) -> None:
+ """
+... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/ios/modules/mixed/applications.py |
Add docstrings following best practices | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import logging
import operator
import sqlite3
from pathlib import Path
from typing import Optional, Union
from mvt.common.utils ... | --- +++ @@ -15,6 +15,8 @@
class NetBase(IOSExtraction):
+ """This class provides a base for DataUsage and NetUsage extraction
+ modules."""
def __init__(
self,
@@ -239,6 +241,7 @@ )
def check_manipulated(self):
+ """Check for missing or manipulate DB entries"""
... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/ios/modules/net_base.py |
Add docstrings to incomplete code |
import numpy as np
import torch as th
from .gaussian_diffusion import GaussianDiffusion, mean_flat
class KarrasDenoiser:
def __init__(self, sigma_data: float = 0.5):
self.sigma_data = sigma_data
def get_snr(self, sigmas):
return sigmas**-2
def get_sigmas(self, sigmas):
return s... | --- +++ @@ -1,3 +1,26 @@+"""
+Based on: https://github.com/crowsonkb/k-diffusion
+
+Copyright (c) 2022 Katherine Crowson
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, in... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/diffusion/k_diffusion.py |
Generate docstrings for this script |
import math
from typing import Any, Dict, Iterable, Optional, Sequence, Union
import blobfile as bf
import numpy as np
import torch as th
import yaml
def diffusion_from_config(config: Union[str, Dict[str, Any]]) -> "GaussianDiffusion":
if isinstance(config, str):
with bf.BlobFile(config, "rb") as f:
... | --- +++ @@ -1,3 +1,6 @@+"""
+Based on https://github.com/openai/glide-text2im/blob/main/glide_text2im/gaussian_diffusion.py
+"""
import math
from typing import Any, Dict, Iterable, Optional, Sequence, Union
@@ -40,6 +43,11 @@
def get_beta_schedule(beta_schedule, *, beta_start, beta_end, num_diffusion_timesteps)... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/diffusion/gaussian_diffusion.py |
Add docstrings to existing functions | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import datetime
import io
import logging
import os
import plistlib
from typing import Optional
from mvt.common.module import Dat... | --- +++ @@ -18,6 +18,7 @@
class Manifest(IOSExtraction):
+ """This module extracts information from a backup Manifest.db file."""
def __init__(
self,
@@ -38,10 +39,22 @@ )
def _get_key(self, dictionary, key):
+ """Unserialized plist objects can have keys which are str or byt... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/ios/modules/backup/manifest.py |
Help me document legacy Python code |
import hashlib
import os
from functools import lru_cache
from typing import Dict, Optional
import requests
import torch
import yaml
from filelock import FileLock
from tqdm.auto import tqdm
MODEL_PATHS = {
"transmitter": "https://openaipublic.azureedge.net/main/shap-e/transmitter.pt",
"decoder": "https://open... | --- +++ @@ -1,3 +1,6 @@+"""
+Adapted from: https://github.com/openai/glide-text2im/blob/69b530740eb6cef69442d6180579ef5ba9ef063e/glide_text2im/download.py
+"""
import hashlib
import os
@@ -46,6 +49,11 @@ def fetch_file_cached(
url: str, progress: bool = True, cache_dir: Optional[str] = None, chunk_size: int = ... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/download.py |
Provide clean and structured docstrings | import math
from typing import Any, Dict, Iterable, List, Optional, Sequence, Tuple
import torch
import torch.nn as nn
from shap_e.models.nn.checkpoint import checkpoint
from .pretrained_clip import FrozenImageCLIP, ImageCLIP, ImageType
from .util import timestep_embedding
def init_linear(l, stddev):
nn.init.n... | --- +++ @@ -201,6 +201,11 @@ )
def forward(self, x: torch.Tensor, t: torch.Tensor):
+ """
+ :param x: an [N x C x T] tensor.
+ :param t: an [N] tensor.
+ :return: an [N x C' x T] tensor.
+ """
assert x.shape[-1] == self.n_ctx
t_embed = self.time_em... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/generation/transformer.py |
Generate helpful docstrings for debugging | from abc import ABC, abstractmethod
from functools import partial
from typing import Any, Dict, Optional, Tuple
import numpy as np
import torch
import torch.nn as nn
from shap_e.models.nn.checkpoint import checkpoint
from shap_e.models.nn.encoding import encode_position, spherical_harmonics_basis
from shap_e.models.n... | --- +++ @@ -16,6 +16,9 @@
class NeRFModel(ABC):
+ """
+ Parametric scene representation whose outputs are integrated by NeRFRenderer
+ """
@abstractmethod
def forward(
@@ -24,9 +27,22 @@ params: Optional[Dict[str, torch.Tensor]] = None,
options: Optional[Dict[str, Any]] = None,... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nerf/model.py |
Add docstrings to improve readability | from functools import partial
from typing import Any, Dict, Optional, Sequence, Tuple, Union
import torch
from shap_e.models.nerf.model import NeRFModel
from shap_e.models.nerf.ray import RayVolumeIntegral, StratifiedRaySampler, render_rays
from shap_e.models.nn.meta import subdict
from shap_e.models.nn.utils import ... | --- +++ @@ -95,6 +95,12 @@ params: Optional[Dict] = None,
options: Optional[AttrDict] = None,
) -> AttrDict:
+ """
+ :param batch: has
+
+ - rays: [batch_size x ... x 2 x 3] specify the origin and direction of each ray.
