


import os
import re
import shutil
from argparse import ArgumentParser, Namespace

from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger


UpperCAmelCase_      : Optional[int]  					=       '<<<<<<< This should probably be modified because it mentions: '

UpperCAmelCase_      : Tuple  					=       '=======\n>>>>>>>\n'

UpperCAmelCase_      : Tuple  					=       [
    'TextEncoderConfig',
    'ByteTextEncoder',
    'SubwordTextEncoder',
    'encoder_config',
    'maybe_build_from_corpus',
    'manual_dir',
]

UpperCAmelCase_      : List[str]  					=       [
    # (pattern, replacement)
    # Order is important here for some replacements
    (R'tfds\.core', R'datasets'),
    (R'tf\.io\.gfile\.GFile', R'open'),
    (R'tf\.([\w\d]+)', R'datasets.Value(\'\1\')'),
    (R'tfds\.features\.Text\(\)', R'datasets.Value(\'string\')'),
    (R'tfds\.features\.Text\(', R'datasets.Value(\'string\'),'),
    (R'features\s*=\s*tfds.features.FeaturesDict\(', R'features=datasets.Features('),
    (R'tfds\.features\.FeaturesDict\(', R'dict('),
    (R'The TensorFlow Datasets Authors', R'The TensorFlow Datasets Authors and the HuggingFace Datasets Authors'),
    (R'tfds\.', R'datasets.'),
    (R'dl_manager\.manual_dir', R'self.config.data_dir'),
    (R'self\.builder_config', R'self.config'),
]







def        SCREAMING_SNAKE_CASE_						(			__A :			Namespace				)	->		Optional[Any]:

       """simple docstring"""

       return ConvertCommand(args.tfds_path  ,    args.datasets_directory				)
class  SCREAMING_SNAKE_CASE__  (				lowercase__			):
      @staticmethod
      def        SCREAMING_SNAKE_CASE							(       SCREAMING_SNAKE_CASE__				:       ArgumentParser     )		->			int:
             a_					:		Tuple							=  parser.add_parser(
                 'convert'     ,							help='Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.'     ,							)
             train_parser.add_argument(
                 '--tfds_path'     ,							type=SCREAMING_SNAKE_CASE__     ,							required=SCREAMING_SNAKE_CASE__     ,							help='Path to a TensorFlow Datasets folder to convert or a single tfds file to convert.'     ,							)
             train_parser.add_argument(
                 '--datasets_directory'     ,							type=SCREAMING_SNAKE_CASE__     ,							required=SCREAMING_SNAKE_CASE__     ,							help='Path to the HuggingFace Datasets folder.'     )
             train_parser.set_defaults(func=SCREAMING_SNAKE_CASE__     )
      def __init__(       self				:       int     ,							SCREAMING_SNAKE_CASE__				:       str     ,							SCREAMING_SNAKE_CASE__				:       str     ,							*SCREAMING_SNAKE_CASE__				:       Optional[Any]     )		->			Tuple:
             a_					:		List[str]							=  get_logger('datasets-cli/converting'     )

             a_					:		Union[str, Any]							=  tfds_path
             a_					:		Any							=  datasets_directory

      def        SCREAMING_SNAKE_CASE							(       self				:       str     )		->			Tuple:
             if os.path.isdir(self._tfds_path     ):
                    a_					:		Dict							=  os.path.abspath(self._tfds_path     )
             elif os.path.isfile(self._tfds_path     ):
                    a_					:		Tuple							=  os.path.dirname(self._tfds_path     )
             else:
                    raise ValueError('--tfds_path is neither a directory nor a file. Please check path.'     )

             a_					:		Dict							=  os.path.abspath(self._datasets_directory     )

             self._logger.info(F"""Converting datasets from {abs_tfds_path} to {abs_datasets_path}"""     )

             a_					:		Optional[Any]							=  []
             a_					:		Any							=  []
             a_					:		Union[str, Any]							=  {}

             if os.path.isdir(self._tfds_path     ):
                    a_					:		Any							=  os.listdir(SCREAMING_SNAKE_CASE__     )
             else:
                    a_					:		int							=  [os.path.basename(self._tfds_path     )]

             for f_name in file_names:
                    self._logger.info(F"""Looking at file {f_name}"""     )
                    a_					:		List[str]							=  os.path.join(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
                    a_					:		List[Any]							=  os.path.join(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )

                    if not os.path.isfile(SCREAMING_SNAKE_CASE__     ) or "__init__" in f_name or "_test" in f_name or ".py" not in f_name:
                           self._logger.info('Skipping file'     )
                           continue

                    with open(SCREAMING_SNAKE_CASE__     ,							encoding='utf-8'     ) as f:
                           a_					:		Union[str, Any]							=  f.readlines()

                    a_					:		List[str]							=  []
                    a_					:		Optional[int]							=  False
                    a_					:		List[str]							=  False
                    a_					:		List[str]							=  []
                    for line in lines:
                           a_					:		str							=  line

