




"""simple docstring"""





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 						lowerCAmelCase							(	):
						'''simple docstring'''


						snake_case__    :   List[str]							     =   Dataset.from_dict({'''i''': range(17						)}						)
						snake_case__    :   int							     =   len(lowerCamelCase						)
						snake_case__    :   str							     =   3
						snake_case__    :   Optional[Any]							     =   [
						    split_dataset_by_node(lowerCamelCase ,     rank=lowerCamelCase ,     world_size=lowerCamelCase						) for rank in range(lowerCamelCase						)
						]
						assert sum(len(lowerCamelCase						) 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 						lowerCAmelCase							(	):
						'''simple docstring'''


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

						snake_case__    :   int							     =   3
						snake_case__    :   str							     =   IterableDataset.from_generator(lowerCamelCase						)
						snake_case__    :   List[str]							     =   len(list(lowerCamelCase						)						)
						snake_case__    :   str							     =   [
						    split_dataset_by_node(lowerCamelCase ,     rank=lowerCamelCase ,     world_size=lowerCamelCase						) for rank in range(lowerCamelCase						)
						]
						assert sum(len(list(lowerCamelCase						)						) 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 						lowerCAmelCase							(	lowerCamelCase						):
						'''simple docstring'''


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

						snake_case__    :   Optional[int]							     =   3
						snake_case__    :   Union[str, Any]							     =   shards_per_node * world_size
						snake_case__    :   Any							     =   {'''shards''': [f'''shard_{shard_idx}.txt''' for shard_idx in range(lowerCamelCase						)]}
						snake_case__    :   List[str]							     =   IterableDataset.from_generator(lowerCamelCase ,     gen_kwargs=lowerCamelCase						)
						snake_case__    :   Union[str, Any]							     =   len(list(lowerCamelCase						)						)
						assert full_ds.n_shards == world_size * shards_per_node
						snake_case__    :   Any							     =   [
						    split_dataset_by_node(lowerCamelCase ,     rank=lowerCamelCase ,     world_size=lowerCamelCase						) for rank in range(lowerCamelCase						)
						]
						assert [ds.n_shards for ds in datasets_per_rank] == [shards_per_node] * world_size
						assert sum(len(list(lowerCamelCase						)						) 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 						lowerCAmelCase							(	):
						'''simple docstring'''


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

						snake_case__    :   List[Any]							     =   2
						snake_case__    :   Dict							     =   IterableDataset.from_generator(lowerCamelCase						)
						snake_case__    :   str							     =   len(list(lowerCamelCase						)						)

						snake_case__    :   Optional[int]							     =   split_dataset_by_node(lowerCamelCase ,     rank=0 ,     world_size=lowerCamelCase						).shuffle(seed=42						)
						assert len(list(lowerCamelCase						)						) == 1 + full_size // world_size
						with pytest.raises(lowerCamelCase						):
												split_dataset_by_node(lowerCamelCase ,     rank=0 ,     world_size=lowerCamelCase						).shuffle()

						snake_case__    :   Optional[int]							     =   split_dataset_by_node(full_ds.shuffle(seed=42						) ,     rank=0 ,     world_size=lowerCamelCase						)
						assert len(list(lowerCamelCase						)						) == 1 + full_size // world_size
						with pytest.raises(lowerCamelCase						):
												split_dataset_by_node(full_ds.shuffle() ,     rank=0 ,     world_size=lowerCamelCase						)

@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 						lowerCAmelCase							(	lowerCamelCase						):
						'''simple docstring'''


						snake_case__    :   Optional[int]							     =   2
						snake_case__    :   Optional[Any]							     =   get_torch_dist_unique_port()
						snake_case__    :   Dict							     =   Path(lowerCamelCase						).resolve().parent / '''distributed_scripts''' / '''launch_torch_distributed.py'''
						snake_case__    :   Optional[int]							     =   f'''
        -m torch.distributed.launch
        --nproc_per_node={nproc_per_node}
        --master_port={master_port}
        {test_script}
    '''.split()
						snake_case__    :   List[Any]							     =   f'''
        --streaming={streaming}
    '''.split()
						snake_case__    :   Dict							     =   [sys.executable] + distributed_args + args
						execute_subprocess_async(lowerCamelCase ,     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 						lowerCAmelCase							(	lowerCamelCase ,     lowerCamelCase						):
						'''simple docstring'''


