




'''simple docstring'''




from __future__ import annotations

a_      :		Any							      =       [
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]





def      a_							(      __snake_case							:			list[list[int]]   ,       __snake_case							:			list[int]   ,       __snake_case							:			list[int]   ,       __snake_case							:			int   ,       __snake_case							:			list[list[int]]   ,       )							->						tuple[list[list[int]], list[list[int]]]:



       """simple docstring"""
       lowerCamelCase_							=[
           [0 for col in range(len(grid[0]   )   )] for row in range(len(__snake_case   )   )
       ]  # the reference grid
       lowerCamelCase_							=1
       lowerCamelCase_							=[
           [0 for col in range(len(grid[0]   )   )] for row in range(len(__snake_case   )   )
       ]  # the action grid

       lowerCamelCase_							=init[0]
       lowerCamelCase_							=init[1]
       lowerCamelCase_							=0
       lowerCamelCase_							=g + heuristic[x][y]  # cost from starting cell to destination cell
       lowerCamelCase_							=[[f, g, x, y]]

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

       while not found and not resign:
              if len(__snake_case   ) == 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()
                     lowerCamelCase_							=cell.pop()
                     lowerCamelCase_							=next_cell[2]
                     lowerCamelCase_							=next_cell[3]
                     lowerCamelCase_							=next_cell[1]

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

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


if __name__ == "__main__":
     a_      :		Dict							      =       [
         [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],
     ]

     a_      :		Tuple							      =       [0, 0]
     # all coordinates are given in format [y,x]
     a_      :		Optional[int]							      =       [len(grid) - 1, len(grid[0]) - 1]
     a_      :		List[Any]							      =       1

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

     a_      ,       a_      :		str							      =       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])







import os

import pytest
import yaml

from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict





@pytest.mark.parametrize(
    'files'   ,							[
        ['full:README.md', 'dataset_infos.json'],
        ['empty:README.md', 'dataset_infos.json'],
        ['dataset_infos.json'],
        ['full:README.md'],
    ]   ,							)
def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    tmp_path_factory.mktemp('dset_infos_dir'      )
							if "full:README.md" in files:
														with open(dataset_infos_dir / 'README.md'   ,							'w'      ) as f:
																					f.write('---\ndataset_info:\n  dataset_size: 42\n---'      )
							if "empty:README.md" in files:
														with open(dataset_infos_dir / 'README.md'   ,							'w'      ) as f:
																					f.write(''      )
    # we want to support dataset_infos.json for backward compatibility
							if "dataset_infos.json" in files:
														with open(dataset_infos_dir / 'dataset_infos.json'   ,							'w'      ) as f:
																					f.write('{"default": {"dataset_size": 42}}'      )
							snake_case_							=    DatasetInfosDict.from_directory(UpperCamelCase__      )
							assert dataset_infos
							assert dataset_infos["default"].dataset_size == 42





@pytest.mark.parametrize(
    'dataset_info'   ,							[
        DatasetInfo(),
        DatasetInfo(
            description='foo'   ,							features=Features({'a': Value('int32'      )}      )   ,							builder_name='builder'   ,							config_name='config'   ,							version='1.0.0'   ,							splits=[{'name': 'train'}]   ,							download_size=42   ,							),
    ]   ,							)
def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    str(UpperCamelCase__      )
							dataset_info.write_to_directory(UpperCamelCase__      )
							snake_case_							=    DatasetInfo.from_directory(UpperCamelCase__      )
							assert dataset_info == reloaded
							assert os.path.exists(os.path.join(UpperCamelCase__   ,							'dataset_info.json'      )      )





def 					__lowerCamelCase	( ):







							'''simple docstring'''






							snake_case_							=    DatasetInfo(
							    description='foo'   ,							citation='bar'   ,							homepage='https://foo.bar'   ,							license='CC0'   ,							features=Features({'a': Value('int32'      )}      )   ,							post_processed={}   ,							supervised_keys=()   ,							task_templates=[]   ,							builder_name='builder'   ,							config_name='config'   ,							version='1.0.0'   ,							splits=[{'name': 'train', 'num_examples': 42}]   ,							download_checksums={}   ,							download_size=1337   ,							post_processing_size=442   ,							dataset_size=1234   ,							size_in_bytes=1337 + 442 + 1234   ,							)
							snake_case_							=    dataset_info._to_yaml_dict()
							assert sorted(UpperCamelCase__      ) == sorted(DatasetInfo._INCLUDED_INFO_IN_YAML      )
							for key in DatasetInfo._INCLUDED_INFO_IN_YAML:
														assert key in dataset_info_yaml_dict
														assert isinstance(dataset_info_yaml_dict[key]   ,							(list, dict, int, str)      )
							snake_case_							=    yaml.safe_dump(UpperCamelCase__      )
							snake_case_							=    yaml.safe_load(UpperCamelCase__      )
							assert dataset_info_yaml_dict == reloaded





def 					__lowerCamelCase	( ):







							'''simple docstring'''






							snake_case_							=    DatasetInfo()
							snake_case_							=    dataset_info._to_yaml_dict()
							assert dataset_info_yaml_dict == {}





@pytest.mark.parametrize(
    'dataset_infos_dict'   ,							[
        DatasetInfosDict(),
        DatasetInfosDict({'default': DatasetInfo()}      ),
        DatasetInfosDict({'my_config_name': DatasetInfo()}      ),
        DatasetInfosDict(
            {
                'default': DatasetInfo(
                    description='foo'   ,							features=Features({'a': Value('int32'      )}      )   ,							builder_name='builder'   ,							config_name='config'   ,							version='1.0.0'   ,							splits=[{'name': 'train'}]   ,							download_size=42   ,							)
            }      ),
        DatasetInfosDict(
            {
                'v1': DatasetInfo(dataset_size=42      ),
                'v2': DatasetInfo(dataset_size=1337      ),
            }      ),
    ]   ,							)
def 					__lowerCamelCase	( UpperCamelCase__   ,							UpperCamelCase__      ):







							'''simple docstring'''






							snake_case_							=    str(UpperCamelCase__      )
							dataset_infos_dict.write_to_directory(UpperCamelCase__      )
							snake_case_							=    DatasetInfosDict.from_directory(UpperCamelCase__      )

							# the config_name of the dataset_infos_dict take over the attribute
							for config_name, dataset_info in dataset_infos_dict.items():
														snake_case_							=    config_name
														# the yaml representation doesn't include fields like description or citation
														# so we just test that we can recover what we can from the yaml
														snake_case_							=    DatasetInfo._from_yaml_dict(dataset_info._to_yaml_dict()      )
							assert dataset_infos_dict == reloaded

							if dataset_infos_dict:
														assert os.path.exists(os.path.join(UpperCamelCase__   ,							'README.md'      )      )




