code: 
  
  
  
  
  
  
  import os
  import tempfile
  from pathlib import Path
  from unittest import TestCase
  
  import pyarrow as pa
  import pytest
  
  from datasets.arrow_dataset import Dataset
  from datasets.arrow_reader import ArrowReader, BaseReader, FileInstructions, ReadInstruction, make_file_instructions
  from datasets.info import DatasetInfo
  from datasets.splits import NamedSplit, Split, SplitDict, SplitInfo
  
  from .utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
  
  
  
  
  
  
  
  class 							UpperCAmelCase_     (		__lowerCamelCase		):
  
  
  
  
       def      __UpperCAmelCase     (							self  ,	_lowerCAmelCase  ,	_lowerCAmelCase=False		):
            UpperCAmelCase__			,		UpperCAmelCase__			,		UpperCAmelCase__			:     int										= (
                filename_skip_take["""filename"""],
                filename_skip_take["""skip"""] if """skip""" in filename_skip_take else None,
                filename_skip_take["""take"""] if """take""" in filename_skip_take else None,
            )
            open(os.path.join(_lowerCAmelCase		)  ,	"""wb"""		).close()
            UpperCAmelCase__			:     List[Any]										= pa.Table.from_pydict({"""filename""": [Path(_lowerCAmelCase		).name] * 100}		)
            if take == -1:
                 UpperCAmelCase__			:     Tuple										= len(_lowerCAmelCase		) - skip
            if skip is not None and take is not None:
                 UpperCAmelCase__			:     Tuple										= pa_table.slice(_lowerCAmelCase  ,	_lowerCAmelCase		)
            return pa_table
  
  
  
  
  
  
  
  class 							UpperCAmelCase_     (		__lowerCamelCase		):
  
  
  
  
       def      __UpperCAmelCase     (							self		):
            UpperCAmelCase__			:     Tuple										= """my_name"""
            UpperCAmelCase__			:     Optional[int]										= SplitInfo(name="""train"""  ,	num_examples=100		)
            UpperCAmelCase__			:     Optional[Any]										= SplitInfo(name="""test"""  ,	num_examples=100		)
            UpperCAmelCase__			:     Tuple										= [train_info, test_info]
            UpperCAmelCase__			:     Any										= SplitDict()
            split_dict.add(_lowerCAmelCase		)
            split_dict.add(_lowerCAmelCase		)
            UpperCAmelCase__			:     Union[str, Any]										= DatasetInfo(splits=_lowerCAmelCase		)
  
            with tempfile.TemporaryDirectory() as tmp_dir:
                 UpperCAmelCase__			:     Any										= ReaderTest(_lowerCAmelCase  ,	_lowerCAmelCase		)
  
                 UpperCAmelCase__			:     Optional[Any]										= """test[:33%]"""
                 UpperCAmelCase__			:     Optional[Any]										= Dataset(**reader.read(_lowerCAmelCase  ,	_lowerCAmelCase  ,	_lowerCAmelCase		)		)
                 self.assertEqual(dset["""filename"""][0]  ,	f"{name}-test"		)
                 self.assertEqual(dset.num_rows  ,	33		)
                 self.assertEqual(dset.num_columns  ,	1		)
  
                 UpperCAmelCase__			:     Optional[Any]										= ["""train""", """test[:33%]"""]
                 UpperCAmelCase__			:     List[Any]										= [Split.TRAIN, ReadInstruction.from_spec("""test[:33%]"""		)]
                 for instructions in [instructionsa, instructionsa]:
                      UpperCAmelCase__			:     Optional[int]										= [reader.read(_lowerCAmelCase  ,	_lowerCAmelCase  ,	_lowerCAmelCase		) for instr in instructions]
                      UpperCAmelCase__			,		UpperCAmelCase__			:     Tuple										= (Dataset(**_lowerCAmelCase		) for dataset_kwargs in datasets_kwargs)
                      self.assertEqual(train_dset["""filename"""][0]  ,	f"{name}-train"		)
                      self.assertEqual(train_dset.num_rows  ,	100		)
                      self.assertEqual(train_dset.num_columns  ,	1		)
                      self.assertIsInstance(train_dset.split  ,	_lowerCAmelCase		)
                      self.assertEqual(str(train_dset.split		)  ,	"""train"""		)
                      self.assertEqual(test_dset["""filename"""][0]  ,	f"{name}-test"		)
                      self.assertEqual(test_dset.num_rows  ,	33		)
                      self.assertEqual(test_dset.num_columns  ,	1		)
                      self.assertIsInstance(test_dset.split  ,	_lowerCAmelCase		)
                      self.assertEqual(str(test_dset.split		)  ,	"""test[:33%]"""		)
                      del train_dset, test_dset
  
