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 __SCREAMING_SNAKE_CASE							(						self   )			->   Optional[int]:
								__a		 =       inspect.getfile(accelerate.test_utils   )
								__a		 =       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

								__a		 =       test_metrics



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



			@require_cpu
			def __SCREAMING_SNAKE_CASE							(						self   )			->   List[str]:
								debug_launcher(self.test_metrics.main   )



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







			@require_multi_gpu
			def __SCREAMING_SNAKE_CASE							(						self   )			->   int:
								print(f'''Found {torch.cuda.device_count()} devices.'''   )
								__a		 =       ['torchrun', f'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
								with patch_environment(omp_num_threads=1   ):
													execute_subprocess_async(UpperCAmelCase				,						env=os.environ.copy()   )





from typing import TYPE_CHECKING

from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


lowerCamelCase_    :		Union[str, Any]							=	{"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCamelCase_    :		Union[str, Any]							=	["""GPTNeoXTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCamelCase_    :		List[str]							=	[
	    """GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """GPTNeoXForCausalLM""",
	    """GPTNeoXForQuestionAnswering""",
	    """GPTNeoXForSequenceClassification""",
	    """GPTNeoXForTokenClassification""",
	    """GPTNeoXLayer""",
	    """GPTNeoXModel""",
	    """GPTNeoXPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_gpt_neox import GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXConfig

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_gpt_neox_fast import GPTNeoXTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_gpt_neox import (
		    GPT_NEOX_PRETRAINED_MODEL_ARCHIVE_LIST,
		    GPTNeoXForCausalLM,
		    GPTNeoXForQuestionAnswering,
		    GPTNeoXForSequenceClassification,
		    GPTNeoXForTokenClassification,
		    GPTNeoXLayer,
		    GPTNeoXModel,
		    GPTNeoXPreTrainedModel,
		)


else:
	import sys

	lowerCamelCase_    :		Dict							=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




