




from heapq import heappop, heappush

import numpy as np




def     __magic_name__       (				A	:      np.ndarray,						A	:      tuple[int, int],						A	:      tuple[int, int],						A	:      bool,						):






			'''simple docstring'''







			a					,	a					=    grid.shape
			a					=    [-1, 1, 0, 0]
			a					=    [0, 0, -1, 1]
			if allow_diagonal:
						dx += [-1, -1, 1, 1]
						dy += [-1, 1, -1, 1]

			a					,	a					=    [(0, source)], set()
			a					=    np.full((rows, cols),						np.inf     )
			a					=    0
			a					=    np.empty((rows, cols),						dtype=A     )
			a					=    None

			while queue:
						((a)					,	(a))					=    heappop(A     )
						if (x, y) in visited:
									continue
						visited.add((x, y)     )

						if (x, y) == destination:
									a					=    []
									while (x, y) != source:
												path.append((x, y)     )
												a					,	a					=    predecessors[x, y]
									path.append(A     )  # add the source manually
									path.reverse()
									return matrix[destination], path

						for i in range(len(A     )     ):
									a					,	a					=    x + dx[i], y + dy[i]
									if 0 <= nx < rows and 0 <= ny < cols:
												a					=    grid[nx][ny]
												if next_node == 1 and matrix[nx, ny] > dist + 1:
															heappush(A,						(dist + 1, (nx, ny))     )
															a					=    dist + 1
															a					=    (x, y)

			return np.inf, []


if __name__ == "__main__":
		import doctest

		doctest.testmod()












from typing import TYPE_CHECKING

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


__lowerCAmelCase	:       Dict     =	{
    'configuration_blip': [
        'BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'BlipConfig',
        'BlipTextConfig',
        'BlipVisionConfig',
    ],
    'processing_blip': ['BlipProcessor'],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Optional[Any]     =	['BlipImageProcessor']


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       List[Any]     =	[
		    'BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'BlipModel',
		    'BlipPreTrainedModel',
		    'BlipForConditionalGeneration',
		    'BlipForQuestionAnswering',
		    'BlipVisionModel',
		    'BlipTextModel',
		    'BlipForImageTextRetrieval',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCAmelCase	:       Any     =	[
		    'TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'TFBlipModel',
		    'TFBlipPreTrainedModel',
		    'TFBlipForConditionalGeneration',
		    'TFBlipForQuestionAnswering',
		    'TFBlipVisionModel',
		    'TFBlipTextModel',
		    'TFBlipForImageTextRetrieval',
		]

if TYPE_CHECKING:
		from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
		from .processing_blip import BlipProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .image_processing_blip import BlipImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_blip import (
				    BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BlipForConditionalGeneration,
				    BlipForImageTextRetrieval,
				    BlipForQuestionAnswering,
				    BlipModel,
				    BlipPreTrainedModel,
				    BlipTextModel,
				    BlipVisionModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_blip import (
				    TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    TFBlipForConditionalGeneration,
				    TFBlipForImageTextRetrieval,
				    TFBlipForQuestionAnswering,
				    TFBlipModel,
				    TFBlipPreTrainedModel,
				    TFBlipTextModel,
				    TFBlipVisionModel,
				)

else:
		import sys

		__lowerCAmelCase	:       List[str]     =	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






