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
)
__lowerCamelCase					:	int       =  logging.getLogger(__name__)




def       _snake_case	(   ):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Dict				      =    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."	)
		SCREAMING_SNAKE_CASE_  :		str				      =    parser.parse_args()

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

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

		SCREAMING_SNAKE_CASE_  :		Any				      =    []
		SCREAMING_SNAKE_CASE_  :		List[str]				      =    0
		SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    1_0_0_0_0
		SCREAMING_SNAKE_CASE_  :		Optional[Any]				      =    time.time()
		for text in data:
				SCREAMING_SNAKE_CASE_  :		Tuple				      =    f'{bos} {text.strip()} {sep}'
				SCREAMING_SNAKE_CASE_  :		List[str]				      =    tokenizer.encode(lowerCAmelCase   , add_special_tokens=lowerCAmelCase	)
				rslt.append(lowerCAmelCase	)

				iter += 1
				if iter % interval == 0:
						SCREAMING_SNAKE_CASE_  :		List[Any]				      =    time.time()
						logger.info(f'{iter} examples processed. - {(end-start):.2f}s/{interval}expl'	)
						SCREAMING_SNAKE_CASE_  :		Dict				      =    time.time()
		logger.info("Finished binarization"	)
		logger.info(f'{len(lowerCAmelCase	)} examples processed.'	)

		SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    f'{args.dump_file}.{args.tokenizer_name}.pickle'
		SCREAMING_SNAKE_CASE_  :		Dict				      =    tokenizer.vocab_size
		if vocab_size < (1 << 1_6):
				SCREAMING_SNAKE_CASE_  :		Union[str, Any]				      =    [np.uintaa(lowerCAmelCase	) for d in rslt]
		else:
				SCREAMING_SNAKE_CASE_  :		Dict				      =    [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()

from collections import defaultdict




def       _snake_case	(   lowerCAmelCase							:   int	):
		"""simple docstring"""







		SCREAMING_SNAKE_CASE_  :		Any				      =    1
		SCREAMING_SNAKE_CASE_  :		Tuple				      =    True
		for v in tree[start]:
				if v not in visited:
						ret += dfs(lowerCAmelCase	)
		if ret % 2 == 0:
				cuts.append(lowerCAmelCase	)
		return ret




def       _snake_case	(   ):
		"""simple docstring"""







		dfs(1	)


if __name__ == "__main__":
		__lowerCamelCase   ,						__lowerCamelCase					:	Union[str, Any]       =  10, 9
		__lowerCamelCase					:	Optional[int]       =  defaultdict(list)
		__lowerCamelCase					:	dict[int, bool]       =  {}
		__lowerCamelCase					:	list[int]       =  []
		__lowerCamelCase					:	Optional[Any]       =  0
		__lowerCamelCase					:	Any       =  [(2, 1), (3, 1), (4, 3), (5, 2), (6, 1), (7, 2), (8, 6), (9, 8), (10, 8)]
		for u, v in edges:
				tree[u].append(v)
				tree[v].append(u)
		even_tree()
		print(len(cuts) - 1)