+ :param options: Optional[Dict]
+ """
... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nerstf/renderer.py |
Generate NumPy-style docstrings | from abc import ABC, abstractmethod
from dataclasses import dataclass
from functools import partial
from typing import Any, Dict, List, Optional, Tuple
import torch
from shap_e.models.nn.utils import sample_pmf
from shap_e.models.volume import Volume, VolumeRange
from shap_e.util.collections import AttrDict
from .mo... | --- +++ @@ -21,6 +21,45 @@ render_with_direction: bool = True,
importance_sampling_options: Optional[Dict[str, Any]] = None,
) -> Tuple["RayVolumeIntegralResults", List["RaySampler"], List[AttrDict]]:
+ """
+ Perform volumetric rendering over a partition of possible t's in the union
+ of rendering vo... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nerf/ray.py |
Document classes and their methods | from functools import partial
from typing import Any, Dict, Optional
import torch
from shap_e.models.nn.meta import subdict
from shap_e.models.renderer import RayRenderer
from shap_e.models.volume import Volume
from shap_e.util.collections import AttrDict
from .model import NeRFModel
from .ray import RayVolumeIntegr... | --- +++ @@ -13,6 +13,10 @@
class TwoStepNeRFRenderer(RayRenderer):
+ """
+ Coarse and fine-grained rendering as proposed by NeRF. This class
+ additionally supports background rendering like NeRF++.
+ """
def __init__(
self,
@@ -32,6 +36,9 @@ device: torch.device = torch.device("... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nerf/renderer.py |
Generate docstrings for this script | import math
from functools import lru_cache
from typing import Optional
import torch
import torch.nn as nn
def encode_position(version: str, *, position: torch.Tensor):
if version == "v1":
freqs = get_scales(0, 10, position.dtype, position.device).view(1, -1)
freqs = position.reshape(-1, 1) * fre... | --- +++ @@ -84,6 +84,12 @@ def forward(
self, channels: torch.Tensor, position: torch.Tensor, direction: torch.Tensor
) -> torch.Tensor:
+ """
+ :param channels: [batch_shape, inner_batch_shape, n_channels, height, width]
+ :param position: [batch_shape, inner_batch_shape, 3, heig... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nn/encoding.py |
Document this module using docstrings | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from shap_e.rendering.view_data import ProjectiveCamera
@dataclass
class DifferentiableCamera(ABC):
@abstractmethod
def camera_rays(self, coords: torch.Tensor) -> ... | --- +++ @@ -10,16 +10,34 @@
@dataclass
class DifferentiableCamera(ABC):
+ """
+ An object describing how a camera corresponds to pixels in an image.
+ """
@abstractmethod
def camera_rays(self, coords: torch.Tensor) -> torch.Tensor:
+ """
+ For every (x, y) coordinate in a rendered ... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nn/camera.py |
Add standardized docstrings across the file | import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from shap_e.util.collections import AttrDict
from .meta import MetaModule, subdict
from .pointnet2_utils import sample_and_group, sample_and_group_all
def gelu(x):
r... | --- +++ @@ -232,6 +232,10 @@ init_scale: float = 1.0,
zero_out: bool = False,
):
+ """
+ Required: d_input, d_hidden, d_output
+ Optional: act_name, bias
+ """
super().__init__()
ds = [d_input] + d_hidden + [d_output]
@@ -364,6 +368,13 @@ sel... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nn/ops.py |
Add docstrings with type hints explained |
import itertools
import re
from collections import OrderedDict
import torch.nn as nn
from shap_e.util.collections import AttrDict
__all__ = [
"MetaModule",
"subdict",
"superdict",
"leveldict",
"leveliter",
"batch_meta_parameters",
"batch_meta_state_dict",
]
def subdict(dictionary, key=... | --- +++ @@ -1,3 +1,28 @@+"""
+Meta-learning modules based on: https://github.com/tristandeleu/pytorch-meta
+
+MIT License
+
+Copyright (c) 2019-2020 Tristan Deleu
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to dea... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nn/meta.py |
Document classes and their methods | from abc import abstractmethod
from typing import Callable, Dict, List, Optional, Tuple
import numpy as np
import torch
from shap_e.models.nn.camera import (
DifferentiableCamera,
DifferentiableProjectiveCamera,
get_image_coords,
projective_camera_frame,
)
from shap_e.models.nn.meta import MetaModule
... | --- +++ @@ -15,6 +15,11 @@
class Renderer(MetaModule):
+ """
+ A rendering abstraction that can render rays and views by calling the
+ appropriate models. The models are instantiated outside but registered in
+ this module.
+ """
@abstractmethod
def render_views(
@@ -23,9 +28,36 @@ ... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/renderer.py |
Add docstrings to improve collaboration | from functools import partial
from typing import Any, Dict, Optional, Tuple
import torch
import torch.nn as nn
from shap_e.models.nn.checkpoint import checkpoint
from shap_e.models.nn.encoding import encode_position, maybe_encode_direction
from shap_e.models.nn.meta import MetaModule, subdict
from shap_e.models.nn.op... | --- +++ @@ -110,6 +110,11 @@ params: Optional[Dict[str, torch.Tensor]] = None,
options: Optional[Dict[str, Any]] = None,
) -> AttrDict:
+ """
+ :param position: [batch_size x ... x 3]
+ :param params: Meta parameters
+ :param options: Optional hyperparameters
+ "... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/stf/mlp.py |
Generate NumPy-style docstrings | from abc import ABC, abstractmethod
from dataclasses import dataclass
from functools import partial
from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
import torch.distributed as dist
import torch.nn as nn
import torch.nn.functional as F
from PIL import Image
from torch import torc... | --- +++ @@ -27,6 +27,10 @@
class TransformerChannelsEncoder(ChannelsEncoder, ABC):
+ """
+ Encode point clouds using a transformer model with an extra output
+ token used to extract a latent vector.
+ """
def __init__(
self,
@@ -95,6 +99,10 @@
class PerceiverChannelsEncoder(ChannelsE... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/transmitter/channels_encoder.py |
Create docstrings for API functions |
from time import time
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
def timeit(tag, t):
print("{}: {}s".format(tag, time() - t))
return time()
def pc_normalize(pc):
l = pc.shape[0]
centroid = np.mean(pc, axis=0)
pc = pc - centroid
m = np.max(np.sqrt(... | --- +++ @@ -1,3 +1,28 @@+"""
+Based on https://github.com/yanx27/Pointnet_Pointnet2_pytorch/blob/master/models/pointnet2_utils.py
+
+MIT License
+
+Copyright (c) 2019 benny
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/nn/pointnet2_utils.py |
Add professional docstrings to my codebase | from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from PIL import Image
from shap_e.models.generation.transformer import Transformer
from shap_e.rendering.view_data import ProjectiveCamera
from shap_e.util.collections impor... | --- +++ @@ -14,6 +14,10 @@
class MultiviewTransformerEncoder(VectorEncoder):
+ """
+ Encode cameras and views using a transformer model with extra output
+ token(s) used to extract a latent vector.