                           # Convert imports
                           if "import tensorflow.compat.v2 as tf" in out_line:
                                  continue
                           elif "@tfds.core" in out_line:
                                  continue
                           elif "builder=self" in out_line:
                                  continue
                           elif "import tensorflow_datasets.public_api as tfds" in out_line:
                                  a_					:		Optional[int]							=  'import datasets\n'
                           elif "import tensorflow" in out_line:
                                  # order is important here
                                  a_					:		Optional[int]							=  ''
                                  continue
                           elif "from absl import logging" in out_line:
                                  a_					:		Dict							=  'from datasets import logging\n'
                           elif "getLogger" in out_line:
                                  a_					:		Optional[Any]							=  out_line.replace('getLogger'     ,							'get_logger'     )
                           elif any(expression in out_line for expression in TO_HIGHLIGHT     ):
                                  a_					:		List[str]							=  True
                                  a_					:		int							=  list(filter(lambda SCREAMING_SNAKE_CASE__     : e in out_line     ,							SCREAMING_SNAKE_CASE__     )     )
                                  out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(SCREAMING_SNAKE_CASE__     ) + '\n'     )
                                  out_lines.append(SCREAMING_SNAKE_CASE__     )
                                  out_lines.append(SCREAMING_SNAKE_CASE__     )
                                  continue
                           else:
                                  for pattern, replacement in TO_CONVERT:
                                         a_					:		Dict							=  re.sub(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )

                # Take care of saving utilities (to later move them together with main script)
                           if "tensorflow_datasets" in out_line:
                                  a_					:		str							=  re.match(r'from\stensorflow_datasets.*import\s([^\.\r\n]+)'     ,							SCREAMING_SNAKE_CASE__     )
                                  tfds_imports.extend(imp.strip() for imp in match.group(1     ).split(','     )     )
                                  a_					:		Optional[int]							=  'from . import ' + match.group(1     )

                           # Check we have not forget anything
                           if "tf." in out_line or "tfds." in out_line or "tensorflow_datasets" in out_line:
                                  raise ValueError(F"""Error converting {out_line.strip()}"""     )

                           if "GeneratorBasedBuilder" in out_line or "BeamBasedBuilder" in out_line:
                                  a_					:		Dict							=  True
                           out_lines.append(SCREAMING_SNAKE_CASE__     )

                    if is_builder or "wmt" in f_name:
                           # We create a new directory for each dataset
                           a_					:		Any							=  f_name.replace('.py'     ,							''     )
                           a_					:		Union[str, Any]							=  os.path.join(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
                           a_					:		Any							=  os.path.join(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
                           os.makedirs(SCREAMING_SNAKE_CASE__     ,							exist_ok=SCREAMING_SNAKE_CASE__     )
                           self._logger.info(F"""Adding directory {output_dir}"""     )
                           imports_to_builder_map.update({imp: output_dir for imp in tfds_imports}     )
                    else:
                           # Utilities will be moved at the end
                           utils_files.append(SCREAMING_SNAKE_CASE__     )

                    if needs_manual_update:
                           with_manual_update.append(SCREAMING_SNAKE_CASE__     )

                    with open(SCREAMING_SNAKE_CASE__     ,							'w'     ,							encoding='utf-8'     ) as f:
                           f.writelines(SCREAMING_SNAKE_CASE__     )
                    self._logger.info(F"""Converted in {output_file}"""     )

             for utils_file in utils_files:
                    try:
                           a_					:		List[Any]							=  os.path.basename(SCREAMING_SNAKE_CASE__     )
                           a_					:		Dict							=  imports_to_builder_map[f_name.replace('.py'     ,							''     )]
                           self._logger.info(F"""Moving {dest_folder} to {utils_file}"""     )
                           shutil.copy(SCREAMING_SNAKE_CASE__     ,							SCREAMING_SNAKE_CASE__     )
                    except KeyError:
                           self._logger.error(F"""Cannot find destination folder for {utils_file}. Please copy manually."""     )

             if with_manual_update:
                    for file_path in with_manual_update:
                           self._logger.warning(
                               F"""You need to manually update file {file_path} to remove configurations using 'TextEncoderConfig'."""     )






from __future__ import annotations

UpperCAmelCase_      : Tuple  					=       []







def        SCREAMING_SNAKE_CASE_						(			__A :			list[list[int]]  ,    __A :			int  ,    __A :			int				)	->		bool:

       """simple docstring"""

       for i in range(len(__A				)				):
              if board[row][i] == 1:
                     return False
       for i in range(len(__A				)				):
              if board[i][column] == 1:
                     return False
       for i, j in zip(range(__A  ,    -1  ,    -1				)  ,    range(__A  ,    -1  ,    -1				)				):
              if board[i][j] == 1:
                     return False
       for i, j in zip(range(__A  ,    -1  ,    -1				)  ,    range(__A  ,    len(__A				)				)				):
              if board[i][j] == 1:
                     return False
       return True







def        SCREAMING_SNAKE_CASE_						(			__A :			list[list[int]]  ,    __A :			int				)	->		bool:

       """simple docstring"""

       if row >= len(__A				):
              solution.append(__A				)
              printboard(__A				)
              print()
              return True
       for i in range(len(__A				)				):
              if is_safe(__A  ,    __A  ,    __A				):
                     a_					:		Any							=  1
                     solve(__A  ,    row + 1				)
                     a_					:		Tuple							=  0
       return False







def        SCREAMING_SNAKE_CASE_						(			__A :			list[list[int]]				)	->		None:

       """simple docstring"""

       for i in range(len(__A				)				):
              for j in range(len(__A				)				):
                     if board[i][j] == 1:
                            print('Q'  ,    end=' '				)
                     else:
                            print('.'  ,    end=' '				)
              print()


# n=int(input("The no. of queens"))
UpperCAmelCase_      : List[str]  					=       8
UpperCAmelCase_      : str  					=       [[0 for i in range(n)] for j in range(n)]
solve(board, 0)
print('The total no. of solutions are :', len(solution))


