






"""simple docstring"""






import argparse
import logging
import pickle
import random
import time

import numpy as np

from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer


logging.basicConfig(
    format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
SCREAMING_SNAKE_CASE						:						Optional[int]					   =       logging.getLogger(__name__)



def  __lowerCamelCase					(					):
    A__							 =       argparse.ArgumentParser(
        description='Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids).'				)
    parser.add_argument('--file_path'       ,type=lowerCAmelCase__       ,default='data/dump.txt'       ,help='The path to the data.'				)
    parser.add_argument('--tokenizer_type'       ,type=lowerCAmelCase__       ,default='bert'       ,choices=['bert', 'roberta', 'gpt2']				)
    parser.add_argument('--tokenizer_name'       ,type=lowerCAmelCase__       ,default='bert-base-uncased'       ,help='The tokenizer to use.'				)
    parser.add_argument('--dump_file'       ,type=lowerCAmelCase__       ,default='data/dump'       ,help='The dump file prefix.'				)
    A__							 =       parser.parse_args()

    logger.info(f'''Loading Tokenizer ({args.tokenizer_name})'''				)
    if args.tokenizer_type == "bert":
        A__							 =       BertTokenizer.from_pretrained(args.tokenizer_name				)
        A__							 =       tokenizer.special_tokens_map['cls_token']  # `[CLS]`
        A__							 =       tokenizer.special_tokens_map['sep_token']  # `[SEP]`
    elif args.tokenizer_type == "roberta":
        A__							 =       RobertaTokenizer.from_pretrained(args.tokenizer_name				)
        A__							 =       tokenizer.special_tokens_map['cls_token']  # `<s>`
        A__							 =       tokenizer.special_tokens_map['sep_token']  # `</s>`
    elif args.tokenizer_type == "gpt2":
        A__							 =       GPTaTokenizer.from_pretrained(args.tokenizer_name				)
        A__							 =       tokenizer.special_tokens_map['bos_token']  # `<|endoftext|>`
        A__							 =       tokenizer.special_tokens_map['eos_token']  # `<|endoftext|>`

    logger.info(f'''Loading text from {args.file_path}'''				)
    with open(args.file_path       ,'r'       ,encoding='utf8'				) as fp:
        A__							 =       fp.readlines()

    logger.info('Start encoding'				)
    logger.info(f'''{len(lowerCAmelCase__				)} examples to process.'''				)

    A__							 =       []
    A__							 =       0
    A__							 =       1_0000
    A__							 =       time.time()
    for text in data:
        A__							 =       f'''{bos} {text.strip()} {sep}'''
        A__							 =       tokenizer.encode(lowerCAmelCase__       ,add_special_tokens=lowerCAmelCase__				)
        rslt.append(lowerCAmelCase__				)

        iter += 1
        if iter % interval == 0:
            A__							 =       time.time()
            logger.info(f'''{iter} examples processed. - {(end-start):.2f}s/{interval}expl'''				)
            A__							 =       time.time()
    logger.info('Finished binarization'				)
    logger.info(f'''{len(lowerCAmelCase__				)} examples processed.'''				)

    A__							 =       f'''{args.dump_file}.{args.tokenizer_name}.pickle'''
    A__							 =       tokenizer.vocab_size
    if vocab_size < (1 << 16):
        A__							 =       [np.uintaa(lowerCAmelCase__				) for d in rslt]
    else:
        A__							 =       [np.intaa(lowerCAmelCase__				) for d in rslt]
    random.shuffle(rslt_				)
    logger.info(f'''Dump to {dp_file}'''				)
    with open(lowerCAmelCase__       ,'wb'				) as handle:
        pickle.dump(rslt_       ,lowerCAmelCase__       ,protocol=pickle.HIGHEST_PROTOCOL				)


if __name__ == "__main__":
     main()










"""simple docstring"""






from math import factorial, pi



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__ = 30				):

				if not isinstance(lowerCAmelCase__       ,(int, float)				):
								raise ValueError('maclaurin_sin() requires either an int or float for theta'				)

				if not isinstance(lowerCAmelCase__       ,lowerCAmelCase__				) or accuracy <= 0:
								raise ValueError('maclaurin_sin() requires a positive int for accuracy'				)

				A__							 =       float(lowerCAmelCase__				)
				A__							 =       theta // (2 * pi)
				theta -= 2 * div * pi
				return sum(
				    (-1) ** r * theta ** (2 * r + 1) / factorial(2 * r + 1				) for r in range(lowerCAmelCase__				)				)



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__ = 30				):

				if not isinstance(lowerCAmelCase__       ,(int, float)				):
								raise ValueError('maclaurin_cos() requires either an int or float for theta'				)

				if not isinstance(lowerCAmelCase__       ,lowerCAmelCase__				) or accuracy <= 0:
								raise ValueError('maclaurin_cos() requires a positive int for accuracy'				)

				A__							 =       float(lowerCAmelCase__				)
				A__							 =       theta // (2 * pi)
				theta -= 2 * div * pi
				return sum((-1) ** r * theta ** (2 * r) / factorial(2 * r				) for r in range(lowerCAmelCase__				)				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					print(maclaurin_sin(10))
					print(maclaurin_sin(-10))
					print(maclaurin_sin(10, 15))
					print(maclaurin_sin(-10, 15))

					print(maclaurin_cos(5))
					print(maclaurin_cos(-5))
					print(maclaurin_cos(10, 15))
					print(maclaurin_cos(-10, 15))


