



"""simple docstring"""






def 			_lowercase				(  __snake_case					,__snake_case	)						->   list:
			__lowerCAmelCase      :  Optional[int]												=       word.split()

			def justify(__snake_case					,__snake_case					,__snake_case	) -> str:
						__lowerCAmelCase      :  Tuple												=       max_width - width
						__lowerCAmelCase      :  str												=       len(__snake_case	)
						if len(__snake_case	) == 1:
									# if there is only word in line
									# just insert overall_spaces_count for the remainder of line
									return line[0] + " " * overall_spaces_count
						else:
									__lowerCAmelCase      :  Dict												=       words_count - 1
									# num_spaces_between_words_list[i] : tells you to insert
									# num_spaces_between_words_list[i] spaces
									# after word on line[i]
									__lowerCAmelCase      :  Dict												=       spaces_to_insert_between_words * [
									    overall_spaces_count // spaces_to_insert_between_words
									]
									__lowerCAmelCase      :  Optional[int]												=       (
									    overall_spaces_count % spaces_to_insert_between_words
									)
									# distribute spaces via round robin to the left words
									for i in range(__snake_case	):
												num_spaces_between_words_list[i] += 1
									__lowerCAmelCase      :  Union[str, Any]												=       []
									for i in range(__snake_case	):
												# add the word
												aligned_words_list.append(line[i]	)
												# add the spaces to insert
												aligned_words_list.append(num_spaces_between_words_list[i] * " "	)
									# just add the last word to the sentence
									aligned_words_list.append(line[-1]	)
									# join the aligned words list to form a justified line
									return "".join(__snake_case	)

			__lowerCAmelCase      :  List[str]												=       []
			__lowerCAmelCase      :  list[str]												=       []
			__lowerCAmelCase      :  Tuple												=       0
			for word in words:
						if width + len(__snake_case	) + len(__snake_case	) <= max_width:
									# keep adding words until we can fill out max_width
									# width = sum of length of all words (without overall_spaces_count)
									# len(word) = length of current word
									# len(line) = number of overall_spaces_count to insert between words
									line.append(__snake_case	)
									width += len(__snake_case	)
						else:
									# justify the line and add it to result
									answer.append(justify(__snake_case					,__snake_case					,__snake_case	)	)
									# reset new line and new width
									__lowerCAmelCase						,	__lowerCAmelCase      :  Any												=       [word], len(__snake_case	)
			__lowerCAmelCase      :  Dict												=       max_width - width - len(__snake_case	)
			answer.append(" ".join(__snake_case	) + (remaining_spaces + 1) * " "	)
			return answer


if __name__ == "__main__":
	from doctest import testmod

	testmod()




"""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 			_lowercase				(  *__snake_case	)						->   Optional[Any]:
			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	)


__snake_case							:   List[Any]      =    int(os.environ['LOCAL_RANK'])
torch.cuda.set_device(local_rank)
__snake_case							:   List[str]      =    torch.device('cuda', local_rank)
__snake_case							:   Optional[Any]      =    socket.gethostname()

__snake_case							:   str      =    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
	__snake_case							:   Tuple      =    dist.get_rank()
	__snake_case							:   Any      =    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