


"""simple docstring"""







from typing import TYPE_CHECKING

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


a__    :							List[str]            =					{
    '''configuration_trajectory_transformer''': [
        '''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''TrajectoryTransformerConfig''',
    ],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__    :							List[Any]            =					[
		    '''TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TrajectoryTransformerModel''',
		    '''TrajectoryTransformerPreTrainedModel''',
		    '''load_tf_weights_in_trajectory_transformer''',
		]


if TYPE_CHECKING:
		from .configuration_trajectory_transformer import (
		    TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    TrajectoryTransformerConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_trajectory_transformer import (
				    TRAJECTORY_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TrajectoryTransformerModel,
				    TrajectoryTransformerPreTrainedModel,
				    load_tf_weights_in_trajectory_transformer,
				)


else:
		import sys

		a__    :							Dict            =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




"""simple docstring"""







from typing import TYPE_CHECKING

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


a__    :							List[str]            =					{
    '''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
    '''tokenization_biogpt''': ['''BioGptTokenizer'''],
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__    :							Union[str, Any]            =					[
		    '''BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''BioGptForCausalLM''',
		    '''BioGptForTokenClassification''',
		    '''BioGptForSequenceClassification''',
		    '''BioGptModel''',
		    '''BioGptPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
		from .tokenization_biogpt import BioGptTokenizer

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_biogpt import (
				    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BioGptForCausalLM,
				    BioGptForSequenceClassification,
				    BioGptForTokenClassification,
				    BioGptModel,
				    BioGptPreTrainedModel,
				)


else:
		import sys

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