






"""simple docstring"""


from typing import TYPE_CHECKING

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


lowercase_								=	{
    'configuration_esm': ['ESM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'EsmConfig'],
    'tokenization_esm': ['EsmTokenizer'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           'ESM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'EsmForMaskedLM',
           'EsmForSequenceClassification',
           'EsmForTokenClassification',
           'EsmModel',
           'EsmPreTrainedModel',
       ]
       lowercase_								=	['EsmForProteinFolding', 'EsmFoldPreTrainedModel']

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_								=	[
           'TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFEsmForMaskedLM',
           'TFEsmForSequenceClassification',
           'TFEsmForTokenClassification',
           'TFEsmModel',
           'TFEsmPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_esm import ESM_PRETRAINED_CONFIG_ARCHIVE_MAP, EsmConfig
       from .tokenization_esm import EsmTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_esm import (
                  ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  EsmForMaskedLM,
                  EsmForSequenceClassification,
                  EsmForTokenClassification,
                  EsmModel,
                  EsmPreTrainedModel,
              )
              from .modeling_esmfold import EsmFoldPreTrainedModel, EsmForProteinFolding

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_esm import (
                  TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFEsmForMaskedLM,
                  TFEsmForSequenceClassification,
                  TFEsmForTokenClassification,
                  TFEsmModel,
                  TFEsmPreTrainedModel,
              )


else:
       import sys

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












"""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__)




