"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_UpperCamelCase         =		{
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCamelCase         =		["BartTokenizerFast"]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCamelCase         =		[
	    "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
	    "BartForCausalLM",
	    "BartForConditionalGeneration",
	    "BartForQuestionAnswering",
	    "BartForSequenceClassification",
	    "BartModel",
	    "BartPretrainedModel",
	    "PretrainedBartModel",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCamelCase         =		[
	    "TFBartForConditionalGeneration",
	    "TFBartForSequenceClassification",
	    "TFBartModel",
	    "TFBartPretrainedModel",
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_UpperCamelCase         =		[
	    "FlaxBartDecoderPreTrainedModel",
	    "FlaxBartForCausalLM",
	    "FlaxBartForConditionalGeneration",
	    "FlaxBartForQuestionAnswering",
	    "FlaxBartForSequenceClassification",
	    "FlaxBartModel",
	    "FlaxBartPreTrainedModel",
	]

if TYPE_CHECKING:
	from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
	from .tokenization_bart import BartTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_bart_fast import BartTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_bart import (
		    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BartForCausalLM,
		    BartForConditionalGeneration,
		    BartForQuestionAnswering,
		    BartForSequenceClassification,
		    BartModel,
		    BartPretrainedModel,
		    PretrainedBartModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_bart import (
		    TFBartForConditionalGeneration,
		    TFBartForSequenceClassification,
		    TFBartModel,
		    TFBartPretrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_bart import (
		    FlaxBartDecoderPreTrainedModel,
		    FlaxBartForCausalLM,
		    FlaxBartForConditionalGeneration,
		    FlaxBartForQuestionAnswering,
		    FlaxBartForSequenceClassification,
		    FlaxBartModel,
		    FlaxBartPreTrainedModel,
		)

else:
	import sys

	_UpperCamelCase         =		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






"""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_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment
class 	__UpperCAmelCase						(unittest.TestCase    ):







			'''simple docstring'''





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Optional[int]														= inspect.getfile(accelerate.test_utils       )
										A__					:    Tuple														= os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ["""scripts""", """test_sync.py"""]       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main      ,			num_processes=1       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main       )





			@require_single_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										test_sync.main()





			@require_multi_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


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





