


import os
from typing import BinaryIO, Optional, Union

import numpy as np
import pyarrow.parquet as pq

from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MODULES
from ..packaged_modules.parquet.parquet import Parquet
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader




def     __SCREAMING_SNAKE_CASE							(       lowercase_      )		->     Optional[int]:




						'''simple docstring'''







						__UpperCAmelCase			:							List[Any]	    =	np.inf

						def set_batch_size(lowercase_      ) -> None:
												nonlocal batch_size
												if isinstance(lowercase_      ,       lowercase_      ):
																		__UpperCAmelCase			:							Optional[int]	    =	min(lowercase_      ,       config.PARQUET_ROW_GROUP_SIZE_FOR_IMAGE_DATASETS      )
												elif isinstance(lowercase_      ,       lowercase_      ):
																		__UpperCAmelCase			:							Dict	    =	min(lowercase_      ,       config.PARQUET_ROW_GROUP_SIZE_FOR_AUDIO_DATASETS      )
												elif isinstance(lowercase_      ,       lowercase_      ) and feature.dtype == "binary":
																		__UpperCAmelCase			:							List[Any]	    =	min(lowercase_      ,       config.PARQUET_ROW_GROUP_SIZE_FOR_BINARY_DATASETS      )

						_visit(lowercase_      ,       lowercase_      )

						return None if batch_size is np.inf else batch_size




class 							lowerCamelCase   (  _UpperCamelCase ):


	def __init__(    self				,     lowercase__				,     lowercase__ = None				,     lowercase__ = None				,     lowercase__ = None				,     lowercase__ = False				,     lowercase__ = False				,     lowercase__ = None				,     **lowercase__				,     ):
							super().__init__(
							    lowercase__				,     split=lowercase__				,     features=lowercase__				,     cache_dir=lowercase__				,     keep_in_memory=lowercase__				,     streaming=lowercase__				,     num_proc=lowercase__				,     **lowercase__				,     )
							__UpperCAmelCase			:							int	    =	path_or_paths if isinstance(lowercase__				,     lowercase__) else {self.split: path_or_paths}
							__UpperCAmelCase			:							Optional[int]	    =	_PACKAGED_DATASETS_MODULES['''parquet'''][1]
							__UpperCAmelCase			:							Optional[Any]	    =	Parquet(
							    cache_dir=lowercase__				,     data_files=lowercase__				,     features=lowercase__				,     hash=lowercase__				,     **lowercase__				,     )


	def  A(    self):
							# Build iterable dataset
							if self.streaming:
													__UpperCAmelCase			:							int	    =	self.builder.as_streaming_dataset(split=self.split)
							# Build regular (map-style) dataset
							else:
													__UpperCAmelCase			:							Optional[int]	    =	None
													__UpperCAmelCase			:							List[Any]	    =	None
													__UpperCAmelCase			:							Tuple	    =	None
													__UpperCAmelCase			:							Union[str, Any]	    =	None

													self.builder.download_and_prepare(
													    download_config=lowercase__				,     download_mode=lowercase__				,     verification_mode=lowercase__				,     base_path=lowercase__				,     num_proc=self.num_proc				,     )
													__UpperCAmelCase			:							Optional[Any]	    =	self.builder.as_dataset(
													    split=self.split				,     verification_mode=lowercase__				,     in_memory=self.keep_in_memory)
							return dataset






class 							lowerCamelCase   :


	def __init__(    self				,     lowercase__				,     lowercase__				,     lowercase__ = None				,     **lowercase__				,     ):
							__UpperCAmelCase			:							Optional[int]	    =	dataset
							__UpperCAmelCase			:							str	    =	path_or_buf
							__UpperCAmelCase			:							int	    =	batch_size or get_writer_batch_size(dataset.features)
							__UpperCAmelCase			:							List[str]	    =	parquet_writer_kwargs


	def  A(    self):
							__UpperCAmelCase			:							Dict	    =	self.batch_size if self.batch_size else config.DEFAULT_MAX_BATCH_SIZE

