

"""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


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

_a							=							"""=======
>>>>>>>
"""

_a							=							[
    """TextEncoderConfig""",
    """ByteTextEncoder""",
    """SubwordTextEncoder""",
    """encoder_config""",
    """maybe_build_from_corpus""",
    """manual_dir""",
]

_a							=							[
    # (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_					:	Namespace)     ->						Optional[int]:
   '''simple docstring'''


   return ConvertCommand(args.tfds_path,      args.datasets_directory)




class  _lowerCAmelCase  (     lowercase       ):







   """simple docstring"""







   @staticmethod
   def  _lowercase			(      UpperCAmelCase__							:      ArgumentParser     ):
      __lowercase								=						parser.add_parser(
          "convert", help="Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset.", )
      train_parser.add_argument(
          "--tfds_path", type=UpperCAmelCase__, required=UpperCAmelCase__, help="Path to a TensorFlow Datasets folder to convert or a single tfds file to convert.", )
      train_parser.add_argument(
          "--datasets_directory", type=UpperCAmelCase__, required=UpperCAmelCase__, help="Path to the HuggingFace Datasets folder."     )
      train_parser.set_defaults(func=UpperCAmelCase__     )


   def __init__(      self							:      List[str], UpperCAmelCase__							:      str, UpperCAmelCase__							:      str, *UpperCAmelCase__							:      Tuple     ):
      __lowercase								=						get_logger("datasets-cli/converting"     )

      __lowercase								=						tfds_path
      __lowercase								=						datasets_directory



   def  _lowercase			(      self							:      Dict     ):




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

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

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

      __lowercase								=						[]
      __lowercase								=						[]
      __lowercase								=						{}

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

      for f_name in file_names:
         self._logger.info(F"""Looking at file {f_name}"""     )
         __lowercase								=						os.path.join(UpperCAmelCase__, UpperCAmelCase__     )
         __lowercase								=						os.path.join(UpperCAmelCase__, UpperCAmelCase__     )

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

         with open(UpperCAmelCase__, encoding="utf-8"     ) as f:
            __lowercase								=						f.readlines()

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

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

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

         if needs_manual_update:
            with_manual_update.append(UpperCAmelCase__     )

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

      for utils_file in utils_files:
         try:
            __lowercase								=						os.path.basename(UpperCAmelCase__     )
            __lowercase								=						imports_to_builder_map[f_name.replace(".py", ""     )]
            self._logger.info(F"""Moving {dest_folder} to {utils_file}"""     )
            shutil.copy(UpperCAmelCase__, UpperCAmelCase__     )
         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 ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable


try:
   if not (is_transformers_available() and is_torch_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_torch_and_transformers_objects import *  # noqa F403
else:
   from .notes_encoder import SpectrogramNotesEncoder
   from .continous_encoder import SpectrogramContEncoder
   from .pipeline_spectrogram_diffusion import (
       SpectrogramContEncoder,
       SpectrogramDiffusionPipeline,
       TaFilmDecoder,
   )

try:
   if not (is_transformers_available() and is_torch_available() and is_note_seq_available()):
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   from ...utils.dummy_transformers_and_torch_and_note_seq_objects import *  # noqa F403
else:
   from .midi_utils import MidiProcessor




