






"""simple docstring"""


from typing import TYPE_CHECKING

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


lowercase_								=	{
    'configuration_ernie_m': ['ERNIE_M_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieMConfig'],
}

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

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           '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

       lowercase_								=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)












"""simple docstring"""


from typing import TYPE_CHECKING

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


lowercase_								=	{
    'configuration_gptsan_japanese': ['GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTSanJapaneseConfig'],
    'tokenization_gptsan_japanese': ['GPTSanJapaneseTokenizer'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           'GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST',
           'GPTSanJapaneseForConditionalGeneration',
           'GPTSanJapaneseModel',
           'GPTSanJapanesePreTrainedModel',
       ]
       lowercase_								=	[
           'GPTSanJapaneseTokenizer',
       ]


if TYPE_CHECKING:
       from .configuration_gptsan_japanese import GPTSAN_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTSanJapaneseConfig
       from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_gptsan_japanese import (
                  GPTSAN_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  GPTSanJapaneseForConditionalGeneration,
                  GPTSanJapaneseModel,
                  GPTSanJapanesePreTrainedModel,
              )
              from .tokenization_gptsan_japanese import GPTSanJapaneseTokenizer


else:
       import sys

       lowercase_								=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




