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

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


UpperCamelCase     :    Union[str, Any]       =			"<<<<<<< This should probably be modified because it mentions: "

UpperCamelCase     :    List[str]       =			"=======\n>>>>>>>\n"

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

UpperCamelCase     :    str       =			[
    # (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						(    snake_case				:Namespace		)				->     List[str]:
 return ConvertCommand(args.tfds_path    , args.datasets_directory		)





class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):





     @staticmethod
     def 						UpperCAmelCase (     __UpperCAmelCase				):

      '''simple docstring'''




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





     def __init__(     self     ,					__UpperCAmelCase     ,					__UpperCAmelCase     ,					*__UpperCAmelCase				):

      '''simple docstring'''




      __UpperCamelCase      =	get_logger('datasets-cli/converting'				)

      __UpperCamelCase      =	tfds_path
      __UpperCamelCase      =	datasets_directory







     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




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

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

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

      __UpperCamelCase      =	[]
      __UpperCamelCase      =	[]
      __UpperCamelCase      =	{}

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

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

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

       with open(_a     ,					encoding='utf-8'				) as f:
        __UpperCamelCase      =	f.readlines()

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

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

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

       if needs_manual_update:
        with_manual_update.append(_a				)

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

      for utils_file in utils_files:
       try:
        __UpperCamelCase      =	os.path.basename(_a				)
        __UpperCamelCase      =	imports_to_builder_map[f_name.replace('.py'     ,					''				)]
        self._logger.info(F'Moving {dest_folder} to {utils_file}'				)
        shutil.copy(_a     ,					_a				)
       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 collections import OrderedDict
from typing import Mapping

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


UpperCamelCase     :    Union[str, Any]       =			logging.get_logger(__name__)

UpperCamelCase     :    int       =			{
    "distilbert-base-uncased": "https://huggingface.co/distilbert-base-uncased/resolve/main/config.json",
    "distilbert-base-uncased-distilled-squad": (
        "https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-cased": "https://huggingface.co/distilbert-base-cased/resolve/main/config.json",
    "distilbert-base-cased-distilled-squad": (
        "https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/config.json"
    ),
    "distilbert-base-german-cased": "https://huggingface.co/distilbert-base-german-cased/resolve/main/config.json",
    "distilbert-base-multilingual-cased": (
        "https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/config.json"
    ),
    "distilbert-base-uncased-finetuned-sst-2-english": (
        "https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english/resolve/main/config.json"
    ),
}

class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):
     lowercase						       =						"distilbert"
     lowercase						       =						{
         "hidden_size": "dim",
         "num_attention_heads": "n_heads",
         "num_hidden_layers": "n_layers",
     }





     def __init__(     self     ,					__UpperCAmelCase=3_0522     ,					__UpperCAmelCase=512     ,					__UpperCAmelCase=False     ,					__UpperCAmelCase=6     ,					__UpperCAmelCase=12     ,					__UpperCAmelCase=768     ,					__UpperCAmelCase=4 * 768     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase="gelu"     ,					__UpperCAmelCase=0.0_2     ,					__UpperCAmelCase=0.1     ,					__UpperCAmelCase=0.2     ,					__UpperCAmelCase=0     ,					**__UpperCAmelCase     ,					):

      '''simple docstring'''




      __UpperCamelCase      =	vocab_size
      __UpperCamelCase      =	max_position_embeddings
      __UpperCamelCase      =	sinusoidal_pos_embds
      __UpperCamelCase      =	n_layers
      __UpperCamelCase      =	n_heads
      __UpperCamelCase      =	dim
      __UpperCamelCase      =	hidden_dim
      __UpperCamelCase      =	dropout
      __UpperCamelCase      =	attention_dropout
      __UpperCamelCase      =	activation
      __UpperCamelCase      =	initializer_range
      __UpperCamelCase      =	qa_dropout
      __UpperCamelCase      =	seq_classif_dropout
      super().__init__(**__UpperCAmelCase     ,					pad_token_id=__UpperCAmelCase				)


class __lowerCAmelCase		(				__SCREAMING_SNAKE_CASE      ):





     @property
     def 						UpperCAmelCase (     self				):

      '''simple docstring'''




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



