





"""simple docstring"""


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    lowercase_ (   __lowerCAmelCase							):

       def 						_SCREAMING_SNAKE_CASE(	self      ,    __SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE=False   ):






        '''simple docstring'''

        snake_case__							,      snake_case__							,      snake_case__										= (
            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(__SCREAMING_SNAKE_CASE   )      ,    "wb"   ).close()
        snake_case__										= pa.Table.from_pydict({"filename": [Path(__SCREAMING_SNAKE_CASE   ).name] * 100}   )
        if take == -1:
         snake_case__										= len(__SCREAMING_SNAKE_CASE   ) - skip
        if skip is not None and take is not None:
         snake_case__										= pa_table.slice(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   )
        return pa_table



class    lowercase_ (   __lowerCAmelCase							):

       def 						_SCREAMING_SNAKE_CASE(	self   ):






        '''simple docstring'''

        snake_case__										= "my_name"
        snake_case__										= SplitInfo(name="train"      ,    num_examples=100   )
        snake_case__										= SplitInfo(name="test"      ,    num_examples=100   )
        snake_case__										= [train_info, test_info]
        snake_case__										= SplitDict()
        split_dict.add(__SCREAMING_SNAKE_CASE   )
        split_dict.add(__SCREAMING_SNAKE_CASE   )
        snake_case__										= DatasetInfo(splits=__SCREAMING_SNAKE_CASE   )

        with tempfile.TemporaryDirectory() as tmp_dir:
         snake_case__										= ReaderTest(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   )

         snake_case__										= "test[:33%]"
         snake_case__										= Dataset(**reader.read(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   )   )
         self.assertEqual(dset["filename"][0]      ,    F"{name}-test"   )
         self.assertEqual(dset.num_rows      ,    33   )
         self.assertEqual(dset.num_columns      ,    1   )

         snake_case__										= ["train", "test[:33%]"]
         snake_case__										= [Split.TRAIN, ReadInstruction.from_spec("test[:33%]"   )]
         for instructions in [instructionsa, instructionsa]:
          snake_case__										= [reader.read(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   ) for instr in instructions]
          snake_case__							,      snake_case__										= (Dataset(**__SCREAMING_SNAKE_CASE   ) 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      ,    __SCREAMING_SNAKE_CASE   )
          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      ,    __SCREAMING_SNAKE_CASE   )
          self.assertEqual(str(test_dset.split   )      ,    "test[:33%]"   )
          del train_dset, test_dset

       def 						_SCREAMING_SNAKE_CASE(	self   ):






        '''simple docstring'''

        snake_case__										= "my_name"
        snake_case__										= SplitInfo(name="train"      ,    num_examples=1000      ,    shard_lengths=[100] * 10   )
        snake_case__										= [train_info]
        snake_case__										= SplitDict()
        split_dict.add(__SCREAMING_SNAKE_CASE   )
        snake_case__										= DatasetInfo(splits=__SCREAMING_SNAKE_CASE   )

        with tempfile.TemporaryDirectory() as tmp_dir:
         snake_case__										= ReaderTest(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   )

         snake_case__										= "train[:33%]"
         snake_case__										= Dataset(**reader.read(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   )   )
         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 						_SCREAMING_SNAKE_CASE(	self   ):






        '''simple docstring'''

        snake_case__										= SplitInfo(name="train"      ,    num_examples=100   )
        snake_case__										= SplitInfo(name="test"      ,    num_examples=100   )
        snake_case__										= SplitDict()
        split_dict.add(__SCREAMING_SNAKE_CASE   )
        split_dict.add(__SCREAMING_SNAKE_CASE   )
        snake_case__										= DatasetInfo(splits=__SCREAMING_SNAKE_CASE   )

        with tempfile.TemporaryDirectory() as tmp_dir:
         snake_case__										= ReaderTest(__SCREAMING_SNAKE_CASE      ,    __SCREAMING_SNAKE_CASE   )

         snake_case__										= [
             {"filename": os.path.join(__SCREAMING_SNAKE_CASE      ,    "train"   )},
             {"filename": os.path.join(__SCREAMING_SNAKE_CASE      ,    "test"   ), "skip": 10, "take": 10},
         ]
         snake_case__										= Dataset(**reader.read_files(__SCREAMING_SNAKE_CASE      ,    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 							a__	(     _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		)			->     str:

 '''simple docstring'''






 snake_case__										= arrow_file
 with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
  snake_case__										= ArrowReader.read_table(_UpperCAmelCase		,   in_memory=_UpperCAmelCase		)
 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 							a__	(     _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		)			->     Tuple:

