




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,
        BertTokenizerFast,
        BlipImageProcessor,
        GPTaTokenizer,
        InstructBlipProcessor,
        PreTrainedTokenizerFast,
    )







@require_vision
class __snake_case			(			unittest.TestCase		):







   def lowerCamelCase						(      self		:						str):

        """simple docstring"""


        UpperCAmelCase_          =							tempfile.mkdtemp()

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

        UpperCAmelCase_          =							InstructBlipProcessor(UpperCamelCase_					,						UpperCamelCase_					,						UpperCamelCase_)

        processor.save_pretrained(self.tmpdirname)







   def lowerCamelCase						(      self		:						Union[str, Any]					,						**_snake_case		:						Tuple):

        """simple docstring"""


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







   def lowerCamelCase						(      self		:						Union[str, Any]					,						**_snake_case		:						List[Any]):

        """simple docstring"""


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







   def lowerCamelCase						(      self		:						Tuple					,						**_snake_case		:						Optional[Any]):

        """simple docstring"""


        return AutoProcessor.from_pretrained(self.tmpdirname					,						**UpperCamelCase_).qformer_tokenizer







   def lowerCamelCase						(      self		:						List[str]):

        """simple docstring"""


        shutil.rmtree(self.tmpdirname)







   def lowerCamelCase						(      self		:						Optional[Any]):

        """simple docstring"""


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

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

        return image_inputs







   def lowerCamelCase						(      self		:						Union[str, Any]):

        """simple docstring"""


        UpperCAmelCase_          =							InstructBlipProcessor(
            tokenizer=self.get_tokenizer()					,						image_processor=self.get_image_processor()					,						qformer_tokenizer=self.get_qformer_tokenizer()					,						)
        processor.save_pretrained(self.tmpdirname)

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

        UpperCAmelCase_          =							InstructBlipProcessor.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_)
        self.assertIsInstance(processor.qformer_tokenizer					,						UpperCamelCase_)







   def lowerCamelCase						(      self		:						Any):

        """simple docstring"""


        UpperCAmelCase_          =							self.get_image_processor()
        UpperCAmelCase_          =							self.get_tokenizer()
        UpperCAmelCase_          =							self.get_qformer_tokenizer()

        UpperCAmelCase_          =							InstructBlipProcessor(
            tokenizer=UpperCamelCase_					,						image_processor=UpperCamelCase_					,						qformer_tokenizer=UpperCamelCase_)

        UpperCAmelCase_          =							self.prepare_image_inputs()

        UpperCAmelCase_          =							image_processor(UpperCamelCase_					,						return_tensors='''np''')
        UpperCAmelCase_          =							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 lowerCamelCase						(      self		:						int):

        """simple docstring"""


        UpperCAmelCase_          =							self.get_image_processor()
        UpperCAmelCase_          =							self.get_tokenizer()
        UpperCAmelCase_          =							self.get_qformer_tokenizer()

        UpperCAmelCase_          =							InstructBlipProcessor(
            tokenizer=UpperCamelCase_					,						image_processor=UpperCamelCase_					,						qformer_tokenizer=UpperCamelCase_)

        UpperCAmelCase_          =							'''lower newer'''

        UpperCAmelCase_          =							processor(text=UpperCamelCase_)

        UpperCAmelCase_          =							tokenizer(UpperCamelCase_					,						return_token_type_ids=UpperCamelCase_)
        UpperCAmelCase_          =							qformer_tokenizer(UpperCamelCase_					,						return_token_type_ids=UpperCamelCase_)

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

        for key in encoded_tokens_qformer.keys():
             self.assertListEqual(encoded_tokens_qformer[key]					,						encoded_processor['''qformer_''' + key])







   def lowerCamelCase						(      self		:						List[Any]):

        """simple docstring"""


        UpperCAmelCase_          =							self.get_image_processor()
        UpperCAmelCase_          =							self.get_tokenizer()
        UpperCAmelCase_          =							self.get_qformer_tokenizer()

        UpperCAmelCase_          =							InstructBlipProcessor(
            tokenizer=UpperCamelCase_					,						image_processor=UpperCamelCase_					,						qformer_tokenizer=UpperCamelCase_)

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

        UpperCAmelCase_          =							processor(text=UpperCamelCase_					,						images=UpperCamelCase_)

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

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







   def lowerCamelCase						(      self		:						str):

        """simple docstring"""


        UpperCAmelCase_          =							self.get_image_processor()
        UpperCAmelCase_          =							self.get_tokenizer()
        UpperCAmelCase_          =							self.get_qformer_tokenizer()

        UpperCAmelCase_          =							InstructBlipProcessor(
            tokenizer=UpperCamelCase_					,						image_processor=UpperCamelCase_					,						qformer_tokenizer=UpperCamelCase_)

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

        UpperCAmelCase_          =							processor.batch_decode(UpperCamelCase_)
        UpperCAmelCase_          =							tokenizer.batch_decode(UpperCamelCase_)

        self.assertListEqual(UpperCamelCase_					,						UpperCamelCase_)







   def lowerCamelCase						(      self		:						Any):

        """simple docstring"""


        UpperCAmelCase_          =							self.get_image_processor()
        UpperCAmelCase_          =							self.get_tokenizer()
        UpperCAmelCase_          =							self.get_qformer_tokenizer()

        UpperCAmelCase_          =							InstructBlipProcessor(
            tokenizer=UpperCamelCase_					,						image_processor=UpperCamelCase_					,						qformer_tokenizer=UpperCamelCase_)

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

        UpperCAmelCase_          =							processor(text=UpperCamelCase_					,						images=UpperCamelCase_)

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










from __future__ import annotations

from collections.abc import Iterator


class        _a							:

							def __init__(							self:	List[str]    ,						UpperCamelCase_:	int							)			->   None:





									"""simple docstring"""







									lowercase__            =      value
									lowercase__            =      None
									lowercase__            =      None


class        _a							:

							def __init__(							self:	Union[str, Any]    ,						UpperCamelCase_:	Node							)			->   None:





									"""simple docstring"""







									lowercase__            =      tree

							def       lowerCamelCase_ (							self:	Any    ,						UpperCamelCase_:	Node | None							)			->   int:





									"""simple docstring"""







									if node is None:
											return 0
									return node.value + (
									    self.depth_first_search(node.left							) + self.depth_first_search(node.right							)
									)


							def __iter__(							self:	List[str]							)			->   Iterator[int]:





									"""simple docstring"""







									yield self.depth_first_search(self.tree							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()


