
import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class     UpperCAmelCase						(		__lowercase			,unittest.TestCase					):
   A__   :						Union[str, Any]			=	GPTSanJapaneseTokenizer
   A__   :						Optional[Any]			=	False
   A__   :						Any			=	{"do_clean_text": False, "add_prefix_space": False}



   def 							_SCREAMING_SNAKE_CASE  (self						:   Dict					)						->      int:


          '''simple docstring'''


          super().setUp()

          # fmt: off
          snake_case			:  Dict     							= ["こん", "こんに", "にちは", "ばんは", "世界,㔺界", "、", "。", "<BR>", "<SP>", "<TAB>", "<URL>", "<EMAIL>", "<TEL>", "<DATE>", "<PRICE>", "<BLOCK>", "<KIGOU>", "<U2000U2BFF>", "<|emoji1|>", "<unk>", "<|bagoftoken|>", "<|endoftext|>"]
          # fmt: on
          snake_case			:  List[Any]     							= {"emoji": {"\ud83d\ude00": "<|emoji1|>"}, "emoji_inv": {"<|emoji1|>": "\ud83d\ude00"}}  # 😀
          snake_case			:  int     							= {"unk_token": "<unk>"}

          snake_case			:  Union[str, Any]     							= os.path.join(self.tmpdirname       ,		VOCAB_FILES_NAMES["vocab_file"]					)
          snake_case			:  List[str]     							= os.path.join(self.tmpdirname       ,		VOCAB_FILES_NAMES["emoji_file"]					)
          with open(self.vocab_file       ,		"w"       ,		encoding="utf-8"					) as vocab_writer:
                 vocab_writer.write("".join([x + "\n" for x in vocab_tokens]					)					)
          with open(self.emoji_file       ,		"w"					) as emoji_writer:
                 emoji_writer.write(json.dumps(SCREAMING_SNAKE_CASE_					)					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Any       ,		**snake_case__						:   Union[str, Any]					)						->      Optional[int]:


          '''simple docstring'''


          kwargs.update(self.special_tokens_map					)
          return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname       ,		**SCREAMING_SNAKE_CASE_					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[int]       ,		snake_case__						:   Optional[Any]					)						->      str:


          '''simple docstring'''


          snake_case			:  str     							= "こんにちは、世界。 \nこんばんは、㔺界。😀"
          snake_case			:  str     							= "こんにちは、世界。 \nこんばんは、世界。😀"
          return input_text, output_text



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]       ,		snake_case__						:   Dict					)						->      List[Any]:


          '''simple docstring'''


          snake_case							,   snake_case			:  Union[str, Any]     							= self.get_input_output_texts(SCREAMING_SNAKE_CASE_					)
          snake_case			:  Any     							= tokenizer.encode(SCREAMING_SNAKE_CASE_       ,		add_special_tokens=SCREAMING_SNAKE_CASE_					)
          snake_case			:  List[str]     							= tokenizer.decode(SCREAMING_SNAKE_CASE_       ,		clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE_					)
          return text, ids



   def 							_SCREAMING_SNAKE_CASE  (self						:   List[str]					)						->      Dict:


          '''simple docstring'''


          pass  # TODO add if relevant



   def 							_SCREAMING_SNAKE_CASE  (self						:   str					)						->      Optional[Any]:


          '''simple docstring'''


          pass  # TODO add if relevant



   def 							_SCREAMING_SNAKE_CASE  (self						:   Any					)						->      Optional[int]:


          '''simple docstring'''


          pass  # TODO add if relevant



   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple					)						->      List[str]:


          '''simple docstring'''


          snake_case			:  str     							= self.get_tokenizer()

          # Testing tokenization
          snake_case			:  Dict     							= "こんにちは、世界。　こんばんは、㔺界。"
          snake_case			:  Any     							= ["こん", "にちは", "、", "世界", "。", "<SP>", "こん", "ばんは", "、", "㔺界", "。"]
          snake_case			:  str     							= tokenizer.tokenize(SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)

          # Testing conversion to ids without special tokens
          snake_case			:  str     							= [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
          snake_case			:  List[str]     							= tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)

          # Testing conversion to ids with special tokens
          snake_case			:  Union[str, Any]     							= tokens + [tokenizer.unk_token]
          snake_case			:  Union[str, Any]     							= [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
          snake_case			:  List[str]     							= tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   int					)						->      Any:


          '''simple docstring'''


          snake_case			:  Optional[int]     							= self.get_tokenizer()

          # Testing tokenization
          snake_case			:  List[Any]     							= "こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。"
          snake_case			:  List[str]     							= "こんにちは、、、、世界。こんばんは、、、、世界。"
          snake_case			:  Any     							= tokenizer.encode(SCREAMING_SNAKE_CASE_					)
          snake_case			:  List[Any]     							= tokenizer.decode(SCREAMING_SNAKE_CASE_					)
          self.assertEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)



   @slow
   def 							_SCREAMING_SNAKE_CASE  (self						:   List[Any]					)						->      int:


          '''simple docstring'''


          snake_case			:  int     							= self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"					)

          # Testing tokenization
          snake_case			:  str     							= "こんにちは、世界。"
          snake_case			:  Union[str, Any]     							= "こんばんは、㔺界。😀"
          snake_case			:  Dict     							= "こんにちは、世界。こんばんは、世界。😀"
          snake_case			:  int     							= tokenizer.encode(prefix_text + input_text					)
          snake_case			:  Optional[int]     							= tokenizer.encode(""       ,		prefix_text=prefix_text + input_text					)
          snake_case			:  Optional[Any]     							= tokenizer.encode(SCREAMING_SNAKE_CASE_       ,		prefix_text=SCREAMING_SNAKE_CASE_					)
          snake_case			:  Union[str, Any]     							= tokenizer.decode(SCREAMING_SNAKE_CASE_					)
          snake_case			:  Any     							= tokenizer.decode(SCREAMING_SNAKE_CASE_					)
          snake_case			:  List[str]     							= tokenizer.decode(SCREAMING_SNAKE_CASE_					)
          self.assertEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)
          self.assertEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)
          self.assertEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)