+ """
def __init__(
self,
@@ -125,6 +129,9 @@ return h
def views_to_tensor(... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/transmitter/multiview_encoder.py |
Write docstrings for algorithm functions | from abc import ABC, abstractmethod
from typing import Any, Dict, Optional, Tuple
import torch.nn as nn
from torch import torch
from shap_e.models.renderer import Renderer
from shap_e.util.collections import AttrDict
from .bottleneck import latent_bottleneck_from_config, latent_warp_from_config
from .params_proj imp... | --- +++ @@ -13,12 +13,20 @@
class Encoder(nn.Module, ABC):
def __init__(self, *, device: torch.device, param_shapes: Dict[str, Tuple[int]]):
+ """
+ Instantiate the encoder with information about the renderer's input
+ parameters. This information can be used to create output layers to
+ ... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/transmitter/base.py |
Add structured docstrings to improve clarity | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Dict, Optional, Tuple
import torch
from shap_e.models.nn.meta import MetaModule
from shap_e.models.nn.utils import ArrayType, safe_divide, to_torch
@dataclass
class VolumeRange:
t0: torch.Tensor
t1: torch.Tensor
int... | --- +++ @@ -18,9 +18,18 @@ assert self.t0.shape == self.t1.shape == self.intersected.shape
def next_t0(self):
+ """
+ Given convex volume1 and volume2, where volume1 is contained in
+ volume2, this function returns the t0 at which rays leave volume1 and
+ intersect with volume... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/volume.py |
Write documentation strings for class attributes |
import argparse
import json
import math
import os
import random
import sys
import bpy
from mathutils import Vector
from mathutils.noise import random_unit_vector
MAX_DEPTH = 5.0
FORMAT_VERSION = 6
# Set by main(), these constants are passed to the script to avoid
# duplicating them across multiple files.
UNIFORM_LI... | --- +++ @@ -1,3 +1,9 @@+"""
+Script to run within blender.
+
+Provide arguments after `--`.
+For example: `blender -b -P blender_script.py -- --help`
+"""
import argparse
import json
@@ -267,6 +273,11 @@
def setup_material_extraction_shaders(capturing_material_alpha: bool):
+ """
+ Change every material t... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/blender/blender_script.py |
Create simple docstrings for beginners | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import io
import json
import tarfile
import zlib
from cryptography.hazmat.primitives import hashes, padding
from cryptography.ha... | --- +++ @@ -18,6 +18,7 @@
class AndroidBackupParsingError(Exception):
+ """Exception raised file parsing an android backup file"""
class AndroidBackupNotImplemented(AndroidBackupParsingError):
@@ -44,6 +45,11 @@
def parse_ab_header(data):
+ """
+ Parse the header of an Android Backup file
+ Ret... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/android/parsers/backup.py |
Add docstrings to improve collaboration | import random
from collections import defaultdict
from dataclasses import dataclass
from typing import BinaryIO, Dict, List, Optional, Union
import blobfile as bf
import numpy as np
from shap_e.rendering.view_data import ViewData
from .ply_util import write_ply
COLORS = frozenset(["R", "G", "B", "A"])
def preproc... | --- +++ @@ -21,12 +21,28 @@
@dataclass
class PointCloud:
+ """
+ An array of points sampled on a surface. Each point may have zero or more
+ channel attributes.
+
+ :param coords: an [N x 3] array of point coordinates.
+ :param channels: a dict mapping names to [N] arrays of channel values.
+ """
... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/point_cloud.py |
Add detailed documentation for each class | import random
from typing import Any, List, Optional, Union
import blobfile as bf
import numpy as np
import torch
import torch.nn.functional as F
from PIL import Image
def center_crop(
img: Union[Image.Image, torch.Tensor, np.ndarray]
) -> Union[Image.Image, torch.Tensor, np.ndarray]:
if isinstance(img, (np.... | --- +++ @@ -11,6 +11,9 @@ def center_crop(
img: Union[Image.Image, torch.Tensor, np.ndarray]
) -> Union[Image.Image, torch.Tensor, np.ndarray]:
+ """
+ Center crops an image.
+ """
if isinstance(img, (np.ndarray, torch.Tensor)):
height, width = img.shape[:2]
else:
@@ -33,6 +36,10 @@ ... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/util/image_util.py |
Add docstrings to my Python code | from collections import OrderedDict
from typing import Any, Callable, Dict, List, Optional
from typing import OrderedDict, Generic, TypeVar
K = TypeVar('K')
V = TypeVar('V')
class AttrDict(OrderedDict[K, V], Generic[K, V]):
MARKER = object()
# pylint: disable=super-init-not-called
def __init__(self, *ar... | --- +++ @@ -6,6 +6,11 @@ V = TypeVar('V')
class AttrDict(OrderedDict[K, V], Generic[K, V]):
+ """
+ An attribute dictionary that automatically handles nested keys joined by "/".
