






"""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


UpperCAmelCase_   : Union[str, Any]   			= """<<<<<<< This should probably be modified because it mentions: """

UpperCAmelCase_   : Optional[Any]   			= """=======
>>>>>>>
"""

UpperCAmelCase_   : Union[str, Any]   			= [
    """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 					_A			(__a							) ->       Optional[int]:
    """simple docstring"""






    return ConvertCommand(args.tfds_path    ,				args.datasets_directory							)





class 							lowerCAmelCase__				(			UpperCAmelCase__ ):






      '''simple docstring'''

      @staticmethod
      def _SCREAMING_SNAKE_CASE (						lowercase_     :  ArgumentParser):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  List[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     :  Union[str, Any]						,	lowercase_     :  str						,	lowercase_     :  str						,	*lowercase_     :  Union[str, Any]):




          '''simple docstring'''


          SCREAMING_SNAKE_CASE_      :  Dict    						=		get_logger('''datasets-cli/converting''')

          SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		tfds_path
          SCREAMING_SNAKE_CASE_      :  Tuple    						=		datasets_directory



      def _SCREAMING_SNAKE_CASE (						self     :  str):




          '''simple docstring'''


          if os.path.isdir(self._tfds_path):
              SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		os.path.abspath(self._tfds_path)
          elif os.path.isfile(self._tfds_path):
              SCREAMING_SNAKE_CASE_      :  List[str]    						=		os.path.dirname(self._tfds_path)
          else:
              raise ValueError('''--tfds_path is neither a directory nor a file. Please check path.''')

          SCREAMING_SNAKE_CASE_      :  Any    						=		os.path.abspath(self._datasets_directory)

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

          SCREAMING_SNAKE_CASE_      :  Optional[int]    						=		[]
          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		[]
          SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		{}

          if os.path.isdir(self._tfds_path):
              SCREAMING_SNAKE_CASE_      :  List[str]    						=		os.listdir(lowercase_)
          else:
              SCREAMING_SNAKE_CASE_      :  Any    						=		[os.path.basename(self._tfds_path)]

          for f_name in file_names:
              self._logger.info(F'Looking at file {f_name}')
              SCREAMING_SNAKE_CASE_      :  Tuple    						=		os.path.join(lowercase_						,	lowercase_)
              SCREAMING_SNAKE_CASE_      :  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:
                  SCREAMING_SNAKE_CASE_      :  Any    						=		f.readlines()

              SCREAMING_SNAKE_CASE_      :  List[str]    						=		[]
              SCREAMING_SNAKE_CASE_      :  Dict    						=		False
              SCREAMING_SNAKE_CASE_      :  Any    						=		False
              SCREAMING_SNAKE_CASE_      :  List[str]    						=		[]
              for line in lines:
                  SCREAMING_SNAKE_CASE_      :  List[Any]    						=		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:
                      SCREAMING_SNAKE_CASE_      :  List[str]    						=		'''import datasets\n'''
                  elif "import tensorflow" in out_line:
                      # order is important here
                      SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		''''''
                      continue
                  elif "from absl import logging" in out_line:
                      SCREAMING_SNAKE_CASE_      :  str    						=		'''from datasets import logging\n'''
                  elif "getLogger" in out_line:
                      SCREAMING_SNAKE_CASE_      :  List[str]    						=		out_line.replace('''getLogger'''						,	'''get_logger''')
                  elif any(expression in out_line for expression in TO_HIGHLIGHT):
                      SCREAMING_SNAKE_CASE_      :  Optional[Any]    						=		True
                      SCREAMING_SNAKE_CASE_      :  Dict    						=		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:
                          SCREAMING_SNAKE_CASE_      :  List[Any]    						=		re.sub(lowercase_						,	lowercase_						,	lowercase_)

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

              if is_builder or "wmt" in f_name:
                  # We create a new directory for each dataset
                  SCREAMING_SNAKE_CASE_      :  List[Any]    						=		f_name.replace('''.py'''						,	'''''')
                  SCREAMING_SNAKE_CASE_      :  Any    						=		os.path.join(lowercase_						,	lowercase_)
                  SCREAMING_SNAKE_CASE_      :  str    						=		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:
                  SCREAMING_SNAKE_CASE_      :  Tuple    						=		os.path.basename(lowercase_)
                  SCREAMING_SNAKE_CASE_      :  Union[str, Any]    						=		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\'.')




from __future__ import annotations

from typing import Any



class 		UpperCamelCase__  :
   def __init__(self :					Union[str, Any]					,				snake_case_ :					int   ):
    __a :  Dict						=  num_of_nodes
    __a :  list[list[int]]						=  []
    __a :  dict[int, int]						=  {}
   def       lowerCAmelCase			(self :					Optional[Any]					,				snake_case_ :					int					,				snake_case_ :					int					,				snake_case_ :					int   ):
    self.m_edges.append([u_node, v_node, weight]   )
   def       lowerCAmelCase			(self :					Any					,				snake_case_ :					int   ):

    if self.m_component[u_node] == u_node:
     return u_node
    return self.find_component(self.m_component[u_node]   )
   def       lowerCAmelCase			(self :					str					,				snake_case_ :					int   ):

    if self.m_component[u_node] != u_node:
     for k in self.m_component:
      __a :  Optional[int]						=  self.find_component(snake_case_   )
   def       lowerCAmelCase			(self :					Any					,				snake_case_ :					list[int]					,				snake_case_ :					int					,				snake_case_ :					int   ):

    if component_size[u_node] <= component_size[v_node]:
     __a :  List[str]						=  v_node
     component_size[v_node] += component_size[u_node]
     self.set_component(snake_case_   )

    elif component_size[u_node] >= component_size[v_node]:
     __a :  Optional[int]						=  self.find_component(snake_case_   )
     component_size[u_node] += component_size[v_node]
     self.set_component(snake_case_   )







   def       lowerCAmelCase			(self :					Optional[Any]   ):
    __a :  str						=  []
    __a :  int						=  0

    __a :  list[Any]						=  [-1] * self.m_num_of_nodes

    # A list of components (initialized to all of the nodes)
    for node in range(self.m_num_of_nodes   ):
     self.m_component.update({node: node}   )
     component_size.append(1   )

    __a :  Union[str, Any]						=  self.m_num_of_nodes

    while num_of_components > 1:
     for edge in self.m_edges:
      __a				,       __a				,       __a :  Optional[Any]						=  edge

      __a :  List[str]						=  self.m_component[u]
      __a :  List[Any]						=  self.m_component[v]

      if u_component != v_component:

       for component in (u_component, v_component):
        if (
            minimum_weight_edge[component] == -1
            or minimum_weight_edge[component][2] > w
        ):
         __a :  str						=  [u, v, w]

     for edge in minimum_weight_edge:
      if isinstance(snake_case_					,				snake_case_   ):
       __a				,       __a				,       __a :  str						=  edge

       __a :  Any						=  self.m_component[u]
       __a :  Any						=  self.m_component[v]

       if u_component != v_component:
        mst_weight += w
        self.union(snake_case_					,				snake_case_					,				snake_case_   )
        print(f"Added edge [{u} - {v}]\nAdded weight: {w}\n"   )
        num_of_components -= 1

     __a :  Optional[int]						=  [-1] * self.m_num_of_nodes
    print(f"The total weight of the minimal spanning tree is: {mst_weight}"   )





def    __UpperCamelCase     (				):
 pass


if __name__ == "__main__":
      import doctest

      doctest.testmod()