  
  
  
       def      __UpperCAmelCase     (							self		):
            UpperCAmelCase__			:     List[Any]										= """my_name"""
            UpperCAmelCase__			:     Tuple										= SplitInfo(name="""train"""  ,	num_examples=1000  ,	shard_lengths=[100] * 10		)
            UpperCAmelCase__			:     str										= [train_info]
            UpperCAmelCase__			:     int										= SplitDict()
            split_dict.add(_lowerCAmelCase		)
            UpperCAmelCase__			:     Dict										= DatasetInfo(splits=_lowerCAmelCase		)
  
            with tempfile.TemporaryDirectory() as tmp_dir:
                 UpperCAmelCase__			:     Union[str, Any]										= ReaderTest(_lowerCAmelCase  ,	_lowerCAmelCase		)
  
                 UpperCAmelCase__			:     Tuple										= """train[:33%]"""
                 UpperCAmelCase__			:     Optional[Any]										= Dataset(**reader.read(_lowerCAmelCase  ,	_lowerCAmelCase  ,	_lowerCAmelCase		)		)
                 self.assertEqual(dset["""filename"""][0]  ,	f"{name}-train-00000-of-00010"		)
                 self.assertEqual(dset["""filename"""][-1]  ,	f"{name}-train-00003-of-00010"		)
                 self.assertEqual(dset.num_rows  ,	330		)
                 self.assertEqual(dset.num_columns  ,	1		)
  
  
  
  
       def      __UpperCAmelCase     (							self		):
            UpperCAmelCase__			:     List[Any]										= SplitInfo(name="""train"""  ,	num_examples=100		)
            UpperCAmelCase__			:     Optional[int]										= SplitInfo(name="""test"""  ,	num_examples=100		)
            UpperCAmelCase__			:     Any										= SplitDict()
            split_dict.add(_lowerCAmelCase		)
            split_dict.add(_lowerCAmelCase		)
            UpperCAmelCase__			:     Dict										= DatasetInfo(splits=_lowerCAmelCase		)
  
            with tempfile.TemporaryDirectory() as tmp_dir:
                 UpperCAmelCase__			:     List[str]										= ReaderTest(_lowerCAmelCase  ,	_lowerCAmelCase		)
  
                 UpperCAmelCase__			:     Dict										= [
                     {"""filename""": os.path.join(_lowerCAmelCase  ,	"""train"""		)},
                     {"""filename""": os.path.join(_lowerCAmelCase  ,	"""test"""		), """skip""": 10, """take""": 10},
                 ]
                 UpperCAmelCase__			:     Optional[Any]										= Dataset(**reader.read_files(_lowerCAmelCase  ,	original_instructions="""train+test[10:20]"""		)		)
                 self.assertEqual(dset.num_rows  ,	110		)
                 self.assertEqual(dset.num_columns  ,	1		)
                 del dset
  
  
  
  
  
  @pytest.mark.parametrize("""in_memory"""   ,       [False, True]					)
  def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)   -> Tuple:
  
       '''simple docstring'''
       UpperCAmelCase__			:     str										= arrow_file
       with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
            UpperCAmelCase__			:     Optional[Any]										= ArrowReader.read_table(__lowerCamelCase   ,       in_memory=__lowerCamelCase					)
       assert table.shape == dataset.data.shape
       assert set(table.column_names					) == set(dataset.data.column_names					)
       assert dict(table.to_pydict()					) == dict(dataset.data.to_pydict()					)  # to_pydict returns OrderedDict
  
  
  
  
  
  @pytest.mark.parametrize("""in_memory"""   ,       [False, True]					)
  def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)   -> Union[str, Any]:
  
       '''simple docstring'''
       UpperCAmelCase__			:     int										= arrow_file
       UpperCAmelCase__			:     Optional[int]										= ArrowReader(""""""   ,       __lowerCamelCase					)
       with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
            UpperCAmelCase__			:     List[Any]										= reader.read_files([{"""filename""": filename}]   ,       in_memory=__lowerCamelCase					)
       assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
       UpperCAmelCase__			:     Dict										= dataset_kwargs["""arrow_table"""]
       assert table.shape == dataset.data.shape
       assert set(table.column_names					) == set(dataset.data.column_names					)
       assert dict(table.to_pydict()					) == dict(dataset.data.to_pydict()					)  # to_pydict returns OrderedDict
  
  
  
  
  
  def    _lowerCamelCase	(	)   -> str:
  
       '''simple docstring'''
       assert ReadInstruction("""train"""   ,       to=10   ,       unit="""abs"""					).to_spec() == "train[:10]"
       assert ReadInstruction("""train"""   ,       from_=-80   ,       to=10   ,       unit="""%"""					).to_spec() == "train[-80%:10%]"
  
