




import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import (
       AutoProcessor,
       BertTokenizerFast,
       BlipImageProcessor,
       GPTaTokenizer,
       InstructBlipProcessor,
       PreTrainedTokenizerFast,
   )





@require_vision
class 	lowerCamelCase_							(				unittest.TestCase ):


 '''simple docstring'''







 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      tempfile.mkdtemp()

       SCREAMING_SNAKE_CASE_     						=      BlipImageProcessor()
       SCREAMING_SNAKE_CASE_     						=      GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model'						)
       SCREAMING_SNAKE_CASE_     						=      BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert'						)

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(_lowerCAmelCase    ,    _lowerCAmelCase    ,    _lowerCAmelCase						)

       processor.save_pretrained(self.tmpdirname						)



 def 				lowerCAmelCase_  (							self  :		Any    ,    **_lowerCAmelCase  :		Dict						):
       return AutoProcessor.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						).tokenizer



 def 				lowerCAmelCase_  (							self  :		Tuple    ,    **_lowerCAmelCase  :		List[str]						):
       return AutoProcessor.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						).image_processor



 def 				lowerCAmelCase_  (							self  :		Optional[int]    ,    **_lowerCAmelCase  :		str						):
       return AutoProcessor.from_pretrained(self.tmpdirname    ,    **_lowerCAmelCase						).qformer_tokenizer



 def 				lowerCAmelCase_  (							self  :		str						):
       shutil.rmtree(self.tmpdirname						)



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      [np.random.randint(255    ,    size=(3, 30, 400)    ,    dtype=np.uinta						)]

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

       return image_inputs



 def 				lowerCAmelCase_  (							self  :		Union[str, Any]						):
       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(
           tokenizer=self.get_tokenizer()    ,    image_processor=self.get_image_processor()    ,    qformer_tokenizer=self.get_qformer_tokenizer()    ,    )
       processor.save_pretrained(self.tmpdirname						)

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

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor.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						)
       self.assertIsInstance(processor.qformer_tokenizer    ,    _lowerCAmelCase						)



 def 				lowerCAmelCase_  (							self  :		str						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(
           tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase    ,    qformer_tokenizer=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      self.prepare_image_inputs()

       SCREAMING_SNAKE_CASE_     						=      image_processor(_lowerCAmelCase    ,    return_tensors='np'						)
       SCREAMING_SNAKE_CASE_     						=      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						)



 def 				lowerCAmelCase_  (							self  :		Dict						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(
           tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase    ,    qformer_tokenizer=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      'lower newer'

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase						)

       SCREAMING_SNAKE_CASE_     						=      tokenizer(_lowerCAmelCase    ,    return_token_type_ids=_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      qformer_tokenizer(_lowerCAmelCase    ,    return_token_type_ids=_lowerCAmelCase						)

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

       for key in encoded_tokens_qformer.keys():
             self.assertListEqual(encoded_tokens_qformer[key]    ,    encoded_processor['qformer_' + key]						)



 def 				lowerCAmelCase_  (							self  :		Any						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(
           tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase    ,    qformer_tokenizer=_lowerCAmelCase						)

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

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase    ,    images=_lowerCAmelCase						)

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

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



 def 				lowerCAmelCase_  (							self  :		List[str]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(
           tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase    ,    qformer_tokenizer=_lowerCAmelCase						)

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

       SCREAMING_SNAKE_CASE_     						=      processor.batch_decode(_lowerCAmelCase						)
       SCREAMING_SNAKE_CASE_     						=      tokenizer.batch_decode(_lowerCAmelCase						)

       self.assertListEqual(_lowerCAmelCase    ,    _lowerCAmelCase						)




 def 				lowerCAmelCase_  (							self  :		List[Any]						):
       SCREAMING_SNAKE_CASE_     						=      self.get_image_processor()
       SCREAMING_SNAKE_CASE_     						=      self.get_tokenizer()
       SCREAMING_SNAKE_CASE_     						=      self.get_qformer_tokenizer()

       SCREAMING_SNAKE_CASE_     						=      InstructBlipProcessor(
           tokenizer=_lowerCAmelCase    ,    image_processor=_lowerCAmelCase    ,    qformer_tokenizer=_lowerCAmelCase						)

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

       SCREAMING_SNAKE_CASE_     						=      processor(text=_lowerCAmelCase    ,    images=_lowerCAmelCase						)

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





from json import JSONDecodeError  # Workaround for requests.exceptions.JSONDecodeError

import requests

def  UpperCAmelCase_							(				__UpperCAmelCase						:     str = "isbn/0140328726"							) ->			dict:
      SCREAMING_SNAKE_CASE_     						=      olid.strip().strip('/'							)  # Remove leading/trailing whitespace & slashes
      if new_olid.count('/'							) != 1:
            SCREAMING_SNAKE_CASE_     						=      f"{olid} is not a valid Open Library olid"
            raise ValueError(__UpperCAmelCase							)
      return requests.get(f"https://openlibrary.org/{new_olid}.json"							).json()

def  UpperCAmelCase_							(				__UpperCAmelCase						:     dict							) ->			dict:
      SCREAMING_SNAKE_CASE_     						=      {
          'title': 'Title',
          'publish_date': 'Publish date',
          'authors': 'Authors',
          'number_of_pages': 'Number of pages:',
          'first_sentence': 'First sentence',
          'isbn_10': 'ISBN (10)',
          'isbn_13': 'ISBN (13)',
      }
      SCREAMING_SNAKE_CASE_     						=      {better_key: ol_book_data[key] for key, better_key in desired_keys.items()}
      SCREAMING_SNAKE_CASE_     						=      [
          get_openlibrary_data(author['key']							)['name'] for author in data['Authors']
      ]
      SCREAMING_SNAKE_CASE_     						=      data['First sentence']['value']
      for key, value in data.items():
            if isinstance(__UpperCAmelCase      ,      __UpperCAmelCase							):
                  SCREAMING_SNAKE_CASE_     						=      ', '.join(__UpperCAmelCase							)
      return data


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   while True:
      lowerCamelCase__			:       Optional[Any]         =							input('\nEnter the ISBN code to search (or \'quit\' to stop): ').strip()
      if isbn.lower() in ("", "q", "quit", "exit", "stop"):
         break

      if len(isbn) not in (10, 13) or not isbn.isdigit():
         print(f'''Sorry, {isbn} is not a valid ISBN.  Please, input a valid ISBN.''')
         continue

      print(f'''\nSearching Open Library for ISBN: {isbn}...\n''')

      try:
         lowerCamelCase__			:       Union[str, Any]         =							summarize_book(get_openlibrary_data(f'''isbn/{isbn}'''))
         print('\n'.join(f'''{key}: {value}''' for key, value in book_summary.items()))
      except JSONDecodeError:  # Workaround for requests.exceptions.RequestException:
         print(f'''Sorry, there are no results for ISBN: {isbn}.''')