






from __future__ import annotations

__lowerCamelCase   :					Dict   							=					[
    [-1, 0],  # left
    [0, -1],  # down
    [1, 0],  # right
    [0, 1],  # up
]

def 	__UpperCAmelCase       ( __magic_name__     ,__magic_name__     ,__magic_name__     ,__magic_name__     ,__magic_name__     ,)->    tuple[list[list[int]], list[list[int]]]:



			"""simple docstring"""



			snake_case_				:					List[Any]   =       [
			    [0 for col in range(len(grid[0]						)						)] for row in range(len(__magic_name__						)						)
			]  # the reference grid
			snake_case_				:					Optional[Any]   =       1
			snake_case_				:					Union[str, Any]   =       [
			    [0 for col in range(len(grid[0]						)						)] for row in range(len(__magic_name__						)						)
			]  # the action grid

			snake_case_				:					List[Any]   =       init[0]
			snake_case_				:					List[Any]   =       init[1]
			snake_case_				:					Any   =       0
			snake_case_				:					Tuple   =       g + heuristic[x][y]  # cost from starting cell to destination cell
			snake_case_				:					Tuple   =       [[f, g, x, y]]

			snake_case_				:					List[Any]   =       False  # flag that is set when search is complete
			snake_case_				:					Tuple   =       False  # flag set if we can't find expand

			while not found and not resign:
						if len(__magic_name__						) == 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()
									snake_case_				:					Tuple   =       cell.pop()
									snake_case_				:					List[str]   =       next_cell[2]
									snake_case_				:					int   =       next_cell[3]
									snake_case_				:					Optional[int]   =       next_cell[1]

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

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


if __name__ == "__main__":
		__lowerCamelCase   :					Optional[int]   							=					[
		    [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   :					Any   							=					[0, 0]
		# all coordinates are given in format [y,x]
		__lowerCamelCase   :					Optional[Any]   							=					[len(grid) - 1, len(grid[0]) - 1]
		__lowerCamelCase   :					Any   							=					1

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

		__lowerCamelCase   :					Dict   							=					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'''




import inspect
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowerCamelCase   :					Any   							=					'''src/transformers'''


# This is to make sure the transformers module imported is the one in the repo.
__lowerCamelCase   :					List[str]   							=					direct_transformers_import(PATH_TO_TRANSFORMERS)

__lowerCamelCase   :					Optional[Any]   							=					transformers.models.auto.configuration_auto.CONFIG_MAPPING

# Regex pattern used to find the checkpoint mentioned in the docstring of `config_class`.
# For example, `[bert-base-uncased](https://huggingface.co/bert-base-uncased)`
__lowerCamelCase   :					Union[str, Any]   							=					re.compile(R'''\[(.+?)\]\((https://huggingface\.co/.+?)\)''')


__lowerCamelCase   :					Any   							=					{
    '''DecisionTransformerConfig''',
    '''EncoderDecoderConfig''',
    '''MusicgenConfig''',
    '''RagConfig''',
    '''SpeechEncoderDecoderConfig''',
    '''TimmBackboneConfig''',
    '''VisionEncoderDecoderConfig''',
    '''VisionTextDualEncoderConfig''',
    '''LlamaConfig''',
}

def 	__UpperCAmelCase       ( __magic_name__						)->    List[Any]:



			"""simple docstring"""



			snake_case_				:					Tuple   =       None

			# source code of `config_class`
			snake_case_				:					List[Any]   =       inspect.getsource(__magic_name__						)
			snake_case_				:					List[str]   =       _re_checkpoint.findall(__magic_name__						)

			# Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
			# For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
			for ckpt_name, ckpt_link in checkpoints:
						# allow the link to end with `/`
						if ckpt_link.endswith("/"						):
									snake_case_				:					Optional[Any]   =       ckpt_link[:-1]

						# verify the checkpoint name corresponds to the checkpoint link
						snake_case_				:					str   =       F'''https://huggingface.co/{ckpt_name}'''
						if ckpt_link == ckpt_link_from_name:
									snake_case_				:					Dict   =       ckpt_name
									break

			return checkpoint

def 	__UpperCAmelCase       ( )->    Dict:



			"""simple docstring"""



			snake_case_				:					Optional[int]   =       []

			for config_class in list(CONFIG_MAPPING.values()						):
						# Skip deprecated models
						if "models.deprecated" in config_class.__module__:
									continue
						snake_case_				:					str   =       get_checkpoint_from_config_class(__magic_name__						)

						snake_case_				:					Union[str, Any]   =       config_class.__name__
						if checkpoint is None and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
									configs_without_checkpoint.append(__magic_name__						)

			if len(__magic_name__						) > 0:
						snake_case_				:					Tuple   =       "\n".join(sorted(__magic_name__						)						)
						raise ValueError(F'''The following configurations don\'t contain any valid checkpoint:\n{message}'''						)


if __name__ == "__main__":
		check_config_docstrings_have_checkpoints()




