



from ..utils import DummyObject, requires_backends





class 							lowerCAmelCase_		(		metaclass=lowercase_     ):
		SCREAMING_SNAKE_CASE_       :			Optional[int]					       =	["""torch""", """librosa"""]







		def __init__(    self  :   List[Any]       ,		*UpperCAmelCase_  :   Tuple       ,		**UpperCAmelCase_  :   Tuple					)       ->		Any:


						'''simple docstring'''







						requires_backends(self       ,		['''torch''', '''librosa''']					)







		@classmethod
		def 					a_  (    cls  :   Dict       ,		*UpperCAmelCase_  :   Tuple       ,		**UpperCAmelCase_  :   str					)       ->		Union[str, Any]:


						'''simple docstring'''







						requires_backends(cls       ,		['''torch''', '''librosa''']					)







		@classmethod
		def 					a_  (    cls  :   str       ,		*UpperCAmelCase_  :   int       ,		**UpperCAmelCase_  :   str					)       ->		List[Any]:


						'''simple docstring'''







						requires_backends(cls       ,		['''torch''', '''librosa''']					)





class 							lowerCAmelCase_		(		metaclass=lowercase_     ):
		SCREAMING_SNAKE_CASE_       :			Tuple					       =	["""torch""", """librosa"""]







		def __init__(    self  :   Dict       ,		*UpperCAmelCase_  :   str       ,		**UpperCAmelCase_  :   Any					)       ->		Optional[int]:


						'''simple docstring'''







						requires_backends(self       ,		['''torch''', '''librosa''']					)







		@classmethod
		def 					a_  (    cls  :   Dict       ,		*UpperCAmelCase_  :   str       ,		**UpperCAmelCase_  :   int					)       ->		Tuple:


						'''simple docstring'''







						requires_backends(cls       ,		['''torch''', '''librosa''']					)







		@classmethod
		def 					a_  (    cls  :   int       ,		*UpperCAmelCase_  :   Tuple       ,		**UpperCAmelCase_  :   List[str]					)       ->		Any:


						'''simple docstring'''







						requires_backends(cls       ,		['''torch''', '''librosa''']					)





from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


UpperCAmelCase__			:   Optional[int]      			=    {
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__			:   List[Any]      			=    ['ErnieMTokenizer']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCAmelCase__			:   Dict      			=    [
					    'ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'ErnieMForMultipleChoice',
					    'ErnieMForQuestionAnswering',
					    'ErnieMForSequenceClassification',
					    'ErnieMForTokenClassification',
					    'ErnieMModel',
					    'ErnieMPreTrainedModel',
					    'ErnieMForInformationExtraction',
					]


if TYPE_CHECKING:
					from .configuration_ernie_m import ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP, ErnieMConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_ernie_m import ErnieMTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_ernie_m import (
										    ERNIE_M_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ErnieMForInformationExtraction,
										    ErnieMForMultipleChoice,
										    ErnieMForQuestionAnswering,
										    ErnieMForSequenceClassification,
										    ErnieMForTokenClassification,
										    ErnieMModel,
										    ErnieMPreTrainedModel,
										)


else:
					import sys

					UpperCAmelCase__			:   Union[str, Any]      			=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
