






'''simple docstring'''





from typing import TYPE_CHECKING

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


a_		:						Dict             =    {
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
				if not is_tokenizers_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				pass

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				a_		:						Dict             =    [
				    'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'RoCBertForCausalLM',
				    'RoCBertForMaskedLM',
				    'RoCBertForMultipleChoice',
				    'RoCBertForPreTraining',
				    'RoCBertForQuestionAnswering',
				    'RoCBertForSequenceClassification',
				    'RoCBertForTokenClassification',
				    'RoCBertLayer',
				    'RoCBertModel',
				    'RoCBertPreTrainedModel',
				    'load_tf_weights_in_roc_bert',
				]

if TYPE_CHECKING:
				from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
				from .tokenization_roc_bert import RoCBertTokenizer

				try:
								if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								raise OptionalDependencyNotAvailable()

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_roc_bert import (
								    ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    RoCBertForCausalLM,
								    RoCBertForMaskedLM,
								    RoCBertForMultipleChoice,
								    RoCBertForPreTraining,
								    RoCBertForQuestionAnswering,
								    RoCBertForSequenceClassification,
								    RoCBertForTokenClassification,
								    RoCBertLayer,
								    RoCBertModel,
								    RoCBertPreTrainedModel,
								    load_tf_weights_in_roc_bert,
								)


else:
				import sys

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












import unittest

from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script

@require_cpu
class 		_snake_case  (  unittest.TestCase					):






			def    SCREAMING_SNAKE_CASE__    (       self)      ->       str:
						debug_launcher(test_script.main)







			def    SCREAMING_SNAKE_CASE__    (       self)      ->       Any:
						debug_launcher(test_ops.main)




