




from typing import TYPE_CHECKING

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


__UpperCamelCase					:       Tuple    					=      {
    "configuration_bridgetower": [
        "BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BridgeTowerConfig",
        "BridgeTowerTextConfig",
        "BridgeTowerVisionConfig",
    ],
    "processing_bridgetower": ["BridgeTowerProcessor"],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCamelCase					:       str    					=      ["BridgeTowerImageProcessor"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__UpperCamelCase					:       Optional[Any]    					=      [
		    "BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "BridgeTowerForContrastiveLearning",
		    "BridgeTowerForImageAndTextRetrieval",
		    "BridgeTowerForMaskedLM",
		    "BridgeTowerModel",
		    "BridgeTowerPreTrainedModel",
		]


if TYPE_CHECKING:
		from .configuration_bridgetower import (
		    BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    BridgeTowerConfig,
		    BridgeTowerTextConfig,
		    BridgeTowerVisionConfig,
		)
		from .processing_bridgetower import BridgeTowerProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_bridgetower import BridgeTowerImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bridgetower import (
				    BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BridgeTowerForContrastiveLearning,
				    BridgeTowerForImageAndTextRetrieval,
				    BridgeTowerForMaskedLM,
				    BridgeTowerModel,
				    BridgeTowerPreTrainedModel,
				)


else:
		import sys

		__UpperCamelCase					:       str    					=      _LazyModule(__name__, globals()["__file__"], _import_structure)







from __future__ import annotations





def 		__A		(	__lowerCamelCase							,			__lowerCamelCase    )      ->       float:
	a										=							sorted(numsa + numsa    )
	a				, a										=							divmod(len(__lowerCamelCase    )							,			2    )
	if mod == 1:
		return all_numbers[div]
	else:
		return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		__UpperCamelCase					:       Tuple    					=      [float(x) for x in input("Enter the elements of first array: ").split()]
		__UpperCamelCase					:       List[Any]    					=      [float(x) for x in input("Enter the elements of second array: ").split()]
		print(F'The median of two arrays is: {median_of_two_arrays(array_a, array_a)}')

