


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  _a			(						__UpperCamelCase ):
     return ConvertCommand(args.tfds_path  ,  args.datasets_directory )


class   a__	(						lowercase__    ):

       @staticmethod
       def 						UpperCAmelCase(   lowerCamelCase_      :     ArgumentParser    ):
            a_    :     Dict										=    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      :     Tuple      ,							lowerCamelCase_      :     str      ,							lowerCamelCase_      :     str      ,							*lowerCamelCase_      :     Tuple    ):
            a_    :     int										=    get_logger("""datasets-cli/converting"""    )

            a_    :     List[Any]										=    tfds_path
            a_    :     List[str]										=    datasets_directory

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

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

            if os.path.isdir(self._tfds_path    ):
                 a_    :     Optional[Any]										=    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_    :     Optional[Any]										=    os.path.join(__lowercase      ,							__lowercase    )
                 a_    :     str										=    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_    :     Dict										=    f.readlines()

                 a_    :     Union[str, Any]										=    []
                 a_    :     Union[str, Any]										=    False
                 a_    :     str										=    False
                 a_    :     int										=    []
                 for line in lines:
                      a_    :     Tuple										=    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_    :     Tuple										=    """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_    :     Tuple										=    """from datasets import logging\n"""
                      elif "getLogger" in out_line:
                           a_    :     Any										=    out_line.replace("""getLogger"""      ,							"""get_logger"""    )
                      elif any(expression in out_line for expression in TO_HIGHLIGHT    ):
                           a_    :     str										=    True
                           a_    :     Optional[Any]										=    list(filter(lambda lowerCamelCase_    : 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_    :     str										=    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_    :     Dict										=    """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_    :     str										=    True
                      out_lines.append(__lowercase    )

                 if is_builder or "wmt" in f_name:
                      # We create a new directory for each dataset
                      a_    :     int										=    f_name.replace(""".py"""      ,							""""""    )
                      a_    :     Any										=    os.path.join(__lowercase      ,							__lowercase    )
                      a_    :     Union[str, 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_    :     List[Any]										=    os.path.basename(__lowercase    )
                      a_    :     Optional[int]										=    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 ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__lowerCamelCase        =     logging.get_logger(__name__)

__lowerCamelCase        =     {
    '''facebook/convnextv2-tiny-1k-224''': '''https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json''',
}


class   a__	(						lowerCAmelCase_						,       lowerCAmelCase_    ):
       lowerCamelCase__:     str							    =     """convnextv2"""

       def __init__(   self      :     Tuple      ,							lowerCamelCase_      :     str=3      ,							lowerCamelCase_      :     Tuple=4      ,							lowerCamelCase_      :     Any=4      ,							lowerCamelCase_      :     Optional[int]=None      ,							lowerCamelCase_      :     Optional[int]=None      ,							lowerCamelCase_      :     Optional[int]="gelu"      ,							lowerCamelCase_      :     Optional[Any]=0.0_2      ,							lowerCamelCase_      :     str=1E-12      ,							lowerCamelCase_      :     Dict=0.0      ,							lowerCamelCase_      :     Union[str, Any]=2_2_4      ,							lowerCamelCase_      :     Dict=None      ,							lowerCamelCase_      :     Optional[Any]=None      ,							**lowerCamelCase_      :     List[Any]      ,							):
            super().__init__(**lowerCamelCase_    )

            a_    :     Dict										=    num_channels
            a_    :     Optional[int]										=    patch_size
            a_    :     int										=    num_stages
            a_    :     Any										=    [9_6, 1_9_2, 3_8_4, 7_6_8] if hidden_sizes is None else hidden_sizes
            a_    :     Any										=    [3, 3, 9, 3] if depths is None else depths
            a_    :     Any										=    hidden_act
            a_    :     Dict										=    initializer_range
            a_    :     Optional[Any]										=    layer_norm_eps
            a_    :     int										=    drop_path_rate
            a_    :     Optional[Any]										=    image_size
            a_    :     Dict										=    ["""stem"""] + [F'''stage{idx}''' for idx in range(1      ,							len(self.depths    ) + 1    )]
            a_			,			a_    :     int										=    get_aligned_output_features_output_indices(
                out_features=lowerCamelCase_      ,							out_indices=lowerCamelCase_      ,							stage_names=self.stage_names    )



