


'''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


__snake_case							   =  '''<<<<<<< This should probably be modified because it mentions: '''

__snake_case							   =  '''=======
>>>>>>>
'''

__snake_case							   =  [
    '''TextEncoderConfig''',
    '''ByteTextEncoder''',
    '''SubwordTextEncoder''',
    '''encoder_config''',
    '''maybe_build_from_corpus''',
    '''manual_dir''',
]

__snake_case							   =  [
    # (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   (    __a     )						->			Any:



					'''simple docstring'''






					return ConvertCommand(args.tfds_path				,      args.datasets_directory     )







class      lowercase			(							A__      ):

		"""simple docstring"""

		@staticmethod
		def 					lowerCAmelCase__       (	UpperCamelCase_							):

							'''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=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					,     UpperCamelCase_					,     UpperCamelCase_					,     *UpperCamelCase_							):

							'''simple docstring'''


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

							UpperCamelCase__     :Optional[Any]							      =				tfds_path
							UpperCamelCase__     :List[Any]							      =				datasets_directory




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							if os.path.isdir(self._tfds_path							):
												UpperCamelCase__     :Union[str, Any]							      =				os.path.abspath(self._tfds_path							)
							elif os.path.isfile(self._tfds_path							):
												UpperCamelCase__     :Dict							      =				os.path.dirname(self._tfds_path							)
							else:
												raise ValueError('''--tfds_path is neither a directory nor a file. Please check path.'''							)

							UpperCamelCase__     :Union[str, Any]							      =				os.path.abspath(self._datasets_directory							)

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

							UpperCamelCase__     :int							      =				[]
							UpperCamelCase__     :Union[str, Any]							      =				[]
							UpperCamelCase__     :str							      =				{}

							if os.path.isdir(self._tfds_path							):
												UpperCamelCase__     :Union[str, Any]							      =				os.listdir(UpperCamelCase_							)
							else:
												UpperCamelCase__     :Optional[int]							      =				[os.path.basename(self._tfds_path							)]

							for f_name in file_names:
												self._logger.info(F'''Looking at file {f_name}'''							)
												UpperCamelCase__     :List[str]							      =				os.path.join(UpperCamelCase_					,     UpperCamelCase_							)
												UpperCamelCase__     :Union[str, Any]							      =				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:
																	UpperCamelCase__     :Tuple							      =				f.readlines()

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

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

												if is_builder or "wmt" in f_name:
																	# We create a new directory for each dataset
																	UpperCamelCase__     :Optional[Any]							      =				f_name.replace('''.py'''					,     ''''''							)
																	UpperCamelCase__     :str							      =				os.path.join(UpperCamelCase_					,     UpperCamelCase_							)
																	UpperCamelCase__     :Union[str, Any]							      =				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:
																	UpperCamelCase__     :Tuple							      =				os.path.basename(UpperCamelCase_							)
																	UpperCamelCase__     :int							      =				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 typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


__snake_case							   =  {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ReformerConfig''']}

try:
		if not is_sentencepiece_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							   =  ['''ReformerTokenizer''']

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							   =  ['''ReformerTokenizerFast''']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case							   =  [
		    '''REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ReformerAttention''',
		    '''ReformerForMaskedLM''',
		    '''ReformerForQuestionAnswering''',
		    '''ReformerForSequenceClassification''',
		    '''ReformerLayer''',
		    '''ReformerModel''',
		    '''ReformerModelWithLMHead''',
		    '''ReformerPreTrainedModel''',
		]


if TYPE_CHECKING:
		from .configuration_reformer import REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, ReformerConfig

		try:
				if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_reformer import ReformerTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_reformer_fast import ReformerTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_reformer import (
				    REFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ReformerAttention,
				    ReformerForMaskedLM,
				    ReformerForQuestionAnswering,
				    ReformerForSequenceClassification,
				    ReformerLayer,
				    ReformerModel,
				    ReformerModelWithLMHead,
				    ReformerPreTrainedModel,
				)

else:
		import sys

		__snake_case							   =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)