
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, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast


@require_vision
class        lowercase      (	unittest.TestCase     ):



		def __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				UpperCamelCase						=  tempfile.mkdtemp()

				UpperCamelCase						=  BlipImageProcessor()
				UpperCamelCase						=  GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model' )

				UpperCamelCase						=  BlipaProcessor(A_       ,   A_ )

				processor.save_pretrained(self.tmpdirname )



		def __UpperCamelCase				(				self       ,   **A_ )						->      int:
				"""simple docstring"""
				return AutoProcessor.from_pretrained(self.tmpdirname       ,   **A_ ).tokenizer



		def __UpperCamelCase				(				self       ,   **A_ )						->      Optional[Any]:
				"""simple docstring"""
				return AutoProcessor.from_pretrained(self.tmpdirname       ,   **A_ ).image_processor



		def __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				shutil.rmtree(self.tmpdirname )



		def __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				UpperCamelCase						=  [np.random.randint(255       ,   size=(3, 30, 400)       ,   dtype=np.uinta )]

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

				return image_inputs



		def __UpperCamelCase				(				self )						->      Dict:
				"""simple docstring"""
				UpperCamelCase						=  BlipaProcessor(tokenizer=self.get_tokenizer()       ,   image_processor=self.get_image_processor() )
				processor.save_pretrained(self.tmpdirname )

				UpperCamelCase						=  self.get_tokenizer(bos_token='(BOS)'       ,   eos_token='(EOS)' )
				UpperCamelCase						=  self.get_image_processor(do_normalize=A_       ,   padding_value=1.0 )

				UpperCamelCase						=  BlipaProcessor.from_pretrained(
				    self.tmpdirname       ,   bos_token='(BOS)'       ,   eos_token='(EOS)'       ,   do_normalize=A_       ,   padding_value=1.0 )

				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 __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				UpperCamelCase						=  self.get_image_processor()
				UpperCamelCase						=  self.get_tokenizer()

				UpperCamelCase						=  BlipaProcessor(tokenizer=A_       ,   image_processor=A_ )

				UpperCamelCase						=  self.prepare_image_inputs()

				UpperCamelCase						=  image_processor(A_       ,   return_tensors='np' )
				UpperCamelCase						=  processor(images=A_       ,   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 )						->      Optional[Any]:
				"""simple docstring"""
				UpperCamelCase						=  self.get_image_processor()
				UpperCamelCase						=  self.get_tokenizer()

				UpperCamelCase						=  BlipaProcessor(tokenizer=A_       ,   image_processor=A_ )

				UpperCamelCase						=  'lower newer'

				UpperCamelCase						=  processor(text=A_ )

				UpperCamelCase						=  tokenizer(A_       ,   return_token_type_ids=A_ )

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



		def __UpperCamelCase				(				self )						->      List[Any]:
				"""simple docstring"""
				UpperCamelCase						=  self.get_image_processor()
				UpperCamelCase						=  self.get_tokenizer()

				UpperCamelCase						=  BlipaProcessor(tokenizer=A_       ,   image_processor=A_ )

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

				UpperCamelCase						=  processor(text=A_       ,   images=A_ )

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

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



		def __UpperCamelCase				(				self )						->      List[str]:
				"""simple docstring"""
				UpperCamelCase						=  self.get_image_processor()
				UpperCamelCase						=  self.get_tokenizer()

				UpperCamelCase						=  BlipaProcessor(tokenizer=A_       ,   image_processor=A_ )

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

				UpperCamelCase						=  processor.batch_decode(A_ )
				UpperCamelCase						=  tokenizer.batch_decode(A_ )

				self.assertListEqual(A_       ,   A_ )



		def __UpperCamelCase				(				self )						->      Union[str, Any]:
				"""simple docstring"""
				UpperCamelCase						=  self.get_image_processor()
				UpperCamelCase						=  self.get_tokenizer()

				UpperCamelCase						=  BlipaProcessor(tokenizer=A_       ,   image_processor=A_ )

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

				UpperCamelCase						=  processor(text=A_       ,   images=A_ )

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


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  int(lowercase				)
		if decimal in (0, 1):  # Exit cases for the recursion
				return str(lowercase				)
		UpperCamelCase			,						UpperCamelCase						=  divmod(lowercase					, 2				)
		return binary_recursive(lowercase				) + str(lowercase				)


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  str(lowercase				).strip()
		if not number:
				raise ValueError('No input value was provided'				)
		UpperCamelCase						=  '-' if number.startswith('-'				) else ''
		UpperCamelCase						=  number.lstrip('-'				)
		if not number.isnumeric():
				raise ValueError('Input value is not an integer'				)
		return f'''{negative}0b{binary_recursive(int(lowercase				)				)}'''


if __name__ == "__main__":
					from doctest import testmod

					testmod()
