
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     UpperCAmelCase__							(       ):


					'''simple docstring'''

					lowerCAmelCase		:					List[str]  	=     Dataset.from_dict({'''i''': range(17  )}  )
					lowerCAmelCase		:					Any  	=     len(__magic_name__  )
					lowerCAmelCase		:					Tuple  	=     3
					lowerCAmelCase		:					Optional[Any]  	=     [
					    split_dataset_by_node(__magic_name__							,  rank=__magic_name__							,  world_size=__magic_name__  ) for rank in range(__magic_name__  )
					]
					assert sum(len(__magic_name__  ) 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     UpperCAmelCase__							(       ):


					'''simple docstring'''

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

					lowerCAmelCase		:					Dict  	=     3
					lowerCAmelCase		:					int  	=     IterableDataset.from_generator(__magic_name__  )
					lowerCAmelCase		:					List[str]  	=     len(list(__magic_name__  )  )
					lowerCAmelCase		:					Tuple  	=     [
					    split_dataset_by_node(__magic_name__							,  rank=__magic_name__							,  world_size=__magic_name__  ) for rank in range(__magic_name__  )
					]
					assert sum(len(list(__magic_name__  )  ) 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     UpperCAmelCase__							(       __magic_name__						:     int  ):


					'''simple docstring'''

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

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


					'''simple docstring'''

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

					lowerCAmelCase		:					Dict  	=     2
					lowerCAmelCase		:					str  	=     IterableDataset.from_generator(__magic_name__  )
					lowerCAmelCase		:					Union[str, Any]  	=     len(list(__magic_name__  )  )

					lowerCAmelCase		:					Any  	=     split_dataset_by_node(__magic_name__							,  rank=0							,  world_size=__magic_name__  ).shuffle(seed=42  )
					assert len(list(__magic_name__  )  ) == 1 + full_size // world_size
					with pytest.raises(__magic_name__  ):
										split_dataset_by_node(__magic_name__							,  rank=0							,  world_size=__magic_name__  ).shuffle()

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


					'''simple docstring'''

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


					'''simple docstring'''

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


def     UpperCAmelCase__							(       __magic_name__						:     Tuple							,  __magic_name__						:     int							,  __magic_name__						:     Dict							,  __magic_name__						:     str  ):


					'''simple docstring'''

					if start == end:
										return start if lst[start] > item else start + 1
					if start > end:
										return start

					lowerCAmelCase		:					Optional[Any]  	=     (start + end) // 2
					if lst[mid] < item:
										return binary_search(__magic_name__							,  __magic_name__							,  mid + 1							,  __magic_name__  )
					elif lst[mid] > item:
										return binary_search(__magic_name__							,  __magic_name__							,  __magic_name__							,  mid - 1  )
					else:
										return mid
def     UpperCAmelCase__							(       __magic_name__						:     List[Any]  ):


					'''simple docstring'''

					lowerCAmelCase		:					Union[str, Any]  	=     len(__magic_name__  )

					for index in range(1							,  __magic_name__  ):
										lowerCAmelCase		:					Optional[int]  	=     lst[index]
										lowerCAmelCase		:					Dict  	=     binary_search(__magic_name__							,  __magic_name__							,  0							,  index - 1  )
										lowerCAmelCase		:					Union[str, Any]  	=     lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]

					return lst
def     UpperCAmelCase__							(       __magic_name__						:     Optional[int]							,  __magic_name__						:     List[str]  ):


					'''simple docstring'''

					if not left:
										return right

					if not right:
										return left

					if left[0] < right[0]:
										return [left[0], *merge(left[1:]							,  __magic_name__  )]

					return [right[0], *merge(__magic_name__							,  right[1:]  )]
def     UpperCAmelCase__							(       __magic_name__						:     str  ):


					'''simple docstring'''

					lowerCAmelCase		:					str  	=     len(__magic_name__  )
					lowerCAmelCase	,							lowerCAmelCase		:					Union[str, Any]  	=     [], []
					lowerCAmelCase		:					Union[str, Any]  	=     [lst[0]]
					lowerCAmelCase		:					Optional[Any]  	=     []
					lowerCAmelCase		:					List[Any]  	=     1
					while i < length:
										if lst[i] < lst[i - 1]:
															runs.append(__magic_name__  )
															lowerCAmelCase		:					Any  	=     [lst[i]]
										else:
															new_run.append(lst[i]  )
										i += 1
					runs.append(__magic_name__  )

					for run in runs:
										sorted_runs.append(insertion_sort(__magic_name__  )  )
					for run in sorted_runs:
										lowerCAmelCase		:					int  	=     merge(__magic_name__							,  __magic_name__  )

					return sorted_array
def     UpperCAmelCase__							(       ):


					'''simple docstring'''

					lowerCAmelCase		:					Tuple  	=     [5, 9, 10, 3, -4, 5, 1_78, 92, 46, -18, 0, 7]
					lowerCAmelCase		:					Optional[Any]  	=     tim_sort(__magic_name__  )
					print(__magic_name__  )


if __name__ == "__main__":
		main()
