Marat Mkhitaryan mmkhitaryan

Disk space issue

In my case I used container which had size of 12GB. It contained yolo model for inference, so the container was large. By default the size of template for ECS ec2 is 30GB, so it could not conain entire OS+Image.

The solution was changing the template root storage to 100GB.

Card type issue

Another case of PROVISIONING stuck was with spot instances. I wanted to save on inference costs, so wanted to run spot instead of on-Demand.

I set the filter to GPU accelerator, and selected all the instances which had GPU. The issue was that there are also non-ndidia GPUs in AWS. So Nvidia driver linux got installed on AMD machines, and the tasks got stuck in PROVISIONING state.

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	"basics": {
	"name": "Marat Mkhitaryan",
	"label": "Python Backend Developer",
	"location": "Astana, Kazakhstan",
	"email": "[email protected]",
	"phone": "77082113945",
	"profiles": [
	{

	import datetime

	from tortoise import Tortoise, fields, timezone
	from tortoise.models import Model

	NAIVE_DATETIME = datetime.datetime.strptime("2024-2-11","%Y-%m-%d")

	class TortoiseModel(Model):
	name = fields.CharField(max_length=50, unique=True)
	last_register_date = fields.DatetimeField()

	function sleep(ms) {
	return new Promise(resolve => setTimeout(resolve, ms));
	}

	function generateRandomString() {
	const randomChar1 = String.fromCharCode(Math.floor(Math.random() * 26) + 65); // Random uppercase letter
	const randomChar2 = String.fromCharCode(Math.floor(Math.random() * 26) + 65); // Another random uppercase letter

	// Concatenate the two characters
	const randomString = randomChar1 + randomChar2;

	from collections import defaultdict

	pid_to_command_line = {}

	list_of_all_processes = []

	import csv

	field_names = None

	import r2pipe

	r = r2pipe.open()

	r.cmd('ood')
	r.cmd('dcu @main')

	last_pointer = '1'
	while True:
	poiner_from_stack = str(r.cmdj('pxqj 8 @rsp')[0])

	kubeadm init --config /etc/kubeadm/init.yaml --upload-certs --ignore-preflight-errors=Port-6443

	# r2 /bin/ls
	# . ./run_in_r2.py
	# 1
	# 2
	# ... 1000+

	import r2pipe

	r = r2pipe.open()

	# python stack_seeker.py some_file_in_cwd
	import r2pipe
	import sys

	r = r2pipe.open('/bin/ls')

	r.cmd('ood')
	r.cmd('aaa')
	file_name = sys.argv[1]

	#include <stdio.h>
	#include <unistd.h>

	void
	f (int n)
	{
	printf ("Number: %d\n", n);
	}

	int