






'''simple docstring'''
import json
import os
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 AlignProcessor, EfficientNetImageProcessor






@require_vision
class        __SCREAMING_SNAKE_CASE (     unittest.TestCase			):




 def        __magic_name__		( self		:							Dict )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			Any													=tempfile.mkdtemp()

       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=[
           '''[UNK]''',
           '''[CLS]''',
           '''[SEP]''',
           '''[PAD]''',
           '''[MASK]''',
           '''want''',
           '''##want''',
           '''##ed''',
           '''wa''',
           '''un''',
           '''runn''',
           '''##ing''',
           ''',''',
           '''low''',
           '''lowest''',
       ]
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=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] ) )

       SCREAMING_SNAKE_CASE__       :			Dict													={
           '''do_resize''': True,
           '''size''': 20,
           '''do_center_crop''': True,
           '''crop_size''': 18,
           '''do_normalize''': True,
           '''image_mean''': [0.48145466, 0.4578275, 0.40821073],
           '''image_std''': [0.26862954, 0.26130258, 0.27577711],
       }
       SCREAMING_SNAKE_CASE__       :			List[str]													=os.path.join(self.tmpdirname   , __lowercase )
       with open(self.image_processor_file   , '''w'''   , encoding='''utf-8''' ) as fp:
             json.dump(__lowercase   , __lowercase )




 def        __magic_name__		( self		:							Tuple   , **__lowercase		:							Union[str, Any] )		->  Tuple:
       return BertTokenizer.from_pretrained(self.tmpdirname   , **__lowercase )




 def        __magic_name__		( self		:							Union[str, Any]   , **__lowercase		:							int )		->  Tuple:
       return BertTokenizerFast.from_pretrained(self.tmpdirname   , **__lowercase )




 def        __magic_name__		( self		:							Any   , **__lowercase		:							Union[str, Any] )		->  Union[str, Any]:
       return EfficientNetImageProcessor.from_pretrained(self.tmpdirname   , **__lowercase )




 def        __magic_name__		( self		:							Union[str, Any] )		->  List[Any]:
       shutil.rmtree(self.tmpdirname )




 def        __magic_name__		( self		:							Optional[int] )		->  Any:
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=[np.random.randint(2_55   , size=(3, 30, 4_00)   , dtype=np.uinta )]
       SCREAMING_SNAKE_CASE__       :			List[str]													=[Image.fromarray(np.moveaxis(__lowercase   , 0   , -1 ) ) for x in image_inputs]
       return image_inputs




 def        __magic_name__		( self		:							Optional[Any] )		->  Tuple:
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=self.get_tokenizer()
       SCREAMING_SNAKE_CASE__       :			List[str]													=self.get_rust_tokenizer()
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=self.get_image_processor()

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )
       processor_slow.save_pretrained(self.tmpdirname )
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=AlignProcessor.from_pretrained(self.tmpdirname   , use_fast=__lowercase )

       SCREAMING_SNAKE_CASE__       :			Tuple													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )
       processor_fast.save_pretrained(self.tmpdirname )
       SCREAMING_SNAKE_CASE__       :			List[str]													=AlignProcessor.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   , __lowercase )
       self.assertIsInstance(processor_fast.tokenizer   , __lowercase )

       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   , __lowercase )
       self.assertIsInstance(processor_fast.image_processor   , __lowercase )




 def        __magic_name__		( self		:							str )		->  Any:
       SCREAMING_SNAKE_CASE__       :			List[Any]													=AlignProcessor(tokenizer=self.get_tokenizer()   , image_processor=self.get_image_processor() )
       processor.save_pretrained(self.tmpdirname )

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.get_tokenizer(bos_token='''(BOS)'''   , eos_token='''(EOS)''' )
       SCREAMING_SNAKE_CASE__       :			int													=self.get_image_processor(do_normalize=__lowercase   , padding_value=1.0 )

