





from typing import TYPE_CHECKING

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


__lowerCamelCase :  Optional[Any]										=  {
    """configuration_lxmert""": ["""LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LxmertConfig"""],
    """tokenization_lxmert""": ["""LxmertTokenizer"""],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase :  Optional[int]										=  ["""LxmertTokenizerFast"""]

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

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __lowerCamelCase :  Tuple										=  [
        """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

    __lowerCamelCase :  int										=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)







from ..utils import DummyObject, requires_backends



class       A__     ( metaclass=__snake_case    ):
      _UpperCAmelCase			:Tuple							=     ['note_seq']





      def __init__(				self ,							*A_ ,							**A_     ):
       '''simple docstring'''




       requires_backends(self ,							["note_seq"]     )





      @classmethod
      def  __UpperCamelCase(				cls ,							*A_ ,							**A_     ):
       '''simple docstring'''




       requires_backends(cls ,							["note_seq"]     )





      @classmethod
      def  __UpperCamelCase(				cls ,							*A_ ,							**A_     ):
       '''simple docstring'''




       requires_backends(cls ,							["note_seq"]     )
