
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace

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


a_											=						"<<<<<<< This should probably be modified because it mentions: "

a_											=						"=======\n>>>>>>>\n"

a_											=						[
    "TextEncoderConfig",
    "ByteTextEncoder",
    "SubwordTextEncoder",
    "encoder_config",
    "maybe_build_from_corpus",
    "manual_dir",
]

a_											=						[
    # (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 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    return ConvertCommand(args.tfds_path,		args.datasets_directory       )






class    UpperCAmelCase_				(	snake_case__					):





 @staticmethod
 def        snake_case__		(    lowercase_):
     snake_case_ :    Union[str, Any]     			=						parser.add_parser(
         "convert" ,       help="Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset." ,       )
     train_parser.add_argument(
         "--tfds_path" ,       type=lowercase_ ,       required=lowercase_ ,       help="Path to a TensorFlow Datasets folder to convert or a single tfds file to convert." ,       )
     train_parser.add_argument(
         "--datasets_directory" ,       type=lowercase_ ,       required=lowercase_ ,       help="Path to the HuggingFace Datasets folder.")
     train_parser.set_defaults(func=lowercase_)





 def __init__(    self ,       lowercase_ ,       lowercase_ ,       *lowercase_):
     snake_case_ :    Optional[int]     			=						get_logger("datasets-cli/converting")

     snake_case_ :    List[str]     			=						tfds_path
     snake_case_ :    Optional[Any]     			=						datasets_directory





 def        snake_case__		(    self):
     if os.path.isdir(self._tfds_path):
         snake_case_ :    str     			=						os.path.abspath(self._tfds_path)
     elif os.path.isfile(self._tfds_path):
         snake_case_ :    Dict     			=						os.path.dirname(self._tfds_path)
     else:
         raise ValueError("--tfds_path is neither a directory nor a file. Please check path.")

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

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

     snake_case_ :    Union[str, Any]     			=						[]
     snake_case_ :    List[str]     			=						[]
     snake_case_ :    List[str]     			=						{}

     if os.path.isdir(self._tfds_path):
         snake_case_ :    str     			=						os.listdir(lowercase_)
     else:
         snake_case_ :    Optional[int]     			=						[os.path.basename(self._tfds_path)]

     for f_name in file_names:
         self._logger.info(F'Looking at file {f_name}')
         snake_case_ :    List[Any]     			=						os.path.join(lowercase_ ,       lowercase_)
         snake_case_ :    Union[str, Any]     			=						os.path.join(lowercase_ ,       lowercase_)

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

         with open(lowercase_ ,       encoding="utf-8") as f:
             snake_case_ :    Union[str, Any]     			=						f.readlines()

         snake_case_ :    List[Any]     			=						[]
         snake_case_ :    int     			=						False
         snake_case_ :    Dict     			=						False
         snake_case_ :    Optional[int]     			=						[]
         for line in lines:
             snake_case_ :    Tuple     			=						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:
                 snake_case_ :    List[Any]     			=						"import datasets\n"
             elif "import tensorflow" in out_line:
                 # order is important here
                 snake_case_ :    Optional[int]     			=						""
                 continue
             elif "from absl import logging" in out_line:
                 snake_case_ :    List[Any]     			=						"from datasets import logging\n"
             elif "getLogger" in out_line:
                 snake_case_ :    Union[str, Any]     			=						out_line.replace("getLogger" ,       "get_logger")
             elif any(expression in out_line for expression in TO_HIGHLIGHT):
                 snake_case_ :    Union[str, Any]     			=						True
                 snake_case_ :    Any     			=						list(filter(lambda lowercase_: e in out_line ,       lowercase_))
                 out_lines.append(HIGHLIGHT_MESSAGE_PRE + str(lowercase_) + "\n")
                 out_lines.append(lowercase_)
                 out_lines.append(lowercase_)
                 continue
             else:
                 for pattern, replacement in TO_CONVERT:
                     snake_case_ :    str     			=						re.sub(lowercase_ ,       lowercase_ ,       lowercase_)

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

         if is_builder or "wmt" in f_name:
             # We create a new directory for each dataset
             snake_case_ :    List[Any]     			=						f_name.replace(".py" ,       "")
             snake_case_ :    Dict     			=						os.path.join(lowercase_ ,       lowercase_)
             snake_case_ :    Optional[int]     			=						os.path.join(lowercase_ ,       lowercase_)
             os.makedirs(lowercase_ ,       exist_ok=lowercase_)
             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(lowercase_)

         if needs_manual_update:
             with_manual_update.append(lowercase_)

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

     for utils_file in utils_files:
         try:
             snake_case_ :    Any     			=						os.path.basename(lowercase_)
             snake_case_ :    int     			=						imports_to_builder_map[f_name.replace(".py" ,       "")]
             self._logger.info(F'Moving {dest_folder} to {utils_file}')
             shutil.copy(lowercase_ ,       lowercase_)
         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\'.')






'''simple docstring'''
from __future__ import annotations

import math

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if depth < 0:
        raise ValueError("Depth cannot be less than 0"       )

    if len(__SCREAMING_SNAKE_CASE       ) == 0:
        raise ValueError("Scores cannot be empty"       )

    if depth == height:
        return scores[node_index]

    if is_max:
        return max(
            minimax(depth + 1,		node_index * 2,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		minimax(depth + 1,		node_index * 2 + 1,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		)

    return min(
        minimax(depth + 1,		node_index * 2,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		minimax(depth + 1,		node_index * 2 + 1,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		)

def 						UpperCamelCase_     (	):
    """simple docstring"""






    snake_case_ :    int     			=						[9_0, 2_3, 6, 3_3, 2_1, 6_5, 1_2_3, 3_4_4_2_3]
    snake_case_ :    Union[str, Any]     			=						math.log(len(__SCREAMING_SNAKE_CASE       ),		2       )
    print("Optimal value : ",		end=""       )
    print(minimax(0,		0,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()




