



"""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


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

lowerCAmelCase__              =							'''=======
>>>>>>>
'''

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

lowerCAmelCase__              =							[
    # (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 			snake_case_    ( A_   :						Namespace		):


       '''simple docstring'''





       return ConvertCommand(args.tfds_path,							args.datasets_directory		)







class 			__snake_case			(      _lowercase):




  @staticmethod
  def 		SCREAMING_SNAKE_CASE							(					__lowerCAmelCase	:		ArgumentParser						):






         """simple docstring"""






         _lowerCamelCase		:							List[str]            =					parser.add_parser(
             '''convert'''		,   help='''Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.'''		,   )
         train_parser.add_argument(
             '''--tfds_path'''		,   type=__lowerCAmelCase		,   required=__lowerCAmelCase		,   help='''Path to a TensorFlow Datasets folder to convert or a single tfds file to convert.'''		,   )
         train_parser.add_argument(
             '''--datasets_directory'''		,   type=__lowerCAmelCase		,   required=__lowerCAmelCase		,   help='''Path to the HuggingFace Datasets folder.'''						)
         train_parser.set_defaults(func=__lowerCAmelCase						)




  def __init__(					self	:		str		,   __lowerCAmelCase	:		str		,   __lowerCAmelCase	:		str		,   *__lowerCAmelCase	:		int						):






         """simple docstring"""






         _lowerCamelCase		:							List[str]            =					get_logger('''datasets-cli/converting'''						)

         _lowerCamelCase		:							int            =					tfds_path
         _lowerCamelCase		:							Dict            =					datasets_directory




  def 		SCREAMING_SNAKE_CASE							(					self	:		Dict						):






         """simple docstring"""






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

         _lowerCamelCase		:							int            =					os.path.abspath(self._datasets_directory						)

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

         _lowerCamelCase		:							str            =					[]
         _lowerCamelCase		:							Union[str, Any]            =					[]
         _lowerCamelCase		:							Union[str, Any]            =					{}

         if os.path.isdir(self._tfds_path						):
                _lowerCamelCase		:							List[str]            =					os.listdir(__lowerCAmelCase						)
         else:
                _lowerCamelCase		:							Optional[Any]            =					[os.path.basename(self._tfds_path						)]

         for f_name in file_names:
                self._logger.info(f'''Looking at file {f_name}'''						)
                _lowerCamelCase		:							Union[str, Any]            =					os.path.join(__lowerCAmelCase		,   __lowerCAmelCase						)
                _lowerCamelCase		:							Optional[Any]            =					os.path.join(__lowerCAmelCase		,   __lowerCAmelCase						)

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

                with open(__lowerCAmelCase		,   encoding='''utf-8'''						) as f:
                       _lowerCamelCase		:							Tuple            =					f.readlines()

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

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

                if is_builder or "wmt" in f_name:
                       # We create a new directory for each dataset
                       _lowerCamelCase		:							Union[str, Any]            =					f_name.replace('''.py'''		,   ''''''						)
                       _lowerCamelCase		:							List[str]            =					os.path.join(__lowerCAmelCase		,   __lowerCAmelCase						)
                       _lowerCamelCase		:							List[Any]            =					os.path.join(__lowerCAmelCase		,   __lowerCAmelCase						)
                       os.makedirs(__lowerCAmelCase		,   exist_ok=__lowerCAmelCase						)
                       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(__lowerCAmelCase						)

                if needs_manual_update:
                       with_manual_update.append(__lowerCAmelCase						)

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

         for utils_file in utils_files:
                try:
                       _lowerCamelCase		:							Optional[int]            =					os.path.basename(__lowerCAmelCase						)
                       _lowerCamelCase		:							Union[str, Any]            =					imports_to_builder_map[f_name.replace('''.py'''		,   ''''''						)]
                       self._logger.info(f'''Moving {dest_folder} to {utils_file}'''						)
                       shutil.copy(__lowerCAmelCase		,   __lowerCAmelCase						)
                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 collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_lowercase    	=		logging.get_logger(__name__)

_lowercase    	=		{
    "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/config.json",
    "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/config.json",
    "xlm-roberta-large-finetuned-conll02-dutch": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll02-spanish": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-english": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"
    ),
    "xlm-roberta-large-finetuned-conll03-german": (
        "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"
    ),
}



class      _UpperCAmelCase      (							A__  ):
     UpperCamelCase__		     =					'''xlm-roberta'''




     def __init__(					self			,    a__=3_0_5_2_2			,    a__=7_6_8			,    a__=1_2			,    a__=1_2			,    a__=3_0_7_2			,    a__="gelu"			,    a__=0.1			,    a__=0.1			,    a__=5_1_2			,    a__=2			,    a__=0.0_2			,    a__=1e-12			,    a__=1			,    a__=0			,    a__=2			,    a__="absolute"			,    a__=True			,    a__=None			,    **a__			,    ):
         super().__init__(pad_token_id=a__			,    bos_token_id=a__			,    eos_token_id=a__			,    **a__)

         A__					=       vocab_size
         A__					=       hidden_size
         A__					=       num_hidden_layers
         A__					=       num_attention_heads
         A__					=       hidden_act
         A__					=       intermediate_size
         A__					=       hidden_dropout_prob
         A__					=       attention_probs_dropout_prob
         A__					=       max_position_embeddings
         A__					=       type_vocab_size
         A__					=       initializer_range
         A__					=       layer_norm_eps
         A__					=       position_embedding_type
         A__					=       use_cache
         A__					=       classifier_dropout







class      _UpperCAmelCase      (							A__  ):




     @property
     def 		snake_case_		(					self):
         if self.task == "multiple-choice":
             A__					=       {0: '''batch''', 1: '''choice''', 2: '''sequence'''}
         else:
             A__					=       {0: '''batch''', 1: '''sequence'''}
         return OrderedDict(
             [
                 ('''input_ids''', dynamic_axis),
                 ('''attention_mask''', dynamic_axis),
             ])
