'''simple docstring'''


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():
 snake_case__					:      Optional[Any]				      =  '''pt'''
elif is_tf_available():
 snake_case__					:      Tuple				      =  '''tf'''
else:
 snake_case__					:      Dict				      =  '''jax'''






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_						,     unittest.TestCase	):







  '''simple docstring'''






  lowerCamelCase_		:List[Any]						   =		PerceiverTokenizer
  lowerCamelCase_		:Optional[int]						   =		False


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       super().setUp()
       UpperCAmelCase_							:       Tuple       =				PerceiverTokenizer()
       tokenizer.save_pretrained(self.tmpdirname						)


  @cached_property
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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


  def _UpperCamelCase					(			self				,		**snake_case_						):




       '''simple docstring'''

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


  def _UpperCamelCase					(			self				,		snake_case_				,		snake_case_=False				,		snake_case_=2_0				,		snake_case_=5						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				[]
       for i in range(len(snake_case_						)						):
            try:
                 UpperCAmelCase_							:       Tuple       =				tokenizer.decode([i]				,		clean_up_tokenization_spaces=snake_case_						)
            except UnicodeDecodeError:
                 pass
            toks.append((i, tok)						)

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

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				self.perceiver_tokenizer
       UpperCAmelCase_							:       Tuple       =				'Unicode €.'
       UpperCAmelCase_							:       List[str]       =				tokenizer(snake_case_						)
       UpperCAmelCase_							:       str       =				[4, 9_1, 1_1_6, 1_1_1, 1_0_5, 1_1_7, 1_0_6, 1_0_7, 3_8, 2_3_2, 1_3_6, 1_7_8, 5_2, 5]
       self.assertEqual(encoded['input_ids']				,		snake_case_						)

       # decoding
       UpperCAmelCase_							:       str       =				tokenizer.decode(snake_case_						)
       self.assertEqual(snake_case_				,		'[CLS]Unicode €.[SEP]'						)

       UpperCAmelCase_							:       Any       =				tokenizer('e è é ê ë'						)
       UpperCAmelCase_							:       Optional[int]       =				[4, 1_0_7, 3_8, 2_0_1, 1_7_4, 3_8, 2_0_1, 1_7_5, 3_8, 2_0_1, 1_7_6, 3_8, 2_0_1, 1_7_7, 5]
       self.assertEqual(encoded['input_ids']				,		snake_case_						)
       # decoding
       UpperCAmelCase_							:       Optional[Any]       =				tokenizer.decode(snake_case_						)
       self.assertEqual(snake_case_				,		'[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 _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Tuple       =				self.perceiver_tokenizer
       UpperCAmelCase_							:       List[str]       =				['A long paragraph for summarization.', 'Another paragraph for summarization.']
       # fmt: off
       UpperCAmelCase_							:       Any       =				[4, 7_1, 3_8, 1_1_4, 1_1_7, 1_1_6, 1_0_9, 3_8, 1_1_8, 1_0_3, 1_2_0, 1_0_3, 1_0_9, 1_2_0, 1_0_3, 1_1_8, 1_1_0, 3_8, 1_0_8, 1_1_7, 1_2_0, 3_8, 1_2_1, 1_2_3, 1_1_5, 1_1_5, 1_0_3, 1_2_0, 1_1_1, 1_2_8, 1_0_3, 1_2_2, 1_1_1, 1_1_7, 1_1_6, 5_2, 5, 0]
       # fmt: on
       UpperCAmelCase_							:       Union[str, Any]       =				tokenizer(snake_case_				,		padding=snake_case_				,		return_tensors=snake_case_						)
       self.assertIsInstance(snake_case_				,		snake_case_						)

       if FRAMEWORK != "jax":
            UpperCAmelCase_							:       int       =				list(batch.input_ids.numpy()[0]						)
       else:
            UpperCAmelCase_							:       List[Any]       =				list(batch.input_ids.tolist()[0]						)

       self.assertListEqual(snake_case_				,		snake_case_						)

       self.assertEqual((2, 3_8)				,		batch.input_ids.shape						)
       self.assertEqual((2, 3_8)				,		batch.attention_mask.shape						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

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


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Dict       =				self.perceiver_tokenizer
       UpperCAmelCase_							:       Dict       =				[
           'Summary of the text.',
           'Another summary.',
       ]
       UpperCAmelCase_							:       Union[str, Any]       =				tokenizer(
           text_target=snake_case_				,		max_length=3_2				,		padding='max_length'				,		truncation=snake_case_				,		return_tensors=snake_case_						)
       self.assertEqual(3_2				,		targets['input_ids'].shape[1]						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Any       =				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
       UpperCAmelCase_							:       Any       =				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
                 UpperCAmelCase_							:       Tuple       =				tempfile.mkdtemp()