+
+ Originally copied from: https://stackoverflow.com/questions/3031219/recursively-access-dict-via-attributes-as-well-as-index-ac... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/util/collections.py |
Create docstrings for all classes and functions | # 不想用 Sphinx，也不像弄一堆静态html文件，所以自己写个咯
import os
import sys
import re
def search_code(py_file_name, section_idx):
with open('../' + py_file_name, encoding='utf-8', mode="r") as f:
content = f.readlines()
content_new, i, search_idx, idx_first_match = [], 0, 0, None
while i < len(content) and search... | --- +++ @@ -1,6 +1,17 @@ # 不想用 Sphinx，也不像弄一堆静态html文件，所以自己写个咯
+'''
+需要从readme中解析出：
+1. "-> Demo code: [examples/demo_pso.py](examples/demo_pso.py)"
+2. 三个```python为开头，三个 ``` 为结尾
+3. 从py文件中读出文本，并替换
+4. 前几行是求star，只在readme中出现
+
+
+需要从py文件中解析出：
+1. # %% 做断点后赋予index值，然后插入readme
+'''
import os
import sys
@@ -8,6 +19,1... | https://raw.githubusercontent.com/guofei9987/blind_watermark/HEAD/docs/make_doc.py |
Fill in missing docstrings in my code | # Mobile Verification Toolkit (MVT)
# Copyright (c) 2021-2023 The MVT Authors.
# Use of this software is governed by the MVT License 1.1 that can be found at
# https://license.mvt.re/1.1/
import glob
import logging
import os
import shutil
import sqlite3
import subprocess
from typing import Iterator, Optional, Union
... | --- +++ @@ -15,6 +15,8 @@
class IOSExtraction(MVTModule):
+ """This class provides a base for all iOS filesystem/backup extraction
+ modules."""
def __init__(
self,
@@ -40,6 +42,11 @@ def _recover_sqlite_db_if_needed(
self, file_path: str, forced: bool = False
) -> None:
+ ... | https://raw.githubusercontent.com/mvt-project/mvt/HEAD/src/mvt/ios/modules/base.py |
Help me document legacy Python code | from dataclasses import dataclass, field
from typing import Dict, Optional
import torch
from .mesh import TriMesh
@dataclass
class TorchMesh:
# [N x 3] array of vertex coordinates.
verts: torch.Tensor
# [M x 3] array of triangles, pointing to indices in verts.
faces: torch.Tensor
# Extra data... | --- +++ @@ -8,6 +8,9 @@
@dataclass
class TorchMesh:
+ """
+ A 3D triangle mesh with optional data at the vertices and faces.
+ """
# [N x 3] array of vertex coordinates.
verts: torch.Tensor
@@ -20,6 +23,9 @@ face_channels: Optional[Dict[str, torch.Tensor]] = field(default_factory=dict)
... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/torch_mesh.py |
Write docstrings describing each step | from dataclasses import dataclass
from typing import Iterable, Optional
import numpy as np
import torch
import shap_e.rendering.mesh
from ._utils import cross_product, normalize
@dataclass
class Rays:
origins: torch.Tensor # [N x 3] float tensor
directions: torch.Tensor # [N x 3] float tensor
def n... | --- +++ @@ -11,6 +11,9 @@
@dataclass
class Rays:
+ """
+ A ray in ray casting.
+ """
origins: torch.Tensor # [N x 3] float tensor
directions: torch.Tensor # [N x 3] float tensor
@@ -21,6 +24,9 @@
@dataclass
class RayCollisions:
+ """
+ The result of casting N rays onto a mesh.
+ ""... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/raycast/types.py |
Write docstrings for algorithm functions | import copy
import inspect
from typing import Any, Callable, List, Sequence, Tuple, Union
import numpy as np
import torch
from pytorch3d.renderer import (
BlendParams,
DirectionalLights,
FoVPerspectiveCameras,
MeshRasterizer,
MeshRenderer,
RasterizationSettings,
SoftPhongShader,
Texture... | --- +++ @@ -211,6 +211,10 @@ diffuse_color: Union[float, Tuple[float]] = BASIC_DIFFUSE_COLOR,
specular_color: Union[float, Tuple[float]] = 0.0,
) -> "BidirectionalLights":
+ """
+ Create a light that attempts to match the light used by the Blender
+ renderer when run with `--light_mode basic`.
+ "... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/pytorch3d_util.py |
Generate docstrings for script automation | from abc import ABC, abstractmethod
from dataclasses import dataclass
from typing import Dict, List, Tuple
import numpy as np
@dataclass
class Camera(ABC):
@abstractmethod
def image_coords(self) -> np.ndarray:
@abstractmethod
def camera_rays(self, coords: np.ndarray) -> np.ndarray:
def depth_d... | --- +++ @@ -7,29 +7,72 @@
@dataclass
class Camera(ABC):
+ """
+ An object describing how a camera corresponds to pixels in an image.
+ """
@abstractmethod
def image_coords(self) -> np.ndarray:
+ """
+ :return: ([self.height, self.width, 2]).reshape(self.height * self.width, 2) imag... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/view_data.py |
Help me document legacy Python code | from abc import abstractmethod
from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
import torch.distributed as dist
import torch.nn as nn
import torch.nn.functional as F
from PIL import Image
from torch import torch
from shap_e.models.generation.perceiver import SimplePerceiver
fro... | --- +++ @@ -19,6 +19,10 @@
class PointCloudTransformerEncoder(VectorEncoder):
+ """
+ Encode point clouds using a transformer model with an extra output
+ token used to extract a latent vector.
+ """
def __init__(
self,
@@ -84,6 +88,10 @@
class PerceiverEncoder(VectorEncoder):
+ "... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/transmitter/pc_encoder.py |
Add docstrings for production code | from typing import Iterable, List, Optional, Union
import numpy as np
import torch
import torch.nn as nn
from PIL import Image
from shap_e.models.download import default_cache_dir
ImageType = Union[np.ndarray, torch.Tensor, Image.Image]
class ImageCLIP(nn.Module):
def __init__(
self,
device: t... | --- +++ @@ -11,6 +11,10 @@
class ImageCLIP(nn.Module):
+ """
+ A wrapper around a pre-trained CLIP model that automatically handles
+ batches of texts, images, and embeddings.
+ """
def __init__(
self,
@@ -67,6 +71,15 @@ texts: Optional[Iterable[Optional[str]]] = None,
e... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/models/generation/pretrained_clip.py |
Add docstrings to meet PEP guidelines | from dataclasses import dataclass, field
from typing import BinaryIO, Dict, Optional, Union
import blobfile as bf
import numpy as np
from .ply_util import write_ply
@dataclass
class TriMesh:
# [N x 3] array of vertex coordinates.
verts: np.ndarray
# [M x 3] array of triangles, pointing to indices in v... | --- +++ @@ -9,6 +9,9 @@
@dataclass
class TriMesh:
+ """
+ A 3D triangle mesh with optional data at the vertices and faces.
