



'''simple docstring'''



import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


lowerCamelCase_			=						'sshleifer/bart-tiny-random'
lowerCamelCase_			=						'patrickvonplaten/t5-tiny-random'







@require_torch
class 		lowercase_   (			unittest.TestCase       ):


   """simple docstring"""

   @cached_property
   def 							lowerCAmelCase_      (   self :     Union[str, Any]   ):

      """simple docstring"""
      return AutoConfig.from_pretrained(UpperCamelCase__   )



   def 							lowerCAmelCase_      (   self :     Tuple   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE,	*_SCREAMING_SNAKE_CASE	=				create_student_by_copying_alternating_layers(UpperCamelCase__  ,				tempfile.mkdtemp()  ,				e=1  ,				d=1   )
      self.assertEqual(student.config.num_hidden_layers  ,				1   )



   def 							lowerCAmelCase_      (   self :     Optional[int]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE,	*_SCREAMING_SNAKE_CASE	=				create_student_by_copying_alternating_layers(UpperCamelCase__  ,				tempfile.mkdtemp()  ,				e=1  ,				d=UpperCamelCase__   )



   def 							lowerCAmelCase_      (   self :     List[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE,	*_SCREAMING_SNAKE_CASE	=				create_student_by_copying_alternating_layers(UpperCamelCase__  ,				tempfile.mkdtemp()  ,				e=1  ,				d=UpperCamelCase__   )
      self.assertEqual(student.config.encoder_layers  ,				1   )
      self.assertEqual(student.config.decoder_layers  ,				self.teacher_config.encoder_layers   )



   def 							lowerCAmelCase_      (   self :     List[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE,	*_SCREAMING_SNAKE_CASE	=				create_student_by_copying_alternating_layers(UpperCamelCase__  ,				tempfile.mkdtemp()  ,				e=1  ,				d=1   )
      self.assertEqual(student.config.encoder_layers  ,				1   )
      self.assertEqual(student.config.decoder_layers  ,				1   )



   def 							lowerCAmelCase_      (   self :     Optional[Any]   ):

      """simple docstring"""
      with self.assertRaises(UpperCamelCase__   ):
         create_student_by_copying_alternating_layers(UpperCamelCase__  ,				tempfile.mkdtemp()  ,				e=UpperCamelCase__  ,				d=UpperCamelCase__   )







'''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_			=						'=======\n>>>>>>>\n'

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 			SCREAMING_SNAKE_CASE_			(							__A    :			Namespace  )			->			List[Any]:
   return ConvertCommand(args.tfds_path	,					args.datasets_directory  )







class 		lowercase_   (			A       ):


   """simple docstring"""

   @staticmethod
   def 							lowerCAmelCase_      (   __lowerCamelCase :     ArgumentParser   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				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 :     Dict  ,				__lowerCamelCase :     str  ,				__lowerCamelCase :     str  ,				*__lowerCamelCase :     Tuple   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				get_logger("datasets-cli/converting"   )

      _SCREAMING_SNAKE_CASE	=				tfds_path
      _SCREAMING_SNAKE_CASE	=				datasets_directory



   def 							lowerCAmelCase_      (   self :     List[Any]   ):

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

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

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

      _SCREAMING_SNAKE_CASE	=				[]
      _SCREAMING_SNAKE_CASE	=				[]
      _SCREAMING_SNAKE_CASE	=				{}

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

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

         _SCREAMING_SNAKE_CASE	=				[]
         _SCREAMING_SNAKE_CASE	=				False
         _SCREAMING_SNAKE_CASE	=				False
         _SCREAMING_SNAKE_CASE	=				[]
         for line in lines:
            _SCREAMING_SNAKE_CASE	=				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:
               _SCREAMING_SNAKE_CASE	=				"import datasets\n"
            elif "import tensorflow" in out_line:
               # order is important here
               _SCREAMING_SNAKE_CASE	=				""
               continue
            elif "from absl import logging" in out_line:
               _SCREAMING_SNAKE_CASE	=				"from datasets import logging\n"
            elif "getLogger" in out_line:
               _SCREAMING_SNAKE_CASE	=				out_line.replace("getLogger"  ,				"get_logger"   )
            elif any(expression in out_line for expression in TO_HIGHLIGHT   ):
               _SCREAMING_SNAKE_CASE	=				True
               _SCREAMING_SNAKE_CASE	=				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:
                  _SCREAMING_SNAKE_CASE	=				re.sub(__lowerCamelCase  ,				__lowerCamelCase  ,				__lowerCamelCase   )

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

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

