



import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


UpperCAmelCase :				Optional[Any]							=logging.get_logger(__name__)

UpperCAmelCase :				Optional[Any]							={"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

UpperCAmelCase :				Union[str, Any]							={
    """vocab_file""": {
        """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt""",
    },
    """tokenizer_file""": {
        """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json""",
    },
}

UpperCAmelCase :				Any							={
    """microsoft/mpnet-base""": 512,
}

UpperCAmelCase :				Optional[int]							={
    """microsoft/mpnet-base""": {"""do_lower_case""": True},
}


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







				lowercase__     =    VOCAB_FILES_NAMES
				lowercase__     =    PRETRAINED_VOCAB_FILES_MAP
				lowercase__     =    PRETRAINED_INIT_CONFIGURATION
				lowercase__     =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowercase__     =    MPNetTokenizer
				lowercase__     =    ["""input_ids""", """attention_mask"""]

				def __init__(			self  ,			snake_case__=None  ,			snake_case__=None  ,			snake_case__=True  ,			snake_case__="<s>"  ,			snake_case__="</s>"  ,			snake_case__="</s>"  ,			snake_case__="<s>"  ,			snake_case__="[UNK]"  ,			snake_case__="<pad>"  ,			snake_case__="<mask>"  ,			snake_case__=True  ,			snake_case__=None  ,			**snake_case__  ,			):

									'''simple docstring'''


									super().__init__(
									    snake_case__  ,			tokenizer_file=snake_case__  ,			do_lower_case=snake_case__  ,			bos_token=snake_case__  ,			eos_token=snake_case__  ,			sep_token=snake_case__  ,			cls_token=snake_case__  ,			unk_token=snake_case__  ,			pad_token=snake_case__  ,			mask_token=snake_case__  ,			tokenize_chinese_chars=snake_case__  ,			strip_accents=snake_case__  ,			**snake_case__  ,			)

									UpperCamelCase_			= json.loads(self.backend_tokenizer.normalizer.__getstate__()     )
									if (
									    pre_tok_state.get("lowercase"  ,			snake_case__     ) != do_lower_case
									    or pre_tok_state.get("strip_accents"  ,			snake_case__     ) != strip_accents
									):
														UpperCamelCase_			= getattr(snake_case__  ,			pre_tok_state.pop("type"     )     )
														UpperCamelCase_			= do_lower_case
														UpperCamelCase_			= strip_accents
														UpperCamelCase_			= pre_tok_class(**snake_case__     )

									UpperCamelCase_			= do_lower_case

				@property
				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									if self._mask_token is None:
														if self.verbose:
																			logger.error("Using mask_token, but it is not set yet."     )
														return None
									return str(self._mask_token     )

				@mask_token.setter
				def    _lowerCamelCase       (			self  ,			snake_case__     ):

									'''simple docstring'''


									UpperCamelCase_			= AddedToken(snake_case__  ,			lstrip=snake_case__  ,			rstrip=snake_case__     ) if isinstance(snake_case__  ,			snake_case__     ) else value
									UpperCamelCase_			= value

				def    _lowerCamelCase       (			self  ,			snake_case__  ,			snake_case__=None     ):

									'''simple docstring'''


									UpperCamelCase_			= [self.bos_token_id] + token_ids_a + [self.eos_token_id]
									if token_ids_a is None:
														return output

									return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]

				def    _lowerCamelCase       (			self  ,			snake_case__  ,			snake_case__ = None     ):

									'''simple docstring'''


									UpperCamelCase_			= [self.sep_token_id]
									UpperCamelCase_			= [self.cls_token_id]

									if token_ids_a is None:
														return len(cls + token_ids_a + sep     ) * [0]
									return len(cls + token_ids_a + sep + sep + token_ids_a + sep     ) * [0]

				def    _lowerCamelCase       (			self  ,			snake_case__  ,			snake_case__ = None     ):

									'''simple docstring'''


									UpperCamelCase_			= self._tokenizer.model.save(snake_case__  ,			name=snake_case__     )
									return tuple(snake_case__     )





import json
import os
from dataclasses import dataclass

import numpy as np
import pyarrow as pa

import datasets
from utils import get_duration


UpperCAmelCase :				Any							=1000_0000_0000
UpperCAmelCase :				Any							=1_0000

UpperCAmelCase			,			UpperCAmelCase :				Tuple							=os.path.split(__file__)
UpperCAmelCase :				Tuple							=os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))



def  _lowerCAmelCase     (_lowerCAmelCase ,						_lowerCAmelCase):
					UpperCamelCase_			= pa.Table.from_pydict({"col": [0] * chunk_size})
					UpperCamelCase_			= pa.concat_tables([table] * (num_examples // chunk_size))
					return datasets.Dataset(_lowerCAmelCase ,						fingerprint="table_100B")


@dataclass
class    _lowercase :
				'''simple docstring'''







				lowercase__     =    42
				lowercase__     =    42
				lowercase__     =    42
				lowercase__     =    42

				def    _lowerCamelCase       (			self     ):

									'''simple docstring'''


									UpperCamelCase_			= np.random.default_rng(self.seed     )
									UpperCamelCase_			= rng.integers(low=self.low  ,			high=self.high  ,			size=self.size     ).tolist()

				def __iter__(			self     ):

									'''simple docstring'''


									return iter(self._sampled_values     )

				def __len__(			self     ):

									'''simple docstring'''


									return self.size




@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase):
					UpperCamelCase_			= dataset[0]



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase):
					UpperCamelCase_			= dataset[-1]



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase):
					UpperCamelCase_			= dataset[range(len(_lowerCAmelCase) // 2 ,						len(_lowerCAmelCase) // 2 + 10_24)]



@get_duration
def  _lowerCAmelCase     (_lowerCAmelCase):
					UpperCamelCase_			= dataset[RandIter(0 ,						len(_lowerCAmelCase) ,						10_24 ,						seed=42)]



def  _lowerCAmelCase     ():
					UpperCamelCase_			= {"num examples": SPEED_TEST_N_EXAMPLES}
					UpperCamelCase_			= (get_first_row, get_last_row, get_batch_of_aaaa_rows, get_batch_of_aaaa_random_rows)
					print("generating dataset")
					UpperCamelCase_			= generate_100B_dataset(num_examples=_lowerCAmelCase ,						chunk_size=_lowerCAmelCase)
					print("Functions")
					for func in functions:
										print(func.__name__)
										UpperCamelCase_			= func(_lowerCAmelCase)

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


if __name__ == "__main__":  # useful to run the profiler
	benchmark_table_100B()
