
"""simple docstring"""




from typing import TYPE_CHECKING

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


__lowerCAmelCase    :							Tuple													=						{
    "configuration_conditional_detr": [
        "CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "ConditionalDetrConfig",
        "ConditionalDetrOnnxConfig",
    ]
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__lowerCAmelCase    :							Any													=						["ConditionalDetrFeatureExtractor"]
			__lowerCAmelCase    :							Union[str, Any]													=						["ConditionalDetrImageProcessor"]

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			__lowerCAmelCase    :							str													=						[
			    "CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
			    "ConditionalDetrForObjectDetection",
			    "ConditionalDetrForSegmentation",
			    "ConditionalDetrModel",
			    "ConditionalDetrPreTrainedModel",
			]


if TYPE_CHECKING:
			from .configuration_conditional_detr import (
			    CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    ConditionalDetrConfig,
			    ConditionalDetrOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_conditional_detr import ConditionalDetrFeatureExtractor
						from .image_processing_conditional_detr import ConditionalDetrImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_conditional_detr import (
						    CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ConditionalDetrForObjectDetection,
						    ConditionalDetrForSegmentation,
						    ConditionalDetrModel,
						    ConditionalDetrPreTrainedModel,
						)

else:
			import sys

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





"""simple docstring"""




import os
from math import logaa







def 							_UpperCAmelCase		(       lowerCamelCase__ = "base_exp.txt"     ):





		"""simple docstring"""




		lowerCAmelCase__        =   0
		lowerCAmelCase__        =   0
		for i, line in enumerate(open(os.path.join(os.path.dirname(lowerCamelCase__     )			,  lowerCamelCase__     )     )     ):
				lowerCAmelCase__   ,					lowerCAmelCase__        =   list(map(lowerCamelCase__			,  line.split(""","""     )     )     )
				if x * logaa(lowerCamelCase__     ) > largest:
						lowerCAmelCase__        =   x * logaa(lowerCamelCase__     )
						lowerCAmelCase__        =   i + 1
		return result


if __name__ == "__main__":
			print(solution())




