


'''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  __lowerCAmelCase (__lowerCAmelCase   ):
		return ConvertCommand(args.tfds_path      , args.datasets_directory   )






class 	lowerCAmelCase__			(			UpperCAmelCase__	):




			@staticmethod
			def 							lowerCAmelCase__    (		lowerCamelCase__  :     ArgumentParser )   ->Union[str, Any]:



					'''simple docstring'''







					_UpperCAmelCase		:       Tuple								=      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  :     int	,  lowerCamelCase__  :     str	,  lowerCamelCase__  :     str	,  *lowerCamelCase__  :     Any )   ->int:



					'''simple docstring'''







					_UpperCAmelCase		:       Union[str, Any]								=      get_logger("datasets-cli/converting" )

					_UpperCAmelCase		:       List[str]								=      tfds_path
					_UpperCAmelCase		:       str								=      datasets_directory






			def 							lowerCAmelCase__    (		self  :     Union[str, Any] )   ->Any:



					'''simple docstring'''







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

					_UpperCAmelCase		:       Tuple								=      os.path.abspath(self._datasets_directory )

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

					_UpperCAmelCase		:       List[str]								=      []
					_UpperCAmelCase		:       Optional[Any]								=      []
					_UpperCAmelCase		:       int								=      {}

					if os.path.isdir(self._tfds_path ):
							_UpperCAmelCase		:       Dict								=      os.listdir(lowerCamelCase__ )
					else:
							_UpperCAmelCase		:       Union[str, Any]								=      [os.path.basename(self._tfds_path )]

					for f_name in file_names:
							self._logger.info(F"""Looking at file {f_name}""" )
							_UpperCAmelCase		:       int								=      os.path.join(lowerCamelCase__	,  lowerCamelCase__ )
							_UpperCAmelCase		:       str								=      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:
									_UpperCAmelCase		:       Any								=      f.readlines()

							_UpperCAmelCase		:       List[Any]								=      []
							_UpperCAmelCase		:       Union[str, Any]								=      False
							_UpperCAmelCase		:       Union[str, Any]								=      False
							_UpperCAmelCase		:       Any								=      []
							for line in lines:
									_UpperCAmelCase		:       str								=      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		:       List[Any]								=      "import datasets\n"
									elif "import tensorflow" in out_line:
											# order is important here
											_UpperCAmelCase		:       Tuple								=      ""
											continue
									elif "from absl import logging" in out_line:
											_UpperCAmelCase		:       Optional[Any]								=      "from datasets import logging\n"
									elif "getLogger" in out_line:
											_UpperCAmelCase		:       str								=      out_line.replace("getLogger"	,  "get_logger" )
									elif any(expression in out_line for expression in TO_HIGHLIGHT ):
											_UpperCAmelCase		:       int								=      True
											_UpperCAmelCase		:       Optional[int]								=      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:
													_UpperCAmelCase		:       Dict								=      re.sub(lowerCamelCase__	,  lowerCamelCase__	,  lowerCamelCase__ )

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

							if is_builder or "wmt" in f_name:
									# We create a new directory for each dataset
									_UpperCAmelCase		:       List[str]								=      f_name.replace(".py"	,  "" )
									_UpperCAmelCase		:       Optional[Any]								=      os.path.join(lowerCamelCase__	,  lowerCamelCase__ )
									_UpperCAmelCase		:       List[Any]								=      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:
									_UpperCAmelCase		:       List[Any]								=      os.path.basename(lowerCamelCase__ )
									_UpperCAmelCase		:       Optional[int]								=      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 ...utils import (
    OptionalDependencyNotAvailable,
    is_flax_available,
    is_torch_available,
    is_transformers_available,
)


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 .multicontrolnet import MultiControlNetModel
						from .pipeline_controlnet import StableDiffusionControlNetPipeline
						from .pipeline_controlnet_imgaimg import StableDiffusionControlNetImgaImgPipeline
						from .pipeline_controlnet_inpaint import StableDiffusionControlNetInpaintPipeline


if is_transformers_available() and is_flax_available():
						from .pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline



