import os
import time

import pytest

from datasets.utils.filelock import FileLock, Timeout





def    __lowercase     (						lowerCamelCase					:     int	):
 UpperCamelCase_					:						Tuple =					FileLock(str(tmpdir / 'foo.lock'	)	)
 UpperCamelCase_					:						Tuple =					FileLock(str(tmpdir / 'foo.lock'	)	)
 UpperCamelCase_					:						Dict =					0.0_1
 with locka.acquire():
  with pytest.raises(lowerCamelCase	):
   UpperCamelCase_					:						Optional[Any] =					time.time()
   locka.acquire(lowerCamelCase	)
   assert time.time() - _start > timeout






def    __lowercase     (						lowerCamelCase					:     Any	):
 UpperCamelCase_					:						Optional[int] =					"""a""" * 1000 + """.lock"""
 UpperCamelCase_					:						Optional[Any] =					FileLock(str(tmpdir / filename	)	)
 assert locka._lock_file.endswith('.lock'	)
 assert not locka._lock_file.endswith(lowerCamelCase	)
 assert len(os.path.basename(locka._lock_file	)	) <= 255
 UpperCamelCase_					:						Dict =					FileLock(tmpdir / filename	)
 with locka.acquire():
  with pytest.raises(lowerCamelCase	):
   locka.acquire(0	)











from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
	if not (is_transformers_available() and is_torch_available()):
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	from ...utils.dummy_torch_and_transformers_objects import ShapEPipeline
else:
	from .camera import create_pan_cameras
	from .pipeline_shap_e import ShapEPipeline
	from .pipeline_shap_e_img2img import ShapEImgaImgPipeline
	from .renderer import (
	    BoundingBoxVolume,
	    ImportanceRaySampler,
	    MLPNeRFModelOutput,
	    MLPNeRSTFModel,
	    ShapEParamsProjModel,
	    ShapERenderer,
	    StratifiedRaySampler,
	    VoidNeRFModel,
	)
