


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		):



    """simple docstring"""






    def _a					(			self    )  ->       Optional[int]:
         __UpperCamelCase    							=inspect.getfile(accelerate.test_utils    )
         __UpperCamelCase    							=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

         __UpperCamelCase    							=test_metrics






    @require_cpu
    def _a					(			self    )  ->       Optional[int]:
         debug_launcher(self.test_metrics.main					,   num_processes=1    )






    @require_cpu
    def _a					(			self    )  ->       str:
         debug_launcher(self.test_metrics.main    )






    @require_single_gpu
    def _a					(			self    )  ->       Optional[int]:
         self.test_metrics.main()






    @require_multi_gpu
    def _a					(			self    )  ->       int:
         print(f'Found {torch.cuda.device_count()} devices.'    )
         __UpperCamelCase    							=['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()    )









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_A		       =						{'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _A		       =						[
       'SEW_PRETRAINED_MODEL_ARCHIVE_LIST',
       'SEWForCTC',
       'SEWForSequenceClassification',
       'SEWModel',
       'SEWPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_sew import SEW_PRETRAINED_CONFIG_ARCHIVE_MAP, SEWConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_sew import (
          SEW_PRETRAINED_MODEL_ARCHIVE_LIST,
          SEWForCTC,
          SEWForSequenceClassification,
          SEWModel,
          SEWPreTrainedModel,
      )


else:
   import sys

   _A		       =						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





