




'''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


_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			"<<<<<<< This should probably be modified because it mentions: "

_SCREAMING_SNAKE_CASE							:       Optional[int]						=			"=======\n>>>>>>>\n"

_SCREAMING_SNAKE_CASE							:       Optional[Any]						=			[
    "TextEncoderConfig",
    "ByteTextEncoder",
    "SubwordTextEncoder",
    "encoder_config",
    "maybe_build_from_corpus",
    "manual_dir",
]

_SCREAMING_SNAKE_CASE							:       Dict						=			[
    # (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_(     snake_case							:	Namespace					):

							'''simple docstring'''






							return ConvertCommand(args.tfds_path							,    args.datasets_directory					)




class 			_snake_case		(     lowercase_							):




			@staticmethod
			def        lowerCAmelCase__    ( a__							)    ->    int:

										'''simple docstring'''




										snake_case_      =				parser.add_parser(
										    "convert"    ,							help="Convert a TensorFlow Datasets dataset to a HuggingFace Datasets dataset."    ,							)
										train_parser.add_argument(
										    "--tfds_path"    ,							type=a__    ,							required=a__    ,							help="Path to a TensorFlow Datasets folder to convert or a single tfds file to convert."    ,							)
										train_parser.add_argument(
										    "--datasets_directory"    ,							type=a__    ,							required=a__    ,							help="Path to the HuggingFace Datasets folder."							)
										train_parser.set_defaults(func=a__							)




			def __init__( self    ,							a__    ,							a__    ,							*a__							)    ->    List[Any]:

										'''simple docstring'''




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

										snake_case_      =				tfds_path
										snake_case_      =				datasets_directory




			def        lowerCAmelCase__    ( self							)    ->    Optional[Any]:

										'''simple docstring'''




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

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

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

										snake_case_      =				[]
										snake_case_      =				[]
										snake_case_      =				{}

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

										for f_name in file_names:
																	self._logger.info(F'Looking at file {f_name}'							)
																	snake_case_      =				os.path.join(a__    ,							a__							)
																	snake_case_      =				os.path.join(a__    ,							a__							)

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

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

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

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

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

																	if needs_manual_update:
																								with_manual_update.append(a__							)

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

										for utils_file in utils_files:
																	try:
																								snake_case_      =				os.path.basename(a__							)
																								snake_case_      =				imports_to_builder_map[f_name.replace(".py"    ,							""							)]
																								self._logger.info(F'Moving {dest_folder} to {utils_file}'							)
																								shutil.copy(a__    ,							a__							)
																	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 __future__ import annotations

import numpy as np


def 					UpperCamelCase_(     snake_case							:	np.ndarray					):

							'''simple docstring'''






							snake_case_ ,				snake_case_      =				np.shape(snake_case					)
							if rows != columns:
														snake_case_      =				(
														    "'table' has to be of square shaped array but got a "
														    f'{rows}x{columns} array:\n{table}'
														)
														raise ValueError(snake_case					)

							snake_case_      =				np.zeros((rows, columns)					)
							snake_case_      =				np.zeros((rows, columns)					)
							for i in range(snake_case					):
														for j in range(snake_case					):
																					snake_case_      =				sum(lower[i][k] * upper[k][j] for k in range(snake_case					)					)
																					if upper[j][j] == 0:
																												raise ArithmeticError("No LU decomposition exists"					)
																					snake_case_      =				(table[i][j] - total) / upper[j][j]
														snake_case_      =				1
														for j in range(snake_case							,    snake_case					):
																					snake_case_      =				sum(lower[i][k] * upper[k][j] for k in range(snake_case					)					)
																					snake_case_      =				table[i][j] - total
							return lower, upper


if __name__ == "__main__":
		import doctest

		doctest.testmod()




