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#VERBOSE=0 torchrun --nproc_per_node 3 self_contained_pp_LOC.py
import os, random, numpy as np, torch, torch.nn as nn, torch.distributed as dist, torch.nn.functional as F
from torch.optim import AdamW
from torch.utils.data import DataLoader, DistributedSampler
from datasets import load_dataset
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer

STEP, local_rank, world_size, verbose = 0, int(os.environ["LOCAL_RANK"]), int(os.environ["WORLD_SIZE"]), os.environ.get("VERBOSE", "0") == "1"

def set_all_seed(seed):

itsAnanth

import numpy as np

class LogisticRegression:
    def __init__(self, learning_rate=0.01, epochs=1000):
        self.learning_rate = learning_rate
        self.epochs = epochs
        self.weights = None
        self.bias = None

    def sigmoid(self, z):

itsAnanth

// bubble sort in javascript

Array.prototype.bubbleSort = function(callback = (a, b) => a > b) {
    const array = this;
    for (let i = 0; i < array.length; i++) {
        let swaps = 0;
        for (let j = 0; j < array.length - i - 1; j++) {
            if (callback(array[j], array[j + 1])) {
                let temp = array[j];
                array[j] = array[j + 1];