





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip 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 OwlViTImageProcessor, OwlViTProcessor

@require_vision
class 		SCREAMING_SNAKE_CASE__    (	unittest.TestCase  ):


      def        a			(self	:				Tuple				):





         """simple docstring"""



         __snake_case								=       tempfile.mkdtemp()

         # fmt: off
         __snake_case								=       ['''''', '''l''', '''o''', '''w''', '''e''', '''r''', '''s''', '''t''', '''i''', '''d''', '''n''', '''lo''', '''l</w>''', '''w</w>''', '''r</w>''', '''t</w>''', '''low</w>''', '''er</w>''', '''lowest</w>''', '''newer</w>''', '''wider''', '''<unk>''', '''<|startoftext|>''', '''<|endoftext|>''']
         # fmt: on
         __snake_case								=       dict(zip(a__    ,      range(len(a__				)				)				)				)
         __snake_case								=       ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
         __snake_case								=       {'''unk_token''': '''<unk>'''}

         __snake_case								=       os.path.join(self.tmpdirname    ,      VOCAB_FILES_NAMES['''vocab_file''']				)
         __snake_case								=       os.path.join(self.tmpdirname    ,      VOCAB_FILES_NAMES['''merges_file''']				)
         with open(self.vocab_file    ,      '''w'''    ,      encoding='''utf-8'''				) as fp:
            fp.write(json.dumps(a__				) + '''\n'''				)
         with open(self.merges_file    ,      '''w'''    ,      encoding='''utf-8'''				) as fp:
            fp.write('''\n'''.join(a__				)				)

         __snake_case								=       {
             '''do_resize''': True,
             '''size''': 20,
             '''do_center_crop''': True,
             '''crop_size''': 18,
             '''do_normalize''': True,
             '''image_mean''': [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
             '''image_std''': [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
         }
         __snake_case								=       os.path.join(self.tmpdirname    ,      a__				)
         with open(self.image_processor_file    ,      '''w'''    ,      encoding='''utf-8'''				) as fp:
            json.dump(a__    ,      a__				)


      def        a			(self	:				Any    ,      **a__	:				Optional[int]				):





         """simple docstring"""



         return CLIPTokenizer.from_pretrained(self.tmpdirname    ,      pad_token='''!'''    ,      **a__				)


      def        a			(self	:				Union[str, Any]    ,      **a__	:				Optional[int]				):





         """simple docstring"""



         return CLIPTokenizerFast.from_pretrained(self.tmpdirname    ,      pad_token='''!'''    ,      **a__				)


      def        a			(self	:				Union[str, Any]    ,      **a__	:				Tuple				):





         """simple docstring"""



         return OwlViTImageProcessor.from_pretrained(self.tmpdirname    ,      **a__				)


      def        a			(self	:				Optional[int]				):





         """simple docstring"""



         shutil.rmtree(self.tmpdirname				)


      def        a			(self	:				Union[str, Any]				):





         """simple docstring"""



         __snake_case								=       [np.random.randint(255    ,      size=(3, 30, 400)    ,      dtype=np.uinta				)]

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

         return image_inputs


      def        a			(self	:				List[Any]				):





         """simple docstring"""



         __snake_case								=       self.get_tokenizer()
         __snake_case								=       self.get_rust_tokenizer()
         __snake_case								=       self.get_image_processor()

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)
         processor_slow.save_pretrained(self.tmpdirname				)
         __snake_case								=       OwlViTProcessor.from_pretrained(self.tmpdirname    ,      use_fast=a__				)

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)
         processor_fast.save_pretrained(self.tmpdirname				)
         __snake_case								=       OwlViTProcessor.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    ,      a__				)
         self.assertIsInstance(processor_fast.tokenizer    ,      a__				)

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


      def        a			(self	:				List[Any]				):





         """simple docstring"""



         __snake_case								=       OwlViTProcessor(tokenizer=self.get_tokenizer()    ,      image_processor=self.get_image_processor()				)
         processor.save_pretrained(self.tmpdirname				)

         __snake_case								=       self.get_tokenizer(bos_token='''(BOS)'''    ,      eos_token='''(EOS)'''				)
         __snake_case								=       self.get_image_processor(do_normalize=a__				)

         __snake_case								=       OwlViTProcessor.from_pretrained(
             self.tmpdirname    ,      bos_token='''(BOS)'''    ,      eos_token='''(EOS)'''    ,      do_normalize=a__				)

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

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


      def        a			(self	:				Tuple				):





         """simple docstring"""



         __snake_case								=       self.get_image_processor()
         __snake_case								=       self.get_tokenizer()

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)

         __snake_case								=       self.prepare_image_inputs()

         __snake_case								=       image_processor(a__    ,      return_tensors='''np'''				)
         __snake_case								=       processor(images=a__    ,      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        a			(self	:				Any				):





         """simple docstring"""



         __snake_case								=       self.get_image_processor()
         __snake_case								=       self.get_tokenizer()

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)

