






"""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 _lowerCAmelCase	(						lowerCamelCase_					):







						def  A			(						self      ,							lowerCAmelCase_      ,							lowerCAmelCase_=False       )		->       List[Any]:
										_SCREAMING_SNAKE_CASE      :		List[Any]							=						(
										    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()
										_SCREAMING_SNAKE_CASE      :		Any							=						pa.Table.from_pydict({'filename': [Path(lowerCAmelCase_       ).name] * 1_0_0}       )
										if take == -1:
														_SCREAMING_SNAKE_CASE      :		Dict							=						len(lowerCAmelCase_       ) - skip
										if skip is not None and take is not None:
														_SCREAMING_SNAKE_CASE      :		Dict							=						pa_table.slice(lowerCAmelCase_      ,							lowerCAmelCase_       )
										return pa_table


class _lowerCAmelCase	(						lowerCamelCase_					):







						def  A			(						self       )		->       Dict:
										_SCREAMING_SNAKE_CASE      :		int							=						"my_name"
										_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						SplitInfo(name='train'      ,							num_examples=1_0_0       )
										_SCREAMING_SNAKE_CASE      :		Tuple							=						SplitInfo(name='test'      ,							num_examples=1_0_0       )
										_SCREAMING_SNAKE_CASE      :		int							=						[train_info, test_info]
										_SCREAMING_SNAKE_CASE      :		Dict							=						SplitDict()
										split_dict.add(lowerCAmelCase_       )
										split_dict.add(lowerCAmelCase_       )
										_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						DatasetInfo(splits=lowerCAmelCase_       )

										with tempfile.TemporaryDirectory() as tmp_dir:
														_SCREAMING_SNAKE_CASE      :		List[Any]							=						ReaderTest(lowerCAmelCase_      ,							lowerCAmelCase_       )

														_SCREAMING_SNAKE_CASE      :		List[str]							=						"test[:33%]"
														_SCREAMING_SNAKE_CASE      :		Tuple							=						Dataset(**reader.read(lowerCAmelCase_      ,							lowerCAmelCase_      ,							lowerCAmelCase_       )       )
														self.assertEqual(dset['filename'][0]      ,							F"""{name}-test"""       )
														self.assertEqual(dset.num_rows      ,							3_3       )
														self.assertEqual(dset.num_columns      ,							1       )

														_SCREAMING_SNAKE_CASE      :		Any							=						["train", "test[:33%]"]
														_SCREAMING_SNAKE_CASE      :		int							=						[Split.TRAIN, ReadInstruction.from_spec('test[:33%]'       )]
														for instructions in [instructionsa, instructionsa]:
																		_SCREAMING_SNAKE_CASE      :		Any							=						[reader.read(lowerCAmelCase_      ,							lowerCAmelCase_      ,							lowerCAmelCase_       ) for instr in instructions]
																		_SCREAMING_SNAKE_CASE      :		List[str]							=						(Dataset(**lowerCAmelCase_       ) for dataset_kwargs in datasets_kwargs)
																		self.assertEqual(train_dset['filename'][0]      ,							F"""{name}-train"""       )
																		self.assertEqual(train_dset.num_rows      ,							1_0_0       )
																		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      ,							3_3       )
																		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  A			(						self       )		->       Dict:
										_SCREAMING_SNAKE_CASE      :		Optional[int]							=						"my_name"
										_SCREAMING_SNAKE_CASE      :		List[str]							=						SplitInfo(name='train'      ,							num_examples=1_0_0_0      ,							shard_lengths=[1_0_0] * 1_0       )
										_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						[train_info]
										_SCREAMING_SNAKE_CASE      :		List[str]							=						SplitDict()
										split_dict.add(lowerCAmelCase_       )
										_SCREAMING_SNAKE_CASE      :		Optional[int]							=						DatasetInfo(splits=lowerCAmelCase_       )

										with tempfile.TemporaryDirectory() as tmp_dir:
														_SCREAMING_SNAKE_CASE      :		Tuple							=						ReaderTest(lowerCAmelCase_      ,							lowerCAmelCase_       )

														_SCREAMING_SNAKE_CASE      :		int							=						"train[:33%]"
														_SCREAMING_SNAKE_CASE      :		int							=						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      ,							3_3_0       )
														self.assertEqual(dset.num_columns      ,							1       )







						def  A			(						self       )		->       int:
										_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						SplitInfo(name='train'      ,							num_examples=1_0_0       )
										_SCREAMING_SNAKE_CASE      :		Dict							=						SplitInfo(name='test'      ,							num_examples=1_0_0       )
										_SCREAMING_SNAKE_CASE      :		str							=						SplitDict()
										split_dict.add(lowerCAmelCase_       )
										split_dict.add(lowerCAmelCase_       )
										_SCREAMING_SNAKE_CASE      :		Dict							=						DatasetInfo(splits=lowerCAmelCase_       )

										with tempfile.TemporaryDirectory() as tmp_dir:
														_SCREAMING_SNAKE_CASE      :		str							=						ReaderTest(lowerCAmelCase_      ,							lowerCAmelCase_       )

														_SCREAMING_SNAKE_CASE      :		int							=						[
														    {"filename": os.path.join(lowerCAmelCase_      ,							'train'       )},
														    {"filename": os.path.join(lowerCAmelCase_      ,							'test'       ), "skip": 1_0, "take": 1_0},
														]
														_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						Dataset(**reader.read_files(lowerCAmelCase_      ,							original_instructions='train+test[10:20]'       )       )
														self.assertEqual(dset.num_rows      ,							1_1_0       )
														self.assertEqual(dset.num_columns      ,							1       )
														del dset