							if isinstance(self.path_or_buf				,     (str, bytes, os.PathLike)):
													with open(self.path_or_buf				,     '''wb+''') as buffer:
																			__UpperCAmelCase			:							int	    =	self._write(file_obj=lowercase__				,     batch_size=lowercase__				,     **self.parquet_writer_kwargs)
							else:
													__UpperCAmelCase			:							str	    =	self._write(file_obj=self.path_or_buf				,     batch_size=lowercase__				,     **self.parquet_writer_kwargs)
							return written


	def  A(    self				,     lowercase__				,     lowercase__				,     **lowercase__):
							__UpperCAmelCase			:							Tuple	    =	0
							__UpperCAmelCase			:							str	    =	parquet_writer_kwargs.pop('''path_or_buf'''				,     lowercase__)
							__UpperCAmelCase			:							Tuple	    =	self.dataset.features.arrow_schema

							__UpperCAmelCase			:							Optional[Any]	    =	pq.ParquetWriter(lowercase__				,     schema=lowercase__				,     **lowercase__)

							for offset in logging.tqdm(
							    range(0				,     len(self.dataset)				,     lowercase__)				,     unit='''ba'''				,     disable=not logging.is_progress_bar_enabled()				,     desc='''Creating parquet from Arrow format'''				,     ):
													__UpperCAmelCase			:							Optional[Any]	    =	query_table(
													    table=self.dataset._data				,     key=slice(lowercase__				,     offset + batch_size)				,     indices=self.dataset._indices if self.dataset._indices is not None else None				,     )
													writer.write_table(lowercase__)
													written += batch.nbytes
							writer.close()
							return written





import unittest

from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase       		=    get_tests_dir("""fixtures/test_sentencepiece.model""")




@require_sentencepiece
@require_tokenizers
class 							lowerCamelCase   (  _UpperCamelCase							,						unittest.TestCase ):
	_lowerCAmelCase     :		Union[str, Any]										=						XLNetTokenizer
	_lowerCAmelCase     :		int										=						XLNetTokenizerFast
	_lowerCAmelCase     :		Optional[Any]										=						True
	_lowerCAmelCase     :		Optional[Any]										=						True


	def  A(    self):
							super().setUp()

							# We have a SentencePiece fixture for testing
							__UpperCAmelCase			:							Optional[Any]	    =	XLNetTokenizer(lowercase__				,     keep_accents=lowercase__)
							tokenizer.sanitize_special_tokens()
							tokenizer.save_pretrained(self.tmpdirname)


	def  A(    self):
							__UpperCAmelCase			:							Tuple	    =	'''<s>'''
							__UpperCAmelCase			:							List[str]	    =	1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase__)				,     lowercase__)
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase__)				,     lowercase__)


	def  A(    self):
							__UpperCAmelCase			:							Union[str, Any]	    =	list(self.get_tokenizer().get_vocab().keys())

							self.assertEqual(vocab_keys[0]				,     '''<unk>''')
							self.assertEqual(vocab_keys[1]				,     '''<s>''')
							self.assertEqual(vocab_keys[-1]				,     '''<eod>''')
							self.assertEqual(len(lowercase__)				,     1_0_0_6)


	def  A(    self):
							self.assertEqual(self.get_tokenizer().vocab_size				,     1_0_0_0)


	def  A(    self):
							__UpperCAmelCase			:							List[str]	    =	XLNetTokenizer(lowercase__				,     keep_accents=lowercase__)

							__UpperCAmelCase			:							Optional[Any]	    =	tokenizer.tokenize('''This is a test''')
							self.assertListEqual(lowercase__				,     ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est'''])

							self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__)				,     [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2])

