




import json
import os
import tempfile

import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import ArrayaD
from utils import generate_examples, get_duration


UpperCAmelCase__						:       int							=    (30, 487)
UpperCAmelCase__						:       Optional[int]							=    (36, 1024)
UpperCAmelCase__						:       Optional[Any]							=    (100, 100)
UpperCAmelCase__						:       Dict							=    100

UpperCAmelCase__						:       Tuple							=    datasets.Features(
    {'text': ArrayaD(SHAPE_TEST_1, dtype='float32'), 'image': ArrayaD(SHAPE_TEST_2, dtype='float32')}
)

UpperCAmelCase__		,     UpperCAmelCase__						:       Any							=    os.path.split(__file__)
UpperCAmelCase__						:       List[str]							=    os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace('.py', '.json'))


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		Union[str, Any]:





  """simple docstring"""





  with ArrowWriter(features=UpperCamelCase					,     path=os.path.join(UpperCamelCase					,     'beta.arrow'							)							) as writer:
    for key, record in dummy_data:
      _lowercase: List[str]						     =    my_features.encode_example(UpperCamelCase							)
      writer.write(UpperCamelCase							)
    _lowercase     ,					_lowercase: Tuple						     =    writer.finalize()


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		Optional[Any]:





  """simple docstring"""





  _lowercase: int						     =    datasets.Dataset.from_file(
      filename=os.path.join(UpperCamelCase					,     'beta.arrow'							)					,     info=datasets.DatasetInfo(features=UpperCamelCase							)							)
  for _ in dataset:
    pass


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		str:





  """simple docstring"""





  _lowercase: int						     =    datasets.Dataset.from_file(
      filename=os.path.join(UpperCamelCase					,     'beta.arrow'							)					,     info=datasets.DatasetInfo(features=UpperCamelCase							)							)
  dataset.set_format('numpy'							)
  for _ in dataset:
    pass


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		Optional[Any]:





  """simple docstring"""





  _lowercase: int						     =    10
  _lowercase: Dict						     =    datasets.Dataset.from_file(
      filename=os.path.join(UpperCamelCase					,     'beta.arrow'							)					,     info=datasets.DatasetInfo(features=UpperCamelCase							)							)
  for i in range(0					,     len(UpperCamelCase							)					,     UpperCamelCase							):
    _lowercase: Tuple						     =    dataset[i : i + batch_size]


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		int:





  """simple docstring"""





  _lowercase: Optional[Any]						     =    10
  _lowercase: List[Any]						     =    datasets.Dataset.from_file(
      filename=os.path.join(UpperCamelCase					,     'beta.arrow'							)					,     info=datasets.DatasetInfo(features=UpperCamelCase							)							)
  dataset.set_format('numpy'							)
  for i in range(0					,     len(UpperCamelCase							)					,     UpperCamelCase							):
    _lowercase: List[str]						     =    dataset[i : i + batch_size]


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		Optional[int]:





  """simple docstring"""





  _lowercase: List[str]						     =    datasets.Dataset.from_file(
      filename=os.path.join(UpperCamelCase					,     'beta.arrow'							)					,     info=datasets.DatasetInfo(features=UpperCamelCase							)							)
  for col in feats:
    _lowercase: Union[str, Any]						     =    dataset[col]


@get_duration
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		List[str]:





  """simple docstring"""





  _lowercase: int						     =    datasets.Dataset.from_file(
      filename=os.path.join(UpperCamelCase					,     'beta.arrow'							)					,     info=datasets.DatasetInfo(features=UpperCamelCase							)							)
  dataset.set_format('numpy'							)
  for col in feats:
    _lowercase: str						     =    dataset[col]


def 		_lowerCamelCase				(					)			->		int:





  """simple docstring"""





  _lowercase: int						     =    {}
  _lowercase: Any						     =    (
      read_unformated,
      read_formatted_as_numpy,
      read_batch_unformated,
      read_batch_formatted_as_numpy,
      read_col_unformated,
      read_col_formatted_as_numpy,
  )
  with tempfile.TemporaryDirectory() as tmp_dir:
    _lowercase: str						     =    datasets.Features({'image': ArrayaD(UpperCamelCase					,     dtype='float32'							)}							)
    _lowercase: int						     =    generate_examples(features=UpperCamelCase					,     num_examples=UpperCamelCase							)
    _lowercase: Optional[Any]						     =    write(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
    for read_func in read_functions:
      _lowercase: Optional[Any]						     =    read_func(UpperCamelCase					,     UpperCamelCase							)

  with tempfile.TemporaryDirectory() as tmp_dir:
    # don't use fixed length for fair comparison
    # feats = datasets.Features(
    #     {"image": datasets.Sequence(datasets.Sequence(datasets.Value("float32"), SPEED_TEST_SHAPE[1]), SPEED_TEST_SHAPE[0])}
    # )
    _lowercase: Dict						     =    datasets.Features({'image': datasets.Sequence(datasets.Sequence(datasets.Value('float32'							)							)							)}							)
    _lowercase: str						     =    generate_examples(
        features=UpperCamelCase					,     num_examples=UpperCamelCase					,     seq_shapes={'image': SPEED_TEST_SHAPE}							)
    _lowercase: List[str]						     =    write(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
    for read_func in read_functions:
      _lowercase: List[str]						     =    read_func(UpperCamelCase					,     UpperCamelCase							)

