



'''simple docstring'''

from itertools import permutations







def     __UpperCamelCase					(				_lowercase = 5       )			->      Optional[Any]:


	if gon_side < 3 or gon_side > 5:
		raise ValueError('gon_side must be in the range [3, 5]'       )

	# Since it's 16, we know 10 is on the outer ring
	# Put the big numbers at the end so that they are never the first number
	_lowercase       :							Dict  	=		list(range(gon_side + 1,					0,					-1       )       )
	_lowercase       :							str  	=		list(range(gon_side + 2,					gon_side * 2 + 1       )       )

	for perm in permutations(small_numbers + big_numbers       ):
		_lowercase       :							List[Any]  	=		generate_gon_ring(_lowercase,					list(_lowercase       )       )
		if is_magic_gon(_lowercase       ):
			return int(''.join(str(_lowercase       ) for n in numbers       )       )

	_lowercase       :							Dict  	=		f'''Magic {gon_side}-gon ring is impossible'''
	raise ValueError(_lowercase       )







def     __UpperCamelCase					(				_lowercase,					_lowercase       )			->      List[str]:
	_lowercase       :							Dict  	=		[0] * (gon_side * 3)
	_lowercase       :							Any  	=		perm[0:3]
	perm.append(perm[1]       )

	_lowercase       :							Optional[Any]  	=		1 if gon_side < 5 else 2

	for i in range(1,					len(_lowercase       ) // 3 + magic_number       ):
		_lowercase       :							Tuple  	=		perm[2 * i + 1]
		_lowercase       :							List[Any]  	=		result[3 * i - 1]
		_lowercase       :							Union[str, Any]  	=		perm[2 * i + 2]

	return result







def     __UpperCamelCase					(				_lowercase       )			->      Tuple:


	if len(_lowercase       ) % 3 != 0:
		raise ValueError('a gon ring should have a length that is a multiple of 3'       )

	if min(numbers[::3]       ) != numbers[0]:
		return False

	_lowercase       :							str  	=		sum(numbers[:3]       )

	return all(sum(numbers[i : i + 3]       ) == total for i in range(3,					len(_lowercase       ),					3       )       )


if __name__ == "__main__":
		print(solution())


import os
import sys
from pathlib import Path

import pytest

from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node

from .utils import execute_subprocess_async, get_torch_dist_unique_port, require_torch




def 		A						(  ):




			"""simple docstring"""


			UpperCAmelCase__		:Tuple 		=    Dataset.from_dict({'i': range(17							)}							)
			UpperCAmelCase__		:Optional[Any] 		=    len(SCREAMING_SNAKE_CASE							)
			UpperCAmelCase__		:Dict 		=    3
			UpperCAmelCase__		:List[str] 		=    [
			    split_dataset_by_node(SCREAMING_SNAKE_CASE     ,						rank=SCREAMING_SNAKE_CASE     ,						world_size=SCREAMING_SNAKE_CASE							) for rank in range(SCREAMING_SNAKE_CASE							)
			]
			assert sum(len(SCREAMING_SNAKE_CASE							) for ds in datasets_per_rank							) == full_size
			assert len({tuple(x.values()							) for ds in datasets_per_rank for x in ds}							) == full_size




def 		A						(  ):




			"""simple docstring"""


			def gen():
						return ({"i": i} for i in range(17							))

			UpperCAmelCase__		:Union[str, Any] 		=    3
			UpperCAmelCase__		:Union[str, Any] 		=    IterableDataset.from_generator(SCREAMING_SNAKE_CASE							)
			UpperCAmelCase__		:Union[str, Any] 		=    len(list(SCREAMING_SNAKE_CASE							)							)
			UpperCAmelCase__		:Dict 		=    [
			    split_dataset_by_node(SCREAMING_SNAKE_CASE     ,						rank=SCREAMING_SNAKE_CASE     ,						world_size=SCREAMING_SNAKE_CASE							) for rank in range(SCREAMING_SNAKE_CASE							)
			]
			assert sum(len(list(SCREAMING_SNAKE_CASE							)							) for ds in datasets_per_rank							) == full_size
			assert len({tuple(x.values()							) for ds in datasets_per_rank for x in ds}							) == full_size




@pytest.mark.parametrize('shards_per_node'     ,						[1, 2, 3]							)
def 		A						(  SCREAMING_SNAKE_CASE							):




			"""simple docstring"""


			def gen(SCREAMING_SNAKE_CASE							):
						for shard in shards:
									yield from ({"i": i, "shard": shard} for i in range(17							))