							__UpperCAmelCase			:							Tuple	    =	tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
							self.assertListEqual(
							    lowercase__				,     [
							        SPIECE_UNDERLINE + '''I''',
							        SPIECE_UNDERLINE + '''was''',
							        SPIECE_UNDERLINE + '''b''',
							        '''or''',
							        '''n''',
							        SPIECE_UNDERLINE + '''in''',
							        SPIECE_UNDERLINE + '''''',
							        '''9''',
							        '''2''',
							        '''0''',
							        '''0''',
							        '''0''',
							        ''',''',
							        SPIECE_UNDERLINE + '''and''',
							        SPIECE_UNDERLINE + '''this''',
							        SPIECE_UNDERLINE + '''is''',
							        SPIECE_UNDERLINE + '''f''',
							        '''al''',
							        '''s''',
							        '''é''',
							        '''.''',
							    ]				,     )
							__UpperCAmelCase			:							Union[str, Any]	    =	tokenizer.convert_tokens_to_ids(lowercase__)
							self.assertListEqual(lowercase__				,     [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4])

							__UpperCAmelCase			:							int	    =	tokenizer.convert_ids_to_tokens(lowercase__)
							self.assertListEqual(
							    lowercase__				,     [
							        SPIECE_UNDERLINE + '''I''',
							        SPIECE_UNDERLINE + '''was''',
							        SPIECE_UNDERLINE + '''b''',
							        '''or''',
							        '''n''',
							        SPIECE_UNDERLINE + '''in''',
							        SPIECE_UNDERLINE + '''''',
							        '''<unk>''',
							        '''2''',
							        '''0''',
							        '''0''',
							        '''0''',
							        ''',''',
							        SPIECE_UNDERLINE + '''and''',
							        SPIECE_UNDERLINE + '''this''',
							        SPIECE_UNDERLINE + '''is''',
							        SPIECE_UNDERLINE + '''f''',
							        '''al''',
							        '''s''',
							        '''<unk>''',
							        '''.''',
							    ]				,     )


	def  A(    self):
							__UpperCAmelCase			:							str	    =	XLNetTokenizer(lowercase__				,     do_lower_case=lowercase__)
							__UpperCAmelCase			:							int	    =	tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
							self.assertListEqual(
							    lowercase__				,     [
							        SPIECE_UNDERLINE + '''''',
							        '''i''',
							        SPIECE_UNDERLINE + '''was''',
							        SPIECE_UNDERLINE + '''b''',
							        '''or''',
							        '''n''',
							        SPIECE_UNDERLINE + '''in''',
							        SPIECE_UNDERLINE + '''''',
							        '''9''',
							        '''2''',
							        '''0''',
							        '''0''',
							        '''0''',
							        ''',''',
							        SPIECE_UNDERLINE + '''and''',
							        SPIECE_UNDERLINE + '''this''',
							        SPIECE_UNDERLINE + '''is''',
							        SPIECE_UNDERLINE + '''f''',
							        '''al''',
							        '''se''',
							        '''.''',
							    ]				,     )
							self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''')				,     ['''▁he''', '''ll''', '''o'''])


	def  A(    self):
							__UpperCAmelCase			:							Optional[Any]	    =	XLNetTokenizer(lowercase__				,     do_lower_case=lowercase__)
							__UpperCAmelCase			:							Union[str, Any]	    =	tokenizer.tokenize('''I was born in 92000, and this is falsé.''')
							self.assertListEqual(
							    lowercase__				,     [
							        SPIECE_UNDERLINE + '''I''',
							        SPIECE_UNDERLINE + '''was''',
							        SPIECE_UNDERLINE + '''b''',
							        '''or''',
							        '''n''',
							        SPIECE_UNDERLINE + '''in''',
							        SPIECE_UNDERLINE + '''''',
							        '''9''',
							        '''2''',
							        '''0''',
							        '''0''',
							        '''0''',
							        ''',''',
							        SPIECE_UNDERLINE + '''and''',
							        SPIECE_UNDERLINE + '''this''',
							        SPIECE_UNDERLINE + '''is''',
							        SPIECE_UNDERLINE + '''f''',
							        '''al''',
							        '''se''',
							        '''.''',
							    ]				,     )


	@slow
	def  A(    self):
							__UpperCAmelCase			:							Tuple	    =	XLNetTokenizer.from_pretrained('''xlnet-base-cased''')

