


'''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():
  UpperCamelCase__    					=      "pt"
elif is_tf_available():
  UpperCamelCase__    					=      "tf"
else:
  UpperCamelCase__    					=      "jax"




class 			lowerCamelCase_   (	lowerCAmelCase__     ,       unittest.TestCase      ):
      lowerCAmelCase__		     =     PerceiverTokenizer
      lowerCAmelCase__		     =     False






      def lowercase_							(					self				:    Optional[int] ):


          '''simple docstring'''


          super().setUp()
          UpperCAmelCase__			:		List[str]													=				PerceiverTokenizer()
          tokenizer.save_pretrained(self.tmpdirname )






      @cached_property
      def lowercase_							(					self				:    int ):


          '''simple docstring'''


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






      def lowercase_							(					self				:    List[Any]						,						**_A				:    Optional[Any] ):


          '''simple docstring'''


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






      def lowercase_							(					self				:    Tuple						,						_A				:    Dict						,						_A				:    str=False						,						_A				:    List[str]=20						,						_A				:    Optional[Any]=5 ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[int]													=				[]
          for i in range(len(__a ) ):
              try:
                  UpperCAmelCase__			:		Optional[int]													=				tokenizer.decode([i]						,						clean_up_tokenization_spaces=__a )
              except UnicodeDecodeError:
                  pass
              toks.append((i, tok) )

          UpperCAmelCase__			:		Optional[Any]													=				list(filter(lambda _A : re.match(R'''^[ a-zA-Z]+$'''						,						t[1] )						,						__a ) )
          UpperCAmelCase__			:		Optional[int]													=				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:
              UpperCAmelCase__			:		str													=				toks[:max_length]
          if min_length is not None and len(__a ) < min_length and len(__a ) > 0:
              while len(__a ) < min_length:
                  UpperCAmelCase__			:		Union[str, Any]													=				toks + toks
        # toks_str = [t[1] for t in toks]
          UpperCAmelCase__			:		int													=				[t[0] for t in toks]

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






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


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

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

          UpperCAmelCase__			:		Tuple													=				tokenizer('''e è é ê ë''' )
          UpperCAmelCase__			:		Optional[Any]													=				[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
          self.assertEqual(encoded['''input_ids''']						,						__a )
          # decoding
          UpperCAmelCase__			:		List[Any]													=				tokenizer.decode(__a )
          self.assertEqual(__a						,						'''[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				:    List[Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[int]													=				self.perceiver_tokenizer
          UpperCAmelCase__			:		List[Any]													=				['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
          # fmt: off
          UpperCAmelCase__			:		Optional[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
          UpperCAmelCase__			:		List[str]													=				tokenizer(__a						,						padding=__a						,						return_tensors=__a )
          self.assertIsInstance(__a						,						__a )

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

          self.assertListEqual(__a						,						__a )

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






      def lowercase_							(					self				:    Dict ):


          '''simple docstring'''


          UpperCAmelCase__			:		List[Any]													=				self.perceiver_tokenizer
          UpperCAmelCase__			:		Dict													=				['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
          UpperCAmelCase__			:		Any													=				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 lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Optional[int]													=				self.perceiver_tokenizer
          UpperCAmelCase__			:		List[str]													=				[
              '''Summary of the text.''',
              '''Another summary.''',
          ]
          UpperCAmelCase__			:		int													=				tokenizer(
              text_target=__a						,						max_length=32						,						padding='''max_length'''						,						truncation=__a						,						return_tensors=__a )
          self.assertEqual(32						,						targets['''input_ids'''].shape[1] )






      def lowercase_							(					self				:    List[str] ):


          '''simple docstring'''


          UpperCAmelCase__			:		str													=				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
          UpperCAmelCase__			:		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
                  UpperCAmelCase__			:		Optional[int]													=				tempfile.mkdtemp()

                  UpperCAmelCase__			:		List[str]													=				''' He is very happy, UNwant\u00E9d,running'''
                  UpperCAmelCase__			:		Any													=				tokenizer.encode(__a						,						add_special_tokens=__a )
                  tokenizer.save_pretrained(__a )

                  UpperCAmelCase__			:		Any													=				tokenizer.__class__.from_pretrained(__a )
                  UpperCAmelCase__			:		Dict													=				after_tokenizer.encode(__a						,						add_special_tokens=__a )
                  self.assertListEqual(__a						,						__a )

                  shutil.rmtree(__a )

          UpperCAmelCase__			:		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
                  UpperCAmelCase__			:		Any													=				tempfile.mkdtemp()

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

                  UpperCAmelCase__			:		str													=				tokenizer.__class__.from_pretrained(__a )
                  UpperCAmelCase__			:		Optional[Any]													=				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						,						42 )

                  UpperCAmelCase__			:		List[str]													=				tokenizer.__class__.from_pretrained(__a						,						model_max_length=43 )
                  self.assertEqual(tokenizer.model_max_length						,						43 )

                  shutil.rmtree(__a )






      def lowercase_							(					self				:    Optional[int] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Tuple													=				[]
          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:
                      UpperCAmelCase__			:		List[Any]													=				json.load(__a )

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

                  UpperCAmelCase__			:		str													=				[f"""<extra_id_{i}>""" for i in range(125 )]

                  UpperCAmelCase__			:		Tuple													=				added_tokens_extra_ids + [
                      '''an_additional_special_token'''
                  ]
                  UpperCAmelCase__			:		Dict													=				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
                  UpperCAmelCase__			:		Optional[Any]													=				tokenizer_class.from_pretrained(
                      __a						,						)
                  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__			:		Optional[int]													=				added_tokens_extra_ids + [AddedToken('''a_new_additional_special_token'''						,						lstrip=__a )]
                  UpperCAmelCase__			:		Union[str, Any]													=				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 lowercase_							(					self				:    Union[str, Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		List[Any]													=				self.perceiver_tokenizer
          self.assertEqual(tokenizer.decode([178] )						,						'''�''' )






      def lowercase_							(					self				:    Any ):


          '''simple docstring'''


          pass






      def lowercase_							(					self				:    Dict ):


          '''simple docstring'''


          pass






      def lowercase_							(					self				:    Optional[int] ):


          '''simple docstring'''


          pass






      def lowercase_							(					self				:    Union[str, Any] ):


          '''simple docstring'''


          pass






      def lowercase_							(					self				:    Optional[Any] ):


          '''simple docstring'''


          UpperCAmelCase__			:		Any													=				self.get_tokenizers(fast=__a						,						do_lower_case=__a )
          for tokenizer in tokenizers:
              with self.subTest(f"""{tokenizer.__class__.__name__}""" ):
                  UpperCAmelCase__			:		Dict													=				['''[CLS]''', '''t''', '''h''', '''i''', '''s''', ''' ''', '''i''', '''s''', ''' ''', '''a''', ''' ''', '''t''', '''e''', '''s''', '''t''', '''[SEP]''']
                  UpperCAmelCase__			:		List[str]													=				tokenizer.convert_tokens_to_string(__a )

                  self.assertIsInstance(__a						,						__a )




"""simple docstring"""


from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class   _UpperCamelCase  :
							'''simple docstring'''







							pass




