






"""simple docstring"""







#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-test.py
#
# You may need to add --master_addr $MASTER_ADDR --master_port $MASTER_PORT if using a custom addr:port
#
# You can also use the rdzv API: --rdzv_endpoint $MASTER_ADDR:$MASTER_PORT --rdzv_backend c10d
#
# use torch.distributed.launch instead of torch.distributed.run for torch < 1.9
#
# If you get a hanging in `barrier` calls you have some network issues, you may try to debug this with:
#
# NCCL_DEBUG=INFO python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-test.py
#
# which should tell you what's going on behind the scenes.
#
#
# This script can be run via `srun` in the SLURM environment as well. Here is a SLURM script that
# runs on 2 nodes of 4 gpus per node:
#
# #SBATCH --job-name=test-nodes        # name
# #SBATCH --nodes=2                    # nodes
# #SBATCH --ntasks-per-node=1          # crucial - only 1 task per dist per node!
# #SBATCH --cpus-per-task=10           # number of cores per tasks
# #SBATCH --gres=gpu:4                 # number of gpus
# #SBATCH --time 0:05:00               # maximum execution time (HH:MM:SS)
# #SBATCH --output=%x-%j.out           # output file name
#
# GPUS_PER_NODE=4
# MASTER_ADDR=$(scontrol show hostnames $SLURM_JOB_NODELIST | head -n 1)
# MASTER_PORT=6000
#
# srun --jobid $SLURM_JOBID bash -c 'python -m torch.distributed.run \
# --nproc_per_node $GPUS_PER_NODE --nnodes $SLURM_NNODES --node_rank $SLURM_PROCID \
# --master_addr $MASTER_ADDR --master_port $MASTER_PORT \
# torch-distributed-gpu-test.py'
#

import fcntl
import os
import socket

import torch
import torch.distributed as dist

def _a			(		*_snake_case							):







      """simple docstring"""






      with open(_snake_case				,	"""r"""							) as fh:
            fcntl.flock(_snake_case				,	fcntl.LOCK_EX							)
            try:
                  print(*_snake_case							)
            finally:
                  fcntl.flock(_snake_case				,	fcntl.LOCK_UN							)


_UpperCamelCase					      =  int(os.environ["""LOCAL_RANK"""])
torch.cuda.set_device(local_rank)
_UpperCamelCase					      =  torch.device("""cuda""", local_rank)
_UpperCamelCase					      =  socket.gethostname()

_UpperCamelCase					      =  F"""[{hostname}-{local_rank}]"""

try:
  # test distributed
  dist.init_process_group("""nccl""")
  dist.all_reduce(torch.ones(1).to(device), op=dist.ReduceOp.SUM)
  dist.barrier()

  # test cuda is available and can allocate memory
  torch.cuda.is_available()
  torch.ones(1).cuda(local_rank)

  # global rank
  _UpperCamelCase					      =  dist.get_rank()
  _UpperCamelCase					      =  dist.get_world_size()

  printflock(F"""{gpu} is OK (global rank: {rank}/{world_size})""")

  dist.barrier()
  if rank == 0:
    printflock(F"""pt={torch.__version__}, cuda={torch.version.cuda}, nccl={torch.cuda.nccl.version()}""")

except Exception:
  printflock(F"""{gpu} is broken""")
  raise











"""simple docstring"""







from __future__ import annotations

import json

import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent

_UpperCamelCase					      =  {"""UserAgent""": UserAgent().random}

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	script.contents[0]
      UpperCAmelCase          =	json.loads(data[data.find("""{\"config\""""							) : -1]							)
      return info["entry_data"]["ProfilePage"][0]["graphql"]["user"]







class  lowerCamelCase__ :






    def __init__(			self     ,A ):
          UpperCAmelCase          =	F'''https://www.instagram.com/{username}/'''
          UpperCAmelCase          =	self.get_json()






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	requests.get(self.url     ,headers=A ).text
          UpperCAmelCase          =	BeautifulSoup(A     ,"""html.parser""" ).find_all("""script""" )
          try:
                return extract_user_profile(scripts[4] )
          except (json.decoder.JSONDecodeError, KeyError):
                return extract_user_profile(scripts[3] )






    def __repr__(			self ):
          return F'''{self.__class__.__name__}(\'{self.username}\')'''






    def __str__(			self ):
          return F'''{self.fullname} ({self.username}) is {self.biography}'''






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["username"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["full_name"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["biography"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["business_email"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["external_url"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["edge_followed_by"]["count"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["edge_follow"]["count"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["edge_owner_to_timeline_media"]["count"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["profile_pic_url_hd"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["is_verified"]






    @property
    def     _UpperCamelCase							(			self ):
          return self.user_data["is_private"]







def _a			(		_snake_case = "github"							):







      """simple docstring"""






      import os

      if os.environ.get("""CI"""							):
            return  # test failing on GitHub Actions
      UpperCAmelCase          =	InstagramUser(_snake_case							)
      assert instagram_user.user_data
      assert isinstance(instagram_user.user_data				,	_snake_case							)
      assert instagram_user.username == username
      if username != "github":
            return
      assert instagram_user.fullname == "GitHub"
      assert instagram_user.biography == "Built for developers."
      assert instagram_user.number_of_posts > 150
      assert instagram_user.number_of_followers > 12_0000
      assert instagram_user.number_of_followings > 15
      assert instagram_user.email == "support@github.com"
      assert instagram_user.website == "https://github.com/readme"
      assert instagram_user.profile_picture_url.startswith("""https://instagram."""							)
      assert instagram_user.is_verified is True
      assert instagram_user.is_private is False


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  _UpperCamelCase					      =  InstagramUser("""github""")
  print(instagram_user)
  print(F"""{instagram_user.number_of_posts = }""")
  print(F"""{instagram_user.number_of_followers = }""")
  print(F"""{instagram_user.number_of_followings = }""")
  print(F"""{instagram_user.email = }""")
  print(F"""{instagram_user.website = }""")
  print(F"""{instagram_user.profile_picture_url = }""")
  print(F"""{instagram_user.is_verified = }""")
  print(F"""{instagram_user.is_private = }""")



