






"""simple docstring"""






from __future__ import annotations



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__				):
				A__							 =       position
				A__							 =       [
				    (y + 1, x + 2),
				    (y - 1, x + 2),
				    (y + 1, x - 2),
				    (y - 1, x - 2),
				    (y + 2, x + 1),
				    (y + 2, x - 1),
				    (y - 2, x + 1),
				    (y - 2, x - 1),
				]
				A__							 =       []

				for position in positions:
								A__							 =       position
								if 0 <= y_test < n and 0 <= x_test < n:
												permissible_positions.append(_lowerCamelCase				)

				return permissible_positions



def  __lowerCamelCase					(					lowerCAmelCase__				):
				return not any(elem == 0 for row in board for elem in row				)



def  __lowerCamelCase					(					lowerCAmelCase__       ,lowerCAmelCase__       ,lowerCAmelCase__				):

				if is_complete(_lowerCamelCase				):
								return True

				for position in get_valid_pos(_lowerCamelCase       ,len(_lowerCamelCase				)				):
								A__							 =       position

								if board[y][x] == 0:
												A__							 =       curr + 1
												if open_knight_tour_helper(_lowerCamelCase       ,_lowerCamelCase       ,curr + 1				):
																return True
												A__							 =       0

				return False



def  __lowerCamelCase					(					lowerCAmelCase__				):
				A__							 =       [[0 for i in range(_lowerCamelCase				)] for j in range(_lowerCamelCase				)]

				for i in range(_lowerCamelCase				):
								for j in range(_lowerCamelCase				):
												A__							 =       1
												if open_knight_tour_helper(_lowerCamelCase       ,(i, j)       ,1				):
																return board
												A__							 =       0

				A__							 =       f'''Open Kight Tour cannot be performed on a board of size {n}'''
				raise ValueError(_lowerCamelCase				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()










"""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()