 '''simple docstring'''






 snake_case__										= arrow_file
 snake_case__										= ArrowReader(""		,   _UpperCAmelCase		)
 with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
  snake_case__										= reader.read_files([{"filename": filename}]		,   in_memory=_UpperCAmelCase		)
 assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
 snake_case__										= 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 							a__	(     )			->     Optional[Any]:

 '''simple docstring'''






 assert ReadInstruction("train"		,   to=1_0		,   unit="abs"		).to_spec() == "train[:10]"
 assert ReadInstruction("train"		,   from_=-8_0		,   to=1_0		,   unit="%"		).to_spec() == "train[-80%:10%]"

 snake_case__										= "train+test"
 assert ReadInstruction.from_spec(_UpperCAmelCase		).to_spec() == spec_train_test

 snake_case__										= "train[2:10]"
 assert ReadInstruction.from_spec(_UpperCAmelCase		).to_spec() == spec_train_abs

 snake_case__										= "train[15%:-20%]"
 assert ReadInstruction.from_spec(_UpperCAmelCase		).to_spec() == spec_train_pct

 snake_case__										= "train[:10%](closest)"
 assert ReadInstruction.from_spec(_UpperCAmelCase		).to_spec() == "train[:10%]"

 snake_case__										= "train[:10%](pct1_dropremainder)"
 assert ReadInstruction.from_spec(_UpperCAmelCase		).to_spec() == spec_train_pct_rounding

 snake_case__										= "train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)"
 assert ReadInstruction.from_spec(_UpperCAmelCase		).to_spec() == spec_train_test_pct_rounding





def 							a__	(     )			->     int:

 '''simple docstring'''






 snake_case__										= "dummy"
 snake_case__										= [SplitInfo(name="train"		,   num_examples=1_0_0		)]
 snake_case__										= "train[:33%]"
 snake_case__										= "arrow"
 snake_case__										= "prefix"

 snake_case__										= make_file_instructions(_UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		)
 assert isinstance(_UpperCAmelCase		,   _UpperCAmelCase		)
 assert file_instructions.num_examples == 3_3
 assert file_instructions.file_instructions == [
     {"filename": os.path.join(_UpperCAmelCase		,   f"{name}-train.arrow"		), "skip": 0, "take": 3_3}
 ]

 snake_case__										= [SplitInfo(name="train"		,   num_examples=1_0_0		,   shard_lengths=[1_0] * 1_0		)]
 snake_case__										= make_file_instructions(_UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		)
 assert isinstance(_UpperCAmelCase		,   _UpperCAmelCase		)
 assert file_instructions.num_examples == 3_3
 assert file_instructions.file_instructions == [
     {"filename": os.path.join(_UpperCAmelCase		,   f"{name}-train-00000-of-00010.arrow"		), "skip": 0, "take": -1},
     {"filename": os.path.join(_UpperCAmelCase		,   f"{name}-train-00001-of-00010.arrow"		), "skip": 0, "take": -1},
     {"filename": os.path.join(_UpperCAmelCase		,   f"{name}-train-00002-of-00010.arrow"		), "skip": 0, "take": -1},
     {"filename": os.path.join(_UpperCAmelCase		,   f"{name}-train-00003-of-00010.arrow"		), "skip": 0, "take": 3},
 ]





@pytest.mark.parametrize("name, expected_exception"		,   [(None, TypeError), ("", ValueError)]		)
def 							a__	(     _UpperCAmelCase		,   _UpperCAmelCase		)			->     Any:

 '''simple docstring'''






 snake_case__										= [SplitInfo(name="train"		,   num_examples=1_0_0		)]
 snake_case__										= "train"
 snake_case__										= "arrow"
 snake_case__										= "prefix_path"
 with pytest.raises(_UpperCAmelCase		):
  snake_case__										= make_file_instructions(_UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		,   _UpperCAmelCase		)








"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_vilt import ViltImageProcessor


a__    :   str    						= logging.get_logger(__name__)



class    lowercase_ (   __lowerCAmelCase							):

       def __init__(	self      ,    *__SCREAMING_SNAKE_CASE      ,    **__SCREAMING_SNAKE_CASE   ):






        '''simple docstring'''

        warnings.warn(
            "The class ViltFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
            " use ViltImageProcessor instead."      ,    __SCREAMING_SNAKE_CASE      ,    )
        super().__init__(*__SCREAMING_SNAKE_CASE      ,    **__SCREAMING_SNAKE_CASE   )

