



from typing import TYPE_CHECKING

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


_lowercase				:					Optional[int]     					={
    """configuration_layoutlm""": ["""LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LayoutLMConfig""", """LayoutLMOnnxConfig"""],
    """tokenization_layoutlm""": ["""LayoutLMTokenizer"""],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase				:					Union[str, Any]     					=["""LayoutLMTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase				:					List[str]     					=[
	    """LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """LayoutLMForMaskedLM""",
	    """LayoutLMForSequenceClassification""",
	    """LayoutLMForTokenClassification""",
	    """LayoutLMForQuestionAnswering""",
	    """LayoutLMModel""",
	    """LayoutLMPreTrainedModel""",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_lowercase				:					Tuple     					=[
	    """TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFLayoutLMForMaskedLM""",
	    """TFLayoutLMForSequenceClassification""",
	    """TFLayoutLMForTokenClassification""",
	    """TFLayoutLMForQuestionAnswering""",
	    """TFLayoutLMMainLayer""",
	    """TFLayoutLMModel""",
	    """TFLayoutLMPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig, LayoutLMOnnxConfig
	from .tokenization_layoutlm import LayoutLMTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_layoutlm_fast import LayoutLMTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_layoutlm import (
		    LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    LayoutLMForMaskedLM,
		    LayoutLMForQuestionAnswering,
		    LayoutLMForSequenceClassification,
		    LayoutLMForTokenClassification,
		    LayoutLMModel,
		    LayoutLMPreTrainedModel,
		)
	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_layoutlm import (
		    TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFLayoutLMForMaskedLM,
		    TFLayoutLMForQuestionAnswering,
		    TFLayoutLMForSequenceClassification,
		    TFLayoutLMForTokenClassification,
		    TFLayoutLMMainLayer,
		    TFLayoutLMModel,
		    TFLayoutLMPreTrainedModel,
		)

else:
	import sys

	_lowercase				:					Tuple     					=_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






from typing import TYPE_CHECKING

from ...utils import _LazyModule


_lowercase				:					List[Any]     					={"""tokenization_bert_japanese""": ["""BertJapaneseTokenizer""", """CharacterTokenizer""", """MecabTokenizer"""]}


if TYPE_CHECKING:
	from .tokenization_bert_japanese import BertJapaneseTokenizer, CharacterTokenizer, MecabTokenizer

else:
	import sys

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

