"""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 		UpperCamelCase      (   unittest.TestCase						):



				def  _lowercase					(self    :				Optional[int])   ->     Optional[int]:
					__snake_case      :							Optional[Any]						=			inspect.getfile(accelerate.test_utils)
					__snake_case      :							Dict						=			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

					__snake_case      :							Tuple						=			test_metrics



				@require_cpu
				def  _lowercase					(self    :				Tuple)   ->     List[str]:
					debug_launcher(self.test_metrics.main     ,  num_processes=1)



				@require_cpu
				def  _lowercase					(self    :				List[Any])   ->     Dict:
					debug_launcher(self.test_metrics.main)



				@require_single_gpu
				def  _lowercase					(self    :				Union[str, Any])   ->     Union[str, Any]:
					self.test_metrics.main()






				@require_multi_gpu
				def  _lowercase					(self    :				Tuple)   ->     List[str]:
					print(f"Found {torch.cuda.device_count()} devices.")
					__snake_case      :							Any						=			['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"""







import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


_a					:					Dict=			logging.get_logger(__name__)

class 		UpperCamelCase      (   lowercase						):



				def __init__(self    :				List[str]     ,  *_A    :				Dict     ,  **_A    :				Optional[Any])   ->     None:
					warnings.warn(
					    'The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
					    ' use CLIPImageProcessor instead.'     ,  _A     ,  )
					super().__init__(*_A     ,  **_A)





