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

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

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
      SCREAMING_SNAKE_CASE__		:					List[str]						=					"pt"
elif is_tf_available():
      SCREAMING_SNAKE_CASE__		:					str						=					"tf"
else:
      SCREAMING_SNAKE_CASE__		:					str						=					"jax"

class       snake_case					(      lowercase__   ,						unittest.TestCase						):
  lowercase_			=     PerceiverTokenizer
  lowercase_			=     False




  def 	__lowercase(      self     :	List[Any]				)->       int:




       """simple docstring"""
       super().setUp()
       __A				:				Tuple			=		PerceiverTokenizer()
       tokenizer.save_pretrained(self.tmpdirname				)




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




       """simple docstring"""
       return PerceiverTokenizer.from_pretrained('deepmind/language-perceiver'				)




  def 	__lowercase(      self     :	Union[str, Any]     , **a_     :	str				)->       str:




       """simple docstring"""
       return self.tokenizer_class.from_pretrained(self.tmpdirname     , **__lowerCamelCase				)




  def 	__lowercase(      self     :	Any     , a_     :	Union[str, Any]     , a_     :	Dict=False     , a_     :	int=20     , a_     :	Optional[Any]=5				)->       Any:




       """simple docstring"""
       __A				:				Tuple			=		[]
       for i in range(len(__lowerCamelCase				)				):
            try:
                 __A				:				Any			=		tokenizer.decode([i]     , clean_up_tokenization_spaces=__lowerCamelCase				)
            except UnicodeDecodeError:
                 pass
            toks.append((i, tok)				)

       __A				:				Union[str, Any]			=		list(filter(lambda a_				: re.match(r'^[ a-zA-Z]+$'     , t[1]				)     , __lowerCamelCase				)				)
       __A				:				List[str]			=		list(filter(lambda a_				: [t[0]] == tokenizer.encode(t[1]     , add_special_tokens=__lowerCamelCase				)     , __lowerCamelCase				)				)
       if max_length is not None and len(__lowerCamelCase				) > max_length:
            __A				:				Union[str, Any]			=		toks[:max_length]
       if min_length is not None and len(__lowerCamelCase				) < min_length and len(__lowerCamelCase				) > 0:
            while len(__lowerCamelCase				) < min_length:
                 __A				:				Dict			=		toks + toks
        # toks_str = [t[1] for t in toks]
       __A				:				Tuple			=		[t[0] for t in toks]

       # Ensure consistency
       __A				:				Optional[int]			=		tokenizer.decode(__lowerCamelCase     , clean_up_tokenization_spaces=__lowerCamelCase				)
       if " " not in output_txt and len(__lowerCamelCase				) > 1:
            __A				:				Any			=		(
                tokenizer.decode([toks_ids[0]]     , clean_up_tokenization_spaces=__lowerCamelCase				)
                + " "
                + tokenizer.decode(toks_ids[1:]     , clean_up_tokenization_spaces=__lowerCamelCase				)
            )
       if with_prefix_space:
            __A				:				Union[str, Any]			=		" " + output_txt
       __A				:				List[Any]			=		tokenizer.encode(__lowerCamelCase     , add_special_tokens=__lowerCamelCase				)
       return output_txt, output_ids




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




       """simple docstring"""
       __A				:				Optional[int]			=		self.perceiver_tokenizer
       __A				:				Optional[Any]			=		"Unicode €."
       __A				:				Dict			=		tokenizer(__lowerCamelCase				)
       __A				:				List[str]			=		[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
       self.assertEqual(encoded['input_ids']     , __lowerCamelCase				)

       # decoding
       __A				:				Any			=		tokenizer.decode(__lowerCamelCase				)
       self.assertEqual(__lowerCamelCase     , '[CLS]Unicode €.[SEP]'				)

       __A				:				int			=		tokenizer('e è é ê ë'				)
       __A				:				List[Any]			=		[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
       self.assertEqual(encoded['input_ids']     , __lowerCamelCase				)
       # decoding
       __A				:				str			=		tokenizer.decode(__lowerCamelCase				)
       self.assertEqual(__lowerCamelCase     , '[CLS]e è é ê ë[SEP]'				)

       # encode/decode, but with `encode` instead of `__call__`
       self.assertEqual(tokenizer.decode(tokenizer.encode('e è é ê ë'				)				)     , '[CLS]e è é ê ë[SEP]'				)