  with tempfile.TemporaryDirectory() as tmp_dir:
    # don't use fixed length for fair comparison
    # feats = datasets.Features(
    #     {"image": datasets.Sequence(datasets.Value("float32"), SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1])}
    # )
    _lowercase: str						     =    datasets.Features({'image': datasets.Sequence(datasets.Value('float32'							)							)}							)
    _lowercase: List[Any]						     =    generate_examples(
        features=UpperCamelCase					,     num_examples=UpperCamelCase					,     seq_shapes={'image': [SPEED_TEST_SHAPE[0] * SPEED_TEST_SHAPE[1]]}					,     )
    _lowercase: List[str]						     =    write(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
    for read_func in read_functions:
      _lowercase: Optional[Any]						     =    read_func(UpperCamelCase					,     UpperCamelCase							)

  with open(UpperCamelCase					,     'wb'							) as f:
    f.write(json.dumps(UpperCamelCase							).encode('utf-8'							)							)


if __name__ == "__main__":  # useful to run the profiler
   benchmark_array_xd()






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						(			A   ):






   def  _a						(	self   :       List[str]						,					UpperCamelCase_   :       str						,					UpperCamelCase_   :       Optional[Any]=False     )->			List[str]:
     _lowercase     ,					_lowercase     ,					_lowercase: Dict						     =    (
         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(UpperCamelCase_     )						,					'wb'     ).close()
     _lowercase: int						     =    pa.Table.from_pydict({'filename': [Path(UpperCamelCase_     ).name] * 1_00}     )
     if take == -1:
       _lowercase: int						     =    len(UpperCamelCase_     ) - skip
     if skip is not None and take is not None:
       _lowercase: Any						     =    pa_table.slice(UpperCamelCase_						,					UpperCamelCase_     )
     return pa_table

class      UpperCAmelCase						(			A   ):






   def  _a						(	self   :       Any     )->			Dict:
     _lowercase: str						     =    'my_name'
     _lowercase: Optional[int]						     =    SplitInfo(name='train'						,					num_examples=1_00     )
     _lowercase: Dict						     =    SplitInfo(name='test'						,					num_examples=1_00     )
     _lowercase: Any						     =    [train_info, test_info]
     _lowercase: Any						     =    SplitDict()
     split_dict.add(UpperCamelCase_     )
     split_dict.add(UpperCamelCase_     )
     _lowercase: Tuple						     =    DatasetInfo(splits=UpperCamelCase_     )

     with tempfile.TemporaryDirectory() as tmp_dir:
       _lowercase: List[str]						     =    ReaderTest(UpperCamelCase_						,					UpperCamelCase_     )

       _lowercase: Dict						     =    'test[:33%]'
       _lowercase: Optional[Any]						     =    Dataset(**reader.read(UpperCamelCase_						,					UpperCamelCase_						,					UpperCamelCase_     )     )
       self.assertEqual(dset['filename'][0]						,					f'{name}-test'     )
       self.assertEqual(dset.num_rows						,					33     )
       self.assertEqual(dset.num_columns						,					1     )

       _lowercase: Tuple						     =    ['train', 'test[:33%]']
       _lowercase: Union[str, Any]						     =    [Split.TRAIN, ReadInstruction.from_spec('test[:33%]'     )]
       for instructions in [instructionsa, instructionsa]:
         _lowercase: int						     =    [reader.read(UpperCamelCase_						,					UpperCamelCase_						,					UpperCamelCase_     ) for instr in instructions]
         _lowercase     ,					_lowercase: Dict						     =    (Dataset(**UpperCamelCase_     ) for dataset_kwargs in datasets_kwargs)
         self.assertEqual(train_dset['filename'][0]						,					f'{name}-train'     )
         self.assertEqual(train_dset.num_rows						,					1_00     )
         self.assertEqual(train_dset.num_columns						,					1     )
         self.assertIsInstance(train_dset.split						,					UpperCamelCase_     )
         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						,					UpperCamelCase_     )
         self.assertEqual(str(test_dset.split     )						,					'test[:33%]'     )
         del train_dset, test_dset






   def  _a						(	self   :       Any     )->			List[str]:
     _lowercase: int						     =    'my_name'
     _lowercase: List[str]						     =    SplitInfo(name='train'						,					num_examples=10_00						,					shard_lengths=[1_00] * 10     )
     _lowercase: Optional[Any]						     =    [train_info]
     _lowercase: Optional[int]						     =    SplitDict()
     split_dict.add(UpperCamelCase_     )
     _lowercase: Optional[Any]						     =    DatasetInfo(splits=UpperCamelCase_     )

     with tempfile.TemporaryDirectory() as tmp_dir:
       _lowercase: Optional[int]						     =    ReaderTest(UpperCamelCase_						,					UpperCamelCase_     )

