

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

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


UpperCamelCase__		 =     '''<<<<<<< This should probably be modified because it mentions: '''

UpperCamelCase__		 =     '''=======
>>>>>>>
'''

UpperCamelCase__		 =     [
    '''TextEncoderConfig''',
    '''ByteTextEncoder''',
    '''SubwordTextEncoder''',
    '''encoder_config''',
    '''maybe_build_from_corpus''',
    '''manual_dir''',
]

UpperCamelCase__		 =     [
    # (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 						lowerCamelCase__      ( __A    :Namespace		):


       """simple docstring"""




       return ConvertCommand(args.tfds_path	,args.datasets_directory		)




class     __snake_case    (				snake_case__  ):
       """simple docstring"""







       @staticmethod
       def 			a		(		_UpperCamelCase   )      ->							List[Any]:






              """simple docstring"""


              __snake_case       	=							parser.add_parser(
                  """convert"""      , help="""Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset."""      , )
              train_parser.add_argument(
                  """--tfds_path"""      , type=_UpperCamelCase      , required=_UpperCamelCase      , help="""Path to a TensorFlow Datasets folder to convert or a single tfds file to convert."""      , )
              train_parser.add_argument(
                  """--datasets_directory"""      , type=_UpperCamelCase      , required=_UpperCamelCase      , help="""Path to the HuggingFace Datasets folder."""   )
              train_parser.set_defaults(func=_UpperCamelCase   )


       def __init__(		self      , _UpperCamelCase      , _UpperCamelCase      , *_UpperCamelCase   )      ->							str:






              """simple docstring"""


              __snake_case       	=							get_logger("""datasets-cli/converting"""   )

              __snake_case       	=							tfds_path
              __snake_case       	=							datasets_directory






       def 			a		(		self   )      ->							List[str]:






              """simple docstring"""


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

              __snake_case       	=							os.path.abspath(self._datasets_directory   )

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

              __snake_case       	=							[]
              __snake_case       	=							[]
              __snake_case       	=							{}

              if os.path.isdir(self._tfds_path   ):
                     __snake_case       	=							os.listdir(_UpperCamelCase   )
              else:
                     __snake_case       	=							[os.path.basename(self._tfds_path   )]

              for f_name in file_names:
                     self._logger.info(F'Looking at file {f_name}'   )
                     __snake_case       	=							os.path.join(_UpperCamelCase      , _UpperCamelCase   )
                     __snake_case       	=							os.path.join(_UpperCamelCase      , _UpperCamelCase   )

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

                     with open(_UpperCamelCase      , encoding="""utf-8"""   ) as f:
                            __snake_case       	=							f.readlines()

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

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

                     if is_builder or "wmt" in f_name:
                            # We create a new directory for each dataset
                            __snake_case       	=							f_name.replace(""".py"""      , """"""   )
                            __snake_case       	=							os.path.join(_UpperCamelCase      , _UpperCamelCase   )
                            __snake_case       	=							os.path.join(_UpperCamelCase      , _UpperCamelCase   )
                            os.makedirs(_UpperCamelCase      , exist_ok=_UpperCamelCase   )
                            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(_UpperCamelCase   )

                     if needs_manual_update:
                            with_manual_update.append(_UpperCamelCase   )

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

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







def 						lowerCamelCase__      ( __A    :list[float]	,__A    :Union[str, Any]		):


       """simple docstring"""




       print(F'Vertex\tShortest Distance from vertex {src}'		)
       for i, d in enumerate(__A		):
              print(F'{i}\t\t{d}'		)







def 						lowerCamelCase__      ( __A    :list[dict[str, int]]	,__A    :list[float]	,__A    :int		):


       """simple docstring"""




       for j in range(__A		):
              __snake_case	,    __snake_case	,    __snake_case       	=							(graph[j][k] for k in ["""src""", """dst""", """weight"""])
              if distance[u] != float("""inf"""		) and distance[u] + w < distance[v]:
                     return True
       return False







def 						lowerCamelCase__      ( __A    :list[dict[str, int]]	,__A    :int	,__A    :int	,__A    :int		):


       """simple docstring"""




       __snake_case       	=							[float("""inf"""		)] * vertex_count
       __snake_case       	=							0.0

       for _ in range(vertex_count - 1		):
              for j in range(__A		):
                     __snake_case	,    __snake_case	,    __snake_case       	=							(graph[j][k] for k in ["""src""", """dst""", """weight"""])

                     if distance[u] != float("""inf"""		) and distance[u] + w < distance[v]:
                            __snake_case       	=							distance[u] + w

       __snake_case       	=							check_negative_cycle(__A	,__A	,__A		)
       if negative_cycle_exists:
              raise Exception("""Negative cycle found"""		)

       return distance


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    UpperCamelCase__		 =     int(input('''Enter number of vertices: ''').strip())
    UpperCamelCase__		 =     int(input('''Enter number of edges: ''').strip())

    UpperCamelCase__		 =     [{} for _ in range(E)]

    for i in range(E):
        print('''Edge ''', i + 1)
        UpperCamelCase__ ,UpperCamelCase__ ,UpperCamelCase__		 =     (
            int(x)
            for x in input('''Enter source, destination, weight: ''').strip().split(''' ''')
        )
        UpperCamelCase__		 =     {'''src''': src, '''dst''': dest, '''weight''': weight}

    UpperCamelCase__		 =     int(input('''\nEnter shortest path source:''').strip())
    UpperCamelCase__		 =     bellman_ford(graph, V, E, source)
    print_distance(shortest_distance, 0)

