"""simple docstring"""






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  _A						(       unittest.TestCase	):

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	tempfile.mkdtemp()

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

            lowercase														=	BlipProcessor(__lowerCAmelCase		,       __lowerCAmelCase						)

            processor.save_pretrained(self.tmpdirname						)

      def 				A__       (						self		,       **__lowerCAmelCase						):







            """simple docstring"""



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

      def 				A__       (						self		,       **__lowerCAmelCase						):







            """simple docstring"""



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

      def 				A__       (						self						):







            """simple docstring"""



            shutil.rmtree(self.tmpdirname						)

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	[np.random.randint(255		,       size=(3, 30, 400)		,       dtype=np.uinta						)]

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

            return image_inputs

      def 				A__       (						self						):







            """simple docstring"""



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

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

            lowercase														=	BlipProcessor.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 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	BlipProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	self.prepare_image_inputs()

            lowercase														=	image_processor(__lowerCAmelCase		,       return_tensors="""np"""						)
            lowercase														=	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 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	BlipProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

            lowercase														=	"""lower newer"""

            lowercase														=	processor(text=__lowerCAmelCase						)

            lowercase														=	tokenizer(__lowerCAmelCase		,       return_token_type_ids=__lowerCAmelCase						)

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

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	BlipProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

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

            lowercase														=	processor(text=__lowerCAmelCase		,       images=__lowerCAmelCase						)

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

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

      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	BlipProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

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

            lowercase														=	processor.batch_decode(__lowerCAmelCase						)
            lowercase														=	tokenizer.batch_decode(__lowerCAmelCase						)

            self.assertListEqual(__lowerCAmelCase		,       __lowerCAmelCase						)







      def 				A__       (						self						):







            """simple docstring"""



            lowercase														=	self.get_image_processor()
            lowercase														=	self.get_tokenizer()

            lowercase														=	BlipProcessor(tokenizer=__lowerCAmelCase		,       image_processor=__lowerCAmelCase						)

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

            lowercase														=	processor(text=__lowerCAmelCase		,       images=__lowerCAmelCase						)

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




"""simple docstring"""






from __future__ import annotations

import numpy as np


def 			UpperCAmelCase__       (				lowerCAmelCase__     :list[float]		) ->    Optional[Any]:
      '''simple docstring'''


      return np.maximum(0					,		lowerCAmelCase__		)


if __name__ == "__main__":
       print(np.array(relu([-1, 0, 5])))  # --> [0, 0, 5]



