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  __magic_name__  (					unittest.TestCase    ):





   """simple docstring"""




   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    _UpperCamelCase:     int							= tempfile.mkdtemp()

    _UpperCamelCase:     Any							= [
        '''[UNK]''',
        '''[CLS]''',
        '''[SEP]''',
        '''[PAD]''',
        '''[MASK]''',
        '''want''',
        '''##want''',
        '''##ed''',
        '''wa''',
        '''un''',
        '''runn''',
        '''##ing''',
        ''',''',
        '''low''',
        '''lowest''',
    ]
    _UpperCamelCase:     Any							= 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:     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],
    }
    _UpperCamelCase:     int							= os.path.join(self.tmpdirname		,  _lowercase							)
    with open(self.image_processor_file		,  '''w'''		,  encoding='''utf-8'''							) as fp:
     json.dump(_lowercase		,  _lowercase							)



   def   lowerCAmelCase						(	self					:  List[Any]		,  **_lowercase					:  Tuple							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  Tuple		,  **_lowercase					:  Tuple							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  Tuple		,  **_lowercase					:  int							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    shutil.rmtree(self.tmpdirname							)



   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  List[Any]							):



    """simple docstring"""



    _UpperCamelCase:     int							= self.get_tokenizer()
    _UpperCamelCase:     Optional[Any]							= self.get_rust_tokenizer()
    _UpperCamelCase:     Any							= self.get_image_processor()

    _UpperCamelCase:     Any							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)
    processor_slow.save_pretrained(self.tmpdirname							)
    _UpperCamelCase:     str							= AlignProcessor.from_pretrained(self.tmpdirname		,  use_fast=_lowercase							)

    _UpperCamelCase:     str							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)
    processor_fast.save_pretrained(self.tmpdirname							)
    _UpperCamelCase:     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   lowerCAmelCase						(	self					:  int							):



    """simple docstring"""



    _UpperCamelCase:     Union[str, Any]							= AlignProcessor(tokenizer=self.get_tokenizer()		,  image_processor=self.get_image_processor()							)
    processor.save_pretrained(self.tmpdirname							)

    _UpperCamelCase:     Tuple							= self.get_tokenizer(bos_token='''(BOS)'''		,  eos_token='''(EOS)'''							)
    _UpperCamelCase:     Dict							= self.get_image_processor(do_normalize=_lowercase		,  padding_value=1.0							)

    _UpperCamelCase:     List[Any]							= 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   lowerCAmelCase						(	self					:  Tuple							):



    """simple docstring"""



    _UpperCamelCase:     Tuple							= self.get_image_processor()
    _UpperCamelCase:     Tuple							= self.get_tokenizer()

    _UpperCamelCase:     List[Any]							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)

    _UpperCamelCase:     Any							= self.prepare_image_inputs()

    _UpperCamelCase:     int							= image_processor(_lowercase		,  return_tensors='''np'''							)
    _UpperCamelCase:     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   lowerCAmelCase						(	self					:  Any							):



    """simple docstring"""



    _UpperCamelCase:     int							= self.get_image_processor()
    _UpperCamelCase:     Any							= self.get_tokenizer()

    _UpperCamelCase:     Optional[int]							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)

    _UpperCamelCase:     List[Any]							= '''lower newer'''

    _UpperCamelCase:     Tuple							= processor(text=_lowercase							)

    _UpperCamelCase:     Optional[int]							= tokenizer(_lowercase		,  padding='''max_length'''		,  max_length=64							)

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



   def   lowerCAmelCase						(	self					:  Optional[Any]							):



    """simple docstring"""



    _UpperCamelCase:     int							= self.get_image_processor()
    _UpperCamelCase:     Union[str, Any]							= self.get_tokenizer()

    _UpperCamelCase:     Union[str, Any]							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)

    _UpperCamelCase:     Dict							= '''lower newer'''
    _UpperCamelCase:     Optional[int]							= self.prepare_image_inputs()

    _UpperCamelCase:     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   lowerCAmelCase						(	self					:  int							):



    """simple docstring"""



    _UpperCamelCase:     Any							= self.get_image_processor()
    _UpperCamelCase:     int							= self.get_tokenizer()

    _UpperCamelCase:     Optional[Any]							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)

    _UpperCamelCase:     int							= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

    _UpperCamelCase:     str							= processor.batch_decode(_lowercase							)
    _UpperCamelCase:     Any							= tokenizer.batch_decode(_lowercase							)

    self.assertListEqual(_lowercase		,  _lowercase							)



   def   lowerCAmelCase						(	self					:  List[str]							):



    """simple docstring"""



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

    _UpperCamelCase:     List[str]							= AlignProcessor(tokenizer=_lowercase		,  image_processor=_lowercase							)

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

    _UpperCamelCase:     List[str]							= processor(text=_lowercase		,  images=_lowercase							)

    self.assertListEqual(list(inputs.keys()							)		,  processor.model_input_names							)
def       lowerCAmelCase_     (		lowercase:							int = 10**9		)    ->				int:







 '''simple docstring'''
 _UpperCamelCase:     List[Any]							= 1
 _UpperCamelCase:     Dict							= 2

 _UpperCamelCase:     Tuple							= 0
 _UpperCamelCase:     int							= 0
 _UpperCamelCase:     Dict							= 0
 while perimeter <= max_perimeter:
  perimeters_sum += perimeter

  prev_value += 2 * value
  value += prev_value

  _UpperCamelCase:     str							= 2 * value + 2 if i % 2 == 0 else 2 * value - 2
  i += 1

 return perimeters_sum


if __name__ == "__main__":
  print(f"""{solution() = }""")