





import os
import unittest

from transformers import ElectraTokenizerFast
from transformers.models.electra.tokenization_electra import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    ElectraTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english



@require_tokenizers
class 				_UpperCamelCase       (						lowerCAmelCase_	,    unittest.TestCase  ):
       _UpperCamelCase					:       Tuple       = ElectraTokenizer
       _UpperCamelCase					:       Any       = ElectraTokenizerFast
       _UpperCamelCase					:       Dict       = True
       _UpperCamelCase					:       Optional[int]       = True
       _UpperCamelCase					:       Union[str, Any]       = filter_non_english

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




              """simple docstring"""


              super().setUp()

              UpperCamelCase_ 							=	[
                  "[UNK]",
                  "[CLS]",
                  "[SEP]",
                  "[PAD]",
                  "[MASK]",
                  "want",
                  "##want",
                  "##ed",
                  "wa",
                  "un",
                  "runn",
                  "##ing",
                  ",",
                  "low",
                  "lowest",
              ]
              UpperCamelCase_ 							=	os.path.join(self.tmpdirname       , VOCAB_FILES_NAMES["vocab_file"]		)
              with open(self.vocab_file       , "w"       , encoding="utf-8"		) as vocab_writer:
                     vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	"UNwant\u00E9d,running"
              UpperCamelCase_ 							=	"unwanted, running"
              return input_text, output_text

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




              """simple docstring"""


              UpperCamelCase_ 							=	self.tokenizer_class(self.vocab_file		)

              UpperCamelCase_ 							=	tokenizer.tokenize("UNwant\u00E9d,running"		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , ["un", "##want", "##ed", ",", "runn", "##ing"]		)
              self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE		)       , [9, 6, 7, 12, 10, 11]		)

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




              """simple docstring"""


              if not self.test_rust_tokenizer:
                     return

              UpperCamelCase_ 							=	self.get_tokenizer()
              UpperCamelCase_ 							=	self.get_rust_tokenizer()

              UpperCamelCase_ 							=	"UNwant\u00E9d,running"

              UpperCamelCase_ 							=	tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	tokenizer.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	self.get_rust_tokenizer()
              UpperCamelCase_ 							=	tokenizer.encode(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.encode(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              # With lower casing
              UpperCamelCase_ 							=	self.get_tokenizer(do_lower_case=_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	self.get_rust_tokenizer(do_lower_case=_SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	"UNwant\u00E9d,running"

              UpperCamelCase_ 							=	tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	tokenizer.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	self.get_rust_tokenizer()
              UpperCamelCase_ 							=	tokenizer.encode(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	rust_tokenizer.encode(_SCREAMING_SNAKE_CASE		)
              self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

       def lowercase			(		self:			str		)							->			str:




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer()

              self.assertListEqual(tokenizer.tokenize("ah\u535A\u63A8zz"		)       , ["ah", "\u535A", "\u63A8", "zz"]		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "		)       , ["hello", "!", "how", "are", "you", "?"]		)
              self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)       , ["hello"]		)

       def lowercase			(		self:			List[Any]		)							->			Tuple:




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE       , strip_accents=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)       , ["hällo", "!", "how", "are", "you", "?"]		)
              self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)       , ["h\u00E9llo"]		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE       , strip_accents=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)       , ["hallo", "!", "how", "are", "you", "?"]		)
              self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)       , ["hello"]		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)       , ["hallo", "!", "how", "are", "you", "?"]		)
              self.assertListEqual(tokenizer.tokenize("H\u00E9llo"		)       , ["hello"]		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHeLLo!how  \n Are yoU?  "		)       , ["HeLLo", "!", "how", "Are", "yoU", "?"]		)

       def lowercase			(		self:			Dict		)							->			List[Any]:




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE       , strip_accents=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)       , ["HäLLo", "!", "how", "Are", "yoU", "?"]		)

       def lowercase			(		self:			Optional[int]		)							->			str:




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE       , strip_accents=_SCREAMING_SNAKE_CASE		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHäLLo!how  \n Are yoU?  "		)       , ["HaLLo", "!", "how", "Are", "yoU", "?"]		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	BasicTokenizer(do_lower_case=_SCREAMING_SNAKE_CASE       , never_split=["[UNK]"]		)

              self.assertListEqual(
                  tokenizer.tokenize(" \tHeLLo!how  \n Are yoU? [UNK]"		)       , ["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"]		)

