from typing import TYPE_CHECKING

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


lowerCAmelCase__					:       Tuple		=       {
    '''configuration_dpr''': ['''DPR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPRConfig'''],
    '''tokenization_dpr''': [
        '''DPRContextEncoderTokenizer''',
        '''DPRQuestionEncoderTokenizer''',
        '''DPRReaderOutput''',
        '''DPRReaderTokenizer''',
    ],
}


try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__					:       str		=       [
				    '''DPRContextEncoderTokenizerFast''',
				    '''DPRQuestionEncoderTokenizerFast''',
				    '''DPRReaderTokenizerFast''',
				]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__					:       str		=       [
				    '''DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''DPRContextEncoder''',
				    '''DPRPretrainedContextEncoder''',
				    '''DPRPreTrainedModel''',
				    '''DPRPretrainedQuestionEncoder''',
				    '''DPRPretrainedReader''',
				    '''DPRQuestionEncoder''',
				    '''DPRReader''',
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowerCAmelCase__					:       Optional[Any]		=       [
				    '''TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''TFDPRContextEncoder''',
				    '''TFDPRPretrainedContextEncoder''',
				    '''TFDPRPretrainedQuestionEncoder''',
				    '''TFDPRPretrainedReader''',
				    '''TFDPRQuestionEncoder''',
				    '''TFDPRReader''',
				]


if TYPE_CHECKING:
				from .configuration_dpr import DPR_PRETRAINED_CONFIG_ARCHIVE_MAP, DPRConfig
				from .tokenization_dpr import (
				    DPRContextEncoderTokenizer,
				    DPRQuestionEncoderTokenizer,
				    DPRReaderOutput,
				    DPRReaderTokenizer,
				)

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_dpr_fast import (
								    DPRContextEncoderTokenizerFast,
								    DPRQuestionEncoderTokenizerFast,
								    DPRReaderTokenizerFast,
								)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_dpr import (
								    DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    DPRContextEncoder,
								    DPRPretrainedContextEncoder,
								    DPRPreTrainedModel,
								    DPRPretrainedQuestionEncoder,
								    DPRPretrainedReader,
								    DPRQuestionEncoder,
								    DPRReader,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_dpr import (
								    TF_DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TF_DPR_QUESTION_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TF_DPR_READER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFDPRContextEncoder,
								    TFDPRPretrainedContextEncoder,
								    TFDPRPretrainedQuestionEncoder,
								    TFDPRPretrainedReader,
								    TFDPRQuestionEncoder,
								    TFDPRReader,
								)

else:
				import sys

				lowerCAmelCase__					:       List[Any]		=       _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



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 			__snake_case  (      unittest.TestCase     ):




					def       __a      (       self		)					->  Union[str, Any]:



									'''simple docstring'''







									snake_case__ :     List[Any] 							=				inspect.getfile(accelerate.test_utils		)
									snake_case__ :     Tuple 							=				os.path.sep.join(mod_file.split(os.path.sep		)[:-1] + ['scripts', 'test_sync.py']		)




					@require_cpu
					def       __a      (       self		)					->  int:



									'''simple docstring'''







									debug_launcher(test_sync.main   ,	num_processes=1		)




					@require_cpu
					def       __a      (       self		)					->  Dict:



									'''simple docstring'''







									debug_launcher(test_sync.main		)




					@require_single_gpu
					def       __a      (       self		)					->  int:



									'''simple docstring'''







									test_sync.main()




					@require_multi_gpu
					def       __a      (       self		)					->  str:



									'''simple docstring'''







									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(__UpperCamelCase   ,	env=os.environ.copy()		)


