



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__   ):
				'''simple docstring'''







				def    _lowerCamelCase       (			self  ,			snake_case__  ,			snake_case__=False     ):

									'''simple docstring'''


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




class    _lowercase (lowerCAmelCase__   ):
				'''simple docstring'''







				def    _lowerCamelCase       (			self     ):

									'''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(snake_case__     )
									split_dict.add(snake_case__     )
									UpperCamelCase_			= DatasetInfo(splits=snake_case__     )

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

														UpperCamelCase_			= 'test[:33%]'
														UpperCamelCase_			= Dataset(**reader.read(snake_case__  ,			snake_case__  ,			snake_case__     )     )
														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(snake_case__  ,			snake_case__  ,			snake_case__     ) for instr in instructions]
																			UpperCamelCase_			= (Dataset(**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  ,			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  ,			snake_case__     )
																			self.assertEqual(str(test_dset.split     )  ,			"test[:33%]"     )
																			del train_dset, test_dset

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


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

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

														UpperCamelCase_			= 'train[:33%]'
														UpperCamelCase_			= Dataset(**reader.read(snake_case__  ,			snake_case__  ,			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    _lowerCamelCase       (			self     ):

									'''simple docstring'''


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

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

														UpperCamelCase_			= [
														    {'filename': os.path.join(snake_case__  ,			"train"     )},
														    {'filename': os.path.join(snake_case__  ,			"test"     ), 'skip': 10, 'take': 10},
														]
														UpperCamelCase_			= Dataset(**reader.read_files(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  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= arrow_file
					with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
										UpperCamelCase_			= ArrowReader.read_table(_lowerCAmelCase ,						in_memory=_lowerCAmelCase)
					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     (_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= arrow_file
					UpperCamelCase_			= ArrowReader("" ,						_lowerCAmelCase)
					with assert_arrow_memory_increases() if in_memory else assert_arrow_memory_doesnt_increase():
										UpperCamelCase_			= reader.read_files([{"filename": filename}] ,						in_memory=_lowerCAmelCase)
					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  _lowerCAmelCase     ():
					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(_lowerCAmelCase).to_spec() == spec_train_test

					UpperCamelCase_			= 'train[2:10]'
					assert ReadInstruction.from_spec(_lowerCAmelCase).to_spec() == spec_train_abs

					UpperCamelCase_			= 'train[15%:-20%]'
					assert ReadInstruction.from_spec(_lowerCAmelCase).to_spec() == spec_train_pct

					UpperCamelCase_			= 'train[:10%](closest)'
					assert ReadInstruction.from_spec(_lowerCAmelCase).to_spec() == "train[:10%]"

					UpperCamelCase_			= 'train[:10%](pct1_dropremainder)'
					assert ReadInstruction.from_spec(_lowerCAmelCase).to_spec() == spec_train_pct_rounding

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



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

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

					UpperCamelCase_			= [SplitInfo(name="train" ,						num_examples=1_00 ,						shard_lengths=[10] * 10)]
					UpperCamelCase_			= make_file_instructions(_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase)
					assert isinstance(_lowerCAmelCase ,						_lowerCAmelCase)
					assert file_instructions.num_examples == 33
					assert file_instructions.file_instructions == [
					    {"filename": os.path.join(_lowerCAmelCase ,						f"""{name}-train-00000-of-00010.arrow"""), "skip": 0, "take": -1},
					    {"filename": os.path.join(_lowerCAmelCase ,						f"""{name}-train-00001-of-00010.arrow"""), "skip": 0, "take": -1},
					    {"filename": os.path.join(_lowerCAmelCase ,						f"""{name}-train-00002-of-00010.arrow"""), "skip": 0, "take": -1},
					    {"filename": os.path.join(_lowerCAmelCase ,						f"""{name}-train-00003-of-00010.arrow"""), "skip": 0, "take": 3},
					]






@pytest.mark.parametrize("name, expected_exception" ,						[(None, TypeError), ("", ValueError)])
def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= [SplitInfo(name="train" ,						num_examples=1_00)]
					UpperCamelCase_			= 'train'
					UpperCamelCase_			= 'arrow'
					UpperCamelCase_			= 'prefix_path'
					with pytest.raises(_lowerCAmelCase):
										UpperCamelCase_			= make_file_instructions(_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase ,						_lowerCAmelCase)





'''simple docstring'''







from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__     : int				=   {"""configuration_bert_generation""": ["""BertGenerationConfig"""]}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : List[Any]				=   ["""BertGenerationTokenizer"""]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							SCREAMING_SNAKE_CASE__     : Optional[Any]				=   [
							    """BertGenerationDecoder""",
							    """BertGenerationEncoder""",
							    """BertGenerationPreTrainedModel""",
							    """load_tf_weights_in_bert_generation""",
							]


if TYPE_CHECKING:
							from .configuration_bert_generation import BertGenerationConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_bert_generation import BertGenerationTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bert_generation import (
														    BertGenerationDecoder,
														    BertGenerationEncoder,
														    BertGenerationPreTrainedModel,
														    load_tf_weights_in_bert_generation,
														)

else:
							import sys

							SCREAMING_SNAKE_CASE__     : Any				=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