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




              """simple docstring"""


              UpperCamelCase_ 							=	["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"]

              UpperCamelCase_ 							=	{}
              for i, token in enumerate(_SCREAMING_SNAKE_CASE		):
                     UpperCamelCase_ 							=	i
              UpperCamelCase_ 							=	WordpieceTokenizer(vocab=_SCREAMING_SNAKE_CASE       , unk_token="[UNK]"		)

              self.assertListEqual(tokenizer.tokenize(""		)       , []		)

              self.assertListEqual(tokenizer.tokenize("unwanted running"		)       , ["un", "##want", "##ed", "runn", "##ing"]		)

              self.assertListEqual(tokenizer.tokenize("unwantedX running"		)       , ["[UNK]", "runn", "##ing"]		)

       def lowercase			(		self:			Dict		)							->			Tuple:




              """simple docstring"""


              self.assertTrue(_is_whitespace(" "		)		)
              self.assertTrue(_is_whitespace("\t"		)		)
              self.assertTrue(_is_whitespace("\r"		)		)
              self.assertTrue(_is_whitespace("\n"		)		)
              self.assertTrue(_is_whitespace("\u00A0"		)		)

              self.assertFalse(_is_whitespace("A"		)		)
              self.assertFalse(_is_whitespace("-"		)		)

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




              """simple docstring"""


              self.assertTrue(_is_control("\u0005"		)		)

              self.assertFalse(_is_control("A"		)		)
              self.assertFalse(_is_control(" "		)		)
              self.assertFalse(_is_control("\t"		)		)
              self.assertFalse(_is_control("\r"		)		)

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




              """simple docstring"""


              self.assertTrue(_is_punctuation("-"		)		)
              self.assertTrue(_is_punctuation("$"		)		)
              self.assertTrue(_is_punctuation("`"		)		)
              self.assertTrue(_is_punctuation("."		)		)

              self.assertFalse(_is_punctuation("A"		)		)
              self.assertFalse(_is_punctuation(" "		)		)

       def lowercase			(		self:			Any		)							->			Dict:




              """simple docstring"""


              UpperCamelCase_ 							=	self.get_tokenizer()
              UpperCamelCase_ 							=	self.get_rust_tokenizer()

              # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
              self.assertListEqual([tokenizer.tokenize(_SCREAMING_SNAKE_CASE		) for t in ["Test", "\xad", "test"]]       , [["[UNK]"], [], ["[UNK]"]]		)

              self.assertListEqual(
                  [rust_tokenizer.tokenize(_SCREAMING_SNAKE_CASE		) for t in ["Test", "\xad", "test"]]       , [["[UNK]"], [], ["[UNK]"]]		)

       @slow
       def lowercase			(		self:			List[Any]		)							->			Dict:




              """simple docstring"""


              UpperCamelCase_ 							=	self.tokenizer_class.from_pretrained("google/electra-base-discriminator"		)

              UpperCamelCase_ 							=	tokenizer.encode("sequence builders"       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	tokenizer.encode("multi-sequence build"       , add_special_tokens=_SCREAMING_SNAKE_CASE		)

              UpperCamelCase_ 							=	tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE		)
              UpperCamelCase_ 							=	tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

              assert encoded_sentence == [101] + text + [102]
              assert encoded_pair == [101] + text + [102] + text_a + [102]

       def lowercase			(		self:			List[str]		)							->			int:




              """simple docstring"""


              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
                            UpperCamelCase_ 							=	self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)

                            UpperCamelCase_ 							=	f'''A, naïve {tokenizer_r.mask_token} AllenNLP sentence.'''
                            UpperCamelCase_ 							=	tokenizer_r.encode_plus(
                                _SCREAMING_SNAKE_CASE       , return_attention_mask=_SCREAMING_SNAKE_CASE       , return_token_type_ids=_SCREAMING_SNAKE_CASE       , return_offsets_mapping=_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE       , )

