



'''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							       =			'''=======
>>>>>>>
'''

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  UpperCAmelCase_       (		lowercase__       ):


     '''simple docstring'''







     return ConvertCommand(args.tfds_path       ,	args.datasets_directory       )







class 	UpperCAmelCase	(		__a):


 '''simple docstring'''




 @staticmethod
 def       lowercase_  (   lowerCAmelCase_) ->      Dict:



      """simple docstring"""







      a_       		=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							,  lowerCAmelCase_							,  lowerCAmelCase_							,  *lowerCAmelCase_) ->      Union[str, Any]:



      """simple docstring"""







      a_       		=get_logger("datasets-cli/converting")

      a_       		=tfds_path
      a_       		=datasets_directory




 def       lowercase_  (   self) ->      List[str]:



      """simple docstring"""







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

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

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

      a_       		=[]
      a_       		=[]
      a_       		={}

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

      for f_name in file_names:
           self._logger.info(f"""Looking at file {f_name}""")
           a_       		=os.path.join(lowerCAmelCase_							,  lowerCAmelCase_)
           a_       		=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_       		=f.readlines()

           a_       		=[]
           a_       		=False
           a_       		=False
           a_       		=[]
           for line in lines:
                a_       		=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_       		="import datasets\n"
                elif "import tensorflow" in out_line:
                     # order is important here
                     a_       		=""
                     continue
                elif "from absl import logging" in out_line:
                     a_       		="from datasets import logging\n"
                elif "getLogger" in out_line:
                     a_       		=out_line.replace("getLogger"							,  "get_logger")
                elif any(expression in out_line for expression in TO_HIGHLIGHT):
                     a_       		=True
                     a_       		=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_       		=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_       		=re.match(r"from\stensorflow_datasets.*import\s([^\.\r\n]+)"							,  lowerCAmelCase_)
                     tfds_imports.extend(imp.strip() for imp in match.group(1).split(","))
                     a_       		="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_       		=True
                out_lines.append(lowerCAmelCase_)

           if is_builder or "wmt" in f_name:
                # We create a new directory for each dataset
                a_       		=f_name.replace(".py"							,  "")
                a_       		=os.path.join(lowerCAmelCase_							,  lowerCAmelCase_)
                a_       		=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_       		=os.path.basename(lowerCAmelCase_)
                a_       		=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 collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig


lowercase							       =			{
    '''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
    '''albert-large-v1''': '''https://huggingface.co/albert-large-v1/resolve/main/config.json''',
    '''albert-xlarge-v1''': '''https://huggingface.co/albert-xlarge-v1/resolve/main/config.json''',
    '''albert-xxlarge-v1''': '''https://huggingface.co/albert-xxlarge-v1/resolve/main/config.json''',
    '''albert-base-v2''': '''https://huggingface.co/albert-base-v2/resolve/main/config.json''',
    '''albert-large-v2''': '''https://huggingface.co/albert-large-v2/resolve/main/config.json''',
    '''albert-xlarge-v2''': '''https://huggingface.co/albert-xlarge-v2/resolve/main/config.json''',
    '''albert-xxlarge-v2''': '''https://huggingface.co/albert-xxlarge-v2/resolve/main/config.json''',
}







class 	UpperCAmelCase	(		__a):


 '''simple docstring'''




 __magic_name__					: int  =      "albert"




 def __init__(   self							,  lowerCAmelCase_=3_0_0_0_0							,  lowerCAmelCase_=1_2_8							,  lowerCAmelCase_=4_0_9_6							,  lowerCAmelCase_=1_2							,  lowerCAmelCase_=1							,  lowerCAmelCase_=6_4							,  lowerCAmelCase_=1_6_3_8_4							,  lowerCAmelCase_=1							,  lowerCAmelCase_="gelu_new"							,  lowerCAmelCase_=0							,  lowerCAmelCase_=0							,  lowerCAmelCase_=5_1_2							,  lowerCAmelCase_=2							,  lowerCAmelCase_=0.0_2							,  lowerCAmelCase_=1e-12							,  lowerCAmelCase_=0.1							,  lowerCAmelCase_="absolute"							,  lowerCAmelCase_=0							,  lowerCAmelCase_=2							,  lowerCAmelCase_=3							,  **lowerCAmelCase_							,  ) ->      Any:



      """simple docstring"""







      super().__init__(pad_token_id=lowerCAmelCase_							,  bos_token_id=lowerCAmelCase_							,  eos_token_id=lowerCAmelCase_							,  **lowerCAmelCase_)

      a_       		=vocab_size
      a_       		=embedding_size
      a_       		=hidden_size
      a_       		=num_hidden_layers
      a_       		=num_hidden_groups
      a_       		=num_attention_heads
      a_       		=inner_group_num
      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_       		=classifier_dropout_prob
      a_       		=position_embedding_type







class 	UpperCAmelCase	(		__a):


 '''simple docstring'''




 @property
 def       lowercase_  (   self) ->      Mapping[str, Mapping[int, str]]:



      """simple docstring"""







      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),
              ("token_type_ids", dynamic_axis),
          ])