							__UpperCAmelCase			:							Optional[int]	    =	tokenizer.encode('''sequence builders'''				,     add_special_tokens=lowercase__)
							__UpperCAmelCase			:							Optional[int]	    =	tokenizer.encode('''multi-sequence build'''				,     add_special_tokens=lowercase__)

							__UpperCAmelCase			:							Union[str, Any]	    =	tokenizer.build_inputs_with_special_tokens(lowercase__)
							__UpperCAmelCase			:							Optional[Any]	    =	tokenizer.build_inputs_with_special_tokens(lowercase__				,     lowercase__)

							assert encoded_sentence == text + [4, 3]
							assert encoded_pair == text + [4] + text_a + [4, 3]


	@slow
	def  A(    self):
							# fmt: off
							__UpperCAmelCase			:							Optional[Any]	    =	{'''input_ids''': [[1_7, 2_1_4_4_2, 2_7_0, 1_7, 1_0, 1_4_6_4_5, 3_1_8, 3_4, 1_7, 4_5_4_6, 3_1_4_5, 7_8_7, 1_3, 7_7_5_2, 2_2_0_1_8, 2_3, 2_1, 1_7, 4_5_4_6, 3_1_4_5, 7_8_7, 1_3, 3_3_5_2, 1_4_4_3_1, 1_3, 5_5_0_0, 1_1, 1_1_7_6, 5_8_0, 1_3, 1_6_8_1_9, 4_7_9_7, 2_3, 1_7, 1_0, 1_7_1_3_5, 6_5_8, 1_9, 4_5_7, 7_9_3_2, 1_3, 1_8_4, 1_9, 3_1_5_4, 1_7_1_3_5, 6_4_6_8, 1_9, 1_4_0_4, 1_2_2_6_9, 1_9, 4_2_2_9, 5_3_5_6, 1_6_2_6_4, 4_6, 1_9, 1_7, 2_0_5_4_5, 1_0_3_9_5, 9, 9, 9, 1_1, 2_8, 6_4_2_1, 9_5_3_1, 2_0_7_2_9, 1_7, 1_0, 3_5_3, 1_7_0_2_2, 1_1, 2_1, 6_4_2_1, 9_5_3_1, 1_6_9_4_9, 1_7, 1_0, 1_1_5_0_9, 7_5_3, 1_1, 3_3, 9_5, 2_4_2_1, 7_3_8_5, 9_5_6, 1_4_4_3_1, 2_6_2_6, 2_5, 8_4_2, 7_3_8_5, 4_8_3_6, 2_1, 1_4_2_9, 2_2_7_2, 9_8_5_5, 3_1_2_0, 1_6_1, 2_4_7_3_8, 1_9, 1_3_2_0_3, 6_5_8, 2_1_8, 7_8_7, 2_1, 4_3_0, 1_8_4_8_2, 8_4_7, 2_6_3_7, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3_2_2, 2_2_1_7_8, 2_7, 1_0_6_4, 2_2, 9_5_6, 1_3, 1_1_1_0_1, 1_4_2_9, 5_8_5_4, 2_4_3_1_3, 1_8_9_5_3, 4_0, 4_2_2, 2_4_3_6_6, 6_8, 1_7_5_8, 3_7, 1_0_4_8_3, 1_4_2_5_7, 3_1, 2_0_7, 2_6_3, 2_1, 2_0_3, 3_7_7_3, 2_5, 7_1, 9_7_3_5, 9, 4, 3], [5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 3_2, 2_0_4_9, 3_4_4_2, 1_7, 1_3_8_9_4, 3_3_8_0, 2_3, 9_5, 1_8, 1_7_6_3_4, 2_2_8_8, 9, 4, 3]], '''token_type_ids''': [[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2], [3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2]], '''attention_mask''': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=lowercase__				,     model_name='''xlnet-base-cased'''				,     revision='''c841166438c31ec7ca9a106dee7bb312b73ae511'''				,     )

