
"""simple docstring"""
lowercase		:    str			=       [
    [0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
    [0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
    [0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 0, 0],
    [0, 1, 0, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0],
    [0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
]


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)  ->      bool:


					'''simple docstring'''
					return 0 <= row < rows and 0 <= col < cols


def      lowerCamelCase_     (						lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)  ->      int:


					'''simple docstring'''
					__a:    Union[str, Any]		     =       len(lowerCamelCase_			)
					__a:    Union[str, Any]		     =       len(mat[0]			)
					if is_safe(lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			) and (row, col) not in seen and mat[row][col] == 1:
										seen.add((row, col)			)
										return (
										    1
										    + depth_first_search(row + 1						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)
										    + depth_first_search(row - 1						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)
										    + depth_first_search(lowerCamelCase_						,					col + 1						,					lowerCamelCase_						,					lowerCamelCase_			)
										    + depth_first_search(lowerCamelCase_						,					col - 1						,					lowerCamelCase_						,					lowerCamelCase_			)
										)
					else:
										return 0


def      lowerCamelCase_     (						lowerCamelCase_			)  ->      int:


					'''simple docstring'''
					__a:    set		     =       set()

					__a:    Dict		     =       0
					for row, line in enumerate(lowerCamelCase_			):
										for col, item in enumerate(lowerCamelCase_			):
															if item == 1 and (row, col) not in seen:
																				# Maximizing the area
																				__a:    Dict		     =       max(lowerCamelCase_						,					depth_first_search(lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_						,					lowerCamelCase_			)			)
					return max_area


if __name__ == "__main__":
			import doctest

			print(find_max_area(matrix))  # Output -> 6
			doctest.testmod()


"""simple docstring"""
from typing import TYPE_CHECKING

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


lowercase		:    Dict			=       {
    'configuration_mobilenet_v1': [
        'MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileNetV1Config',
        'MobileNetV1OnnxConfig',
    ],
}

try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Optional[int]			=       ['MobileNetV1FeatureExtractor']
			lowercase		:    Union[str, Any]			=       ['MobileNetV1ImageProcessor']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowercase		:    Tuple			=       [
			    'MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'MobileNetV1ForImageClassification',
			    'MobileNetV1Model',
			    'MobileNetV1PreTrainedModel',
			    'load_tf_weights_in_mobilenet_v1',
			]


if TYPE_CHECKING:
			from .configuration_mobilenet_va import (
			    MOBILENET_V1_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    MobileNetVaConfig,
			    MobileNetVaOnnxConfig,
			)

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .feature_extraction_mobilenet_va import MobileNetVaFeatureExtractor
						from .image_processing_mobilenet_va import MobileNetVaImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_mobilenet_va import (
						    MOBILENET_V1_PRETRAINED_MODEL_ARCHIVE_LIST,
						    MobileNetVaForImageClassification,
						    MobileNetVaModel,
						    MobileNetVaPreTrainedModel,
						    load_tf_weights_in_mobilenet_va,
						)


else:
			import sys

			lowercase		:    Union[str, Any]			=       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
