drbh

# /// script
# dependencies = [
#   "numpy",
#   "torch",
#   "kernels",
#   "pandas",
#   "matplotlib"
# ]
# ///
# Benchmarking common shapes for Flux 1024x1024px image + varying text sequence lengths

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///
import torch
import torch.nn as nn

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///
import torch

# reuse the models from the previous snippets or copy the class

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///
import torch
import torch.nn as nn

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///

import torch
import torch.nn.functional as F

drbh

# /// script
# dependencies = [
#  "numpy",
#  "torch",
#  "kernels",
# ]
# ///

import torch

drbh

# /// script
# dependencies = [
#   "requests<3",
# ]
# ///

import requests
import concurrent.futures
import time
from datetime import datetime

drbh

// Roku device IP address
const rokuIp = "192.168.1.252";
// Base URL for ECP commands
const baseUrl = `http://${rokuIp}:8060/keypress`;
// Delay between commands in milliseconds
const delay = 3000;

async function sendKeypress(command) {
    try {
        const response = await fetch(`${baseUrl}/${command}`, { method: 'POST' });

drbh

from collections import deque
import time
from dataclasses import dataclass
from typing import Deque, List, Dict
import requests
import os


class Colors:
    PURPLE = "\033[95m"

drbh

from openai import OpenAI

ENDPOINT_URL = "ENDPOINT_URL"
HF_TOKEN = "YOUR_TOKEN"

# Initialize the client, pointing it to one of the available models
client = OpenAI(
    base_url=ENDPOINT_URL + "/v1/",
    api_key=HF_TOKEN,
)