                            UpperCamelCase_ 							=	tokenizer_r.do_lower_case if hasattr(_SCREAMING_SNAKE_CASE       , "do_lower_case"		) else False
                            UpperCamelCase_ 							=	(
                                [
                                    ((0, 0), tokenizer_r.cls_token),
                                    ((0, 1), "A"),
                                    ((1, 2), ","),
                                    ((3, 5), "na"),
                                    ((5, 6), "##ï"),
                                    ((6, 8), "##ve"),
                                    ((9, 15), tokenizer_r.mask_token),
                                    ((16, 21), "Allen"),
                                    ((21, 23), "##NL"),
                                    ((23, 24), "##P"),
                                    ((25, 33), "sentence"),
                                    ((33, 34), "."),
                                    ((0, 0), tokenizer_r.sep_token),
                                ]
                                if not do_lower_case
                                else [
                                    ((0, 0), tokenizer_r.cls_token),
                                    ((0, 1), "a"),
                                    ((1, 2), ","),
                                    ((3, 8), "naive"),
                                    ((9, 15), tokenizer_r.mask_token),
                                    ((16, 21), "allen"),
                                    ((21, 23), "##nl"),
                                    ((23, 24), "##p"),
                                    ((25, 33), "sentence"),
                                    ((33, 34), "."),
                                    ((0, 0), tokenizer_r.sep_token),
                                ]
                            )

                            self.assertEqual(
                                [e[1] for e in expected_results]       , tokenizer_r.convert_ids_to_tokens(tokens["input_ids"]		)		)
                            self.assertEqual([e[0] for e in expected_results]       , tokens["offset_mapping"]		)



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




              """simple docstring"""


              UpperCamelCase_ 							=	["的", "人", "有"]
              UpperCamelCase_ 							=	"".join(_SCREAMING_SNAKE_CASE		)
              for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                     with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
                            UpperCamelCase_ 							=	True
                            UpperCamelCase_ 							=	self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)
                            UpperCamelCase_ 							=	self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)

                            UpperCamelCase_ 							=	tokenizer_p.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
                            UpperCamelCase_ 							=	tokenizer_r.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)

                            UpperCamelCase_ 							=	tokenizer_r.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)
                            UpperCamelCase_ 							=	tokenizer_p.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)

                            # it is expected that each Chinese character is not preceded by "##"
                            self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)
                            self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)

                            UpperCamelCase_ 							=	False
                            UpperCamelCase_ 							=	self.rust_tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)
                            UpperCamelCase_ 							=	self.tokenizer_class.from_pretrained(_SCREAMING_SNAKE_CASE       , **_SCREAMING_SNAKE_CASE		)

                            UpperCamelCase_ 							=	tokenizer_r.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)
                            UpperCamelCase_ 							=	tokenizer_p.encode(_SCREAMING_SNAKE_CASE       , add_special_tokens=_SCREAMING_SNAKE_CASE		)

                            UpperCamelCase_ 							=	tokenizer_r.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)
                            UpperCamelCase_ 							=	tokenizer_p.convert_ids_to_tokens(_SCREAMING_SNAKE_CASE		)

                            # it is expected that only the first Chinese character is not preceded by "##".
                            UpperCamelCase_ 							=	[
                                f'''##{token}''' if idx != 0 else token for idx, token in enumerate(_SCREAMING_SNAKE_CASE		)
                            ]
                            self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)
                            self.assertListEqual(_SCREAMING_SNAKE_CASE       , _SCREAMING_SNAKE_CASE		)









"""simple docstring"""



import json
import os
import random
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
    from PIL import Image

    from transformers import FlavaImageProcessor, FlavaProcessor
    from transformers.models.flava.image_processing_flava import (
        FLAVA_CODEBOOK_MEAN,
        FLAVA_CODEBOOK_STD,
        FLAVA_IMAGE_MEAN,
        FLAVA_IMAGE_STD,
    )

@require_vision
class 			a	(  unittest.TestCase      ):







    def      UpperCamelCase_ (     self			):
      lowercase				       =			tempfile.mkdtemp()