       UpperCAmelCase__			:     str										= """train+test"""
       assert ReadInstruction.from_spec(__lowerCamelCase					).to_spec() == spec_train_test
  
       UpperCAmelCase__			:     int										= """train[2:10]"""
       assert ReadInstruction.from_spec(__lowerCamelCase					).to_spec() == spec_train_abs
  
       UpperCAmelCase__			:     List[Any]										= """train[15%:-20%]"""
       assert ReadInstruction.from_spec(__lowerCamelCase					).to_spec() == spec_train_pct
  
       UpperCAmelCase__			:     List[Any]										= """train[:10%](closest)"""
       assert ReadInstruction.from_spec(__lowerCamelCase					).to_spec() == "train[:10%]"
  
       UpperCAmelCase__			:     str										= """train[:10%](pct1_dropremainder)"""
       assert ReadInstruction.from_spec(__lowerCamelCase					).to_spec() == spec_train_pct_rounding
  
       UpperCAmelCase__			:     Dict										= """train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"""
       assert ReadInstruction.from_spec(__lowerCamelCase					).to_spec() == spec_train_test_pct_rounding
  
  
  
  
  
  def    _lowerCamelCase	(	)   -> Tuple:
  
       '''simple docstring'''
       UpperCAmelCase__			:     Optional[Any]										= """dummy"""
       UpperCAmelCase__			:     Union[str, Any]										= [SplitInfo(name="""train"""   ,       num_examples=100					)]
       UpperCAmelCase__			:     Dict										= """train[:33%]"""
       UpperCAmelCase__			:     Optional[Any]										= """arrow"""
       UpperCAmelCase__			:     Optional[Any]										= """prefix"""
  
       UpperCAmelCase__			:     Union[str, Any]										= make_file_instructions(__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)
       assert isinstance(__lowerCamelCase   ,       __lowerCamelCase					)
       assert file_instructions.num_examples == 33
       assert file_instructions.file_instructions == [
           {"filename": os.path.join(__lowerCamelCase   ,       F"{name}-train.arrow"					), "skip": 0, "take": 33}
       ]
  
       UpperCAmelCase__			:     List[Any]										= [SplitInfo(name="""train"""   ,       num_examples=100   ,       shard_lengths=[10] * 10					)]
       UpperCAmelCase__			:     Any										= make_file_instructions(__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)
       assert isinstance(__lowerCamelCase   ,       __lowerCamelCase					)
       assert file_instructions.num_examples == 33
       assert file_instructions.file_instructions == [
           {"filename": os.path.join(__lowerCamelCase   ,       F"{name}-train-00000-of-00010.arrow"					), "skip": 0, "take": -1},
           {"filename": os.path.join(__lowerCamelCase   ,       F"{name}-train-00001-of-00010.arrow"					), "skip": 0, "take": -1},
           {"filename": os.path.join(__lowerCamelCase   ,       F"{name}-train-00002-of-00010.arrow"					), "skip": 0, "take": -1},
           {"filename": os.path.join(__lowerCamelCase   ,       F"{name}-train-00003-of-00010.arrow"					), "skip": 0, "take": 3},
       ]
  
  
  
  
  
  
  
  @pytest.mark.parametrize("""name, expected_exception"""   ,       [(None, TypeError), ("""""", ValueError)]					)
  def    _lowerCamelCase	(	__lowerCamelCase   ,       __lowerCamelCase					)   -> str:
  
       '''simple docstring'''
       UpperCAmelCase__			:     str										= [SplitInfo(name="""train"""   ,       num_examples=100					)]
       UpperCAmelCase__			:     Union[str, Any]										= """train"""
       UpperCAmelCase__			:     Tuple										= """arrow"""
       UpperCAmelCase__			:     Union[str, Any]										= """prefix_path"""
       with pytest.raises(__lowerCamelCase					):
            UpperCAmelCase__			:     Union[str, Any]										= make_file_instructions(__lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase   ,       __lowerCamelCase					)
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  
  import warnings
  
  from ...utils import logging
  from .image_processing_vilt import ViltImageProcessor
  
  
  SCREAMING_SNAKE_CASE__		:       Optional[int]   							=							logging.get_logger(__name__)
  
  
  
  
  
  
  
  class 							UpperCAmelCase_     (		__lowerCamelCase		):
  
  
  
  
       def __init__(							self  ,	*_lowerCAmelCase  ,	**_lowerCAmelCase		):
            warnings.warn(
                """The class ViltFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
                """ use ViltImageProcessor instead."""  ,	_lowerCAmelCase  ,	)
            super().__init__(*_lowerCAmelCase  ,	**_lowerCAmelCase		)
  
  
  
  
  
  
  