         __snake_case								=       '''lower newer'''

         __snake_case								=       processor(text=a__    ,      return_tensors='''np'''				)

         __snake_case								=       tokenizer(a__    ,      return_tensors='''np'''				)

         for key in encoded_tok.keys():
            self.assertListEqual(encoded_tok[key][0].tolist()    ,      encoded_processor[key][0].tolist()				)


      def        a			(self	:				Any				):





         """simple docstring"""



         __snake_case								=       self.get_image_processor()
         __snake_case								=       self.get_tokenizer()

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)

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

         __snake_case								=       processor(text=a__    ,      images=a__				)

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

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


      def        a			(self	:				str				):





         """simple docstring"""



         __snake_case								=       '''google/owlvit-base-patch32'''
         __snake_case								=       OwlViTProcessor.from_pretrained(a__				)

         __snake_case								=       ['''cat''', '''nasa badge''']
         __snake_case								=       processor(text=a__				)

         __snake_case								=       16
         self.assertListEqual(list(inputs.keys()				)    ,      ['''input_ids''', '''attention_mask''']				)
         self.assertEqual(inputs['''input_ids'''].shape    ,      (2, seq_length)				)

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


      def        a			(self	:				Optional[int]				):





         """simple docstring"""



         __snake_case								=       '''google/owlvit-base-patch32'''
         __snake_case								=       OwlViTProcessor.from_pretrained(a__				)

         __snake_case								=       [['''cat''', '''nasa badge'''], ['''person''']]
         __snake_case								=       processor(text=a__				)

         __snake_case								=       16
         __snake_case								=       len(a__				)
         __snake_case								=       max([len(a__				) for texts in input_texts]				)

         self.assertListEqual(list(inputs.keys()				)    ,      ['''input_ids''', '''attention_mask''']				)
         self.assertEqual(inputs['''input_ids'''].shape    ,      (batch_size * num_max_text_queries, seq_length)				)

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


      def        a			(self	:				int				):





         """simple docstring"""



         __snake_case								=       '''google/owlvit-base-patch32'''
         __snake_case								=       OwlViTProcessor.from_pretrained(a__				)

         __snake_case								=       ['''cat''', '''nasa badge''']
         __snake_case								=       processor(text=a__				)

         __snake_case								=       16
         __snake_case								=       inputs['''input_ids''']
         __snake_case								=       [
             [4_9406, 2368, 4_9407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
             [4_9406, 6841, 1_1301, 4_9407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
         ]

         self.assertListEqual(list(inputs.keys()				)    ,      ['''input_ids''', '''attention_mask''']				)
         self.assertEqual(inputs['''input_ids'''].shape    ,      (2, seq_length)				)
         self.assertListEqual(list(input_ids[0]				)    ,      predicted_ids[0]				)
         self.assertListEqual(list(input_ids[1]				)    ,      predicted_ids[1]				)


      def        a			(self	:				int				):





         """simple docstring"""



         __snake_case								=       self.get_image_processor()
         __snake_case								=       self.get_tokenizer()

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)

         __snake_case								=       self.prepare_image_inputs()
         __snake_case								=       self.prepare_image_inputs()

         __snake_case								=       processor(images=a__    ,      query_images=a__				)

         self.assertListEqual(list(inputs.keys()				)    ,      ['''query_pixel_values''', '''pixel_values''']				)

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


      def        a			(self	:				Optional[Any]				):





         """simple docstring"""



         __snake_case								=       self.get_image_processor()
         __snake_case								=       self.get_tokenizer()

         __snake_case								=       OwlViTProcessor(tokenizer=a__    ,      image_processor=a__				)

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

         __snake_case								=       processor.batch_decode(a__				)
         __snake_case								=       tokenizer.batch_decode(a__				)

         self.assertListEqual(a__    ,      a__				)








# Algorithm for the pigeonhole sorting








def lowerCamelCase__   (							snake_case_     :  int	)				->    Optional[int]:
   __snake_case								=       min(snake_case_	)  # min() finds the minimum value
   __snake_case								=       max(snake_case_	)  # max() finds the maximum value

   __snake_case								=       max_val - min_val + 1  # size is difference of max and min values plus one

   # list of pigeonholes of size equal to the variable size
   __snake_case								=       [0] * size

   # Populate the pigeonholes.
   for x in a:
      assert isinstance(snake_case_	,				snake_case_	), "integers only please"
      holes[x - min_val] += 1

   # Putting the elements back into the array in an order.
   __snake_case								=       0
   for count in range(snake_case_	):
      while holes[count] > 0:
         holes[count] -= 1
         __snake_case								=       count + min_val
         i += 1






def lowerCamelCase__   (							)				->    Union[str, Any]:
   __snake_case								=       [8, 3, 2, 7, 4, 6, 8]
   pigeonhole_sort(snake_case_	)
   print('''Sorted order is:'''	,				''' '''.join(snake_case_	)	)


if __name__ == "__main__":
    main()

