


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    UpperCAmelCase_	(							unittest.TestCase):
       '''simple docstring'''






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		tempfile.mkdtemp()

              UpperCamelCase    :	List[str]   	=		[
                  '''[UNK]''',
                  '''[CLS]''',
                  '''[SEP]''',
                  '''[PAD]''',
                  '''[MASK]''',
                  '''want''',
                  '''##want''',
                  '''##ed''',
                  '''wa''',
                  '''un''',
                  '''runn''',
                  '''##ing''',
                  ''',''',
                  '''low''',
                  '''lowest''',
              ]
              UpperCamelCase    :	List[str]   	=		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]						)						)

              UpperCamelCase    :	str   	=		{
                  '''do_resize''': True,
                  '''size''': 20,
                  '''do_center_crop''': True,
                  '''crop_size''': 18,
                  '''do_normalize''': True,
                  '''image_mean''': [0.48_145_466, 0.4_578_275, 0.40_821_073],
                  '''image_std''': [0.26_862_954, 0.26_130_258, 0.27_577_711],
              }
              UpperCamelCase    :	Union[str, Any]   	=		os.path.join(self.tmpdirname ,					__SCREAMING_SNAKE_CASE						)
              with open(self.image_processor_file ,					'''w''' ,					encoding='''utf-8'''						) as fp:
                     json.dump(__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self ,					**__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              return BertTokenizer.from_pretrained(self.tmpdirname ,					**__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self ,					**__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              return BertTokenizerFast.from_pretrained(self.tmpdirname ,					**__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self ,					**__SCREAMING_SNAKE_CASE						):




              """simple docstring"""




              return EfficientNetImageProcessor.from_pretrained(self.tmpdirname ,					**__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self						):




              """simple docstring"""




              shutil.rmtree(self.tmpdirname						)






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Dict   	=		[np.random.randint(255 ,					size=(3, 30, 400) ,					dtype=np.uinta						)]
              UpperCamelCase    :	Tuple   	=		[Image.fromarray(np.moveaxis(__SCREAMING_SNAKE_CASE ,					0 ,					-1						)						) for x in image_inputs]
              return image_inputs






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	int   	=		self.get_tokenizer()
              UpperCamelCase    :	Optional[int]   	=		self.get_rust_tokenizer()
              UpperCamelCase    :	str   	=		self.get_image_processor()

              UpperCamelCase    :	int   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)
              processor_slow.save_pretrained(self.tmpdirname						)
              UpperCamelCase    :	Any   	=		AlignProcessor.from_pretrained(self.tmpdirname ,					use_fast=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	List[Any]   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)
              processor_fast.save_pretrained(self.tmpdirname						)
              UpperCamelCase    :	Optional[int]   	=		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 ,					__SCREAMING_SNAKE_CASE						)
              self.assertIsInstance(processor_fast.tokenizer ,					__SCREAMING_SNAKE_CASE						)

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






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	List[Any]   	=		AlignProcessor(tokenizer=self.get_tokenizer() ,					image_processor=self.get_image_processor()						)
              processor.save_pretrained(self.tmpdirname						)

              UpperCamelCase    :	Optional[int]   	=		self.get_tokenizer(bos_token='''(BOS)''' ,					eos_token='''(EOS)'''						)
              UpperCamelCase    :	Tuple   	=		self.get_image_processor(do_normalize=__SCREAMING_SNAKE_CASE ,					padding_value=1.0						)

              UpperCamelCase    :	int   	=		AlignProcessor.from_pretrained(
                  self.tmpdirname ,					bos_token='''(BOS)''' ,					eos_token='''(EOS)''' ,					do_normalize=__SCREAMING_SNAKE_CASE ,					padding_value=1.0						)

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

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






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	List[Any]   	=		self.get_image_processor()
              UpperCamelCase    :	Any   	=		self.get_tokenizer()

              UpperCamelCase    :	Union[str, Any]   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	str   	=		self.prepare_image_inputs()

              UpperCamelCase    :	Union[str, Any]   	=		image_processor(__SCREAMING_SNAKE_CASE ,					return_tensors='''np'''						)
              UpperCamelCase    :	Union[str, Any]   	=		processor(images=__SCREAMING_SNAKE_CASE ,					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  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	Any   	=		self.get_image_processor()
              UpperCamelCase    :	str   	=		self.get_tokenizer()

              UpperCamelCase    :	List[str]   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	Any   	=		'''lower newer'''

              UpperCamelCase    :	Any   	=		processor(text=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	Tuple   	=		tokenizer(__SCREAMING_SNAKE_CASE ,					padding='''max_length''' ,					max_length=64						)

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






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	str   	=		self.get_image_processor()
              UpperCamelCase    :	List[str]   	=		self.get_tokenizer()

              UpperCamelCase    :	Tuple   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	Optional[Any]   	=		'''lower newer'''
              UpperCamelCase    :	List[str]   	=		self.prepare_image_inputs()

              UpperCamelCase    :	Optional[int]   	=		processor(text=__SCREAMING_SNAKE_CASE ,					images=__SCREAMING_SNAKE_CASE						)

              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(__SCREAMING_SNAKE_CASE						):
                     processor()






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	str   	=		self.get_image_processor()
              UpperCamelCase    :	List[Any]   	=		self.get_tokenizer()

              UpperCamelCase    :	Union[str, Any]   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)

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

              UpperCamelCase    :	List[str]   	=		processor.batch_decode(__SCREAMING_SNAKE_CASE						)
              UpperCamelCase    :	Optional[Any]   	=		tokenizer.batch_decode(__SCREAMING_SNAKE_CASE						)

              self.assertListEqual(__SCREAMING_SNAKE_CASE ,					__SCREAMING_SNAKE_CASE						)






       def  _lowercase   (     self						):




              """simple docstring"""




              UpperCamelCase    :	List[Any]   	=		self.get_image_processor()
              UpperCamelCase    :	Union[str, Any]   	=		self.get_tokenizer()

              UpperCamelCase    :	Tuple   	=		AlignProcessor(tokenizer=__SCREAMING_SNAKE_CASE ,					image_processor=__SCREAMING_SNAKE_CASE						)

              UpperCamelCase    :	Tuple   	=		'''lower newer'''
              UpperCamelCase    :	Optional[int]   	=		self.prepare_image_inputs()

              UpperCamelCase    :	Any   	=		processor(text=__SCREAMING_SNAKE_CASE ,					images=__SCREAMING_SNAKE_CASE						)

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







def      a	(							SCREAMING_SNAKE_CASE_      :		int       ):






       """simple docstring"""





       if number > 0:
              raise ValueError('''input must be a negative integer'''       )
       UpperCamelCase    :	List[str]   	=		len(bin(SCREAMING_SNAKE_CASE_       )[3:]       )
       UpperCamelCase    :	List[str]   	=		bin(abs(SCREAMING_SNAKE_CASE_       ) - (1 << binary_number_length)       )[3:]
       UpperCamelCase    :	Dict   	=		(
           (
               '''1'''
               + '''0''' * (binary_number_length - len(SCREAMING_SNAKE_CASE_       ))
               + twos_complement_number
           )
           if number < 0
           else '''0'''
       )
       return "0b" + twos_complement_number


if __name__ == "__main__":
  import doctest

  doctest.testmod()

