




'''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    snake_case__     (  )			->       Tuple:





			'''simple docstring'''






			snake_case__          =						Dataset.from_dict({"""i""": range(17	)}	)
			snake_case__          =						len(a	)
			snake_case__          =						3
			snake_case__          =						[
			    split_dataset_by_node(a       ,      rank=a       ,      world_size=a	) for rank in range(a	)
			]
			assert sum(len(a	) 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    snake_case__     (  )			->       List[Any]:





			'''simple docstring'''






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

			snake_case__          =						3
			snake_case__          =						IterableDataset.from_generator(a	)
			snake_case__          =						len(list(a	)	)
			snake_case__          =						[
			    split_dataset_by_node(a       ,      rank=a       ,      world_size=a	) for rank in range(a	)
			]
			assert sum(len(list(a	)	) 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    snake_case__     (  a	)			->       int:





			'''simple docstring'''






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

			snake_case__          =						3
			snake_case__          =						shards_per_node * world_size
			snake_case__          =						{"""shards""": [F"""shard_{shard_idx}.txt""" for shard_idx in range(a	)]}
			snake_case__          =						IterableDataset.from_generator(a       ,      gen_kwargs=a	)
			snake_case__          =						len(list(a	)	)
			assert full_ds.n_shards == world_size * shards_per_node
			snake_case__          =						[
			    split_dataset_by_node(a       ,      rank=a       ,      world_size=a	) for rank in range(a	)
			]
			assert [ds.n_shards for ds in datasets_per_rank] == [shards_per_node] * world_size
			assert sum(len(list(a	)	) 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    snake_case__     (  )			->       List[str]:





			'''simple docstring'''






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

			snake_case__          =						2
			snake_case__          =						IterableDataset.from_generator(a	)
			snake_case__          =						len(list(a	)	)

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

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




@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    snake_case__     (  a	)			->       str:





			'''simple docstring'''






			snake_case__          =						2
			snake_case__          =						get_torch_dist_unique_port()
			snake_case__          =						Path(a	).resolve().parent / """distributed_scripts""" / """launch_torch_distributed.py"""
			snake_case__          =						F"""
        -m torch.distributed.launch
        --nproc_per_node={nproc_per_node}
        --master_port={master_port}
        {test_script}
    """.split()
			snake_case__          =						F"""
        --streaming={streaming}
    """.split()
			snake_case__          =						[sys.executable] + distributed_args + args
			execute_subprocess_async(a       ,      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    snake_case__     (  a       ,      a	)			->       int:





			'''simple docstring'''






			snake_case__          =						True
			snake_case__          =						get_torch_dist_unique_port()
			snake_case__          =						Path(a	).resolve().parent / """distributed_scripts""" / """launch_torch_distributed.py"""
			snake_case__          =						F"""
        -m torch.distributed.launch
        --nproc_per_node={nproc_per_node}
        --master_port={master_port}
        {test_script}
    """.split()
			snake_case__          =						F"""
        --streaming={streaming}
        --num_workers={num_workers}
    """.split()
			snake_case__          =						[sys.executable] + distributed_args + args
			execute_subprocess_async(a       ,      env=os.environ.copy()	)




"""simple docstring"""







from collections import namedtuple

A     =      namedtuple('from_to', 'from_ to')

A     =      {
    'millimeter': 'mm',
    'centimeter': 'cm',
    'meter': 'm',
    'kilometer': 'km',
    'inch': 'in',
    'inche': 'in',  # Trailing 's' has been stripped off
    'feet': 'ft',
    'foot': 'ft',
    'yard': 'yd',
    'mile': 'mi',
}

A     =      {
    'mm': from_to(0.001, 1_0_0_0),
    'cm': from_to(0.01, 1_0_0),
    'm': from_to(1, 1),
    'km': from_to(1_0_0_0, 0.001),
    'in': from_to(0.0254, 39.3701),
    'ft': from_to(0.3048, 3.2_8084),
    'yd': from_to(0.9144, 1.0_9361),
    'mi': from_to(1609.34, 0.0_0062_1371),
}

def 	lowerCAmelCase__      (  lowerCamelCase__					,   lowerCamelCase__					,   lowerCamelCase__      )			->				float:
							A    =       from_type.lower().rstrip('s'      )
							A    =       TYPE_CONVERSION.get(lowerCamelCase__					,   lowerCamelCase__      )
							A    =       to_type.lower().rstrip('s'      )
							A    =       TYPE_CONVERSION.get(lowerCamelCase__					,   lowerCamelCase__      )
							if new_from not in METRIC_CONVERSION:
														A    =       (
														    f"""Invalid 'from_type' value: {from_type!r}.\n"""
														    f"""Conversion abbreviations are: {', '.join(lowerCamelCase__      )}"""
														)
														raise ValueError(lowerCamelCase__      )
							if new_to not in METRIC_CONVERSION:
														A    =       (
														    f"""Invalid 'to_type' value: {to_type!r}.\n"""
														    f"""Conversion abbreviations are: {', '.join(lowerCamelCase__      )}"""
														)
														raise ValueError(lowerCamelCase__      )
							return value * METRIC_CONVERSION[new_from].from_ * METRIC_CONVERSION[new_to].to


if __name__ == "__main__":
							import doctest

							doctest.testmod()



