
"""simple docstring"""





import os
from collections import deque

import torch
from torch.utils.data import Dataset
class 						SCREAMING_SNAKE_CASE_ (						__a ):




		"""simple docstring"""





		def __init__(     self							,  lowerCAmelCase__=""							,  lowerCAmelCase__="train"):
				assert os.path.isdir(lowerCAmelCase__)

				__SCREAMING_SNAKE_CASE            = []
				__SCREAMING_SNAKE_CASE            = os.listdir(lowerCAmelCase__)
				for story_filename in story_filenames_list:
						if "summary" in story_filename:
								continue
						__SCREAMING_SNAKE_CASE            = os.path.join(lowerCAmelCase__							,  lowerCAmelCase__)
						if not os.path.isfile(lowerCAmelCase__):
								continue
						self.documents.append(lowerCAmelCase__)




		def __len__(     self):
				return len(self.documents)




		def __getitem__(     self							,  lowerCAmelCase__):
				__SCREAMING_SNAKE_CASE            = self.documents[idx]
				__SCREAMING_SNAKE_CASE            = document_path.split("""/""")[-1]
				with open(lowerCAmelCase__							,  encoding="""utf-8""") as source:
						__SCREAMING_SNAKE_CASE            = source.read()
						__SCREAMING_SNAKE_CASE       ,__SCREAMING_SNAKE_CASE            = process_story(lowerCAmelCase__)
				return document_name, story_lines, summary_lines



def 						_lowerCAmelCase				(				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = list(filter(lambda UpperCamelCase_				: len(UpperCamelCase_				) != 0  ,				[line.strip() for line in raw_story.split("""\n"""				)]				)				)

		# for some unknown reason some lines miss a period, add it
		__SCREAMING_SNAKE_CASE            = [_add_missing_period(UpperCamelCase_				) for line in nonempty_lines]

		# gather article lines
		__SCREAMING_SNAKE_CASE            = []
		__SCREAMING_SNAKE_CASE            = deque(UpperCamelCase_				)
		while True:
				try:
						__SCREAMING_SNAKE_CASE            = lines.popleft()
						if element.startswith("""@highlight"""				):
								break
						story_lines.append(UpperCamelCase_				)
				except IndexError:
						# if "@highlight" is absent from the file we pop
						# all elements until there is None, raising an exception.
						return story_lines, []

    # gather summary lines
		__SCREAMING_SNAKE_CASE            = list(filter(lambda UpperCamelCase_				: not t.startswith("""@highlight"""				)  ,				UpperCamelCase_				)				)

		return story_lines, summary_lines



def 						_lowerCAmelCase				(				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = [""".""", """!""", """?""", """...""", """'""", """`""", """\"""", """\u2019""", """\u2019""", """)"""]
		if line.startswith("""@highlight"""				):
				return line
		if line[-1] in END_TOKENS:
				return line
		return line + "."



def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_				):
		if len(UpperCamelCase_				) > block_size:
				return sequence[:block_size]
		else:
				sequence.extend([pad_token_id] * (block_size - len(UpperCamelCase_				))				)
				return sequence



def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = torch.ones_like(UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = sequence == pad_token_id
		__SCREAMING_SNAKE_CASE            = 0
		return mask



def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_  ,				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = [tokenizer.encode(UpperCamelCase_				) for line in story_lines]
		__SCREAMING_SNAKE_CASE            = [token for sentence in story_lines_token_ids for token in sentence]
		__SCREAMING_SNAKE_CASE            = [tokenizer.encode(UpperCamelCase_				) for line in summary_lines]
		__SCREAMING_SNAKE_CASE            = [token for sentence in summary_lines_token_ids for token in sentence]

		return story_token_ids, summary_token_ids



def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = []
		for sequence in batch:
				__SCREAMING_SNAKE_CASE            = -1
				__SCREAMING_SNAKE_CASE            = []
				for s in sequence:
						if s == separator_token_id:
								sentence_num += 1
						embeddings.append(sentence_num % 2				)
				batch_embeddings.append(UpperCamelCase_				)
		return torch.tensor(UpperCamelCase_				)






"""simple docstring"""





from math import isqrt, loga



def 						_lowerCAmelCase				(				UpperCamelCase_				):
		__SCREAMING_SNAKE_CASE            = [True] * max_number
		for i in range(2  ,				isqrt(max_number - 1				) + 1				):
				if is_prime[i]:
						for j in range(i**2  ,				UpperCamelCase_  ,				UpperCamelCase_				):
								__SCREAMING_SNAKE_CASE            = False

		return [i for i in range(2  ,				UpperCamelCase_				) if is_prime[i]]



def 						_lowerCAmelCase				(				UpperCamelCase_ = 80_0800  ,				UpperCamelCase_ = 80_0800				):
		__SCREAMING_SNAKE_CASE            = degree * loga(UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = int(UpperCamelCase_				)
		__SCREAMING_SNAKE_CASE            = calculate_prime_numbers(UpperCamelCase_				)

		__SCREAMING_SNAKE_CASE            = 0
		__SCREAMING_SNAKE_CASE            = 0
		__SCREAMING_SNAKE_CASE            = len(UpperCamelCase_				) - 1
		while left < right:
				while (
				    prime_numbers[right] * loga(prime_numbers[left]				)
				    + prime_numbers[left] * loga(prime_numbers[right]				)
				    > upper_bound
				):
						right -= 1
				hybrid_integers_count += right - left
				left += 1

		return hybrid_integers_count


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




