


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

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


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

UpperCamelCase					:       List[Any]			    =     """=======
>>>>>>>
"""

UpperCamelCase					:       Optional[Any]			    =     [
    """TextEncoderConfig""",
    """ByteTextEncoder""",
    """SubwordTextEncoder""",
    """encoder_config""",
    """maybe_build_from_corpus""",
    """manual_dir""",
]

UpperCamelCase					:       Any			    =     [
    # (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_				(				__a      )	->   Optional[Any]:
      return ConvertCommand(args.tfds_path			,				args.datasets_directory      )



class A__     ( A__  ):



  """simple docstring"""



  @staticmethod
  def    _UpperCamelCase( lowerCamelCase__			:  ArgumentParser       ):
        a__	:  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			:  List[str]				,				lowerCamelCase__			:  str				,				lowerCamelCase__			:  str				,				*lowerCamelCase__			:  Tuple       ):
        a__	:  str     =   get_logger("datasets-cli/converting"       )

        a__	:  Optional[Any]     =   tfds_path
        a__	:  Optional[int]     =   datasets_directory

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

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

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

        a__	:  Tuple     =   []
        a__	:  str     =   []
        a__	:  List[Any]     =   {}

        if os.path.isdir(self._tfds_path       ):
              a__	:  List[str]     =   os.listdir(lowerCamelCase__       )
        else:
              a__	:  Union[str, Any]     =   [os.path.basename(self._tfds_path       )]

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

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

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

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


"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase__			=    logging.get_logger(__name__)

UpperCAmelCase__			=    {
    """google/realm-cc-news-pretrained-embedder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-encoder""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-encoder/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-scorer""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-scorer/resolve/main/config.json"""
    ),
    """google/realm-cc-news-pretrained-openqa""": (
        """https://huggingface.co/google/realm-cc-news-pretrained-openqa/aresolve/main/config.json"""
    ),
    """google/realm-orqa-nq-openqa""": """https://huggingface.co/google/realm-orqa-nq-openqa/resolve/main/config.json""",
    """google/realm-orqa-nq-reader""": """https://huggingface.co/google/realm-orqa-nq-reader/resolve/main/config.json""",
    """google/realm-orqa-wq-openqa""": """https://huggingface.co/google/realm-orqa-wq-openqa/resolve/main/config.json""",
    """google/realm-orqa-wq-reader""": """https://huggingface.co/google/realm-orqa-wq-reader/resolve/main/config.json""",
    # See all REALM models at https://huggingface.co/models?filter=realm
}


class 							a					(		lowerCAmelCase_ ):
    _snake_case  :	List[Any]  				=				'realm'


    def __init__(       self						:	List[Any] ,					__lowerCAmelCase						:	List[str]=3_0522 ,					__lowerCAmelCase						:	Tuple=768 ,					__lowerCAmelCase						:	List[Any]=128 ,					__lowerCAmelCase						:	Tuple=12 ,					__lowerCAmelCase						:	List[str]=12 ,					__lowerCAmelCase						:	Union[str, Any]=8 ,					__lowerCAmelCase						:	List[str]=3072 ,					__lowerCAmelCase						:	Union[str, Any]="gelu_new" ,					__lowerCAmelCase						:	str=0.1 ,					__lowerCAmelCase						:	Tuple=0.1 ,					__lowerCAmelCase						:	List[str]=512 ,					__lowerCAmelCase						:	Dict=2 ,					__lowerCAmelCase						:	List[Any]=0.02 ,					__lowerCAmelCase						:	Optional[int]=1e-1_2 ,					__lowerCAmelCase						:	Any=256 ,					__lowerCAmelCase						:	Union[str, Any]=10 ,					__lowerCAmelCase						:	Dict=1e-3 ,					__lowerCAmelCase						:	str=5 ,					__lowerCAmelCase						:	str=320 ,					__lowerCAmelCase						:	Tuple=1335_3718 ,					__lowerCAmelCase						:	Optional[Any]=5000 ,					__lowerCAmelCase						:	int=1 ,					__lowerCAmelCase						:	Dict=0 ,					__lowerCAmelCase						:	Any=2 ,					**__lowerCAmelCase						:	Optional[int] ,					):
      super().__init__(pad_token_id=__lowerCAmelCase ,					bos_token_id=__lowerCAmelCase ,					eos_token_id=__lowerCAmelCase ,					**__lowerCAmelCase       )

      # Common config
      _UpperCAmelCase    			=   vocab_size
      _UpperCAmelCase    			=   max_position_embeddings
      _UpperCAmelCase    			=   hidden_size
      _UpperCAmelCase    			=   retriever_proj_size
      _UpperCAmelCase    			=   num_hidden_layers
      _UpperCAmelCase    			=   num_attention_heads
      _UpperCAmelCase    			=   num_candidates
      _UpperCAmelCase    			=   intermediate_size
      _UpperCAmelCase    			=   hidden_act
      _UpperCAmelCase    			=   hidden_dropout_prob
      _UpperCAmelCase    			=   attention_probs_dropout_prob
      _UpperCAmelCase    			=   initializer_range
      _UpperCAmelCase    			=   type_vocab_size
      _UpperCAmelCase    			=   layer_norm_eps

      # Reader config
      _UpperCAmelCase    			=   span_hidden_size
      _UpperCAmelCase    			=   max_span_width
      _UpperCAmelCase    			=   reader_layer_norm_eps
      _UpperCAmelCase    			=   reader_beam_size
      _UpperCAmelCase    			=   reader_seq_len

      # Retrieval config
      _UpperCAmelCase    			=   num_block_records
      _UpperCAmelCase    			=   searcher_beam_size
