leimao

import onnxruntime
import numpy as np
import time
from onnxruntime.datasets import get_example

# ONNXRuntime API Documentation
# https://microsoft.github.io/onnxruntime/python/api_summary.html

log_severity_level = 0
model_name = "logreg_iris.onnx"

leimao

#include <iostream>
#include <limits>
using namespace std;

int main(){
	char var[10];
	bool valid = false;

	while(!valid){
		cout << "Enter a string 9 characters long: ";

leimao

#include "class.h"

Test::Test(int a, int b): mA{a}, mB{b}
{
}

int Test::getA()
{
    return this->mA;
}

leimao

from __future__ import annotations
from typing import IO
import asyncio
import sys
import contextlib
import aiofiles.threadpool

from chat_streams import split_lines, write, handle_writes

async def handle_reads(reader: asyncio.StreamReader) -> None:

leimao

mkdir coco
cd coco
mkdir images
cd images

wget http://images.cocodataset.org/zips/train2017.zip
wget http://images.cocodataset.org/zips/val2017.zip
wget http://images.cocodataset.org/zips/test2017.zip
wget http://images.cocodataset.org/zips/unlabeled2017.zip

leimao

import torch
from torch.utils.data.distributed import DistributedSampler
from torch.utils.data import DataLoader
import torch.nn as nn
import torch.optim as optim

import torchvision
import torchvision.transforms as transforms

import argparse

leimao

from typing import Iterable, List, Union, Set


class Graph:
    def __init__(self) -> None:

        # Adjacency set representation.
        # key: node name, value: adjacency node name set.
        self.edges = dict()

leimao

import torch
from torch.utils.data.distributed import DistributedSampler
from torch.utils.data import DataLoader
import torch.nn as nn
import torch.optim as optim

import torchvision
import torchvision.transforms as transforms

import argparse

leimao

import argparse
import os
from filelock import FileLock

import torch.multiprocessing as mp
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torchvision import datasets, transforms
import torch.utils.data.distributed

leimao

mkdir -p n01440764	
mkdir -p n01443537	
mkdir -p n01484850	
mkdir -p n01491361	
mkdir -p n01494475	
mkdir -p n01496331	
mkdir -p n01498041	
mkdir -p n01514668	
mkdir -p n01514859	
mkdir -p n01518878