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 CLIPImageProcessor, CLIPProcessor






@require_vision
class 		_lowerCamelCase		(   unittest.TestCase    ):
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__:   Any=      tempfile.mkdtemp()

     # fmt: off
     SCREAMING_SNAKE_CASE__:   List[str]=      ['''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
     SCREAMING_SNAKE_CASE__:   List[Any]=      dict(zip(lowerCAmelCase , range(len(lowerCAmelCase   )   )   )   )
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
     SCREAMING_SNAKE_CASE__:   Tuple=      {'''unk_token''': '''<unk>'''}

     SCREAMING_SNAKE_CASE__:   Tuple=      os.path.join(self.tmpdirname , VOCAB_FILES_NAMES['''vocab_file''']   )
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      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(lowerCAmelCase   ) + '''\n'''   )
     with open(self.merges_file , '''w''' , encoding='''utf-8'''   ) as fp:
      fp.write('''\n'''.join(lowerCAmelCase   )   )

     SCREAMING_SNAKE_CASE__:   List[Any]=      {
         '''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__:   Dict=      os.path.join(self.tmpdirname , lowerCAmelCase   )
     with open(self.image_processor_file , '''w''' , encoding='''utf-8'''   ) as fp:
      json.dump(lowerCAmelCase , lowerCAmelCase   )
    def 						UpperCamelCase_				(  self , **lowerCAmelCase   )       ->					Dict:
     return CLIPTokenizer.from_pretrained(self.tmpdirname , **lowerCAmelCase   )
    def 						UpperCamelCase_				(  self , **lowerCAmelCase   )       ->					List[Any]:
     return CLIPTokenizerFast.from_pretrained(self.tmpdirname , **lowerCAmelCase   )
    def 						UpperCamelCase_				(  self , **lowerCAmelCase   )       ->					Union[str, Any]:
     return CLIPImageProcessor.from_pretrained(self.tmpdirname , **lowerCAmelCase   )
    def 						UpperCamelCase_				(  self   )       ->					Optional[int]:
     shutil.rmtree(self.tmpdirname   )
    def 						UpperCamelCase_				(  self   )       ->					Optional[int]:
     SCREAMING_SNAKE_CASE__:   str=      [np.random.randint(255 , size=(3, 30, 400) , dtype=np.uinta   )]

     SCREAMING_SNAKE_CASE__:   str=      [Image.fromarray(np.moveaxis(lowerCAmelCase , 0 , -1   )   ) for x in image_inputs]

     return image_inputs
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.get_tokenizer()
     SCREAMING_SNAKE_CASE__:   List[Any]=      self.get_rust_tokenizer()
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self.get_image_processor()

     SCREAMING_SNAKE_CASE__:   Dict=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )
     processor_slow.save_pretrained(self.tmpdirname   )
     SCREAMING_SNAKE_CASE__:   Optional[int]=      CLIPProcessor.from_pretrained(self.tmpdirname , use_fast=lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   List[Any]=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )
     processor_fast.save_pretrained(self.tmpdirname   )
     SCREAMING_SNAKE_CASE__:   Tuple=      CLIPProcessor.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 , lowerCAmelCase   )
     self.assertIsInstance(processor_fast.tokenizer , lowerCAmelCase   )

     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 , lowerCAmelCase   )
     self.assertIsInstance(processor_fast.image_processor , lowerCAmelCase   )
    def 						UpperCamelCase_				(  self   )       ->					Optional[Any]:
     SCREAMING_SNAKE_CASE__:   Tuple=      CLIPProcessor(tokenizer=self.get_tokenizer() , image_processor=self.get_image_processor()   )
     processor.save_pretrained(self.tmpdirname   )

     SCREAMING_SNAKE_CASE__:   str=      self.get_tokenizer(bos_token='''(BOS)''' , eos_token='''(EOS)'''   )
     SCREAMING_SNAKE_CASE__:   Dict=      self.get_image_processor(do_normalize=lowerCAmelCase , padding_value=1.0   )

     SCREAMING_SNAKE_CASE__:   Dict=      CLIPProcessor.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   )
    def 						UpperCamelCase_				(  self   )       ->					Union[str, Any]:
     SCREAMING_SNAKE_CASE__:   List[Any]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   List[Any]=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   Any=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__:   Tuple=      image_processor(lowerCAmelCase , return_tensors='''np'''   )
     SCREAMING_SNAKE_CASE__:   str=      processor(images=lowerCAmelCase , 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 						UpperCamelCase_				(  self   )       ->					Union[str, Any]:
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Tuple=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   List[Any]=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   Tuple=      '''lower newer'''

     SCREAMING_SNAKE_CASE__:   Tuple=      processor(text=lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   str=      tokenizer(lowerCAmelCase   )

     for key in encoded_tok.keys():
      self.assertListEqual(encoded_tok[key] , encoded_processor[key]   )
    def 						UpperCamelCase_				(  self   )       ->					Union[str, Any]:
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Dict=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   int=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   str=      '''lower newer'''
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.prepare_image_inputs()

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

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

     # test if it raises when no input is passed
     with pytest.raises(lowerCAmelCase   ):
      processor()
    def 						UpperCamelCase_				(  self   )       ->					Tuple:
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      self.get_image_processor()
     SCREAMING_SNAKE_CASE__:   Optional[int]=      self.get_tokenizer()

     SCREAMING_SNAKE_CASE__:   Dict=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )

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

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

     self.assertListEqual(lowerCAmelCase , lowerCAmelCase   )



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

     SCREAMING_SNAKE_CASE__:   Any=      CLIPProcessor(tokenizer=lowerCAmelCase , image_processor=lowerCAmelCase   )

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

     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      processor(text=lowerCAmelCase , images=lowerCAmelCase   )

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


import re







def 			A__      (	snake_case_ :		str      ):

 if len(re.findall('''[ATCG]'''       ,				snake_case_      )      ) != len(snake_case_      ):
  raise ValueError('''Invalid Strand'''      )

 return dna.translate(dna.maketrans('''ATCG'''       ,				'''TAGC'''      )      )


if __name__ == "__main__":
      import doctest

      doctest.testmod()

