





'''simple docstring'''


from __future__ import annotations

lowerCAmelCase :					Tuple 							=[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]
def 							UpperCAmelCase_  (						__lowerCamelCase : list[list[int]]     ,__lowerCamelCase : list[int]     ,__lowerCamelCase : list[int]     ,__lowerCamelCase : int     ,__lowerCamelCase : list[list[int]]     ,):
   lowercase_      :Union[str, Any]         =			[
       [0 for col in range(len(grid[0]			)			)] for row in range(len(__lowerCamelCase			)			)
   ]  # the reference grid
   lowercase_      :str         =			1
   lowercase_      :Tuple         =			[
       [0 for col in range(len(grid[0]			)			)] for row in range(len(__lowerCamelCase			)			)
   ]  # the action grid

   lowercase_      :str         =			init[0]
   lowercase_      :Union[str, Any]         =			init[1]
   lowercase_      :int         =			0
   lowercase_      :int         =			g + heuristic[x][y]  # cost from starting cell to destination cell
   lowercase_      :Union[str, Any]         =			[[f, g, x, y]]

   lowercase_      :Any         =			False  # flag that is set when search is complete
   lowercase_      :Any         =			False  # flag set if we can't find expand

   while not found and not resign:
      if len(__lowerCamelCase			) == 0:
         raise ValueError("Algorithm is unable to find solution"			)
      else:  # to choose the least costliest action so as to move closer to the goal
         cell.sort()
         cell.reverse()
         lowercase_      :Tuple         =			cell.pop()
         lowercase_      :List[Any]         =			next_cell[2]
         lowercase_      :Tuple         =			next_cell[3]
         lowercase_      :Optional[int]         =			next_cell[1]

         if x == goal[0] and y == goal[1]:
            lowercase_      :Tuple         =			True
         else:
            for i in range(len(__lowerCamelCase			)			):  # to try out different valid actions
               lowercase_      :List[str]         =			x + DIRECTIONS[i][0]
               lowercase_      :Optional[Any]         =			y + DIRECTIONS[i][1]
               if xa >= 0 and xa < len(__lowerCamelCase			) and ya >= 0 and ya < len(grid[0]			):
                  if closed[xa][ya] == 0 and grid[xa][ya] == 0:
                     lowercase_      :str         =			g + cost
                     lowercase_      :Tuple         =			ga + heuristic[xa][ya]
                     cell.append([fa, ga, xa, ya]			)
                     lowercase_      :int         =			1
                     lowercase_      :Any         =			i
   lowercase_      :int         =			[]
   lowercase_      :Dict         =			goal[0]
   lowercase_      :Union[str, Any]         =			goal[1]
   invpath.append([x, y]			)  # we get the reverse path from here
   while x != init[0] or y != init[1]:
      lowercase_      :Dict         =			x - DIRECTIONS[action[x][y]][0]
      lowercase_      :List[Any]         =			y - DIRECTIONS[action[x][y]][1]
      lowercase_      :str         =			xa
      lowercase_      :str         =			ya
      invpath.append([x, y]			)

   lowercase_      :str         =			[]
   for i in range(len(__lowerCamelCase			)			):
      path.append(invpath[len(__lowerCamelCase			) - 1 - i]			)
   return path, action


if __name__ == "__main__":
 lowerCAmelCase :					Optional[Any] 							=[
     [0, 1, 0, 0, 0, 0],
     [0, 1, 0, 0, 0, 0],  # 0 are free path whereas 1's are obstacles
     [0, 1, 0, 0, 0, 0],
     [0, 1, 0, 0, 1, 0],
     [0, 0, 0, 0, 1, 0],
 ]

 lowerCAmelCase :					List[str] 							=[0, 0]
 # all coordinates are given in format [y,x]
 lowerCAmelCase :					str 							=[len(grid) - 1, len(grid[0]) - 1]
 lowerCAmelCase :					int 							=1

 # the cost map which pushes the path closer to the goal
 lowerCAmelCase :					Optional[int] 							=[[0 for row in range(len(grid[0]))] for col in range(len(grid))]
 for i in range(len(grid)):
  for j in range(len(grid[0])):
   lowerCAmelCase :					Optional[int] 							=abs(i - goal[0]) + abs(j - goal[1])
   if grid[i][j] == 1:
    # added extra penalty in the heuristic map
    lowerCAmelCase :					List[Any] 							=99

 lowerCAmelCase :					Union[str, Any] 							=search(grid, init, goal, cost, heuristic)

 print('''ACTION MAP''')
 for i in range(len(action)):
  print(action[i])

 for i in range(len(path)):
  print(path[i])









'''simple docstring'''


from typing import TYPE_CHECKING

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


lowerCAmelCase :					int 							={
    '''configuration_clip''': [
        '''CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''CLIPConfig''',
        '''CLIPOnnxConfig''',
        '''CLIPTextConfig''',
        '''CLIPVisionConfig''',
    ],
    '''processing_clip''': ['''CLIPProcessor'''],
    '''tokenization_clip''': ['''CLIPTokenizer'''],
}

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					Any 							=['''CLIPTokenizerFast''']

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					str 							=['''CLIPFeatureExtractor''']
 lowerCAmelCase :					Optional[int] 							=['''CLIPImageProcessor''']

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					Any 							=[
     '''CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''CLIPModel''',
     '''CLIPPreTrainedModel''',
     '''CLIPTextModel''',
     '''CLIPTextModelWithProjection''',
     '''CLIPVisionModel''',
     '''CLIPVisionModelWithProjection''',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					Union[str, Any] 							=[
     '''TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TFCLIPModel''',
     '''TFCLIPPreTrainedModel''',
     '''TFCLIPTextModel''',
     '''TFCLIPVisionModel''',
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 lowerCAmelCase :					List[Any] 							=[
     '''FlaxCLIPModel''',
     '''FlaxCLIPPreTrainedModel''',
     '''FlaxCLIPTextModel''',
     '''FlaxCLIPTextPreTrainedModel''',
     '''FlaxCLIPVisionModel''',
     '''FlaxCLIPVisionPreTrainedModel''',
 ]


if TYPE_CHECKING:
 from .configuration_clip import (
     CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
     CLIPConfig,
     CLIPOnnxConfig,
     CLIPTextConfig,
     CLIPVisionConfig,
 )
 from .processing_clip import CLIPProcessor
 from .tokenization_clip import CLIPTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_clip_fast import CLIPTokenizerFast

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .feature_extraction_clip import CLIPFeatureExtractor
  from .image_processing_clip import CLIPImageProcessor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_clip import (
      CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      CLIPModel,
      CLIPPreTrainedModel,
      CLIPTextModel,
      CLIPTextModelWithProjection,
      CLIPVisionModel,
      CLIPVisionModelWithProjection,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_clip import (
      TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFCLIPModel,
      TFCLIPPreTrainedModel,
      TFCLIPTextModel,
      TFCLIPVisionModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_clip import (
      FlaxCLIPModel,
      FlaxCLIPPreTrainedModel,
      FlaxCLIPTextModel,
      FlaxCLIPTextPreTrainedModel,
      FlaxCLIPVisionModel,
      FlaxCLIPVisionPreTrainedModel,
  )


else:
 import sys

 lowerCAmelCase :					int 							=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


