






"""simple docstring"""




import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
     UpperCamelCase							       =    """pt"""
elif is_tf_available():
     UpperCamelCase							       =    """tf"""
else:
     UpperCamelCase							       =    """jax"""




class    lowercase_    (_UpperCAmelCase,    unittest.TestCase     ):
      A__	:		List[str]       			=				ByTaTokenizer
      A__	:		List[Any]       			=				False






      def 			lowerCamelCase__    (    self	)	->Any:







        '''simple docstring'''


        super().setUp()
        _a							=	ByTaTokenizer()
        tokenizer.save_pretrained(self.tmpdirname	)






      @cached_property
      def 			lowerCamelCase__    (    self	)	->List[str]:







        '''simple docstring'''


        return ByTaTokenizer.from_pretrained("google/byt5-small"	)






      def 			lowerCamelCase__    (    self     ,     **a_	)	->ByTaTokenizer:







        '''simple docstring'''


        return self.tokenizer_class.from_pretrained(self.tmpdirname     ,     **a_	)






      def 			lowerCamelCase__    (    self     ,     a_     ,     a_=False     ,     a_=2_0     ,     a_=5	)	->Tuple[str, list]:







        '''simple docstring'''


        _a							=	[]
        for i in range(len(a_	)	):
          try:
            _a							=	tokenizer.decode([i]     ,     clean_up_tokenization_spaces=a_	)
          except UnicodeDecodeError:
            pass
          toks.append((i, tok)	)

        _a							=	list(filter(lambda a_	: re.match(R"^[ a-zA-Z]+$"     ,     t[1]	)     ,     a_	)	)
        _a							=	list(filter(lambda a_	: [t[0]] == tokenizer.encode(t[1]     ,     add_special_tokens=a_	)     ,     a_	)	)
        if max_length is not None and len(a_	) > max_length:
          _a							=	toks[:max_length]
        if min_length is not None and len(a_	) < min_length and len(a_	) > 0:
          while len(a_	) < min_length:
            _a							=	toks + toks
        # toks_str = [t[1] for t in toks]
        _a							=	[t[0] for t in toks]

        # Ensure consistency
        _a							=	tokenizer.decode(a_     ,     clean_up_tokenization_spaces=a_	)
        if " " not in output_txt and len(a_	) > 1:
          _a							=	(
              tokenizer.decode([toks_ids[0]]     ,     clean_up_tokenization_spaces=a_	)
              + " "
              + tokenizer.decode(toks_ids[1:]     ,     clean_up_tokenization_spaces=a_	)
          )
        if with_prefix_space:
          _a							=	" " + output_txt
        _a							=	tokenizer.encode(a_     ,     add_special_tokens=a_	)
        return output_txt, output_ids






      def 			lowerCamelCase__    (    self	)	->Union[str, Any]:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	tokenizer(["hi</s>", "I went to the gym</s>", "</s>"]	)
        _a							=	tokenizer(["hi", "I went to the gym", ""]	)
        self.assertListEqual(batch_with_eos_added["input_ids"]     ,     batch_without_eos_added["input_ids"]	)






      def 			lowerCamelCase__    (    self	)	->Tuple:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	"Unicode €."
        _a							=	tokenizer(a_	)
        _a							=	[8_8, 1_1_3, 1_0_8, 1_0_2, 1_1_4, 1_0_3, 1_0_4, 3_5, 2_2_9, 1_3_3, 1_7_5, 4_9, 1]
        self.assertEqual(encoded["input_ids"]     ,     a_	)

        # decoding
        _a							=	tokenizer.decode(a_	)
        self.assertEqual(a_     ,     "Unicode €.</s>"	)

        _a							=	tokenizer("e è é ê ë"	)
        _a							=	[1_0_4, 3_5, 1_9_8, 1_7_1, 3_5, 1_9_8, 1_7_2, 3_5, 1_9_8, 1_7_3, 3_5, 1_9_8, 1_7_4, 1]
        self.assertEqual(encoded["input_ids"]     ,     a_	)
        # decoding
        _a							=	tokenizer.decode(a_	)
        self.assertEqual(a_     ,     "e è é ê ë</s>"	)