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




       """simple docstring"""
       __A				:				Union[str, Any]			=		self.perceiver_tokenizer
       __A				:				Optional[int]			=		["A long paragraph for summarization.", "Another paragraph for summarization."]
       # fmt: off
       __A				:				Any			=		[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
       # fmt: on
       __A				:				str			=		tokenizer(__lowerCamelCase     , padding=__lowerCamelCase     , return_tensors=__lowerCamelCase				)
       self.assertIsInstance(__lowerCamelCase     , __lowerCamelCase				)

       if FRAMEWORK != "jax":
            __A				:				Union[str, Any]			=		list(batch.input_ids.numpy()[0]				)
       else:
            __A				:				int			=		list(batch.input_ids.tolist()[0]				)

       self.assertListEqual(__lowerCamelCase     , __lowerCamelCase				)

       self.assertEqual((2, 38)     , batch.input_ids.shape				)
       self.assertEqual((2, 38)     , batch.attention_mask.shape				)




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




       """simple docstring"""
       __A				:				Union[str, Any]			=		self.perceiver_tokenizer
       __A				:				Optional[int]			=		["A long paragraph for summarization.", "Another paragraph for summarization."]
       __A				:				List[Any]			=		tokenizer(__lowerCamelCase     , padding=__lowerCamelCase     , return_tensors=__lowerCamelCase				)
       # check if input_ids are returned and no decoder_input_ids
       self.assertIn('input_ids'     , __lowerCamelCase				)
       self.assertIn('attention_mask'     , __lowerCamelCase				)
       self.assertNotIn('decoder_input_ids'     , __lowerCamelCase				)
       self.assertNotIn('decoder_attention_mask'     , __lowerCamelCase				)




  def 	__lowercase(      self     :	Tuple				)->       str:




       """simple docstring"""
       __A				:				Tuple			=		self.perceiver_tokenizer
       __A				:				Tuple			=		[
           "Summary of the text.",
           "Another summary.",
       ]
       __A				:				List[Any]			=		tokenizer(
           text_target=__lowerCamelCase     , max_length=32     , padding='max_length'     , truncation=__lowerCamelCase     , return_tensors=__lowerCamelCase				)
       self.assertEqual(32     , targets['input_ids'].shape[1]				)




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




       """simple docstring"""
       __A				:				Union[str, Any]			=		self.get_tokenizers()
       for tokenizer in tokenizers:
            with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
                 self.assertNotEqual(tokenizer.model_max_length     , 42				)

        # Now let's start the test
       __A				:				List[str]			=		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				:				int			=		tempfile.mkdtemp()

                 __A				:				List[Any]			=		" He is very happy, UNwant\u00E9d,running"
                 __A				:				Any			=		tokenizer.encode(__lowerCamelCase     , add_special_tokens=__lowerCamelCase				)
                 tokenizer.save_pretrained(__lowerCamelCase				)

                 __A				:				Optional[int]			=		tokenizer.__class__.from_pretrained(__lowerCamelCase				)
                 __A				:				str			=		after_tokenizer.encode(__lowerCamelCase     , add_special_tokens=__lowerCamelCase				)
                 self.assertListEqual(__lowerCamelCase     , __lowerCamelCase				)

                 shutil.rmtree(__lowerCamelCase				)

       __A				:				int			=		self.get_tokenizers(model_max_length=42				)
       for tokenizer in tokenizers:
            with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
                 # Isolate this from the other tests because we save additional tokens/etc
                 __A				:				str			=		tempfile.mkdtemp()

                 __A				:				Optional[Any]			=		" He is very happy, UNwant\u00E9d,running"
                 tokenizer.add_tokens(['bim', 'bambam']				)
                 __A				:				List[str]			=		tokenizer.additional_special_tokens
                 additional_special_tokens.append('new_additional_special_token'				)
                 tokenizer.add_special_tokens({'additional_special_tokens': additional_special_tokens}				)
                 __A				:				Union[str, Any]			=		tokenizer.encode(__lowerCamelCase     , add_special_tokens=__lowerCamelCase				)
                 tokenizer.save_pretrained(__lowerCamelCase				)