			UpperCAmelCase__		:int 		=    3
			UpperCAmelCase__		:Any 		=    shards_per_node * world_size
			UpperCAmelCase__		:int 		=    {'shards': [f"""shard_{shard_idx}.txt""" for shard_idx in range(SCREAMING_SNAKE_CASE							)]}
			UpperCAmelCase__		:Optional[Any] 		=    IterableDataset.from_generator(SCREAMING_SNAKE_CASE     ,						gen_kwargs=SCREAMING_SNAKE_CASE							)
			UpperCAmelCase__		:Tuple 		=    len(list(SCREAMING_SNAKE_CASE							)							)
			assert full_ds.n_shards == world_size * shards_per_node
			UpperCAmelCase__		:Optional[Any] 		=    [
			    split_dataset_by_node(SCREAMING_SNAKE_CASE     ,						rank=SCREAMING_SNAKE_CASE     ,						world_size=SCREAMING_SNAKE_CASE							) for rank in range(SCREAMING_SNAKE_CASE							)
			]
			assert [ds.n_shards for ds in datasets_per_rank] == [shards_per_node] * world_size
			assert sum(len(list(SCREAMING_SNAKE_CASE							)							) for ds in datasets_per_rank							) == full_size
			assert len({tuple(x.values()							) for ds in datasets_per_rank for x in ds}							) == full_size




def 		A						(  ):




			"""simple docstring"""


			def gen():
						return ({"i": i} for i in range(17							))

			UpperCAmelCase__		:Tuple 		=    2
			UpperCAmelCase__		:List[str] 		=    IterableDataset.from_generator(SCREAMING_SNAKE_CASE							)
			UpperCAmelCase__		:str 		=    len(list(SCREAMING_SNAKE_CASE							)							)

			UpperCAmelCase__		:List[str] 		=    split_dataset_by_node(SCREAMING_SNAKE_CASE     ,						rank=0     ,						world_size=SCREAMING_SNAKE_CASE							).shuffle(seed=42							)
			assert len(list(SCREAMING_SNAKE_CASE							)							) == 1 + full_size // world_size
			with pytest.raises(SCREAMING_SNAKE_CASE							):
						split_dataset_by_node(SCREAMING_SNAKE_CASE     ,						rank=0     ,						world_size=SCREAMING_SNAKE_CASE							).shuffle()

			UpperCAmelCase__		:Dict 		=    split_dataset_by_node(full_ds.shuffle(seed=42							)     ,						rank=0     ,						world_size=SCREAMING_SNAKE_CASE							)
			assert len(list(SCREAMING_SNAKE_CASE							)							) == 1 + full_size // world_size
			with pytest.raises(SCREAMING_SNAKE_CASE							):
						split_dataset_by_node(full_ds.shuffle()     ,						rank=0     ,						world_size=SCREAMING_SNAKE_CASE							)




@pytest.mark.parametrize('streaming'     ,						[False, True]							)
@require_torch
@pytest.mark.skipif(os.name == 'nt'     ,						reason='execute_subprocess_async doesn\'t support windows'							)
@pytest.mark.integration
def 		A						(  SCREAMING_SNAKE_CASE							):




			"""simple docstring"""


			UpperCAmelCase__		:Dict 		=    2
			UpperCAmelCase__		:str 		=    get_torch_dist_unique_port()
			UpperCAmelCase__		:Optional[int] 		=    Path(SCREAMING_SNAKE_CASE							).resolve().parent / 'distributed_scripts' / 'launch_torch_distributed.py'
			UpperCAmelCase__		:Any 		=    f"""
        -m torch.distributed.launch
        --nproc_per_node={nproc_per_node}
        --master_port={master_port}
        {test_script}
    """.split()
			UpperCAmelCase__		:Optional[int] 		=    f"""
        --streaming={streaming}
    """.split()
			UpperCAmelCase__		:Optional[Any] 		=    [sys.executable] + distributed_args + args
			execute_subprocess_async(SCREAMING_SNAKE_CASE     ,						env=os.environ.copy()							)




@pytest.mark.parametrize(
    'nproc_per_node, num_workers'     ,						[
        (2, 2),  # each node has 2 shards and each worker has 1 shards
        (3, 2),  # each node uses all the shards but skips examples, and each worker has 2 shards
    ]     ,						)
@require_torch
@pytest.mark.skipif(os.name == 'nt'     ,						reason='execute_subprocess_async doesn\'t support windows'							)
@pytest.mark.integration
def 		A						(  SCREAMING_SNAKE_CASE     ,						SCREAMING_SNAKE_CASE							):




			"""simple docstring"""


			UpperCAmelCase__		:List[str] 		=    True
			UpperCAmelCase__		:Optional[Any] 		=    get_torch_dist_unique_port()
			UpperCAmelCase__		:Union[str, Any] 		=    Path(SCREAMING_SNAKE_CASE							).resolve().parent / 'distributed_scripts' / 'launch_torch_distributed.py'
			UpperCAmelCase__		:Union[str, Any] 		=    f"""
        -m torch.distributed.launch
        --nproc_per_node={nproc_per_node}
        --master_port={master_port}
        {test_script}
    """.split()
			UpperCAmelCase__		:Union[str, Any] 		=    f"""
        --streaming={streaming}
        --num_workers={num_workers}
    """.split()
			UpperCAmelCase__		:List[Any] 		=    [sys.executable] + distributed_args + args
			execute_subprocess_async(SCREAMING_SNAKE_CASE     ,						env=os.environ.copy()							)





