
'''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
)
A			      =      logging.getLogger(__name__)





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

				logger.info(F'''Loading Tokenizer ({args.tokenizer_name})''')
				if args.tokenizer_type == "bert":
								lowerCamelCase					:			List[Any]									= BertTokenizer.from_pretrained(args.tokenizer_name)
								lowerCamelCase					:			Optional[int]									= tokenizer.special_tokens_map['cls_token']  # `[CLS]`
								lowerCamelCase					:			Union[str, Any]									= tokenizer.special_tokens_map['sep_token']  # `[SEP]`
				elif args.tokenizer_type == "roberta":
								lowerCamelCase					:			str									= RobertaTokenizer.from_pretrained(args.tokenizer_name)
								lowerCamelCase					:			Any									= tokenizer.special_tokens_map['cls_token']  # `<s>`
								lowerCamelCase					:			Optional[Any]									= tokenizer.special_tokens_map['sep_token']  # `</s>`
				elif args.tokenizer_type == "gpt2":
								lowerCamelCase					:			Any									= GPTaTokenizer.from_pretrained(args.tokenizer_name)
								lowerCamelCase					:			List[str]									= tokenizer.special_tokens_map['bos_token']  # `<|endoftext|>`
								lowerCamelCase					:			Optional[int]									= 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:
								lowerCamelCase					:			str									= fp.readlines()

				logger.info('Start encoding')
				logger.info(F'''{len(UpperCAmelCase__)} examples to process.''')

				lowerCamelCase					:			int									= []
				lowerCamelCase					:			Union[str, Any]									= 0
				lowerCamelCase					:			Dict									= 1_00_00
				lowerCamelCase					:			int									= time.time()
				for text in data:
								lowerCamelCase					:			Optional[Any]									= F'''{bos} {text.strip()} {sep}'''
								lowerCamelCase					:			Optional[int]									= tokenizer.encode(UpperCAmelCase__       ,							add_special_tokens=UpperCAmelCase__)
								rslt.append(UpperCAmelCase__)

								iter += 1
								if iter % interval == 0:
												lowerCamelCase					:			Optional[int]									= time.time()
												logger.info(F'''{iter} examples processed. - {(end-start):.2f}s/{interval}expl''')
												lowerCamelCase					:			str									= time.time()
				logger.info('Finished binarization')
				logger.info(F'''{len(UpperCAmelCase__)} examples processed.''')

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


if __name__ == "__main__":
					main()







'''simple docstring'''






from __future__ import annotations

import string
from itertools import cycle, product
from pathlib import Path

A			      =      (
    string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A			      =      [ord(letter) for letter in string.ascii_lowercase]
A			      =      {ord(char) for char in VALID_CHARS}

A			      =      ["the", "be", "to", "of", "and", "in", "that", "have"]





def    UpperCAmelCase							(  UpperCAmelCase__							:							list[int]       ,							UpperCAmelCase__							:							tuple[int, ...]):
				lowerCamelCase					:			str									= ""
				lowerCamelCase					:			int
				lowerCamelCase					:			int
				lowerCamelCase					:			int

				for keychar, cipherchar in zip(cycle(UpperCAmelCase__)       ,							UpperCAmelCase__):
								lowerCamelCase					:			Optional[Any]									= cipherchar ^ keychar
								if decodedchar not in VALID_INTS:
												return None
								decoded += chr(UpperCAmelCase__)

				return decoded





def    UpperCAmelCase							(  UpperCAmelCase__							:							list[int]):
				lowerCamelCase					:			list[str]									= []
				for key in product(UpperCAmelCase__       ,							repeat=3):
								lowerCamelCase					:			Dict									= try_key(UpperCAmelCase__       ,							UpperCAmelCase__)
								if encoded is not None:
												possibles.append(UpperCAmelCase__)
				return possibles





def    UpperCAmelCase							(  UpperCAmelCase__							:							list[str]       ,							UpperCAmelCase__							:							str):
				return [possible for possible in possibles if common_word in possible.lower()]





def    UpperCAmelCase							(  UpperCAmelCase__							:							str = "p059_cipher.txt"):
				lowerCamelCase					:			list[int]
				lowerCamelCase					:			list[str]
				lowerCamelCase					:			str
				lowerCamelCase					:			str
				lowerCamelCase					:			str									= Path(UpperCAmelCase__).parent.joinpath(UpperCAmelCase__).read_text(encoding='utf-8')

				lowerCamelCase					:			Tuple									= [int(UpperCAmelCase__) for number in data.strip().split(',')]

				lowerCamelCase					:			str									= filter_valid_chars(UpperCAmelCase__)
				for common_word in COMMON_WORDS:
								lowerCamelCase					:			List[str]									= filter_common_word(UpperCAmelCase__       ,							UpperCAmelCase__)
								if len(UpperCAmelCase__) == 1:
												break

				lowerCamelCase					:			Dict									= possibles[0]
				return sum(ord(UpperCAmelCase__) for char in decoded_text)


if __name__ == "__main__":
					print(f"""{solution() = }""")
