





"""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


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

lowercase__ 	=     '=======\n>>>>>>>\n'

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

lowercase__ 	=     [
    # (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       (     _SCREAMING_SNAKE_CASE       )     ->List[str]:
  return ConvertCommand(args.tfds_path		,					args.datasets_directory       )




class        __snake_case	(					__lowerCAmelCase    ):



      @staticmethod
      def   lowerCamelCase_       (						lowercase)     ->      Tuple:





        '''simple docstring'''





        a__:					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)     ->      str:





        '''simple docstring'''





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

        a__:					str      							=     tfds_path
        a__:					Dict      							=     datasets_directory



      def   lowerCamelCase_       (						self)     ->      Dict:





        '''simple docstring'''





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

        a__:					Optional[Any]      							=     os.path.abspath(self._datasets_directory)

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

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

        if os.path.isdir(self._tfds_path):
          a__:					List[str]      							=     os.listdir(lowercase)
        else:
          a__:					List[str]      							=     [os.path.basename(self._tfds_path)]

        for f_name in file_names:
          self._logger.info(f'Looking at file {f_name}')
          a__:					Union[str, Any]      							=     os.path.join(lowercase   ,      lowercase)
          a__:					Tuple      							=     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:
            a__:					List[Any]      							=     f.readlines()

          a__:					List[str]      							=     []
          a__:					str      							=     False
          a__:					Any      							=     False
          a__:					Any      							=     []
          for line in lines:
            a__:					int      							=     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__:					int      							=     'import datasets\n'
            elif "import tensorflow" in out_line:
              # order is important here
              a__:					Union[str, Any]      							=     ''
              continue
            elif "from absl import logging" in out_line:
              a__:					int      							=     '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__:					int      							=     True
              a__:					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:
                a__:					Union[str, 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:
              a__:					Union[str, Any]      							=     re.match(r'from\stensorflow_datasets.*import\s([^\.\r\n]+)'   ,      lowercase)
              tfds_imports.extend(imp.strip() for imp in match.group(1).split(','))
              a__:					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__:					List[Any]      							=     True
            out_lines.append(lowercase)

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



"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position

lowercase__ 	=     '2.13.1'

import platform

import pyarrow
from packaging import version


if version.parse(platform.python_version()) < version.parse('3.7'):
 raise ImportWarning(
     'To use `datasets`, Python>=3.7 is required, and the current version of Python doesn\'t match this condition.'
 )

if version.parse(pyarrow.__version__).major < 8:
 raise ImportWarning(
     'To use `datasets`, the module `pyarrow>=8.0.0` is required, and the current version of `pyarrow` doesn\'t match this condition.\n'
     'If you are running this in a Google Colab, you should probably just restart the runtime to use the right version of `pyarrow`.'
 )

del platform
del pyarrow
del version

from .arrow_dataset import Dataset
from .arrow_reader import ReadInstruction
from .builder import ArrowBasedBuilder, BeamBasedBuilder, BuilderConfig, DatasetBuilder, GeneratorBasedBuilder
from .combine import concatenate_datasets, interleave_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .download import *
from .features import *
from .fingerprint import disable_caching, enable_caching, is_caching_enabled, set_caching_enabled
from .info import DatasetInfo, MetricInfo
from .inspect import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
    list_datasets,
    list_metrics,
)
from .iterable_dataset import IterableDataset
from .load import load_dataset, load_dataset_builder, load_from_disk, load_metric
from .metric import Metric
from .splits import (
    NamedSplit,
    NamedSplitAll,
    Split,
    SplitBase,
    SplitDict,
    SplitGenerator,
    SplitInfo,
    SubSplitInfo,
    percent,
)
from .tasks import *
from .utils import *
from .utils import logging


# deprecated modules
from datasets import arrow_dataset as _arrow_dataset  # isort:skip
from datasets import utils as _utils  # isort:skip
from datasets.utils import download_manager as _deprecated_download_manager  # isort:skip

lowercase__ 	=     concatenate_datasets
lowercase__ 	=     DownloadConfig
lowercase__ 	=     DownloadManager
lowercase__ 	=     DownloadMode
lowercase__ 	=     DownloadConfig
lowercase__ 	=     DownloadMode
lowercase__ 	=     DownloadManager

del _arrow_dataset, _utils, _deprecated_download_manager


