






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       _lowerCAmelCase       (	self				) ->				Optional[Any]:
								snake_case_				:							List[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_				:							str						 =       test_metrics






						@require_cpu
						def       _lowerCAmelCase       (	self				) ->				str:
								debug_launcher(self.test_metrics.main		,				num_processes=1				)






						@require_cpu
						def       _lowerCAmelCase       (	self				) ->				Tuple:
								debug_launcher(self.test_metrics.main				)






						@require_single_gpu
						def       _lowerCAmelCase       (	self				) ->				Dict:
								self.test_metrics.main()






						@require_multi_gpu
						def       _lowerCAmelCase       (	self				) ->				Optional[Any]:
								print(f'''Found {torch.cuda.device_count()} devices.'''				)
								snake_case_				:							List[Any]						 =       ["torchrun", f'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
								with patch_environment(omp_num_threads=1				):
										execute_subprocess_async(_SCREAMING_SNAKE_CASE		,				env=os.environ.copy()				)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase  :							Optional[int]			  =    {
    '''configuration_nllb_moe''': [
        '''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''NllbMoeConfig''',
    ]
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowercase  :							Optional[Any]			  =    [
							    '''NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''NllbMoeForConditionalGeneration''',
							    '''NllbMoeModel''',
							    '''NllbMoePreTrainedModel''',
							    '''NllbMoeTop2Router''',
							    '''NllbMoeSparseMLP''',
							]


if TYPE_CHECKING:
							from .configuration_nllb_moe import (
							    NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    NllbMoeConfig,
							)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_nllb_moe import (
														    NLLB_MOE_PRETRAINED_MODEL_ARCHIVE_LIST,
														    NllbMoeForConditionalGeneration,
														    NllbMoeModel,
														    NllbMoePreTrainedModel,
														    NllbMoeSparseMLP,
														    NllbMoeTopaRouter,
														)


else:
							import sys

							lowercase  :							Tuple			  =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
