






import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


_SCREAMING_SNAKE_CASE   =  logging.get_logger(__name__)






class 					SCREAMING_SNAKE_CASE_  (       _a ):
       """simple docstring"""


       def __init__(				self	:Dict,      *snake_case	:int,      **snake_case	:Dict):



          """simple docstring"""

          warnings.warn(
              'The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
              ' Please use DeformableDetrImageProcessor instead.',      snake_case,      )
          super().__init__(*snake_case,      **snake_case)










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 					SCREAMING_SNAKE_CASE_  (       unittest.TestCase ):
       """simple docstring"""


       def 				UpperCamelCase__						(				self	:List[str]):



          """simple docstring"""

          _lowercase              =tempfile.mkdtemp()

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

          _lowercase              =InstructBlipProcessor(snake_case,      snake_case,      snake_case)

          processor.save_pretrained(self.tmpdirname)





       def 				UpperCamelCase__						(				self	:List[str],      **snake_case	:str):



          """simple docstring"""

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





       def 				UpperCamelCase__						(				self	:Optional[Any],      **snake_case	:List[Any]):



          """simple docstring"""

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





       def 				UpperCamelCase__						(				self	:Tuple,      **snake_case	:Any):



          """simple docstring"""

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





       def 				UpperCamelCase__						(				self	:Optional[int]):



          """simple docstring"""

          shutil.rmtree(self.tmpdirname)





       def 				UpperCamelCase__						(				self	:List[str]):



          """simple docstring"""

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

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

          return image_inputs





       def 				UpperCamelCase__						(				self	:List[Any]):



          """simple docstring"""

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

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

          _lowercase              =InstructBlipProcessor.from_pretrained(
              self.tmpdirname,      bos_token='(BOS)',      eos_token='(EOS)',      do_normalize=snake_case,      padding_value=1.0)

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

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





       def 				UpperCamelCase__						(				self	:Tuple):



          """simple docstring"""

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

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              =self.prepare_image_inputs()

          _lowercase              =image_processor(snake_case,      return_tensors='np')
          _lowercase              =processor(images=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 				UpperCamelCase__						(				self	:List[Any]):



          """simple docstring"""

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

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

          _lowercase              ='lower newer'

          _lowercase              =processor(text=snake_case)

          _lowercase              =tokenizer(snake_case,      return_token_type_ids=snake_case)
          _lowercase              =qformer_tokenizer(snake_case,      return_token_type_ids=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 				UpperCamelCase__						(				self	:Any):



          """simple docstring"""

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

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

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

          _lowercase              =processor(text=snake_case,      images=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(snake_case):
             processor()





       def 				UpperCamelCase__						(				self	:Dict):



          """simple docstring"""

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

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

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

          _lowercase              =processor.batch_decode(snake_case)
          _lowercase              =tokenizer.batch_decode(snake_case)

          self.assertListEqual(snake_case,      snake_case)





       def 				UpperCamelCase__						(				self	:int):



          """simple docstring"""

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

          _lowercase              =InstructBlipProcessor(
              tokenizer=snake_case,      image_processor=snake_case,      qformer_tokenizer=snake_case)

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

          _lowercase              =processor(text=snake_case,      images=snake_case)

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


