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 CLIPSegProcessor, ViTImageProcessor






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

     # fmt: off
     SCREAMING_SNAKE_CASE__: Optional[Any]=   ['''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__: Dict=   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__: Optional[int]=   {'''unk_token''': '''<unk>'''}

     SCREAMING_SNAKE_CASE__: Any=   os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''vocab_file'''] )
     SCREAMING_SNAKE_CASE__: List[str]=   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__: Optional[int]=   {
         '''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__: Any=   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 )							->       Optional[Any]:
     return CLIPTokenizer.from_pretrained(self.tmpdirname			,			**lowerCAmelCase )
    def     UpperCamelCase_					(	self			,			**lowerCAmelCase )							->       Optional[int]:
     return CLIPTokenizerFast.from_pretrained(self.tmpdirname			,			**lowerCAmelCase )
    def     UpperCamelCase_					(	self			,			**lowerCAmelCase )							->       Union[str, Any]:
     return ViTImageProcessor.from_pretrained(self.tmpdirname			,			**lowerCAmelCase )
    def     UpperCamelCase_					(	self )							->       str:
     shutil.rmtree(self.tmpdirname )
    def     UpperCamelCase_					(	self )							->       Dict:
     SCREAMING_SNAKE_CASE__: Tuple=   [np.random.randint(255			,			size=(3, 30, 400)			,			dtype=np.uinta )]

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

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

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

     SCREAMING_SNAKE_CASE__: List[str]=   CLIPSegProcessor(tokenizer=lowerCAmelCase			,			image_processor=lowerCAmelCase )
     processor_fast.save_pretrained(self.tmpdirname )
     SCREAMING_SNAKE_CASE__: Dict=   CLIPSegProcessor.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 )							->       str:
     SCREAMING_SNAKE_CASE__: Tuple=   CLIPSegProcessor(tokenizer=self.get_tokenizer()			,			image_processor=self.get_image_processor() )
     processor.save_pretrained(self.tmpdirname )

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

     SCREAMING_SNAKE_CASE__: Optional[int]=   CLIPSegProcessor.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 )							->       Dict:
     SCREAMING_SNAKE_CASE__: Any=   self.get_image_processor()
     SCREAMING_SNAKE_CASE__: Any=   self.get_tokenizer()

     SCREAMING_SNAKE_CASE__: Optional[int]=   CLIPSegProcessor(tokenizer=lowerCAmelCase			,			image_processor=lowerCAmelCase )

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

     SCREAMING_SNAKE_CASE__: Any=   image_processor(lowerCAmelCase			,			return_tensors='''np''' )
     SCREAMING_SNAKE_CASE__: str=   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     UpperCamelCase_					(	self )							->       Any:
     SCREAMING_SNAKE_CASE__: Optional[int]=   self.get_image_processor()
     SCREAMING_SNAKE_CASE__: Optional[int]=   self.get_tokenizer()

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

     SCREAMING_SNAKE_CASE__: Any=   '''lower newer'''

     SCREAMING_SNAKE_CASE__: List[Any]=   processor(text=lowerCAmelCase )

     SCREAMING_SNAKE_CASE__: Tuple=   tokenizer(lowerCAmelCase )

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

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

     SCREAMING_SNAKE_CASE__: Optional[Any]=   '''lower newer'''
     SCREAMING_SNAKE_CASE__: Dict=   self.prepare_image_inputs()

     SCREAMING_SNAKE_CASE__: Dict=   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 )							->       int:
     SCREAMING_SNAKE_CASE__: Optional[Any]=   self.get_image_processor()
     SCREAMING_SNAKE_CASE__: List[Any]=   self.get_tokenizer()

     SCREAMING_SNAKE_CASE__: Optional[Any]=   CLIPSegProcessor(tokenizer=lowerCAmelCase			,			image_processor=lowerCAmelCase )

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

     SCREAMING_SNAKE_CASE__: List[str]=   processor(images=lowerCAmelCase			,			visual_prompt=lowerCAmelCase )

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

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



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

     SCREAMING_SNAKE_CASE__: Optional[Any]=   CLIPSegProcessor(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__: Any=   processor.batch_decode(lowerCAmelCase )
     SCREAMING_SNAKE_CASE__: Any=   tokenizer.batch_decode(lowerCAmelCase )

     self.assertListEqual(lowerCAmelCase			,			lowerCAmelCase )



'''simple docstring'''

def        UpperCAmelCase_ (  lowerCamelCase_			):







 """simple docstring"""


 return number & 1 == 0


if __name__ == "__main__":
     import doctest

     doctest.testmod()