                 UpperCAmelCase_							:       List[str]       =				' He is very happy, UNwant\u00E9d,running'
                 UpperCAmelCase_							:       Optional[int]       =				tokenizer.encode(snake_case_				,		add_special_tokens=snake_case_						)
                 tokenizer.save_pretrained(snake_case_						)

                 UpperCAmelCase_							:       Optional[int]       =				tokenizer.__class__.from_pretrained(snake_case_						)
                 UpperCAmelCase_							:       Union[str, Any]       =				after_tokenizer.encode(snake_case_				,		add_special_tokens=snake_case_						)
                 self.assertListEqual(snake_case_				,		snake_case_						)

                 shutil.rmtree(snake_case_						)

       UpperCAmelCase_							:       int       =				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
                 UpperCAmelCase_							:       Union[str, Any]       =				tempfile.mkdtemp()

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

                 UpperCAmelCase_							:       List[str]       =				tokenizer.__class__.from_pretrained(snake_case_						)
                 UpperCAmelCase_							:       Any       =				after_tokenizer.encode(snake_case_				,		add_special_tokens=snake_case_						)
                 self.assertListEqual(snake_case_				,		snake_case_						)
                 self.assertIn('new_additional_special_token'				,		after_tokenizer.additional_special_tokens						)
                 self.assertEqual(after_tokenizer.model_max_length				,		4_2						)

                 UpperCAmelCase_							:       str       =				tokenizer.__class__.from_pretrained(snake_case_				,		model_max_length=4_3						)
                 self.assertEqual(tokenizer.model_max_length				,		4_3						)

                 shutil.rmtree(snake_case_						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				[]
       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(snake_case_						)

                 with open(os.path.join(snake_case_				,		'special_tokens_map.json'						)				,		encoding='utf-8'						) as json_file:
                      UpperCAmelCase_							:       Dict       =				json.load(snake_case_						)

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

                 UpperCAmelCase_							:       int       =				[F'''<extra_id_{i}>''' for i in range(1_2_5						)]

                 UpperCAmelCase_							:       Dict       =				added_tokens_extra_ids + [
                     'an_additional_special_token'
                 ]
                 UpperCAmelCase_							:       Union[str, Any]       =				added_tokens_extra_ids + [
                     'an_additional_special_token'
                 ]

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

                 # 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
                 UpperCAmelCase_							:       str       =				tokenizer_class.from_pretrained(
                     snake_case_				,		)
                 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
                 UpperCAmelCase_							:       Tuple       =				added_tokens_extra_ids + [AddedToken('a_new_additional_special_token'				,		lstrip=snake_case_						)]
                 UpperCAmelCase_							:       Optional[int]       =				tokenizer_class.from_pretrained(
                     snake_case_				,		additional_special_tokens=snake_case_				,		)

                 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 _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[Any]       =				self.perceiver_tokenizer
       self.assertEqual(tokenizer.decode([1_7_8]						)				,		'�'						)


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       pass


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       pass


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       pass


  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       pass






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[str]       =				self.get_tokenizers(fast=snake_case_				,		do_lower_case=snake_case_						)
       for tokenizer in tokenizers:
            with self.subTest(F'''{tokenizer.__class__.__name__}'''						):
                 UpperCAmelCase_							:       Optional[Any]       =				['[CLS]', 't', 'h', 'i', 's', ' ', 'i', 's', ' ', 'a', ' ', 't', 'e', 's', 't', '[SEP]']
                 UpperCAmelCase_							:       Tuple       =				tokenizer.convert_tokens_to_string(snake_case_						)

                 self.assertIsInstance(snake_case_				,		snake_case_						)







'''simple docstring'''


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     UpperCAmelCase_							:       Optional[int]       =				[0] * len(lowerCamelCase_       )

     for i in range(1     ,					len(lowerCamelCase_       )       ):
          # use last results for better performance - dynamic programming
          UpperCAmelCase_							:       List[Any]       =				prefix_result[i - 1]
          while j > 0 and input_string[i] != input_string[j]:
               UpperCAmelCase_							:       str       =				prefix_result[j - 1]

          if input_string[i] == input_string[j]:
               j += 1
          UpperCAmelCase_							:       Any       =				j

     return prefix_result


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     return max(prefix_function(lowerCamelCase_       )       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






