


from typing import TYPE_CHECKING

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


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

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

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A :	Dict												=     [
	    '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

	A :	List[Any]												=     _LazyModule(__name__, globals()['__file__'], _import_structure)





from typing import TYPE_CHECKING

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


A :	int												=     {
    'configuration_rwkv': ['RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RwkvConfig', 'RwkvOnnxConfig'],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A :	List[Any]												=     [
	    'RWKV_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'RwkvForCausalLM',
	    'RwkvModel',
	    'RwkvPreTrainedModel',
	]


if TYPE_CHECKING:
	from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_rwkv import (
		    RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
		    RwkvForCausalLM,
		    RwkvModel,
		    RwkvPreTrainedModel,
		)
else:
	import sys

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