+ """
# [N x 3] array of vertex coordinates.
verts: np.ndarray
@@ -25,6 +28,9 @@
@classmethod
def load(cls, f: Union[str, BinaryIO]) -> "TriMesh":
+ """
+ ... | https://raw.githubusercontent.com/openai/shap-e/HEAD/shap_e/rendering/mesh.py |
Write docstrings describing each step | from __future__ import annotations
import functools, math, re, typing
import psutil, pydantic
from pydantic import BeforeValidator
from typing_extensions import override
from openllm.common import BentoInfo, DeploymentTarget, output, Accelerator
def parse_memory_string(v: typing.Any) -> typing.Any:
if isinstance(... | --- +++ @@ -9,6 +9,7 @@
def parse_memory_string(v: typing.Any) -> typing.Any:
+ """Parse memory strings like "60Gi" into float."""
if isinstance(v, str):
match = re.match(r'(\d+(\.\d+)?)\s*Gi$', v, re.IGNORECASE)
if match:
@@ -114,6 +115,9 @@
@functools.lru_cache(typed=True)
def can_run(bento: Bent... | https://raw.githubusercontent.com/bentoml/OpenLLM/HEAD/src/openllm/accelerator_spec.py |
Add detailed docstrings explaining each function | # 2021.06.15-Changed for implementation of TNT model
# Huawei Technologies Co., Ltd. <foss@huawei.com>
import torch
import torch.nn as nn
from functools import partial
import math
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.models.helpers import load_pretrained
from timm.mode... | --- +++ @@ -115,6 +115,8 @@
class Block(nn.Module):
+ """ TNT Block
+ """
def __init__(self, outer_dim, inner_dim, outer_num_heads, inner_num_heads, num_words, mlp_ratio=4.,
qkv_bias=False, qk_scale=None, drop=0., attn_drop=0., drop_path=0., act_layer=nn.GELU,
norm_lay... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/TnT.py |
Add docstrings for utility scripts | # Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the CC-by-NC license found in the
# LICENSE file in the root directory of this source tree.
#
import torch
import torch.nn as nn
from functools import partial
import torch.nn.functional as F
from timm.models.hel... | --- +++ @@ -5,6 +5,9 @@ # LICENSE file in the root directory of this source tree.
#
+'''These modules are adapted from those of timm, see
+https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py
+'''
import torch
import torch.nn as nn
@@ -231,6 +234,8 @@
class Patc... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/ConViT.py |
Generate docstrings with examples |
# --------------------------------------------------------
# Adopted from Swin Transformer
# Modified by Krushi Patel
# --------------------------------------------------------
import torch
import torch.nn as nn
import torch.utils.checkpoint as checkpoint
from timm.models.layers import DropPath, to_2tuple, trunc_norm... | --- +++ @@ -30,6 +30,14 @@
def window_partition(x, window_size):
+ """
+ Args:
+ x: (B, H, W, C)
+ window_size (int): window size
+
+ Returns:
+ windows: (num_windows*B, window_size, window_size, C)
+ """
B, H, W, C = x.shape
x = x.view(B, H // window_size, window_size, W ... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/attention/MOATransformer.py |
Generate docstrings for exported functions | # --------------------------------------------------------
# Swin Transformer V2 reimplementation
# Copyright (c) 2021 Christoph Reich
# Licensed under The MIT License [see LICENSE for details]
# Written by Christoph Reich
# --------------------------------------------------------
import logging
import math
from typing... | --- +++ @@ -1,3 +1,21 @@+""" Swin Transformer V2
+A PyTorch impl of : `Swin Transformer V2: Scaling Up Capacity and Resolution`
+ - https://arxiv.org/pdf/2111.09883
+Code adapted from https://github.com/ChristophReich1996/Swin-Transformer-V2, original copyright/license info below
+This implementation is experimental... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/swin_transformer_v2_cr.py |
Add docstrings for production code | import torch
import torch.nn as nn
from functools import partial
import math
from timm.models.vision_transformer import VisionTransformer, _cfg
from timm.models.registry import register_model
from timm.models.layers import trunc_normal_, DropPath, to_2tuple
import pdb
__all__ = [
'deit_tiny_patch16_224', 'deit_sma... | --- +++ @@ -198,6 +198,8 @@
class PatchEmbed(nn.Module):
# taken from https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py
+ """ Image to Patch Embedding
+ """
def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768):
super().__... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/Container.py |
Add concise docstrings to each method |
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
from timm.models.registry import register_model
from einops import rearrange
from functools import partial
from torch ... | --- +++ @@ -1,3 +1,8 @@+"""
+CoaT architecture.
+
+Modified from timm/models/vision_transformer.py
+"""
import torch
import torch.nn as nn
@@ -33,6 +38,7 @@
class Mlp(nn.Module):
+ """ Feed-forward network (FFN, a.k.a. MLP) class. """
def __init__(self, in_features, hidden_features=None, out_features=N... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/CoaT.py |
Add minimal docstrings for each function | # Copyright 2021 Sea Limited.
#
# 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,... | --- +++ @@ -11,6 +11,9 @@ # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
+"""
+Vision OutLOoker (VOLO) implementation
+"""
import torch
import torch.nn as nn
import torch.nn.functional... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/VOLO.py |
Create docstrings for reusable components | import torch
import torch.nn as nn
from functools import partial
import pickle
from torch.nn.parameter import Parameter
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.models.helpers import load_pretrained
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
from timm.models.re... | --- +++ @@ -1,3 +1,6 @@+"""
+Code for DeepViT. The implementation has heavy reference to timm.
