


import multiprocessing
import time

from arguments import PretokenizationArguments
from datasets import load_dataset

from transformers import AutoTokenizer, HfArgumentParser
def       _a			(				SCREAMING_SNAKE_CASE					):


  """simple docstring"""




  lowercase__						=				{}
  lowercase__						=				tokenizer(example['''content''']						,    truncation=SCREAMING_SNAKE_CASE					)['''input_ids''']
  lowercase__						=				len(example['''content''']					) / len(output['''input_ids''']					)
  return output


lowerCAmelCase	=							HfArgumentParser(PretokenizationArguments)
lowerCAmelCase	=							parser.parse_args()
if args.num_workers is None:
   lowerCAmelCase	=							multiprocessing.cpu_count()
lowerCAmelCase	=							AutoTokenizer.from_pretrained(args.tokenizer_dir)

lowerCAmelCase	=							time.time()
lowerCAmelCase	=							load_dataset(args.dataset_name, split='train')
print(f"""Dataset loaded in {time.time()-t_start:.2f}s""")

lowerCAmelCase	=							time.time()
lowerCAmelCase	=							ds.map(
    tokenize,
    num_proc=args.num_workers,
    remove_columns=[
        'repo_name',
        'path',
        'copies',
        'size',
        'content',
        'license',
        'hash',
        'line_mean',
        'line_max',
        'alpha_frac',
        'autogenerated',
    ],
)
print(f"""Dataset tokenized in {time.time()-t_start:.2f}s""")

lowerCAmelCase	=							time.time()
ds.push_to_hub(args.tokenized_data_repo)
print(f"""Data pushed to the hub in {time.time()-t_start:.2f}s""")






from __future__ import annotations

from collections import namedtuple
from dataclasses import dataclass


@dataclass
class 	_a							:
							_lowercase     :      int
							_lowercase     :      TreeNode | None  				=			None
							_lowercase     :      TreeNode | None  				=			None
lowerCAmelCase	=							namedtuple('CoinsDistribResult', 'moves excess')
def       _a			(				SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		if root is None:
				return 0

		# Validation
		def count_nodes(SCREAMING_SNAKE_CASE					) -> int:
				if node is None:
						return 0

				return count_nodes(node.left					) + count_nodes(node.right					) + 1

		def count_coins(SCREAMING_SNAKE_CASE					) -> int:
				if node is None:
						return 0

				return count_coins(node.left					) + count_coins(node.right					) + node.data

		if count_nodes(SCREAMING_SNAKE_CASE					) != count_coins(SCREAMING_SNAKE_CASE					):
				raise ValueError('''The nodes number should be same as the number of coins'''					)

		# Main calculation
		def get_distrib(SCREAMING_SNAKE_CASE					) -> CoinsDistribResult:

				if node is None:
						return CoinsDistribResult(0						,    1					)

				lowercase__					,		lowercase__						=				get_distrib(node.left					)
				lowercase__					,		lowercase__						=				get_distrib(node.right					)

				lowercase__						=				1 - left_distrib_excess
				lowercase__						=				1 - right_distrib_excess

				lowercase__						=				(
				    left_distrib_moves
				    + right_distrib_moves
				    + abs(SCREAMING_SNAKE_CASE					)
				    + abs(SCREAMING_SNAKE_CASE					)
				)
				lowercase__						=				node.data - coins_to_left - coins_to_right

				return CoinsDistribResult(SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					)

		return get_distrib(SCREAMING_SNAKE_CASE					)[0]


if __name__ == "__main__":
			import doctest

			doctest.testmod()


