hotbaby

# Inspired by https://github.com/vpenso/ganglia-sensors/blob/master/lib/python_modules/infiniband.py#/

import logging
import re
import sys
import json
import time
import subprocess

hotbaby

hotbaby

# encoding: utf8

import json
import torch
import argparse
import whisper
from whisper import Whisper, ModelDimensions
from torch.utils.data import Dataset, DataLoader

from lightning import Trainer

hotbaby

# encoding: utf8

import logging
import torch
import torch.distributed
from torch.distributed import ReduceOp


def print_rank_0(msg, *args, **kwargs):
    rank = torch.distributed.get_rank()

hotbaby

# encoding: utf8

import math
import torch
import torch.nn as nn


class MultiHeadAttention(nn.Module):

    def __init__(self, n_feat, n_head=4):

hotbaby

# encoding: utf8

import os
import torch
import torch.distributed as dist
import torch.multiprocessing as mp


def cm_broadcast_object_demo(rank: int, world_size: int):
    dist.init_process_group("gloo", world_size=world_size, rank=rank)

hotbaby

# encoding: utf8

import os
import time
import random
import contextlib
import torch
import torch.nn as nn
import torch.optim as optim
import torch.distributed as dist

hotbaby

l = [[1, 1675, 4028, 8271, 42, 2], [1, 1675, 4028, 8844, 10135, 10757, 9478, 42, 2]]

# maximum rows and columns
max_rows = len(l)
max_cols = max(len(row) for row in l)

# padded rows
padded = [row + [0] * (max_cols - len(row)) for row in l]

# unpack nested list