       SCREAMING_SNAKE_CASE__       :			str													=AlignProcessor.from_pretrained(
           self.tmpdirname   , bos_token='''(BOS)'''   , eos_token='''(EOS)'''   , do_normalize=__lowercase   , padding_value=1.0 )

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

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




 def        __magic_name__		( self		:							str )		->  Tuple:
       SCREAMING_SNAKE_CASE__       :			List[Any]													=self.get_image_processor()
       SCREAMING_SNAKE_CASE__       :			str													=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__       :			Dict													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )

       SCREAMING_SNAKE_CASE__       :			Tuple													=self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE__       :			List[Any]													=image_processor(__lowercase   , return_tensors='''np''' )
       SCREAMING_SNAKE_CASE__       :			List[str]													=processor(images=__lowercase   , return_tensors='''np''' )

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




 def        __magic_name__		( self		:							Optional[Any] )		->  str:
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=self.get_image_processor()
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )

       SCREAMING_SNAKE_CASE__       :			List[str]													='''lower newer'''

       SCREAMING_SNAKE_CASE__       :			Any													=processor(text=__lowercase )

       SCREAMING_SNAKE_CASE__       :			List[str]													=tokenizer(__lowercase   , padding='''max_length'''   , max_length=64 )

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




 def        __magic_name__		( self		:							Any )		->  Any:
       SCREAMING_SNAKE_CASE__       :			Optional[int]													=self.get_image_processor()
       SCREAMING_SNAKE_CASE__       :			List[Any]													=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__       :			Any													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )

       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													='''lower newer'''
       SCREAMING_SNAKE_CASE__       :			Any													=self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=processor(text=__lowercase   , images=__lowercase )

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

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




 def        __magic_name__		( self		:							List[str] )		->  str:
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.get_image_processor()
       SCREAMING_SNAKE_CASE__       :			str													=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__       :			Tuple													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )

       SCREAMING_SNAKE_CASE__       :			Dict													=[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       SCREAMING_SNAKE_CASE__       :			Tuple													=processor.batch_decode(__lowercase )
       SCREAMING_SNAKE_CASE__       :			List[str]													=tokenizer.batch_decode(__lowercase )

       self.assertListEqual(__lowercase   , __lowercase )




 def        __magic_name__		( self		:							Any )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=self.get_image_processor()
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.get_tokenizer()

       SCREAMING_SNAKE_CASE__       :			List[str]													=AlignProcessor(tokenizer=__lowercase   , image_processor=__lowercase )

       SCREAMING_SNAKE_CASE__       :			Any													='''lower newer'''
       SCREAMING_SNAKE_CASE__       :			int													=self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=processor(text=__lowercase   , images=__lowercase )

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







'''simple docstring'''
from __future__ import annotations





def 	_a(					UpperCamelCase__			:  List[str],		UpperCamelCase__			:  Union[str, Any],		UpperCamelCase__			:  int,		UpperCamelCase__			:  List[str]							):  # noqa: E741




      '''simple docstring'''






      while r - l > 1:
            SCREAMING_SNAKE_CASE__       :			List[str]													=(l + r) // 2
            if v[m] >= key:
                  SCREAMING_SNAKE_CASE__       :			Dict													=m
            else:
                  SCREAMING_SNAKE_CASE__       :			Any													=m  # noqa: E741
      return r





def 	_a(					UpperCamelCase__			:  list[int]							):




      '''simple docstring'''






      if len(UpperCamelCase__							) == 0:
            return 0

      SCREAMING_SNAKE_CASE__       :			List[Any]													=[0] * len(UpperCamelCase__							)
      SCREAMING_SNAKE_CASE__       :			Dict													=1

      SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=v[0]

      for i in range(1,		len(UpperCamelCase__							)							):
            if v[i] < tail[0]:
                  SCREAMING_SNAKE_CASE__       :			List[Any]													=v[i]
            elif v[i] > tail[length - 1]:
                  SCREAMING_SNAKE_CASE__       :			int													=v[i]
                  length += 1
            else:
                  SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=v[i]

      return length


if __name__ == "__main__":
  import doctest

  doctest.testmod()