   @slow
   def 							_SCREAMING_SNAKE_CASE  (self						:   int					)						->      Any:


          '''simple docstring'''


          snake_case			:  Tuple     							= self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"					)

          # Testing tokenization
          snake_case			:  Dict     							= "こんにちは、世界。"
          snake_case			:  List[str]     							= "こんばんは、㔺界。😀"

          snake_case			:  int     							= len(tokenizer.encode(SCREAMING_SNAKE_CASE_					)					) - 2
          snake_case			:  int     							= len(tokenizer.encode(SCREAMING_SNAKE_CASE_					)					) - 2

          snake_case			:  Tuple     							= [1] + [0] * (len_prefix + len_text + 1)
          snake_case			:  Optional[Any]     							= [1] * (len_prefix + len_text + 1) + [0]
          snake_case			:  Tuple     							= [1] + [1] * (len_prefix) + [0] * (len_text + 1)

          snake_case			:  Any     							= tokenizer(prefix_text + input_text					).token_type_ids
          snake_case			:  Optional[int]     							= tokenizer(""       ,		prefix_text=prefix_text + input_text					).token_type_ids
          snake_case			:  Dict     							= tokenizer(SCREAMING_SNAKE_CASE_       ,		prefix_text=SCREAMING_SNAKE_CASE_					).token_type_ids
          self.assertListEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)



   @slow
   def 							_SCREAMING_SNAKE_CASE  (self						:   List[Any]					)						->      Optional[int]:


          '''simple docstring'''


          snake_case			:  Any     							= self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"					)

          snake_case			:  Optional[Any]     							= tokenizer.encode("あンいワ"					)
          snake_case			:  int     							= tokenizer.encode(""       ,		prefix_text="あンいワ"					)
          snake_case			:  Dict     							= tokenizer.encode("いワ"       ,		prefix_text="あン"					)

          self.assertEqual(tokenizer.decode(SCREAMING_SNAKE_CASE_					)       ,		tokenizer.decode(SCREAMING_SNAKE_CASE_					)					)
          self.assertEqual(tokenizer.decode(SCREAMING_SNAKE_CASE_					)       ,		tokenizer.decode(SCREAMING_SNAKE_CASE_					)					)
          self.assertNotEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)
          self.assertNotEqual(SCREAMING_SNAKE_CASE_       ,		SCREAMING_SNAKE_CASE_					)
          self.assertEqual(x_token_a[1]       ,		x_token_a[-1]					)  # SEG token
          self.assertEqual(x_token_a[1]       ,		x_token_a[3]					)  # SEG token



   @slow
   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]					)						->      int:


          '''simple docstring'''


          snake_case			:  Dict     							= self.tokenizer_class.from_pretrained("Tanrei/GPTSAN-japanese"					)

          snake_case			:  Optional[Any]     							= [["武田信玄", "は、"], ["織田信長", "の配下の、"]]
          snake_case			:  Tuple     							= tokenizer(SCREAMING_SNAKE_CASE_       ,		padding=SCREAMING_SNAKE_CASE_					)
          snake_case			:  Optional[Any]     							= tokenizer.batch_encode_plus(SCREAMING_SNAKE_CASE_       ,		padding=SCREAMING_SNAKE_CASE_					)

          # fmt: off
          snake_case			:  str     							= [[3_59_93, 86_40, 2_59_48, 3_59_98, 3_06_47, 3_56_75, 3_59_99, 3_59_99], [3_59_93, 1_03_82, 98_68, 3_59_98, 3_06_46, 94_59, 3_06_46, 3_56_75]]
          snake_case			:  Tuple     							= [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
          snake_case			:  Dict     							= [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
          # fmt: on
          self.assertListEqual(x_token.input_ids       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(x_token.token_type_ids       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(x_token.attention_mask       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(x_token_a.input_ids       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(x_token_a.token_type_ids       ,		SCREAMING_SNAKE_CASE_					)
          self.assertListEqual(x_token_a.attention_mask       ,		SCREAMING_SNAKE_CASE_					)



   def 							_SCREAMING_SNAKE_CASE  (self						:   Optional[Any]					)						->      Any:


          '''simple docstring'''


          pass



   def 							_SCREAMING_SNAKE_CASE  (self						:   Tuple					)						->      str:


          '''simple docstring'''


          pass







"""simple docstring"""




from __future__ import annotations

import math



def 							_lowerCamelCase			(			__a     ):

		if num <= 0:
				SCREAMING_SNAKE_CASE_    			=			F'{num}: Invalid input, please enter a positive integer.'
				raise ValueError(__a     )

		SCREAMING_SNAKE_CASE_    			=			[True] * (num + 1)
		SCREAMING_SNAKE_CASE_    			=			[]
		SCREAMING_SNAKE_CASE_    			=			2
		SCREAMING_SNAKE_CASE_    			=			int(math.sqrt(__a     )     )

		while start <= end:
				# If start is a prime
				if sieve[start] is True:
						prime.append(__a     )

						# Set multiples of start be False
						for i in range(start * start,				num + 1,				__a     ):
								if sieve[i] is True:
										SCREAMING_SNAKE_CASE_    			=			False

				start += 1

		for j in range(end + 1,				num + 1     ):
				if sieve[j] is True:
						prime.append(__a     )

		return prime


if __name__ == "__main__":
						print(prime_sieve(int(input('Enter a positive integer: ').strip())))