

'''simple docstring'''
import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_huggingface_suite,
    require_multi_gpu,
    require_single_gpu,
)
from accelerate.utils import patch_environment







@require_huggingface_suite
class 							A__    (       unittest.TestCase  ):





  def 						A  (		self      :	Optional[Any] )	->    Tuple:





       '''simple docstring'''






       _SCREAMING_SNAKE_CASE							    =inspect.getfile(accelerate.test_utils )
       _SCREAMING_SNAKE_CASE							    =os.path.sep.join(
           mod_file.split(os.path.sep )[:-1] + ['scripts', 'external_deps', 'test_metrics.py'] )

       from accelerate.test_utils.scripts.external_deps import test_metrics  # noqa: F401

       _SCREAMING_SNAKE_CASE							    =test_metrics





  @require_cpu
  def 						A  (		self      :	Optional[int] )	->    str:





       '''simple docstring'''






       debug_launcher(self.test_metrics.main							,					num_processes=1 )





  @require_cpu
  def 						A  (		self      :	Optional[Any] )	->    Union[str, Any]:





       '''simple docstring'''






       debug_launcher(self.test_metrics.main )





  @require_single_gpu
  def 						A  (		self      :	Optional[int] )	->    List[str]:





       '''simple docstring'''






       self.test_metrics.main()





  @require_multi_gpu
  def 						A  (		self      :	List[Any] )	->    Union[str, Any]:





       '''simple docstring'''






       print(f"Found {torch.cuda.device_count()} devices." )
       _SCREAMING_SNAKE_CASE							    =['torchrun', f"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
       with patch_environment(omp_num_threads=1 ):
            execute_subprocess_async(_a							,					env=os.environ.copy() )



'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase :      int					 =     {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase :      int					 =     ["GLPNFeatureExtractor"]
     lowerCamelCase :      Optional[int]					 =     ["GLPNImageProcessor"]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase :      Union[str, Any]					 =     [
         "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "GLPNForDepthEstimation",
         "GLPNLayer",
         "GLPNModel",
         "GLPNPreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_glpn import GLPNFeatureExtractor
          from .image_processing_glpn import GLPNImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_glpn import (
              GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
              GLPNForDepthEstimation,
              GLPNLayer,
              GLPNModel,
              GLPNPreTrainedModel,
          )


else:
     import sys

     lowerCamelCase :      List[Any]					 =     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
