



'''simple docstring'''





from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__      					=     {
    """configuration_squeezebert""": [
        """SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """SqueezeBertConfig""",
        """SqueezeBertOnnxConfig""",
    ],
    """tokenization_squeezebert""": ["""SqueezeBertTokenizer"""],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	SCREAMING_SNAKE_CASE__      					=     ["""SqueezeBertTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	SCREAMING_SNAKE_CASE__      					=     [
	    """SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """SqueezeBertForMaskedLM""",
	    """SqueezeBertForMultipleChoice""",
	    """SqueezeBertForQuestionAnswering""",
	    """SqueezeBertForSequenceClassification""",
	    """SqueezeBertForTokenClassification""",
	    """SqueezeBertModel""",
	    """SqueezeBertModule""",
	    """SqueezeBertPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_squeezebert import (
	    SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    SqueezeBertConfig,
	    SqueezeBertOnnxConfig,
	)
	from .tokenization_squeezebert import SqueezeBertTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_squeezebert import (
		    SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    SqueezeBertForMaskedLM,
		    SqueezeBertForMultipleChoice,
		    SqueezeBertForQuestionAnswering,
		    SqueezeBertForSequenceClassification,
		    SqueezeBertForTokenClassification,
		    SqueezeBertModel,
		    SqueezeBertModule,
		    SqueezeBertPreTrainedModel,
		)

else:
	import sys

	SCREAMING_SNAKE_CASE__      					=     _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









'''simple docstring'''





print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))