        # encode/decode, but with `encode` instead of `__call__`
        self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë"	)	)     ,     "e è é ê ë</s>"	)






      def 			lowerCamelCase__    (    self	)	->int:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	["A long paragraph for summarization.", "Another paragraph for summarization."]
        # fmt: off
        _a							=	[6_8, 3_5, 1_1_1, 1_1_4, 1_1_3, 1_0_6, 3_5, 1_1_5, 1_0_0, 1_1_7, 1_0_0, 1_0_6, 1_1_7, 1_0_0, 1_1_5, 1_0_7, 3_5, 1_0_5, 1_1_4, 1_1_7, 3_5, 1_1_8, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_0_8, 1_2_5, 1_0_0, 1_1_9, 1_0_8, 1_1_4, 1_1_3, 4_9, 1, 0]
        # fmt: on
        _a							=	tokenizer(a_     ,     padding=a_     ,     return_tensors=a_	)
        self.assertIsInstance(a_     ,     a_	)

        if FRAMEWORK != "jax":
          _a							=	list(batch.input_ids.numpy()[0]	)
        else:
          _a							=	list(batch.input_ids.tolist()[0]	)

        self.assertListEqual(a_     ,     a_	)

        self.assertEqual((2, 3_7)     ,     batch.input_ids.shape	)
        self.assertEqual((2, 3_7)     ,     batch.attention_mask.shape	)






      def 			lowerCamelCase__    (    self	)	->Dict:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	["A long paragraph for summarization.", "Another paragraph for summarization."]
        _a							=	tokenizer(a_     ,     padding=a_     ,     return_tensors=a_	)
        # check if input_ids are returned and no decoder_input_ids
        self.assertIn("input_ids"     ,     a_	)
        self.assertIn("attention_mask"     ,     a_	)
        self.assertNotIn("decoder_input_ids"     ,     a_	)
        self.assertNotIn("decoder_attention_mask"     ,     a_	)






      def 			lowerCamelCase__    (    self	)	->List[Any]:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	[
            "Summary of the text.",
            "Another summary.",
        ]
        _a							=	tokenizer(
            text_target=a_     ,     max_length=3_2     ,     padding="max_length"     ,     truncation=a_     ,     return_tensors=a_	)
        self.assertEqual(3_2     ,     targets["input_ids"].shape[1]	)






      def 			lowerCamelCase__    (    self	)	->Dict:







        '''simple docstring'''


        _a							=	self.ta_base_tokenizer
        _a							=	["A long paragraph for summarization. </s>"]
        _a							=	["Summary of the text. </s>"]
        # fmt: off
        _a							=	[6_8, 3_5, 1_1_1, 1_1_4, 1_1_3, 1_0_6, 3_5, 1_1_5, 1_0_0, 1_1_7, 1_0_0, 1_0_6, 1_1_7, 1_0_0, 1_1_5, 1_0_7, 3_5, 1_0_5, 1_1_4, 1_1_7, 3_5, 1_1_8, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_0_8, 1_2_5, 1_0_0, 1_1_9, 1_0_8, 1_1_4, 1_1_3, 4_9, 3_5, 1]
        _a							=	[8_6, 1_2_0, 1_1_2, 1_1_2, 1_0_0, 1_1_7, 1_2_4, 3_5, 1_1_4, 1_0_5, 3_5, 1_1_9, 1_0_7, 1_0_4, 3_5, 1_1_9, 1_0_4, 1_2_3, 1_1_9, 4_9, 3_5, 1]
        # fmt: on

        _a							=	tokenizer(a_     ,     text_target=a_	)

        self.assertEqual(a_     ,     batch["input_ids"][0]	)
        self.assertEqual(a_     ,     batch["labels"][0]	)






      def 			lowerCamelCase__    (    self	)	->int:







        '''simple docstring'''


        _a							=	self.get_tokenizers()
        for tokenizer in tokenizers:
          with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
            self.assertNotEqual(tokenizer.model_max_length     ,     4_2	)

        # Now let's start the test
        _a							=	self.get_tokenizers()
        for tokenizer in tokenizers:
          with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
            # Isolate this from the other tests because we save additional tokens/etc
            _a							=	tempfile.mkdtemp()

            _a							=	" He is very happy, UNwant\u00E9d,running"
            _a							=	tokenizer.encode(a_     ,     add_special_tokens=a_	)
            tokenizer.save_pretrained(a_	)

            _a							=	tokenizer.__class__.from_pretrained(a_	)
            _a							=	after_tokenizer.encode(a_     ,     add_special_tokens=a_	)
            self.assertListEqual(a_     ,     a_	)

            shutil.rmtree(a_	)