+"""
import torch
import torch.nn as nn
from functools import partial
@@ -65,6 +68,10 @@ x = self.proj_drop(x)
return x, attn
class ReAttention(nn.Module):
+ """
+ It is observed that similarity al... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/DViT.py |
Create Google-style docstrings for my code | import numpy as np
import torch
from torch import nn
from torch.nn import init
class MobileViTv2Attention(nn.Module):
def __init__(self, d_model):
super(MobileViTv2Attention, self).__init__()
self.fc_i = nn.Linear(d_model,1)
self.fc_k = nn.Linear(d_model, d_model)
self.fc_v = nn.... | --- +++ @@ -6,8 +6,17 @@
class MobileViTv2Attention(nn.Module):
+ '''
+ Scaled dot-product attention
+ '''
def __init__(self, d_model):
+ '''
+ :param d_model: Output dimensionality of the model
+ :param d_k: Dimensionality of queries and keys
+ :param d_v: Dimensionality... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/attention/MobileViTv2Attention.py |
Create docstrings for each class method | import math
from functools import partial
import torch
from torch import nn
from torch.nn import functional as F
class SwishImplementation(torch.autograd.Function):
@staticmethod
def forward(ctx, i):
result = i * torch.sigmoid(i)
ctx.save_for_backward(i)
return result
@staticmetho... | --- +++ @@ -24,6 +24,7 @@
def drop_connect(inputs, p, training):
+ """ Drop connect. """
if not training: return inputs
batch_size = inputs.shape[0]
keep_prob = 1 - p
@@ -38,11 +39,15 @@ return partial(Conv2dStaticSamePadding, image_size=image_size)
def get_width_and_height_from_size(x):
+... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/conv/MBConv.py |
Write reusable docstrings | import torch.nn as nn
import torch.nn.functional as F
import torch
from einops.layers.torch import Rearrange
from einops import rearrange
import numpy as np
from typing import Any, List
import math
import warnings
from collections import OrderedDict
__all__ = ['ConTBlock', 'ConTNet']
r""" The following trunc_norm... | --- +++ @@ -55,6 +55,22 @@
def trunc_normal_(tensor, mean=0., std=1., a=-2., b=2.):
# type: (Tensor, float, float, float, float) -> Tensor
+ r"""Fills the input Tensor with values drawn from a truncated
+ normal distribution. The values are effectively drawn from the
+ normal distribution :math:`\mathca... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/ConTNet.py |
Document helper functions with docstrings | # --------------------------------------------------------
# Swin Transformer
# Copyright (c) 2021 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu
# --------------------------------------------------------
import logging
import math
from typing import Optional
import torch
impo... | --- +++ @@ -1,3 +1,11 @@+""" Swin Transformer
+A PyTorch impl of : `Swin Transformer: Hierarchical Vision Transformer using Shifted Windows`
+ - https://arxiv.org/pdf/2103.14030
+Code/weights from https://github.com/microsoft/Swin-Transformer, original copyright/license info below
+S3 (AutoFormerV2, https://arxiv.or... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/swin_transformer.py |
Generate NumPy-style docstrings | import numpy as np
import torch
from torch import nn
from torch.nn import init
class SimplifiedScaledDotProductAttention(nn.Module):
def __init__(self, d_model, h,dropout=.1):
super(SimplifiedScaledDotProductAttention, self).__init__()
self.d_model = d_model
self.d_k = d_model//h
... | --- +++ @@ -6,8 +6,17 @@
class SimplifiedScaledDotProductAttention(nn.Module):
+ '''
+ Scaled dot-product attention
+ '''
def __init__(self, d_model, h,dropout=.1):
+ '''
+ :param d_model: Output dimensionality of the model
+ :param d_k: Dimensionality of queries and keys
+ ... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/attention/SimplifiedSelfAttention.py |
Add docstrings to incomplete code | # Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
# This source code is licensed under the license found in the
# LICENSE file in the root directory of this source tree.
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.models.layers import trunc_normal_, DropPath... | --- +++ @@ -11,6 +11,12 @@ from timm.models.layers import trunc_normal_, DropPath
class Block(nn.Module):
+ """ ConvNeXtV2 Block.
+
+ Args:
+ dim (int): Number of input channels.
+ drop_path (float): Stochastic depth rate. Default: 0.0
+ """
def __init__(self, dim, drop_path=0.):
... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/convnextv2.py |
Add minimal docstrings for each function | # --------------------------------------------------------
# Swin Transformer V2
# Copyright (c) 2022 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ze Liu
# --------------------------------------------------------
import math
from typing import Tuple, Optional
import torch
import to... | --- +++ @@ -1,3 +1,9 @@+""" Swin Transformer V2
+A PyTorch impl of : `Swin Transformer V2: Scaling Up Capacity and Resolution`
+ - https://arxiv.org/abs/2111.09883
+Code/weights from https://github.com/microsoft/Swin-Transformer, original copyright/license info below
+Modifications and additions for timm hacked toge... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/swin_transformer_v2.py |
Add documentation for all methods | from functools import partial
from typing import List
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
from timm.layers import SelectAdaptivePool2d, Linear, create_conv2d, get_norm_act_... | --- +++ @@ -1,3 +1,8 @@+""" MobileNet V3
+A PyTorch impl of MobileNet-V3, compatible with TF weights from official impl.
+Paper: Searching for MobileNetV3 - https://arxiv.org/abs/1905.02244
+Hacked together by / Copyright 2019, Ross Wightman
+"""
from functools import partial
from typing import List
@@ -100,6 +105,... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/MobileNetV3.py |
Write docstrings for utility functions | import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
from timm.models.registry import register_model
from timm.models.vision_transformer import _cfg
from timm.models.vision_transformer import Block as TimmBloc... | --- +++ @@ -30,6 +30,9 @@
class GroupAttention(nn.Module):
+ """
+ LSA: self attention within a group
+ """
def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, attn_drop=0., proj_drop=0., ws=1):
assert ws != 1
super(GroupAttention, self).__init__()
@@ -69,6 +72,9 @@
... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/CPVT.py |
Add verbose docstrings with examples | ## Author: Jianyuan Guo (jyguo@pku.edu.cn)
import math
import logging
from functools import partial
from collections import OrderedDict
import torch
import torch.nn as nn
import torch.nn.functional as F
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.models.helpers import load_pretrained
... | --- +++ @@ -154,6 +154,8 @@
class PatchEmbed(nn.Module):
+ """ Image to Patch Embedding
+ """
def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768):
super().__init__()
img_size = to_2tuple(img_size)
@@ -372,6 +374,7 @@
def checkpoint_filter_fn(state_dict, model)... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/CMT.py |
Include argument descriptions in docstrings | import math
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import partial
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
from timm.models.registry import register_model
from timm.models.vision_transformer import default_cfgs, _cfg
__all__ = [
'ceit_tiny_patch... | --- +++ @@ -201,6 +201,9 @@
class HybridEmbed(nn.Module):
+ """ CNN Feature Map Embedding
+ Extract feature map from CNN, flatten, project to embedding dim.
