





"""simple docstring"""






from typing import TYPE_CHECKING

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


lowerCAmelCase_			=							{
    """configuration_blenderbot""": [
        """BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """BlenderbotConfig""",
        """BlenderbotOnnxConfig""",
    ],
    """tokenization_blenderbot""": ["""BlenderbotTokenizer"""],
}

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase_			=							[
        """BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """BlenderbotForCausalLM""",
        """BlenderbotForConditionalGeneration""",
        """BlenderbotModel""",
        """BlenderbotPreTrainedModel""",
    ]


try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase_			=							[
        """TFBlenderbotForConditionalGeneration""",
        """TFBlenderbotModel""",
        """TFBlenderbotPreTrainedModel""",
    ]


try:
    if not is_flax_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase_			=							[
        """FlaxBlenderbotForConditionalGeneration""",
        """FlaxBlenderbotModel""",
        """FlaxBlenderbotPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_blenderbot import (
        BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        BlenderbotConfig,
        BlenderbotOnnxConfig,
    )
    from .tokenization_blenderbot import BlenderbotTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_blenderbot_fast import BlenderbotTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_blenderbot import (
            BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
            BlenderbotForCausalLM,
            BlenderbotForConditionalGeneration,
            BlenderbotModel,
            BlenderbotPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_blenderbot import (
            TFBlenderbotForConditionalGeneration,
            TFBlenderbotModel,
            TFBlenderbotPreTrainedModel,
        )

    try:
        if not is_flax_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_flax_blenderbot import (
            FlaxBlenderbotForConditionalGeneration,
            FlaxBlenderbotModel,
            FlaxBlenderbotPreTrainedModel,
        )

else:
    import sys

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









"""simple docstring"""






def       __lowerCamelCase    (       SCREAMING_SNAKE_CASE,SCREAMING_SNAKE_CASE							)		->       str:






       """simple docstring"""




       if a < 0 or b < 0:
              raise ValueError('the value of both inputs must be positive'							)

       _UpperCAmelCase     =     str(bin(SCREAMING_SNAKE_CASE							)							)[2:]  # remove the leading "0b"
       _UpperCAmelCase     =     str(bin(SCREAMING_SNAKE_CASE							)							)[2:]  # remove the leading "0b"

       _UpperCAmelCase     =     max(len(SCREAMING_SNAKE_CASE							),len(SCREAMING_SNAKE_CASE							)							)

       return "0b" + "".join(
           str(int(char_a == '1' and char_b == '1'							)							)
           for char_a, char_b in zip(a_binary.zfill(SCREAMING_SNAKE_CASE							),b_binary.zfill(SCREAMING_SNAKE_CASE							)							)							)


if __name__ == "__main__":
    import doctest

    doctest.testmod()






