
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			):




				def 	__a		(   self	)							-> int:
							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							,							**_UpperCamelCase	)							-> int:
							return AutoProcessor.from_pretrained(self.tmpdirname							,							**_UpperCamelCase	).tokenizer




				def 	__a		(   self							,							**_UpperCamelCase	)							-> List[Any]:
							return AutoProcessor.from_pretrained(self.tmpdirname							,							**_UpperCamelCase	).image_processor




				def 	__a		(   self	)							-> Union[str, Any]:
							shutil.rmtree(self.tmpdirname	)




				def 	__a		(   self	)							-> List[str]:
							lowerCAmelCase_         =      [np.random.randint(255							,							size=(3, 30, 400)							,							dtype=np.uinta	)]

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

							return image_inputs




				def 	__a		(   self	)							-> Dict:
							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	)							-> Union[str, Any]:
							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	)							-> Optional[Any]:
							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	)							-> str:
							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	)							-> Dict:
							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	)							-> List[Any]:
							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 collections.abc import Callable






def   lowerCamelCase__							(							__lowerCAmelCase    :    Callable[[float], float]       ,				__lowerCAmelCase    :    float       ,				__lowerCAmelCase    :    float							):




			"""simple docstring"""


			lowerCAmelCase_         =      a
			lowerCAmelCase_         =      b
			if function(__lowerCAmelCase							) == 0:  # one of the a or b is a root for the function
						return a
			elif function(__lowerCAmelCase							) == 0:
						return b
			elif (
			    function(__lowerCAmelCase							) * function(__lowerCAmelCase							) > 0
			):  # if none of these are root and they are both positive or negative,
						# then this algorithm can't find the root
						raise ValueError("could not find root in given interval."							)
			else:
						lowerCAmelCase_         =      start + (end - start) / 2.0
						while abs(start - mid							) > 10**-7:  # until precisely equals to 10^-7
									if function(__lowerCAmelCase							) == 0:
												return mid
									elif function(__lowerCAmelCase							) * function(__lowerCAmelCase							) < 0:
												lowerCAmelCase_         =      mid
									else:
												lowerCAmelCase_         =      mid
									lowerCAmelCase_         =      start + (end - start) / 2.0
						return mid






def   lowerCamelCase__							(							__lowerCAmelCase    :    float							):




			"""simple docstring"""


			return x**3 - 2 * x - 5


if __name__ == "__main__":
			print(bisection(f, 1, 10_00))

			import doctest

			doctest.testmod()