      # fmt: off
      lowercase				       =			['[UNK]', '[CLS]', '[SEP]', '[PAD]', '[MASK]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing', ',', 'low', 'lowest']
      # fmt: on
      lowercase				       =			os.path.join(self.tmpdirname				,						VOCAB_FILES_NAMES['vocab_file']			)

      with open(self.vocab_file				,						'w'				,						encoding='utf-8'			) as fp:
        fp.write(''.join([x + '\n' for x in vocab_tokens]			)			)

      lowercase				       =			{
          'image_mean': FLAVA_IMAGE_MEAN,
          'image_std': FLAVA_IMAGE_STD,
          'do_normalize': True,
          'do_resize': True,
          'size': 2_2_4,
          'do_center_crop': True,
          'crop_size': 2_2_4,
          'input_size_patches': 1_4,
          'total_mask_patches': 7_5,
          'mask_group_max_patches': None,
          'mask_group_min_patches': 1_6,
          'mask_group_min_aspect_ratio': 0.3,
          'mask_group_max_aspect_ratio': None,
          'codebook_do_resize': True,
          'codebook_size': 1_1_2,
          'codebook_do_center_crop': True,
          'codebook_crop_size': 1_1_2,
          'codebook_do_map_pixels': True,
          'codebook_do_normalize': True,
          'codebook_image_mean': FLAVA_CODEBOOK_MEAN,
          'codebook_image_std': FLAVA_CODEBOOK_STD,
      }

      lowercase				       =			os.path.join(self.tmpdirname				,						_lowerCamelCase			)
      with open(self.image_processor_file				,						'w'				,						encoding='utf-8'			) as fp:
        json.dump(_lowerCamelCase				,						_lowerCamelCase			)







    def      UpperCamelCase_ (     self				,						**_lowerCamelCase			):
      return BertTokenizer.from_pretrained(self.tmpdirname				,						**_lowerCamelCase			)







    def      UpperCamelCase_ (     self				,						**_lowerCamelCase			):
      return BertTokenizerFast.from_pretrained(self.tmpdirname				,						**_lowerCamelCase			)







    def      UpperCamelCase_ (     self				,						**_lowerCamelCase			):
      return FlavaImageProcessor.from_pretrained(self.tmpdirname				,						**_lowerCamelCase			)







    def      UpperCamelCase_ (     self			):
      shutil.rmtree(self.tmpdirname			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			[np.random.randint(2_5_5				,						size=(3, 3_0, 4_0_0)				,						dtype=np.uinta			)]

      lowercase				       =			[Image.fromarray(np.moveaxis(_lowerCamelCase				,						0				,						-1			)			) for x in image_inputs]

      return image_inputs







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.get_tokenizer()
      lowercase				       =			self.get_rust_tokenizer()
      lowercase				       =			self.get_image_processor()

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)
      processor_slow.save_pretrained(self.tmpdirname			)
      lowercase				       =			FlavaProcessor.from_pretrained(self.tmpdirname				,						use_fast=_lowerCamelCase			)

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)
      processor_fast.save_pretrained(self.tmpdirname			)
      lowercase				       =			FlavaProcessor.from_pretrained(self.tmpdirname			)

      self.assertEqual(processor_slow.tokenizer.get_vocab()				,						tokenizer_slow.get_vocab()			)
      self.assertEqual(processor_fast.tokenizer.get_vocab()				,						tokenizer_fast.get_vocab()			)
      self.assertEqual(tokenizer_slow.get_vocab()				,						tokenizer_fast.get_vocab()			)
      self.assertIsInstance(processor_slow.tokenizer				,						_lowerCamelCase			)
      self.assertIsInstance(processor_fast.tokenizer				,						_lowerCamelCase			)

      self.assertEqual(processor_slow.image_processor.to_json_string()				,						image_processor.to_json_string()			)
      self.assertEqual(processor_fast.image_processor.to_json_string()				,						image_processor.to_json_string()			)
      self.assertIsInstance(processor_slow.image_processor				,						_lowerCamelCase			)
      self.assertIsInstance(processor_fast.image_processor				,						_lowerCamelCase			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			FlavaProcessor(tokenizer=self.get_tokenizer()				,						image_processor=self.get_image_processor()			)
      processor.save_pretrained(self.tmpdirname			)

      lowercase				       =			self.get_tokenizer(bos_token='(BOS)'				,						eos_token='(EOS)'			)
      lowercase				       =			self.get_image_processor(do_normalize=_lowerCamelCase				,						padding_value=1.0			)

