

'''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							( A				):







       def      snake_case				(							self     :	Dict  , __lowercase     :	int  , __lowercase     :	Optional[Any]=False ):







            """simple docstring"""







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






class 					lowerCAmelCase							( A				):







       def      snake_case				(							self     :	Tuple ):







            """simple docstring"""







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

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

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

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







       def      snake_case				(							self     :	str ):







            """simple docstring"""







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

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

                 __lowercase     						="train[:33%]"
                 __lowercase     						=Dataset(**reader.read(__lowercase  , __lowercase  , __lowercase ) )
                 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      snake_case				(							self     :	List[str] ):







            """simple docstring"""







            __lowercase     						=SplitInfo(name='train'  , num_examples=100 )
            __lowercase     						=SplitInfo(name='test'  , num_examples=100 )
            __lowercase     						=SplitDict()
            split_dict.add(__lowercase )
            split_dict.add(__lowercase )
            __lowercase     						=DatasetInfo(splits=__lowercase )

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

                 __lowercase     						=[
                     {"filename": os.path.join(__lowercase  , 'train' )},
                     {"filename": os.path.join(__lowercase  , 'test' ), "skip": 10, "take": 10},
                 ]
                 __lowercase     						=Dataset(**reader.read_files(__lowercase  , 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 			__UpperCamelCase							(		lowercase__  :					Optional[Any],   lowercase__  :					str,   lowercase__  :					int	):






     '''simple docstring'''





     __lowercase     						=arrow_file
     with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
          __lowercase     						=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 			__UpperCamelCase							(		lowercase__  :					List[Any],   lowercase__  :					Dict,   lowercase__  :					List[Any]	):






     '''simple docstring'''





     __lowercase     						=arrow_file
     __lowercase     						=ArrowReader('',   _UpperCamelCase	)
     with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
          __lowercase     						=reader.read_files([{'filename': filename}],   in_memory=_UpperCamelCase	)
     assert dataset_kwargs.keys() == {"arrow_table", "info", "split"}
     __lowercase     						=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 			__UpperCamelCase							(		):






     '''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     						="train+test"
     assert ReadInstruction.from_spec(_UpperCamelCase	).to_spec() == spec_train_test

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

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

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

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

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

def 			__UpperCamelCase							(		):






     '''simple docstring'''





     __lowercase     						="dummy"
     __lowercase     						=[SplitInfo(name='train',   num_examples=1_00	)]
     __lowercase     						="train[:33%]"
     __lowercase     						="arrow"
     __lowercase     						="prefix"

     __lowercase     						=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     						=[SplitInfo(name='train',   num_examples=1_00,   shard_lengths=[10] * 10	)]
     __lowercase     						=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 			__UpperCamelCase							(		lowercase__  :					Tuple,   lowercase__  :					Any	):






     '''simple docstring'''





     __lowercase     						=[SplitInfo(name='train',   num_examples=1_00	)]
     __lowercase     						="train"
     __lowercase     						="arrow"
     __lowercase     						="prefix_path"
     with pytest.raises(_UpperCamelCase	):
          __lowercase     						=make_file_instructions(_UpperCamelCase,   _UpperCamelCase,   _UpperCamelCase,   _UpperCamelCase,   _UpperCamelCase	)





'''simple docstring'''

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


UpperCAmelCase							=					{
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					[
           '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''VideoMAEForPreTraining''',
           '''VideoMAEModel''',
           '''VideoMAEPreTrainedModel''',
           '''VideoMAEForVideoClassification''',
       ]

try:
       if not is_vision_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       UpperCAmelCase							=					['''VideoMAEFeatureExtractor''']
       UpperCAmelCase							=					['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
       from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_videomae import (
                  VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  VideoMAEForPreTraining,
                  VideoMAEForVideoClassification,
                  VideoMAEModel,
                  VideoMAEPreTrainedModel,
              )

       try:
              if not is_vision_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .feature_extraction_videomae import VideoMAEFeatureExtractor
              from .image_processing_videomae import VideoMAEImageProcessor

else:
       import sys

       UpperCAmelCase							=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


