



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, BertTokenizer, BlipImageProcessor, BlipProcessor, PreTrainedTokenizerFast





@require_vision
class    lowerCamelCase__  (						unittest.TestCase):
     """simple docstring"""



     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		tempfile.mkdtemp()

           lowerCamelCase								=		BlipImageProcessor()
           lowerCamelCase								=		BertTokenizer.from_pretrained("hf-internal-testing/tiny-random-BertModel"    )

           lowerCamelCase								=		BlipProcessor(UpperCamelCase__				,			UpperCamelCase__    )

           processor.save_pretrained(self.tmpdirname    )







     def 						_a      (self				,			**__a    ):






           '''simple docstring'''



           return AutoProcessor.from_pretrained(self.tmpdirname				,			**UpperCamelCase__    ).tokenizer







     def 						_a      (self				,			**__a    ):






           '''simple docstring'''



           return AutoProcessor.from_pretrained(self.tmpdirname				,			**UpperCamelCase__    ).image_processor







     def 						_a      (self    ):






           '''simple docstring'''



           shutil.rmtree(self.tmpdirname    )







     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		[np.random.randint(2_55				,			size=(3, 30, 4_00)				,			dtype=np.uinta    )]

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

           return image_inputs







     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		BlipProcessor(tokenizer=self.get_tokenizer()				,			image_processor=self.get_image_processor()    )
           processor.save_pretrained(self.tmpdirname    )

           lowerCamelCase								=		self.get_tokenizer(bos_token="(BOS)"				,			eos_token="(EOS)"    )
           lowerCamelCase								=		self.get_image_processor(do_normalize=UpperCamelCase__				,			padding_value=1.0    )

           lowerCamelCase								=		BlipProcessor.from_pretrained(
               self.tmpdirname				,			bos_token="(BOS)"				,			eos_token="(EOS)"				,			do_normalize=UpperCamelCase__				,			padding_value=1.0    )

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

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







     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		self.get_image_processor()
           lowerCamelCase								=		self.get_tokenizer()

           lowerCamelCase								=		BlipProcessor(tokenizer=UpperCamelCase__				,			image_processor=UpperCamelCase__    )

           lowerCamelCase								=		self.prepare_image_inputs()

           lowerCamelCase								=		image_processor(UpperCamelCase__				,			return_tensors="np"    )
           lowerCamelCase								=		processor(images=UpperCamelCase__				,			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 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		self.get_image_processor()
           lowerCamelCase								=		self.get_tokenizer()

           lowerCamelCase								=		BlipProcessor(tokenizer=UpperCamelCase__				,			image_processor=UpperCamelCase__    )

           lowerCamelCase								=		"lower newer"

           lowerCamelCase								=		processor(text=UpperCamelCase__    )

           lowerCamelCase								=		tokenizer(UpperCamelCase__				,			return_token_type_ids=UpperCamelCase__    )

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







     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		self.get_image_processor()
           lowerCamelCase								=		self.get_tokenizer()

           lowerCamelCase								=		BlipProcessor(tokenizer=UpperCamelCase__				,			image_processor=UpperCamelCase__    )

           lowerCamelCase								=		"lower newer"
           lowerCamelCase								=		self.prepare_image_inputs()

           lowerCamelCase								=		processor(text=UpperCamelCase__				,			images=UpperCamelCase__    )

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

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







     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		self.get_image_processor()
           lowerCamelCase								=		self.get_tokenizer()

           lowerCamelCase								=		BlipProcessor(tokenizer=UpperCamelCase__				,			image_processor=UpperCamelCase__    )

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

           lowerCamelCase								=		processor.batch_decode(UpperCamelCase__    )
           lowerCamelCase								=		tokenizer.batch_decode(UpperCamelCase__    )

           self.assertListEqual(UpperCamelCase__				,			UpperCamelCase__    )







     def 						_a      (self    ):






           '''simple docstring'''



           lowerCamelCase								=		self.get_image_processor()
           lowerCamelCase								=		self.get_tokenizer()

           lowerCamelCase								=		BlipProcessor(tokenizer=UpperCamelCase__				,			image_processor=UpperCamelCase__    )

           lowerCamelCase								=		"lower newer"
           lowerCamelCase								=		self.prepare_image_inputs()

           lowerCamelCase								=		processor(text=UpperCamelCase__				,			images=UpperCamelCase__    )

           # For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
           self.assertListEqual(list(inputs.keys()    )				,			["pixel_values", "input_ids", "attention_mask"]    )




from __future__ import annotations

from collections.abc import Iterable, Iterator
from dataclasses import dataclass

a_						:     Optional[int]	     =		(3, 9, -1_1, 0, 7, 5, 1, -1)
a_						:     str	     =		(4, 6, 2, 0, 8, 1_0, 3, -2)





@dataclass
class    lowerCamelCase__  :
     """simple docstring"""



     _A       =			42
     _A       =			42





class    lowerCamelCase__  :
     """simple docstring"""



     def __init__(self				,			__a    ):






           '''simple docstring'''



           lowerCamelCase								=		None
           for i in sorted(__a				,			reverse=__a    ):
                 lowerCamelCase								=		Node(__a				,			self.head    )







     def __iter__(self    ):






           '''simple docstring'''



           lowerCamelCase								=		self.head
           while node:
                 yield node.data
                 lowerCamelCase								=		node.next_node







     def __len__(self    ):






           '''simple docstring'''



           return sum(1 for _ in self    )







     def __str__(self    ):






           '''simple docstring'''



           return " -> ".join([str(__a    ) for node in self]    )



def     __lowercase(	UpperCAmelCase__   ,   UpperCAmelCase__ ):


      """simple docstring"""



      return SortedLinkedList(list(UpperCAmelCase__ ) + list(UpperCAmelCase__ ) )


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     a_						:     Any	     =		SortedLinkedList
     print(merge_lists(SSL(test_data_odd), SSL(test_data_even)))