hopezh

import torch
from torch import nn
from torch.utils.data import DataLoader
from torchvision import datasets
from torchvision.transforms import ToTensor

print("PyTorch version:", torch.__version__)

# ------------------------------------------------------------------------------
# download training data

hopezh

import "./style.css";
import ReactDOM from "react-dom/client";
// import * as THREE from "three";
import { Canvas } from "@react-three/fiber";
import Episode from "./Episode.js";
import * as THREE from "three";
import React from 'react'
import Plot from 'react-plotly.js'

const root = ReactDOM.createRoot(document.querySelector("#root"));

hopezh

hopezh

{	
	"editor.fontFamily": "JetBrains Mono, Consolas, 'Courier New', monospace",
	"editor.formatOnSave": true,
	"editor.rulers": [80], 
	"editor.scrollBeyondLastLine": false,

	"git.autofetch": true,
	
	"prettier.useTabs": true,
	"prettier.tabWidth": 4,

hopezh

hopezh

from tqdm import tqdm
import torch
import time
from datetime import timedelta

@torch.jit.script
def foo():
    x = torch.ones((1024 * 12, 1024 * 12), dtype=torch.float32)
    y = torch.ones((1024 * 12, 1024 * 12), dtype=torch.float32)
    z = x + y