        _a							=	self.get_tokenizers(model_max_length=4_2	)
        for tokenizer in tokenizers:
          with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
            # Isolate this from the other tests because we save additional tokens/etc
            _a							=	tempfile.mkdtemp()

            _a							=	" He is very happy, UNwant\u00E9d,running"
            tokenizer.add_tokens(["bim", "bambam"]	)
            _a							=	tokenizer.additional_special_tokens
            additional_special_tokens.append("new_additional_special_token"	)
            tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}	)
            _a							=	tokenizer.encode(a_     ,     add_special_tokens=a_	)
            tokenizer.save_pretrained(a_	)

            _a							=	tokenizer.__class__.from_pretrained(a_	)
            _a							=	after_tokenizer.encode(a_     ,     add_special_tokens=a_	)
            self.assertListEqual(a_     ,     a_	)
            self.assertIn("new_additional_special_token"     ,     after_tokenizer.additional_special_tokens	)
            self.assertEqual(after_tokenizer.model_max_length     ,     4_2	)

            _a							=	tokenizer.__class__.from_pretrained(a_     ,     model_max_length=4_3	)
            self.assertEqual(tokenizer.model_max_length     ,     4_3	)

            shutil.rmtree(a_	)






      def 			lowerCamelCase__    (    self	)	->List[str]:







        '''simple docstring'''


        _a							=	[]
        if self.test_slow_tokenizer:
          tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())	)

        if self.test_rust_tokenizer:
          tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())	)

        for tokenizer_class, tokenizer_utils in tokenizer_list:
          with tempfile.TemporaryDirectory() as tmp_dir:
            tokenizer_utils.save_pretrained(a_	)

            with open(os.path.join(a_     ,     "special_tokens_map.json"	)     ,     encoding="utf-8"	) as json_file:
              _a							=	json.load(a_	)

            with open(os.path.join(a_     ,     "tokenizer_config.json"	)     ,     encoding="utf-8"	) as json_file:
              _a							=	json.load(a_	)

            _a							=	[f'''<extra_id_{i}>''' for i in range(1_2_5	)]

            _a							=	added_tokens_extra_ids + [
                "an_additional_special_token"
            ]
            _a							=	added_tokens_extra_ids + [
                "an_additional_special_token"
            ]

            with open(os.path.join(a_     ,     "special_tokens_map.json"	)     ,     "w"     ,     encoding="utf-8"	) as outfile:
              json.dump(a_     ,     a_	)
            with open(os.path.join(a_     ,     "tokenizer_config.json"	)     ,     "w"     ,     encoding="utf-8"	) as outfile:
              json.dump(a_     ,     a_	)

            # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
            # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
            # "special_tokens_map.json" files
            _a							=	tokenizer_class.from_pretrained(
                a_     ,     )
            self.assertIn(
                "an_additional_special_token"     ,     tokenizer_without_change_in_init.additional_special_tokens	)
            # self.assertIn("an_additional_special_token",tokenizer_without_change_in_init.get_vocab()) # ByT5Tokenization no vocab
            self.assertEqual(
                ["an_additional_special_token"]     ,     tokenizer_without_change_in_init.convert_ids_to_tokens(
                    tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"]	)	)     ,     )

            # Now we test that we can change the value of additional_special_tokens in the from_pretrained
            _a							=	added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"     ,     lstrip=a_	)]
            _a							=	tokenizer_class.from_pretrained(
                a_     ,     additional_special_tokens=a_     ,     )

            self.assertIn("a_new_additional_special_token"     ,     tokenizer.additional_special_tokens	)
            self.assertEqual(
                ["a_new_additional_special_token"]     ,     tokenizer.convert_ids_to_tokens(
                    tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"]	)	)     ,     )






      def 			lowerCamelCase__    (    self	)	->List[str]:







        '''simple docstring'''


        _a							=	[]
        if self.test_slow_tokenizer:
          tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())	)

        if self.test_rust_tokenizer:
          tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())	)

        for tokenizer_class, tokenizer_utils in tokenizer_list:
          with tempfile.TemporaryDirectory() as tmp_dir:
            tokenizer_utils.save_pretrained(a_	)

            _a							=	tokenizer_class.from_pretrained(a_	)

            self.assertTrue(tokenizer.decode([2_5_5]	) == ""	)






      def 			lowerCamelCase__    (    self	)	->Optional[int]:







        '''simple docstring'''


        pass






      def 			lowerCamelCase__    (    self	)	->List[Any]:







