






'''simple docstring'''

import importlib
import inspect
import os
import re


# 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
UpperCamelCase      					="src/transformers"


# This is to make sure the transformers module imported is the one in the repo.
UpperCamelCase      					=importlib.util.spec_from_file_location(
    "transformers",
    os.path.join(PATH_TO_TRANSFORMERS, "__init__.py"),
    submodule_search_locations=[PATH_TO_TRANSFORMERS],
)
UpperCamelCase      					=spec.loader.load_module()

UpperCamelCase      					=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)`
UpperCamelCase      					=re.compile("\[(.+?)\]\((https://huggingface\.co/.+?)\)")


UpperCamelCase      					={
    "CLIPConfigMixin",
    "DecisionTransformerConfigMixin",
    "EncoderDecoderConfigMixin",
    "RagConfigMixin",
    "SpeechEncoderDecoderConfigMixin",
    "VisionEncoderDecoderConfigMixin",
    "VisionTextDualEncoderConfigMixin",
}



def 				snake_case       (  )							->					Any:





      """simple docstring"""

      UpperCamelCase_					: List[str]            =				[]

      for config_class in list(CONFIG_MAPPING.values()						):
            UpperCamelCase_					: Dict            =				False

            # source code of `config_class`
            UpperCamelCase_					: List[Any]            =				inspect.getsource(a_						)
            UpperCamelCase_					: Tuple            =				_re_checkpoint.findall(a_						)

            for checkpoint in checkpoints:
                  # Each `checkpoint` is a tuple of a checkpoint name and a checkpoint link.
                  # For example, `('bert-base-uncased', 'https://huggingface.co/bert-base-uncased')`
                  UpperCamelCase_     ,      UpperCamelCase_					: Union[str, Any]            =				checkpoint

                  # verify the checkpoint name corresponds to the checkpoint link
                  UpperCamelCase_					: int            =				f"https://huggingface.co/{ckpt_name}"
                  if ckpt_link == ckpt_link_from_name:
                        UpperCamelCase_					: List[Any]            =				True
                        break

            UpperCamelCase_					: Dict            =				config_class.__name__
            if not checkpoint_found and name not in CONFIG_CLASSES_TO_IGNORE_FOR_DOCSTRING_CHECKPOINT_CHECK:
                  configs_without_checkpoint.append(a_						)

      if len(a_						) > 0:
            UpperCamelCase_					: List[Any]            =				"""\n""".join(sorted(a_						)						)
            raise ValueError(f"The following configurations don't contain any valid checkpoint:\n{message}"						)


if __name__ == "__main__":
      check_config_docstrings_have_checkpoints()














'''simple docstring'''

from __future__ import annotations



def 				snake_case       (  a_				:			list[int]     , a_				:			list[int]     , a_				:			list[int]     , a_				:			list[list[str]]     , a_				:			int     , )							->					None:





      """simple docstring"""

      UpperCamelCase_					: List[Any]            =				len(a_						)

      # If row is equal to the size of the board it means there are a queen in each row in
      # the current board (possible_board)
      if row == n:
            # We convert the variable possible_board that looks like this: [1, 3, 0, 2] to
            # this: ['. Q . . ', '. . . Q ', 'Q . . . ', '. . Q . ']
            boards.append([""". """ * i + """Q """ + """. """ * (n - 1 - i) for i in possible_board]						)
            return

      # We iterate each column in the row to find all possible results in each row
      for col in range(a_						):
            # We apply that we learned previously. First we check that in the current board
            # (possible_board) there are not other same value because if there is it means
            # that there are a collision in vertical. Then we apply the two formulas we
            # learned before:
            #
            # 45º: y - x = b or 45: row - col = b
            # 135º: y + x = b or row + col = b.
            #
            # And we verify if the results of this two formulas not exist in their variables
            # respectively.  (diagonal_right_collisions, diagonal_left_collisions)
            #
            # If any or these are True it means there is a collision so we continue to the
            # next value in the for loop.
            if (
                col in possible_board
                or row - col in diagonal_right_collisions
                or row + col in diagonal_left_collisions
            ):
                  continue

            # If it is False we call dfs function again and we update the inputs
            depth_first_search(
                [*possible_board, col]     , [*diagonal_right_collisions, row - col]     , [*diagonal_left_collisions, row + col]     , a_     , a_     , )



def 				snake_case       (  a_				:			int						)							->					None:





      """simple docstring"""

      UpperCamelCase_					: list[list[str]]            =				[]
      depth_first_search([]     , []     , []     , a_     , a_						)

      # Print all the boards
      for board in boards:
            for column in board:
                  print(a_						)
            print(""""""						)

      print(len(a_						)     , """solutions were found."""						)


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      n_queens_solution(4)