       _lowercase: Any						     =    'train[:33%]'
       _lowercase: List[Any]						     =    Dataset(**reader.read(UpperCamelCase_						,					UpperCamelCase_						,					UpperCamelCase_     )     )
       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_30     )
       self.assertEqual(dset.num_columns						,					1     )






   def  _a						(	self   :       List[Any]     )->			Dict:
     _lowercase: Any						     =    SplitInfo(name='train'						,					num_examples=1_00     )
     _lowercase: List[Any]						     =    SplitInfo(name='test'						,					num_examples=1_00     )
     _lowercase: List[Any]						     =    SplitDict()
     split_dict.add(UpperCamelCase_     )
     split_dict.add(UpperCamelCase_     )
     _lowercase: Union[str, Any]						     =    DatasetInfo(splits=UpperCamelCase_     )

     with tempfile.TemporaryDirectory() as tmp_dir:
       _lowercase: Dict						     =    ReaderTest(UpperCamelCase_						,					UpperCamelCase_     )

       _lowercase: List[Any]						     =    [
           {'filename': os.path.join(UpperCamelCase_						,					'train'     )},
           {'filename': os.path.join(UpperCamelCase_						,					'test'     ), 'skip': 10, 'take': 10},
       ]
       _lowercase: Tuple						     =    Dataset(**reader.read_files(UpperCamelCase_						,					original_instructions='train+test[10:20]'     )     )
       self.assertEqual(dset.num_rows						,					1_10     )
       self.assertEqual(dset.num_columns						,					1     )
       del dset


@pytest.mark.parametrize('in_memory'					,     [False, True]							)
def 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		Union[str, Any]:





  """simple docstring"""





  _lowercase: Optional[Any]						     =    arrow_file
  with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
    _lowercase: List[Any]						     =    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 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)			->		List[Any]:





  """simple docstring"""





  _lowercase: Any						     =    arrow_file
  _lowercase: Union[str, Any]						     =    ArrowReader(''					,     UpperCamelCase							)
  with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
    _lowercase: Tuple						     =    reader.read_files([{'filename': filename}]					,     in_memory=UpperCamelCase							)
  assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
  _lowercase: Any						     =    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				(					)			->		int:





  """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%]"

  _lowercase: List[str]						     =    'train+test'
  assert ReadInstruction.from_spec(UpperCamelCase							).to_spec() == spec_train_test

  _lowercase: Union[str, Any]						     =    'train[2:10]'
  assert ReadInstruction.from_spec(UpperCamelCase							).to_spec() == spec_train_abs

  _lowercase: Any						     =    'train[15%:-20%]'
  assert ReadInstruction.from_spec(UpperCamelCase							).to_spec() == spec_train_pct

  _lowercase: List[Any]						     =    'train[:10%](closest)'
  assert ReadInstruction.from_spec(UpperCamelCase							).to_spec() == "train[:10%]"

  _lowercase: int						     =    'train[:10%](pct1_dropremainder)'
  assert ReadInstruction.from_spec(UpperCamelCase							).to_spec() == spec_train_pct_rounding

  _lowercase: int						     =    'train[:10%](pct1_dropremainder)+test[-10%:](pct1_dropremainder)'
  assert ReadInstruction.from_spec(UpperCamelCase							).to_spec() == spec_train_test_pct_rounding


def 		_lowerCamelCase				(					)			->		Union[str, Any]:





  """simple docstring"""





  _lowercase: int						     =    'dummy'
  _lowercase: Any						     =    [SplitInfo(name='train'					,     num_examples=100							)]
  _lowercase: Any						     =    'train[:33%]'
  _lowercase: Optional[int]						     =    'arrow'
  _lowercase: Optional[int]						     =    'prefix'

  _lowercase: Optional[int]						     =    make_file_instructions(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
  assert isinstance(UpperCamelCase					,     UpperCamelCase							)
  assert file_instructions.num_examples == 33
  assert file_instructions.file_instructions == [
      {"filename": os.path.join(UpperCamelCase					,     F'{name}-train.arrow'							), "skip": 0, "take": 33}
  ]

  _lowercase: int						     =    [SplitInfo(name='train'					,     num_examples=100					,     shard_lengths=[10] * 10							)]
  _lowercase: Dict						     =    make_file_instructions(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
  assert isinstance(UpperCamelCase					,     UpperCamelCase							)
  assert file_instructions.num_examples == 33
  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 		_lowerCamelCase				(					UpperCamelCase					,     UpperCamelCase							)			->		Tuple:





  """simple docstring"""





  _lowercase: List[str]						     =    [SplitInfo(name='train'					,     num_examples=100							)]
  _lowercase: List[Any]						     =    'train'
  _lowercase: List[str]						     =    'arrow'
  _lowercase: Optional[Any]						     =    'prefix_path'
  with pytest.raises(UpperCamelCase							):
    _lowercase: List[str]						     =    make_file_instructions(UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase					,     UpperCamelCase							)
