




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			(	__UpperCAmelCase			):







			def UpperCamelCase      (	self   :      Union[str, Any]   ,   snake_case__   :      Optional[int]   ,   snake_case__   :      List[str]=False				):




									"""simple docstring"""


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






class    __lowerCAmelCase			(	__UpperCAmelCase			):







			def UpperCamelCase      (	self   :      Any				):




									"""simple docstring"""


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

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

															_UpperCAmelCase													=					"test[:33%]"
															_UpperCAmelCase													=					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													=					["train", "test[:33%]"]
															_UpperCAmelCase													=					[Split.TRAIN, ReadInstruction.from_spec("test[:33%]"				)]
															for instructions in [instructionsa, instructionsa]:
																					_UpperCAmelCase													=					[reader.read(lowerCamelCase__   ,   lowerCamelCase__   ,   lowerCamelCase__				) for instr in instructions]
																					_UpperCAmelCase							,			_UpperCAmelCase													=					(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   :      Dict				):




									"""simple docstring"""


									_UpperCAmelCase													=					"my_name"
									_UpperCAmelCase													=					SplitInfo(name="train"   ,   num_examples=1_000   ,   shard_lengths=[100] * 10				)
									_UpperCAmelCase													=					[train_info]
									_UpperCAmelCase													=					SplitDict()
									split_dict.add(lowerCamelCase__				)
									_UpperCAmelCase													=					DatasetInfo(splits=lowerCamelCase__				)

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

															_UpperCAmelCase													=					"train[:33%]"
															_UpperCAmelCase													=					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   :      List[Any]				):




									"""simple docstring"""


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

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

															_UpperCAmelCase													=					[
															    {"filename": os.path.join(lowerCamelCase__   ,   "train"				)},
															    {"filename": os.path.join(lowerCamelCase__   ,   "test"				), "skip": 10, "take": 10},
															]
															_UpperCAmelCase													=					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 							__SCREAMING_SNAKE_CASE  (      snake_case_     ,   snake_case_     ,   snake_case_						):

						'''simple docstring'''


						_UpperCAmelCase													=					arrow_file
						with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
												_UpperCAmelCase													=					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 							__SCREAMING_SNAKE_CASE  (      snake_case_     ,   snake_case_     ,   snake_case_						):

						'''simple docstring'''


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

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

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

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

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

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

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


def 							__SCREAMING_SNAKE_CASE  (      ):

						'''simple docstring'''


						_UpperCAmelCase													=					"dummy"
						_UpperCAmelCase													=					[SplitInfo(name="train"     ,   num_examples=100						)]
						_UpperCAmelCase													=					"train[:33%]"
						_UpperCAmelCase													=					"arrow"
						_UpperCAmelCase													=					"prefix"

						_UpperCAmelCase													=					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}
						]

						_UpperCAmelCase													=					[SplitInfo(name="train"     ,   num_examples=100     ,   shard_lengths=[10] * 10						)]
						_UpperCAmelCase													=					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 							__SCREAMING_SNAKE_CASE  (      snake_case_     ,   snake_case_						):

						'''simple docstring'''


						_UpperCAmelCase													=					[SplitInfo(name="train"     ,   num_examples=100						)]
						_UpperCAmelCase													=					"train"
						_UpperCAmelCase													=					"arrow"
						_UpperCAmelCase													=					"prefix_path"
						with pytest.raises(lowercase__						):
												_UpperCAmelCase													=					make_file_instructions(lowercase__     ,   lowercase__     ,   lowercase__     ,   lowercase__     ,   lowercase__						)












from typing import TYPE_CHECKING

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


lowercase_     :    int      =			{
    'configuration_videomae': ['VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VideoMAEConfig'],
}

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

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_     :    Any      =			['VideoMAEFeatureExtractor']
				lowercase_     :    Dict      =			['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

				lowercase_     :    int      =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




