



from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


_snake_case		=  {"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfig"]}

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case		=  ["GPTNeoXTokenizerFast"]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case		=  [
						    "GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "GPTNeoXForCausalLM",
						    "GPTNeoXForQuestionAnswering",
						    "GPTNeoXForSequenceClassification",
						    "GPTNeoXForTokenClassification",
						    "GPTNeoXLayer",
						    "GPTNeoXModel",
						    "GPTNeoXPreTrainedModel",
						]


if TYPE_CHECKING:
						from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_gpt_neox import (
												    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GPTNeoXForCausalLM,
												    GPTNeoXForQuestionAnswering,
												    GPTNeoXForSequenceClassification,
												    GPTNeoXForTokenClassification,
												    GPTNeoXLayer,
												    GPTNeoXModel,
												    GPTNeoXPreTrainedModel,
												)


else:
						import sys

						_snake_case		=  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs






@pytest.mark.parametrize(
    "kwargs, expected"				, [
        ({"num_shards": 0, "max_num_jobs": 1}, []),
        ({"num_shards": 10, "max_num_jobs": 1}, [range(10  )]),
        ({"num_shards": 10, "max_num_jobs": 10}, [range(_lowerCamelCase				, i + 1  ) for i in range(10  )]),
        ({"num_shards": 1, "max_num_jobs": 10}, [range(1  )]),
        ({"num_shards": 10, "max_num_jobs": 3}, [range(0				, 4  ), range(4				, 7  ), range(7				, 10  )]),
        ({"num_shards": 3, "max_num_jobs": 10}, [range(0				, 1  ), range(1				, 2  ), range(2				, 3  )]),
    ]				, )
def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							List[Any]    =    _distribute_shards(**_lowerCamelCase  )
							assert out == expected






@pytest.mark.parametrize(
    "gen_kwargs, max_num_jobs, expected"				, [
        ({"foo": 0}, 10, [{"foo": 0}]),
        ({"shards": [0, 1, 2, 3]}, 1, [{"shards": [0, 1, 2, 3]}]),
        ({"shards": [0, 1, 2, 3]}, 4, [{"shards": [0]}, {"shards": [1]}, {"shards": [2]}, {"shards": [3]}]),
        ({"shards": [0, 1]}, 4, [{"shards": [0]}, {"shards": [1]}]),
        ({"shards": [0, 1, 2, 3]}, 2, [{"shards": [0, 1]}, {"shards": [2, 3]}]),
    ]				, )
def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Optional[int]    =    _split_gen_kwargs(_lowerCamelCase				, _lowerCamelCase  )
							assert out == expected






@pytest.mark.parametrize(
    "gen_kwargs, expected"				, [
        ({"foo": 0}, 1),
        ({"shards": [0]}, 1),
        ({"shards": [0, 1, 2, 3]}, 4),
        ({"shards": [0, 1, 2, 3], "foo": 0}, 4),
        ({"shards": [0, 1, 2, 3], "other": (0, 1)}, 4),
        ({"shards": [0, 1, 2, 3], "shards2": [0, 1]}, RuntimeError),
    ]				, )
def 				A				(					_lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							if expected is RuntimeError:
														with pytest.raises(_lowerCamelCase  ):
																					_number_of_shards_in_gen_kwargs(_lowerCamelCase  )
							else:
														_lowerCAmelCase     :							Optional[int]    =    _number_of_shards_in_gen_kwargs(_lowerCamelCase  )
														assert out == expected
