



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







@require_vision
class       UpperCamelCase__   (	unittest.TestCase  ):




      """simple docstring"""




      def      SCREAMING_SNAKE_CASE__ (      self				:      int       ):
        lowerCAmelCase_   :				Union[str, Any]								= tempfile.mkdtemp()

        lowerCAmelCase_   :				Optional[Any]								= BlipImageProcessor()
        lowerCAmelCase_   :				str								= GPTaTokenizer.from_pretrained('hf-internal-testing/tiny-random-GPT2Model'       )
        lowerCAmelCase_   :				Tuple								= BertTokenizerFast.from_pretrained('hf-internal-testing/tiny-random-bert'       )

        lowerCAmelCase_   :				Optional[Any]								= InstructBlipProcessor(SCREAMING_SNAKE_CASE_    ,			SCREAMING_SNAKE_CASE_    ,			SCREAMING_SNAKE_CASE_       )

        processor.save_pretrained(self.tmpdirname       )



      def      SCREAMING_SNAKE_CASE__ (      self				:      List[Any]    ,			**SCREAMING_SNAKE_CASE_				:      Dict       ):
        return AutoProcessor.from_pretrained(self.tmpdirname    ,			**SCREAMING_SNAKE_CASE_       ).tokenizer



      def      SCREAMING_SNAKE_CASE__ (      self				:      List[str]    ,			**SCREAMING_SNAKE_CASE_				:      Union[str, Any]       ):
        return AutoProcessor.from_pretrained(self.tmpdirname    ,			**SCREAMING_SNAKE_CASE_       ).image_processor



      def      SCREAMING_SNAKE_CASE__ (      self				:      Tuple    ,			**SCREAMING_SNAKE_CASE_				:      str       ):
        return AutoProcessor.from_pretrained(self.tmpdirname    ,			**SCREAMING_SNAKE_CASE_       ).qformer_tokenizer



      def      SCREAMING_SNAKE_CASE__ (      self				:      Optional[int]       ):
        shutil.rmtree(self.tmpdirname       )



      def      SCREAMING_SNAKE_CASE__ (      self				:      Tuple       ):
        lowerCAmelCase_   :				List[Any]								= [np.random.randint(2_5_5    ,			size=(3, 3_0, 4_0_0)    ,			dtype=np.uinta       )]

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

        return image_inputs



      def      SCREAMING_SNAKE_CASE__ (      self				:      Any       ):
        lowerCAmelCase_   :				Any								= InstructBlipProcessor(
            tokenizer=self.get_tokenizer()    ,			image_processor=self.get_image_processor()    ,			qformer_tokenizer=self.get_qformer_tokenizer()    ,			)
        processor.save_pretrained(self.tmpdirname       )

        lowerCAmelCase_   :				Any								= self.get_tokenizer(bos_token='(BOS)'    ,			eos_token='(EOS)'       )
        lowerCAmelCase_   :				Any								= self.get_image_processor(do_normalize=SCREAMING_SNAKE_CASE_    ,			padding_value=1.0       )

        lowerCAmelCase_   :				List[str]								= InstructBlipProcessor.from_pretrained(
            self.tmpdirname    ,			bos_token='(BOS)'    ,			eos_token='(EOS)'    ,			do_normalize=SCREAMING_SNAKE_CASE_    ,			padding_value=1.0       )

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

        self.assertEqual(processor.image_processor.to_json_string()    ,			image_processor_add_kwargs.to_json_string()       )
        self.assertIsInstance(processor.image_processor    ,			SCREAMING_SNAKE_CASE_       )
        self.assertIsInstance(processor.qformer_tokenizer    ,			SCREAMING_SNAKE_CASE_       )



      def      SCREAMING_SNAKE_CASE__ (      self				:      Dict       ):
        lowerCAmelCase_   :				Dict								= self.get_image_processor()
        lowerCAmelCase_   :				List[str]								= self.get_tokenizer()
        lowerCAmelCase_   :				str								= self.get_qformer_tokenizer()

        lowerCAmelCase_   :				Dict								= InstructBlipProcessor(
            tokenizer=SCREAMING_SNAKE_CASE_    ,			image_processor=SCREAMING_SNAKE_CASE_    ,			qformer_tokenizer=SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				List[str]								= self.prepare_image_inputs()

