



import os
import time

import pytest

from datasets.utils.filelock import FileLock, Timeout






def  UpperCAmelCase__    (    lowercase__   ) ->      str:
						__lowercase					=				FileLock(str(tmpdir / """foo.lock"""   )   )
						__lowercase					=				FileLock(str(tmpdir / """foo.lock"""   )   )
						__lowercase					=				0.01
						with locka.acquire():
												with pytest.raises(lowercase__   ):
																		__lowercase					=				time.time()
																		locka.acquire(lowercase__   )
																		assert time.time() - _start > timeout







def  UpperCAmelCase__    (    lowercase__   ) ->      List[str]:
						__lowercase					=				"""a""" * 1_000 + """.lock"""
						__lowercase					=				FileLock(str(tmpdir / filename   )   )
						assert locka._lock_file.endswith(""".lock"""   )
						assert not locka._lock_file.endswith(lowercase__   )
						assert len(os.path.basename(locka._lock_file   )   ) <= 255
						__lowercase					=				FileLock(tmpdir / filename   )
						with locka.acquire():
												with pytest.raises(lowercase__   ):
																		locka.acquire(0   )










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__ =						{
    "configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
    "tokenization_luke": ["LukeTokenizer"],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			UpperCamelCase__ =						[
			    "LUKE_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "LukeForEntityClassification",
			    "LukeForEntityPairClassification",
			    "LukeForEntitySpanClassification",
			    "LukeForMultipleChoice",
			    "LukeForQuestionAnswering",
			    "LukeForSequenceClassification",
			    "LukeForTokenClassification",
			    "LukeForMaskedLM",
			    "LukeModel",
			    "LukePreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_luke import LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP, LukeConfig
			from .tokenization_luke import LukeTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_luke import (
						    LUKE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    LukeForEntityClassification,
						    LukeForEntityPairClassification,
						    LukeForEntitySpanClassification,
						    LukeForMaskedLM,
						    LukeForMultipleChoice,
						    LukeForQuestionAnswering,
						    LukeForSequenceClassification,
						    LukeForTokenClassification,
						    LukeModel,
						    LukePreTrainedModel,
						)

else:
			import sys

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