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








"""simple docstring"""





class  __lowercase    :


				'''simple docstring'''


				class  __lowercase    :


								'''simple docstring'''


								_lowerCAmelCase		     ="_prev", "_data", "_next"

								def __init__(				self				:       List[Any] ,SCREAMING_SNAKE_CASE_				:       int ,SCREAMING_SNAKE_CASE_				:       Union[str, Any] ,SCREAMING_SNAKE_CASE_				:       Any ):
														snake_case__    :   Any							     =   link_p
														snake_case__    :   List[str]							     =   element
														snake_case__    :   str							     =   link_n





								def  _lowerCamelCase   (				self				:       Optional[Any] ):
														return (
														    F''' Prev -> {self._prev is not None}, Next -> {self._next is not None}'''
														)







				def __init__(				self				:       Any ):
										snake_case__    :   int							     =   self._Node(SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ )
										snake_case__    :   Optional[int]							     =   self._Node(SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ )
										snake_case__    :   Union[str, Any]							     =   self._trailer
										snake_case__    :   Union[str, Any]							     =   self._header
										snake_case__    :   Any							     =   0

				def __len__(				self				:       str ):
										return self._size

				def  _lowerCamelCase   (				self				:       Union[str, Any] ):
										return self.__len__() == 0

				def  _lowerCamelCase   (				self				:       Any ,SCREAMING_SNAKE_CASE_				:       List[Any] ,SCREAMING_SNAKE_CASE_				:       List[str] ,SCREAMING_SNAKE_CASE_				:       Dict ):
										# Create new_node by setting it's prev.link -> header
										# setting it's next.link -> trailer
										snake_case__    :   Dict							     =   self._Node(SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ )
										snake_case__    :   Any							     =   new_node
										snake_case__    :   str							     =   new_node
										self._size += 1
										return self





				def  _lowerCamelCase   (				self				:       Union[str, Any] ,SCREAMING_SNAKE_CASE_				:       Dict ):
										snake_case__    :   Union[str, Any]							     =   node._prev
										snake_case__    :   Union[str, Any]							     =   node._next

										snake_case__    :   List[Any]							     =   successor
										snake_case__    :   Dict							     =   predecessor
										self._size -= 1
										snake_case__    :   Dict							     =   node._data
										snake_case__    :   List[str]							     =   None
										del node
										return temp







class  __lowercase    (     _DoublyLinkedBase		):


				'''simple docstring'''


				def  _lowerCamelCase   (				self				:       Optional[int] ):
										if self.is_empty():
																raise Exception('''List is empty''' )
										return self._header._next._data

				def  _lowerCamelCase   (				self				:       Union[str, Any] ):
										if self.is_empty():
																raise Exception('''List is empty''' )
										return self._trailer._prev._data

				def  _lowerCamelCase   (				self				:       Any ,SCREAMING_SNAKE_CASE_				:       Dict ):
										return self._insert(self._header ,SCREAMING_SNAKE_CASE_ ,self._header._next )

				def  _lowerCamelCase   (				self				:       Dict ,SCREAMING_SNAKE_CASE_				:       Union[str, Any] ):
										return self._insert(self._trailer._prev ,SCREAMING_SNAKE_CASE_ ,self._trailer )

				def  _lowerCamelCase   (				self				:       Optional[int] ):
										if self.is_empty():
																raise IndexError('''remove_first from empty list''' )
										return self._delete(self._header._next )





				def  _lowerCamelCase   (				self				:       Optional[Any] ):
										if self.is_empty():
																raise IndexError('''remove_first from empty list''' )
										return self._delete(self._trailer._prev )


