






from typing import TYPE_CHECKING

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


__UpperCAmelCase								=						{
    'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertConfig'],
    'tokenization_lxmert': ['LxmertTokenizer'],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						['LxmertTokenizerFast']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'LxmertEncoder',
		    'LxmertForPreTraining',
		    'LxmertForQuestionAnswering',
		    'LxmertModel',
		    'LxmertPreTrainedModel',
		    'LxmertVisualFeatureEncoder',
		    'LxmertXLayer',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCAmelCase								=						[
		    'TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFLxmertForPreTraining',
		    'TFLxmertMainLayer',
		    'TFLxmertModel',
		    'TFLxmertPreTrainedModel',
		    'TFLxmertVisualFeatureEncoder',
		]


if TYPE_CHECKING:
		from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
		from .tokenization_lxmert import LxmertTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_lxmert_fast import LxmertTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_lxmert import (
				    LxmertEncoder,
				    LxmertForPreTraining,
				    LxmertForQuestionAnswering,
				    LxmertModel,
				    LxmertPreTrainedModel,
				    LxmertVisualFeatureEncoder,
				    LxmertXLayer,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_lxmert import (
				    TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFLxmertForPreTraining,
				    TFLxmertMainLayer,
				    TFLxmertModel,
				    TFLxmertPreTrainedModel,
				    TFLxmertVisualFeatureEncoder,
				)

else:
		import sys

		__UpperCAmelCase								=						_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)













from ..utils import DummyObject, requires_backends




class     SCREAMING_SNAKE_CASE__ (						metaclass=UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	['''keras_nlp''']



 def __init__(							self,*__lowerCamelCase,**__lowerCamelCase ):
        requires_backends(self,['''keras_nlp'''] )