+ """
def __init__(self, backbone, img_size=224, patch_size=16, feature_size=None, in_chans=3, embed_dim=768):
super().__init__()
... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/CeiT.py |
Write docstrings including parameters and return values | import numpy as np
import torch
from torch import nn
from torch.nn import init
class ScaledDotProductAttention(nn.Module):
def __init__(self, d_model, d_k, d_v, h,dropout=.1):
super(ScaledDotProductAttention, self).__init__()
self.fc_q = nn.Linear(d_model, h * d_k)
self.fc_k = nn.Linear(... | --- +++ @@ -6,8 +6,17 @@
class ScaledDotProductAttention(nn.Module):
+ '''
+ Scaled dot-product attention
+ '''
def __init__(self, d_model, d_k, d_v, h,dropout=.1):
+ '''
+ :param d_model: Output dimensionality of the model
+ :param d_k: Dimensionality of queries and keys
+ ... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/attention/SelfAttention.py |
Add docstrings to clarify complex logic | import os
import copy
import torch
import torch.nn as nn
from typing import Dict
import itertools
from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
from timm.models.layers import DropPath, trunc_normal_
from timm.models.registry import register_model
from timm.models.layers.helpers import to_2tuple
E... | --- +++ @@ -1,3 +1,6 @@+"""
+EfficientFormer
+"""
import os
import copy
import torch
@@ -94,6 +97,11 @@
class Embedding(nn.Module):
+ """
+ Patch Embedding that is implemented by a layer of conv.
+ Input: tensor in shape [B, C, H, W]
+ Output: tensor in shape [B, C, H/stride, W/stride]
+ """
... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/EfficientFormer.py |
Write docstrings for data processing functions | # Copyright IBM All Rights Reserved.
# SPDX-License-Identifier: Apache-2.0
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.hub
from functools import partial
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
from timm.models.registry import register_model
from timm.mo... | --- +++ @@ -2,6 +2,10 @@ # SPDX-License-Identifier: Apache-2.0
+"""
+Modifed from Timm. https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/vision_transformer.py
+
+"""
import torch
import torch.nn as nn
@@ -30,6 +34,8 @@
class PatchEmbed(nn.Module):
+ """ Image to Patch Embedding
+... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/backbone/CrossViT.py |
Document this script properly | import torch
import torch.nn as nn
import torch.utils.checkpoint as checkpoint
from timm.models.layers import DropPath, to_2tuple, trunc_normal_
class Mlp(nn.Module):
def __init__(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.):
super().__init__()
out_featur... | --- +++ @@ -62,6 +62,17 @@ return flops
class Attention(nn.Module):
+ r""" Multi-head self attention module with dynamic position bias.
+
+ Args:
+ dim (int): Number of input channels.
+ group_size (tuple[int]): The height and width of the group.
+ num_heads (int): Number of attent... | https://raw.githubusercontent.com/xmu-xiaoma666/External-Attention-pytorch/HEAD/model/attention/Crossformer.py |
Generate docstrings for script automation | import requests
import base64
import os
import tempfile
import git
import time
import fnmatch
from typing import Union, Set, List, Dict, Tuple, Any
from urllib.parse import urlparse
def crawl_github_files(
repo_url,
token=None,
max_file_size: int = 1 * 1024 * 1024, # 1 MB
use_relative_paths: bool = ... | --- +++ @@ -16,6 +16,26 @@ include_patterns: Union[str, Set[str]] = None,
exclude_patterns: Union[str, Set[str]] = None
):
+ """
+ Crawl files from a specific path in a GitHub repository at a specific commit.
+
+ Args:
+ repo_url (str): URL of the GitHub repository with specific path and commi... | https://raw.githubusercontent.com/The-Pocket/PocketFlow-Tutorial-Codebase-Knowledge/HEAD/utils/crawl_github_files.py |
Add docstrings to existing functions | # this script is modified from https://github.com/MCG-NKU/AMT/blob/main/demos/demo_2x.py
from json import load
import os
import cv2
import sys
import glob
import torch
import argparse
import numpy as np
import os.path as osp
from warnings import warn
from omegaconf import OmegaConf
from torchvision.utils import make_gr... | --- +++ @@ -34,6 +34,9 @@
def init(device="cuda"):
+ '''
+ initialize the device and the anchor resolution.
+ '''
if device == 'cuda':
anchor_resolution = 1024 * 512
@@ -52,6 +55,17 @@
def get_input_video_from_path(input_path, device="cuda"):
+ '''
+ Get the input video fr... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/models/frame_interpolation/interpolation.py |
Document my Python code with docstrings | import math
from typing import TypeVar, Optional, Iterator
import torch
from torch.utils.data import Sampler, Dataset
import torch.distributed as dist
T_co = TypeVar('T_co', covariant=True)
class CustomDistributedSampler(Sampler[T_co]):
def __init__(self, dataset: Dataset, num_replicas: Optional[int] = None,
... | --- +++ @@ -7,6 +7,53 @@
T_co = TypeVar('T_co', covariant=True)
class CustomDistributedSampler(Sampler[T_co]):
+ r"""Sampler that restricts data loading to a subset of the dataset.