        lowerCAmelCase_   :				Optional[int]								= image_processor(SCREAMING_SNAKE_CASE_    ,			return_tensors='np'       )
        lowerCAmelCase_   :				Union[str, Any]								= processor(images=SCREAMING_SNAKE_CASE_    ,			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      SCREAMING_SNAKE_CASE__ (      self				:      Tuple       ):
        lowerCAmelCase_   :				List[Any]								= self.get_image_processor()
        lowerCAmelCase_   :				Any								= self.get_tokenizer()
        lowerCAmelCase_   :				Tuple								= self.get_qformer_tokenizer()

        lowerCAmelCase_   :				List[Any]								= InstructBlipProcessor(
            tokenizer=SCREAMING_SNAKE_CASE_    ,			image_processor=SCREAMING_SNAKE_CASE_    ,			qformer_tokenizer=SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				int								= 'lower newer'

        lowerCAmelCase_   :				Optional[int]								= processor(text=SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				int								= tokenizer(SCREAMING_SNAKE_CASE_    ,			return_token_type_ids=SCREAMING_SNAKE_CASE_       )
        lowerCAmelCase_   :				Optional[int]								= qformer_tokenizer(SCREAMING_SNAKE_CASE_    ,			return_token_type_ids=SCREAMING_SNAKE_CASE_       )

        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      SCREAMING_SNAKE_CASE__ (      self				:      Union[str, Any]       ):
        lowerCAmelCase_   :				Optional[Any]								= self.get_image_processor()
        lowerCAmelCase_   :				Any								= self.get_tokenizer()
        lowerCAmelCase_   :				Dict								= self.get_qformer_tokenizer()

        lowerCAmelCase_   :				List[Any]								= InstructBlipProcessor(
            tokenizer=SCREAMING_SNAKE_CASE_    ,			image_processor=SCREAMING_SNAKE_CASE_    ,			qformer_tokenizer=SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				str								= 'lower newer'
        lowerCAmelCase_   :				Optional[int]								= self.prepare_image_inputs()

        lowerCAmelCase_   :				Optional[Any]								= processor(text=SCREAMING_SNAKE_CASE_    ,			images=SCREAMING_SNAKE_CASE_       )

        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(SCREAMING_SNAKE_CASE_       ):
          processor()



      def      SCREAMING_SNAKE_CASE__ (      self				:      Optional[Any]       ):
        lowerCAmelCase_   :				Dict								= self.get_image_processor()
        lowerCAmelCase_   :				Tuple								= self.get_tokenizer()
        lowerCAmelCase_   :				Any								= self.get_qformer_tokenizer()

        lowerCAmelCase_   :				Any								= InstructBlipProcessor(
            tokenizer=SCREAMING_SNAKE_CASE_    ,			image_processor=SCREAMING_SNAKE_CASE_    ,			qformer_tokenizer=SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				str								= [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        lowerCAmelCase_   :				Dict								= processor.batch_decode(SCREAMING_SNAKE_CASE_       )
        lowerCAmelCase_   :				Any								= tokenizer.batch_decode(SCREAMING_SNAKE_CASE_       )

        self.assertListEqual(SCREAMING_SNAKE_CASE_    ,			SCREAMING_SNAKE_CASE_       )





      def      SCREAMING_SNAKE_CASE__ (      self				:      List[Any]       ):
        lowerCAmelCase_   :				List[str]								= self.get_image_processor()
        lowerCAmelCase_   :				Union[str, Any]								= self.get_tokenizer()
        lowerCAmelCase_   :				Dict								= self.get_qformer_tokenizer()

        lowerCAmelCase_   :				Dict								= InstructBlipProcessor(
            tokenizer=SCREAMING_SNAKE_CASE_    ,			image_processor=SCREAMING_SNAKE_CASE_    ,			qformer_tokenizer=SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				Optional[Any]								= 'lower newer'
        lowerCAmelCase_   :				List[Any]								= self.prepare_image_inputs()

        lowerCAmelCase_   :				Any								= processor(text=SCREAMING_SNAKE_CASE_    ,			images=SCREAMING_SNAKE_CASE_       )

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










"""simple docstring"""







import warnings

from diffusers import StableDiffusionImgaImgPipeline  # noqa F401


warnings.warn(
    """The `image_to_image.py` script is outdated. Please use directly `from diffusers import"""
    """ StableDiffusionImg2ImgPipeline` instead."""
)