        '''simple docstring'''


        pass






      def 			lowerCamelCase__    (    self	)	->Tuple:







        '''simple docstring'''


        pass






      def 			lowerCamelCase__    (    self	)	->List[Any]:







        '''simple docstring'''


        pass






      def 			lowerCamelCase__    (    self	)	->List[Any]:







        '''simple docstring'''


        _a							=	self.get_tokenizers(fast=a_     ,     do_lower_case=a_	)
        for tokenizer in tokenizers:
          with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
            _a							=	["t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "x", "t", "</s>"]
            _a							=	tokenizer.convert_tokens_to_string(a_	)

            self.assertIsInstance(a_     ,     a_	)






      def 			lowerCamelCase__    (    self	)	->Union[str, Any]:







        '''simple docstring'''


        _a							=	self.get_tokenizers()
        for tokenizer in tokenizers:
          with self.subTest(f'''{tokenizer.__class__.__name__}'''	):
            _a							=	[
                "bos_token",
                "eos_token",
                "unk_token",
                "sep_token",
                "pad_token",
                "cls_token",
                "mask_token",
            ]

            _a							=	0
            _a							=	tokenizer.convert_ids_to_tokens(
                a_     ,     skip_special_tokens=a_	)

            for attr in attributes_list:
              setattr(a_     ,     attr + "_id"     ,     a_	)
              self.assertEqual(getattr(a_     ,     a_	)     ,     a_	)
              self.assertEqual(getattr(a_     ,     attr + "_id"	)     ,     a_	)

              setattr(a_     ,     attr + "_id"     ,     a_	)
              self.assertEqual(getattr(a_     ,     a_	)     ,     a_	)
              self.assertEqual(getattr(a_     ,     attr + "_id"	)     ,     a_	)

            setattr(a_     ,     "additional_special_tokens_ids"     ,     []	)
            self.assertListEqual(getattr(a_     ,     "additional_special_tokens"	)     ,     []	)
            self.assertListEqual(getattr(a_     ,     "additional_special_tokens_ids"	)     ,     []	)

            setattr(a_     ,     "additional_special_tokens_ids"     ,     [token_id_to_test_setters]	)
            self.assertListEqual(getattr(a_     ,     "additional_special_tokens"	)     ,     [token_to_test_setters]	)
            self.assertListEqual(getattr(a_     ,     "additional_special_tokens_ids"	)     ,     [token_id_to_test_setters]	)










"""simple docstring"""




import math






def        lowerCAmelCase (      UpperCamelCase_:							int					)       ->							list:







  '''simple docstring'''







  _a							=	[True] * n
  _a							=	False
  _a							=	False
  _a							=	True

  for i in range(3     , int(n**0.5 + 1					)     , 2					):
    _a							=	i * 2
    while index < n:
      _a							=	False
      _a							=	index + i

  _a							=	[2]

  for i in range(3     , UpperCamelCase_     , 2					):
    if is_prime[i]:
      primes.append(UpperCamelCase_					)

  return primes






def        lowerCAmelCase (      UpperCamelCase_:							int = 999966663333					)       ->							int:







  '''simple docstring'''







  _a							=	math.floor(math.sqrt(UpperCamelCase_					)					) + 100
  _a							=	prime_sieve(UpperCamelCase_					)

  _a							=	0
  _a							=	0
  _a							=	primes[prime_index]

  while (last_prime**2) <= limit:
    _a							=	primes[prime_index + 1]

    _a							=	last_prime**2
    _a							=	next_prime**2

    # Get numbers divisible by lps(current)
    _a							=	lower_bound + last_prime
    while upper_bound > current <= limit:
      matches_sum += current
      current += last_prime

    # Reset the upper_bound
    while (upper_bound - next_prime) > limit:
      upper_bound -= next_prime

    # Add the numbers divisible by ups(current)
    _a							=	upper_bound - next_prime
    while current > lower_bound:
      matches_sum += current
      current -= next_prime

    # Remove the numbers divisible by both ups and lps
    _a							=	0
    while upper_bound > current <= limit:
      if current <= lower_bound:
        # Increment the current number
        current += last_prime * next_prime
        continue

      if current > limit:
        break

      # Remove twice since it was added by both ups and lps
      matches_sum -= current * 2

      # Increment the current number
      current += last_prime * next_prime

    # Setup for next pair
    _a							=	next_prime
    prime_index += 1

  return matches_sum


if __name__ == "__main__":
     print(solution())