                 __A				:				Union[str, Any]			=		tokenizer.__class__.from_pretrained(__lowerCamelCase				)
                 __A				:				Union[str, Any]			=		after_tokenizer.encode(__lowerCamelCase     , add_special_tokens=__lowerCamelCase				)
                 self.assertListEqual(__lowerCamelCase     , __lowerCamelCase				)
                 self.assertIn('new_additional_special_token'     , after_tokenizer.additional_special_tokens				)
                 self.assertEqual(after_tokenizer.model_max_length     , 42				)

                 __A				:				Any			=		tokenizer.__class__.from_pretrained(__lowerCamelCase     , model_max_length=43				)
                 self.assertEqual(tokenizer.model_max_length     , 43				)

                 shutil.rmtree(__lowerCamelCase				)




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




       """simple docstring"""
       __A				:				Optional[Any]			=		[]
       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(__lowerCamelCase				)

                 with open(os.path.join(__lowerCamelCase     , 'special_tokens_map.json'				)     , encoding='utf-8'				) as json_file:
                      __A				:				Union[str, Any]			=		json.load(__lowerCamelCase				)

                 with open(os.path.join(__lowerCamelCase     , 'tokenizer_config.json'				)     , encoding='utf-8'				) as json_file:
                      __A				:				List[str]			=		json.load(__lowerCamelCase				)

                 __A				:				int			=		[F'''<extra_id_{i}>''' for i in range(125				)]

                 __A				:				List[Any]			=		added_tokens_extra_ids + [
                     "an_additional_special_token"
                 ]
                 __A				:				List[str]			=		added_tokens_extra_ids + [
                     "an_additional_special_token"
                 ]

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

                 # 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				:				List[Any]			=		tokenizer_class.from_pretrained(
                     __lowerCamelCase     , )
                 self.assertIn(
                     'an_additional_special_token'     , tokenizer_without_change_in_init.additional_special_tokens				)
                 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				:				int			=		added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'     , lstrip=__lowerCamelCase				)]
                 __A				:				Any			=		tokenizer_class.from_pretrained(
                     __lowerCamelCase     , additional_special_tokens=__lowerCamelCase     , )

                 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 	__lowercase(      self     :	int				)->       Optional[Any]:




       """simple docstring"""
       __A				:				Optional[Any]			=		self.perceiver_tokenizer
       self.assertEqual(tokenizer.decode([178]				)     , '�'				)




  def 	__lowercase(      self     :	str				)->       Tuple:




       """simple docstring"""
       pass




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




       """simple docstring"""
       pass




  def 	__lowercase(      self     :	int				)->       int:




       """simple docstring"""
       pass




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




       """simple docstring"""
       pass




  def 	__lowercase(      self     :	Union[str, Any]				)->       Optional[int]:




       """simple docstring"""
       __A				:				Optional[int]			=		self.get_tokenizers(fast=__lowerCamelCase     , do_lower_case=__lowerCamelCase				)
       for tokenizer in tokenizers:
            with self.subTest(F'''{tokenizer.__class__.__name__}'''				):
                 __A				:				Union[str, Any]			=		["[CLS]", "t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "s", "t", "[SEP]"]
                 __A				:				str			=		tokenizer.convert_tokens_to_string(__lowerCamelCase				)

                 self.assertIsInstance(__lowerCamelCase     , __lowerCamelCase				)




import math







def     _a				(      lowercase__  :			int ):







     '''simple docstring'''


     assert isinstance(lowercase__     ,  lowercase__ ) and (
         number >= 0
     ), "'number' must been an int and positive"

     if 1 < number < 4:
          # 2 and 3 are primes
          return True
     elif number < 2 or not number % 2:
          # Negatives, 0, 1 and all even numbers are not primes
          return False

     SCREAMING_SNAKE_CASE__				:				Tuple			=		range(3     ,  int(math.sqrt(lowercase__ ) + 1 )     ,  2 )
     return not any(not number % i for i in odd_numbers )







def     _a				(      lowercase__  :			List[str]     ,  lowercase__  :			Any=1     ,  **lowercase__  :			Any ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				int			=		factor * value
     SCREAMING_SNAKE_CASE__				:				Dict			=		value

     while not is_prime(lowercase__ ):
          value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

     if value == first_value_val:
          return next_prime(value + 1     ,  **lowercase__ )
     return value