@pytest.mark.parametrize('in_memory',	[False, True]					)
def 							lowercase__		(				lowerCamelCase,	lowerCamelCase,	lowerCamelCase					):
				_SCREAMING_SNAKE_CASE      :		Dict							=						arrow_file
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								_SCREAMING_SNAKE_CASE      :		Any							=						ArrowReader.read_table(lowercase__,	in_memory=lowercase__					)
				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 							lowercase__		(				lowerCamelCase,	lowerCamelCase,	lowerCamelCase					):
				_SCREAMING_SNAKE_CASE      :		str							=						arrow_file
				_SCREAMING_SNAKE_CASE      :		Any							=						ArrowReader('',	lowercase__					)
				with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
								_SCREAMING_SNAKE_CASE      :		List[Any]							=						reader.read_files([{'filename': filename}],	in_memory=lowercase__					)
				assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
				_SCREAMING_SNAKE_CASE      :		List[str]							=						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 							lowercase__		(				):
				assert ReadInstruction('train',	to=10,	unit='abs'					).to_spec() == "train[:10]"
				assert ReadInstruction('train',	from_=-80,	to=10,	unit='%'					).to_spec() == "train[-80%:10%]"

				_SCREAMING_SNAKE_CASE      :		Tuple							=						"train+test"
				assert ReadInstruction.from_spec(lowercase__					).to_spec() == spec_train_test

				_SCREAMING_SNAKE_CASE      :		str							=						"train[2:10]"
				assert ReadInstruction.from_spec(lowercase__					).to_spec() == spec_train_abs

				_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						"train[15%:-20%]"
				assert ReadInstruction.from_spec(lowercase__					).to_spec() == spec_train_pct

				_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						"train[:10%](closest)"
				assert ReadInstruction.from_spec(lowercase__					).to_spec() == "train[:10%]"

				_SCREAMING_SNAKE_CASE      :		Dict							=						"train[:10%](pct1_dropremainder)"
				assert ReadInstruction.from_spec(lowercase__					).to_spec() == spec_train_pct_rounding

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





def 							lowercase__		(				):
				_SCREAMING_SNAKE_CASE      :		List[str]							=						"dummy"
				_SCREAMING_SNAKE_CASE      :		Optional[Any]							=						[SplitInfo(name='train',	num_examples=100					)]
				_SCREAMING_SNAKE_CASE      :		List[str]							=						"train[:33%]"
				_SCREAMING_SNAKE_CASE      :		Optional[int]							=						"arrow"
				_SCREAMING_SNAKE_CASE      :		Union[str, Any]							=						"prefix"

				_SCREAMING_SNAKE_CASE      :		Tuple							=						make_file_instructions(lowercase__,	lowercase__,	lowercase__,	lowercase__,	lowercase__					)
				assert isinstance(lowercase__,	lowercase__					)
				assert file_instructions.num_examples == 33
				assert file_instructions.file_instructions == [
				    {"filename": os.path.join(lowercase__,	f"""{name}-train.arrow"""					), "skip": 0, "take": 33}
				]

				_SCREAMING_SNAKE_CASE      :		Tuple							=						[SplitInfo(name='train',	num_examples=100,	shard_lengths=[10] * 10					)]
				_SCREAMING_SNAKE_CASE      :		List[str]							=						make_file_instructions(lowercase__,	lowercase__,	lowercase__,	lowercase__,	lowercase__					)
				assert isinstance(lowercase__,	lowercase__					)
				assert file_instructions.num_examples == 33
				assert file_instructions.file_instructions == [
				    {"filename": os.path.join(lowercase__,	f"""{name}-train-00000-of-00010.arrow"""					), "skip": 0, "take": -1},
				    {"filename": os.path.join(lowercase__,	f"""{name}-train-00001-of-00010.arrow"""					), "skip": 0, "take": -1},
				    {"filename": os.path.join(lowercase__,	f"""{name}-train-00002-of-00010.arrow"""					), "skip": 0, "take": -1},
				    {"filename": os.path.join(lowercase__,	f"""{name}-train-00003-of-00010.arrow"""					), "skip": 0, "take": 3},
				]






@pytest.mark.parametrize('name, expected_exception',	[(None, TypeError), ('', ValueError)]					)
def 							lowercase__		(				lowerCamelCase,	lowerCamelCase					):
				_SCREAMING_SNAKE_CASE      :		Dict							=						[SplitInfo(name='train',	num_examples=100					)]
				_SCREAMING_SNAKE_CASE      :		Any							=						"train"
				_SCREAMING_SNAKE_CASE      :		List[str]							=						"arrow"
				_SCREAMING_SNAKE_CASE      :		Any							=						"prefix_path"
				with pytest.raises(lowercase__					):
								_SCREAMING_SNAKE_CASE      :		Optional[int]							=						make_file_instructions(lowercase__,	lowercase__,	lowercase__,	lowercase__,	lowercase__					)









"""simple docstring"""
import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


lowerCAmelCase__							= logging.get_logger(__name__)


class _lowerCAmelCase	(						__UpperCAmelCase					):







						def __init__(						self      ,							*lowerCAmelCase_      ,							**lowerCAmelCase_       )		->       None:
										warnings.warn(
										    'The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
										    ' use ViTImageProcessor instead.'      ,							lowerCAmelCase_      ,							)
										super().__init__(*lowerCAmelCase_      ,							**lowerCAmelCase_       )

