




'''simple docstring'''





import itertools
from dataclasses import dataclass
from typing import Optional

import pandas as pd
import pyarrow as pa

import datasets
from datasets.table import table_cast




@dataclass
class 					snake_case__							(datasets.BuilderConfig     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Optional[datasets.Features]											=      None




class 					snake_case__							(datasets.ArrowBasedBuilder     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							Union[str, Any]											=      PandasConfig





				def 							__UpperCAmelCase							(   self       :  Tuple							)      ->  List[str]:
							return datasets.DatasetInfo(features=self.config.features							)





				def 							__UpperCAmelCase							(   self       :  Any      ,   __lowerCamelCase       :  Union[str, Any]							)      ->  Any:
							if not self.config.data_files:
										raise ValueError(f"""At least one data file must be specified, but got data_files={self.config.data_files}"""							)
							a					=    dl_manager.download_and_extract(self.config.data_files							)
							if isinstance(__lowerCamelCase      ,   (str, list, tuple)							):
										a					=    data_files
										if isinstance(__lowerCamelCase      ,   __lowerCamelCase							):
													a					=    [files]
										# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
										a					=    [dl_manager.iter_files(__lowerCamelCase							) for file in files]
										return [datasets.SplitGenerator(name=datasets.Split.TRAIN      ,   gen_kwargs={"files": files}							)]
							a					=    []
							for split_name, files in data_files.items():
										if isinstance(__lowerCamelCase      ,   __lowerCamelCase							):
													a					=    [files]
										# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
										a					=    [dl_manager.iter_files(__lowerCamelCase							) for file in files]
										splits.append(datasets.SplitGenerator(name=__lowerCamelCase      ,   gen_kwargs={"files": files}							)							)
							return splits





				def 							__UpperCAmelCase							(   self       :  Optional[int]      ,   __lowerCamelCase       :  pa.Table							)      ->  pa.Table:
							if self.config.features is not None:
										# more expensive cast to support nested features with keys in a different order
										# allows str <-> int/float or str to Audio for example
										a					=    table_cast(__lowerCamelCase      ,   self.config.features.arrow_schema							)
							return pa_table





				def 							__UpperCAmelCase							(   self       :  str      ,   __lowerCamelCase       :  List[str]							)      ->  List[str]:
							for i, file in enumerate(itertools.chain.from_iterable(__lowerCamelCase							)							):
										with open(__lowerCamelCase      ,   "rb"							) as f:
													a					=    pa.Table.from_pandas(pd.read_pickle(__lowerCamelCase							)							)
													yield i, self._cast_table(__lowerCamelCase							)












import argparse
import os
import re


__lowerCAmelCase	:       Union[str, Any]     =	'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
__lowerCAmelCase	:       Dict     =	re.compile(r'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
__lowerCAmelCase	:       Any     =	re.compile(r'\s*\(\s*"(\S[^"]+)"')




def     __magic_name__       (				A	:      int,						A	:      bool = False     ):






			'''simple docstring'''







			with open(A,						"r",						encoding="utf-8"     ) as f:
						a					=    f.read()

			a					=    content.split("\n"     )
			a					=    []
			a					=    0
			while line_idx < len(A     ):
						if _re_intro_mapping.search(lines[line_idx]     ) is not None:
									a					=    len(re.search(R"^(\s*)\S",						lines[line_idx]     ).groups()[0]     ) + 8
									# Start of a new mapping!
									while not lines[line_idx].startswith(" " * indent + "("     ):
												new_lines.append(lines[line_idx]     )
												line_idx += 1

									a					=    []
									while lines[line_idx].strip() != "]":
												# Blocks either fit in one line or not
												if lines[line_idx].strip() == "(":
															a					=    line_idx
															while not lines[line_idx].startswith(" " * indent + ")"     ):
																		line_idx += 1
															blocks.append("\n".join(lines[start_idx : line_idx + 1]     )     )
												else:
															blocks.append(lines[line_idx]     )
												line_idx += 1

									# Sort blocks by their identifiers
									a					=    sorted(A,						key=lambda A     : _re_identifier.search(A     ).groups()[0]     )
									new_lines += blocks
						else:
									new_lines.append(lines[line_idx]     )
									line_idx += 1

			if overwrite:
						with open(A,						"w",						encoding="utf-8"     ) as f:
									f.write("\n".join(A     )     )
			elif "\n".join(A     ) != content:
						return True




def     __magic_name__       (				A	:      bool = False     ):






			'''simple docstring'''







			a					=    [os.path.join(A,						A     ) for f in os.listdir(A     ) if f.endswith(".py"     )]
			a					=    [sort_auto_mapping(A,						overwrite=A     ) for fname in fnames]

			if not overwrite and any(A     ):
						a					=    [f for f, d in zip(A,						A     ) if d]
						raise ValueError(
						    F"""The following files have auto mappings that need sorting: {", ".join(A     )}. Run `make style` to fix"""
						    " this."     )


if __name__ == "__main__":
		__lowerCAmelCase	:       Dict     =	argparse.ArgumentParser()
		parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
		__lowerCAmelCase	:       Optional[Any]     =	parser.parse_args()

		sort_all_auto_mappings(not args.check_only)