      lowercase				       =			FlavaProcessor.from_pretrained(
          self.tmpdirname				,						bos_token='(BOS)'				,						eos_token='(EOS)'				,						do_normalize=_lowerCamelCase				,						padding_value=1.0			)

      self.assertEqual(processor.tokenizer.get_vocab()				,						tokenizer_add_kwargs.get_vocab()			)
      self.assertIsInstance(processor.tokenizer				,						_lowerCamelCase			)

      self.assertEqual(processor.image_processor.to_json_string()				,						image_processor_add_kwargs.to_json_string()			)
      self.assertIsInstance(processor.image_processor				,						_lowerCamelCase			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.get_image_processor()
      lowercase				       =			self.get_tokenizer()

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)

      lowercase				       =			self.prepare_image_inputs()

      lowercase				       =			image_processor(_lowerCamelCase				,						return_tensors='np'			)
      lowercase				       =			processor(images=_lowerCamelCase				,						return_tensors='np'			)

      for key in input_feat_extract.keys():
        self.assertAlmostEqual(input_feat_extract[key].sum()				,						input_processor[key].sum()				,						delta=1e-2			)

      # With rest of the args
      random.seed(1_2_3_4			)
      lowercase				       =			image_processor(
          _lowerCamelCase				,						return_image_mask=_lowerCamelCase				,						return_codebook_pixels=_lowerCamelCase				,						return_tensors='np'			)
      random.seed(1_2_3_4			)
      lowercase				       =			processor(
          images=_lowerCamelCase				,						return_image_mask=_lowerCamelCase				,						return_codebook_pixels=_lowerCamelCase				,						return_tensors='np'			)

      for key in input_feat_extract.keys():
        self.assertAlmostEqual(input_feat_extract[key].sum()				,						input_processor[key].sum()				,						delta=1e-2			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.get_image_processor()
      lowercase				       =			self.get_tokenizer()

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)

      lowercase				       =			'lower newer'

      lowercase				       =			processor(text=_lowerCamelCase			)

      lowercase				       =			tokenizer(_lowerCamelCase			)

      for key in encoded_tok.keys():
        self.assertListEqual(encoded_tok[key]				,						encoded_processor[key]			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.get_image_processor()
      lowercase				       =			self.get_tokenizer()

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)

      lowercase				       =			'lower newer'
      lowercase				       =			self.prepare_image_inputs()

      lowercase				       =			processor(text=_lowerCamelCase				,						images=_lowerCamelCase			)

      self.assertListEqual(list(inputs.keys()			)				,						['input_ids', 'token_type_ids', 'attention_mask', 'pixel_values']			)

      # add extra args
      lowercase				       =			processor(text=_lowerCamelCase				,						images=_lowerCamelCase				,						return_codebook_pixels=_lowerCamelCase				,						return_image_mask=_lowerCamelCase			)

      self.assertListEqual(
          list(inputs.keys()			)				,						[
              'input_ids',
              'token_type_ids',
              'attention_mask',
              'pixel_values',
              'codebook_pixel_values',
              'bool_masked_pos',
          ]				,						)

      # test if it raises when no input is passed
      with pytest.raises(_lowerCamelCase			):
        processor()







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.get_image_processor()
      lowercase				       =			self.get_tokenizer()

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)

      lowercase				       =			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

      lowercase				       =			processor.batch_decode(_lowerCamelCase			)
      lowercase				       =			tokenizer.batch_decode(_lowerCamelCase			)

      self.assertListEqual(_lowerCamelCase				,						_lowerCamelCase			)







    def      UpperCamelCase_ (     self			):
      lowercase				       =			self.get_image_processor()
      lowercase				       =			self.get_tokenizer()

      lowercase				       =			FlavaProcessor(tokenizer=_lowerCamelCase				,						image_processor=_lowerCamelCase			)

      lowercase				       =			'lower newer'
      lowercase				       =			self.prepare_image_inputs()

      lowercase				       =			processor(text=_lowerCamelCase				,						images=_lowerCamelCase			)

      self.assertListEqual(list(inputs.keys()			)				,						processor.model_input_names			)