+
+ It is especially useful in conjunction with
+ :class:`torch.nn.parallel.DistributedDataParallel`. In such a case, each
+ ... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/models/causalvideovae/dataset/ddp_sampler.py |
Add well-formatted docstrings | import torch
import torch_npu
import torch.distributed as dist
import os
try:
from lcalib.functional import lcal_initialize
enable_LCCL = True
except:
lcal_initialize = None
enable_LCCL = False
class COMM_INFO:
def __init__(self):
self.group = None
self.world_size = 0
self.ra... | --- +++ @@ -31,6 +31,7 @@ return _SEQUENCE_PARALLEL_STATE
def initialize_sequence_parallel_group(sequence_parallel_size):
+ """Initialize the sequence parallel group."""
rank = int(os.getenv('RANK', '0'))
world_size = int(os.getenv("WORLD_SIZE", '1'))
assert world_size % sequence_parallel_size ... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/acceleration/parallel_states.py |
Generate docstrings with examples | import torch
from einops import rearrange, repeat
from typing import Any, Dict, Optional, Tuple
import torch
import torch.nn.functional as F
from torch import nn
from diffusers.models.attention_processor import Attention as Attention_
try:
import torch_npu
from opensora.npu_config import npu_config, set_run_dty... | --- +++ @@ -18,6 +18,7 @@ from opensora.utils.communications import all_to_all_SBH
class PatchEmbed2D(nn.Module):
+ """2D Image to Patch Embedding but with video"""
def __init__(
self,
@@ -41,6 +42,7 @@
class PositionGetter3D(object):
+ """ return positions of patches """
def __i... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/models/diffusion/common.py |
Create documentation for each function signature | import os.path as osp
import random
from glob import glob
from torchvision import transforms
import numpy as np
import torch
import torch.utils.data as data
import torch.nn.functional as F
from torchvision.transforms import Lambda
from ..dataset.transform import ToTensorVideo, CenterCropVideo
from ..utils.dataset_uti... | --- +++ @@ -13,6 +13,20 @@ from ..utils.dataset_utils import DecordInit
def TemporalRandomCrop(total_frames, size):
+ """
+ Performs a random temporal crop on a video sequence.
+
+ This function randomly selects a continuous frame sequence of length `size` from a video sequence.
+ `total_frames` indicate... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/models/causalvideovae/model/dataset_videobase.py |
Generate NumPy-style docstrings |
import torch
import torch.nn as nn
from torchvision import models
from collections import namedtuple
from .....utils.taming_download import get_ckpt_path
class LPIPS(nn.Module):
# Learned perceptual metric
def __init__(self, use_dropout=True):
super().__init__()
self.scaling_layer = ScalingLay... | --- +++ @@ -1,3 +1,4 @@+"""Stripped version of https://github.com/richzhang/PerceptualSimilarity/tree/master/models"""
import torch
import torch.nn as nn
@@ -62,6 +63,7 @@
class NetLinLayer(nn.Module):
+ """ A single linear layer which does a 1x1 conv """
def __init__(self, chn_in, chn_out=1, use_dropou... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/models/causalvideovae/model/losses/lpips.py |
Generate docstrings for each module |
import inspect
from typing import Callable, Dict, List, Optional, Tuple, Union
from dataclasses import dataclass
import numpy as np
import torch
from einops import rearrange
from transformers import CLIPTextModelWithProjection, CLIPTokenizer, CLIPImageProcessor, MT5Tokenizer, T5EncoderModel
from diffusers.pipelines.s... | --- +++ @@ -34,6 +34,10 @@
# Copied from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion.rescale_noise_cfg
def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0):
+ """
+ Rescale `noise_cfg` according to `guidance_rescale`. Based on findings of [Common Diffusion Noise Schedules ... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/sample/pipeline_opensora.py |
Create documentation for each function signature | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import os
import re
import stat
import torch
import hashlib
from collections import defaultdict, OrderedDict, deque
from shutil import copyfile
import gc
from torch.nn.modules import Module
from torch.nn.parameter import Pa... | --- +++ @@ -140,6 +140,7 @@
class EngineTimers(object):
+ r"""Wallclock timers for DeepSpeedEngine"""
def __init__(self, enable_micro_timers, enable_global_timers):
self.forward_timers = []
@@ -174,6 +175,7 @@
class DeepSpeedEngine(Module):
+ r"""DeepSpeed engine for training."""
de... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/adaptor/engine.py |
Document my Python code with docstrings | import torch
import random
import numbers
from torchvision.transforms import RandomCrop, RandomResizedCrop
import statistics
import numpy as np
import ftfy
import regex as re
import html
def _is_tensor_video_clip(clip):
if not torch.is_tensor(clip):
raise TypeError("clip should be Tensor. Got %s" % type(c... | --- +++ @@ -20,6 +20,10 @@
def center_crop_arr(pil_image, image_size):
+ """
+ Center cropping implementation from ADM.
+ https://github.com/openai/guided-diffusion/blob/8fb3ad9197f16bbc40620447b2742e13458d2831/guided_diffusion/image_datasets.py#L126
+ """
while min(*pil_image.size) >= 2 * image_si... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/dataset/transform.py |
Write beginner-friendly docstrings | # Copyright (c) Microsoft Corporation.
# SPDX-License-Identifier: Apache-2.0
# DeepSpeed Team
import torch
import os
import pdb
from deepspeed import comm as dist
from packaging import version as pkg_version
from collections import OrderedDict
from torch._utils import _flatten_dense_tensors, _unflatten_dense_tensors
... | --- +++ @@ -119,6 +119,16 @@
class DeepSpeedZeroOptimizer(ZeROOptimizer):
+ """
+ DeepSpeedZeroOptimizer designed to reduce the memory footprint
+ required for training large deep learning models.
+
+ For more details please see ZeRO: Memory Optimization Towards Training A Trillion Parameter Models
+ ... | https://raw.githubusercontent.com/PKU-YuanGroup/Open-Sora-Plan/HEAD/opensora/adaptor/stage_1_and_2.py |
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