
"""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 A_	(unittest.TestCase      ):




  '''simple docstring'''







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    tempfile.mkdtemp()

     UpperCAmelCase_					:					Optional[int]			     =    BlipImageProcessor()
     UpperCAmelCase_					:					Optional[Any]			     =    GPTaTokenizer.from_pretrained("hf-internal-testing/tiny-random-GPT2Model"  )
     UpperCAmelCase_					:					List[Any]			     =    BertTokenizerFast.from_pretrained("hf-internal-testing/tiny-random-bert"  )

     UpperCAmelCase_					:					Tuple			     =    InstructBlipProcessor(lowercase_				,   lowercase_				,   lowercase_  )

     processor.save_pretrained(self.tmpdirname  )







  def        UpperCamelCase__					(		self				,   **lowercase_  ):

     """simple docstring"""
     return AutoProcessor.from_pretrained(self.tmpdirname				,   **lowercase_  ).tokenizer







  def        UpperCamelCase__					(		self				,   **lowercase_  ):

     """simple docstring"""
     return AutoProcessor.from_pretrained(self.tmpdirname				,   **lowercase_  ).image_processor







  def        UpperCamelCase__					(		self				,   **lowercase_  ):

     """simple docstring"""
     return AutoProcessor.from_pretrained(self.tmpdirname				,   **lowercase_  ).qformer_tokenizer







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     shutil.rmtree(self.tmpdirname  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Dict			     =    [np.random.randint(255				,   size=(3, 30, 400)				,   dtype=np.uinta  )]

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

     return image_inputs







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    InstructBlipProcessor(
         tokenizer=self.get_tokenizer()				,   image_processor=self.get_image_processor()				,   qformer_tokenizer=self.get_qformer_tokenizer()				,   )
     processor.save_pretrained(self.tmpdirname  )

     UpperCAmelCase_					:					Optional[int]			     =    self.get_tokenizer(bos_token="(BOS)"				,   eos_token="(EOS)"  )
     UpperCAmelCase_					:					Any			     =    self.get_image_processor(do_normalize=lowercase_				,   padding_value=1.0  )

     UpperCAmelCase_					:					List[str]			     =    InstructBlipProcessor.from_pretrained(
         self.tmpdirname				,   bos_token="(BOS)"				,   eos_token="(EOS)"				,   do_normalize=lowercase_				,   padding_value=1.0  )

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

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







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Tuple			     =    self.get_image_processor()
     UpperCAmelCase_					:					Optional[int]			     =    self.get_tokenizer()
     UpperCAmelCase_					:					Optional[int]			     =    self.get_qformer_tokenizer()

     UpperCAmelCase_					:					Optional[int]			     =    InstructBlipProcessor(
         tokenizer=lowercase_				,   image_processor=lowercase_				,   qformer_tokenizer=lowercase_  )

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

     UpperCAmelCase_					:					List[str]			     =    image_processor(lowercase_				,   return_tensors="np"  )
     UpperCAmelCase_					:					List[Any]			     =    processor(images=lowercase_				,   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  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[Any]			     =    self.get_image_processor()
     UpperCAmelCase_					:					List[Any]			     =    self.get_tokenizer()
     UpperCAmelCase_					:					Union[str, Any]			     =    self.get_qformer_tokenizer()

     UpperCAmelCase_					:					int			     =    InstructBlipProcessor(
         tokenizer=lowercase_				,   image_processor=lowercase_				,   qformer_tokenizer=lowercase_  )

     UpperCAmelCase_					:					str			     =    "lower newer"

     UpperCAmelCase_					:					Dict			     =    processor(text=lowercase_  )

     UpperCAmelCase_					:					List[str]			     =    tokenizer(lowercase_				,   return_token_type_ids=lowercase_  )
     UpperCAmelCase_					:					Dict			     =    qformer_tokenizer(lowercase_				,   return_token_type_ids=lowercase_  )

     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  ):

     """simple docstring"""
     UpperCAmelCase_					:					int			     =    self.get_image_processor()
     UpperCAmelCase_					:					Optional[Any]			     =    self.get_tokenizer()
     UpperCAmelCase_					:					int			     =    self.get_qformer_tokenizer()

     UpperCAmelCase_					:					Dict			     =    InstructBlipProcessor(
         tokenizer=lowercase_				,   image_processor=lowercase_				,   qformer_tokenizer=lowercase_  )

     UpperCAmelCase_					:					List[str]			     =    "lower newer"
     UpperCAmelCase_					:					List[str]			     =    self.prepare_image_inputs()

     UpperCAmelCase_					:					Dict			     =    processor(text=lowercase_				,   images=lowercase_  )

     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(lowercase_  ):
        processor()







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					Optional[Any]			     =    self.get_image_processor()
     UpperCAmelCase_					:					Optional[Any]			     =    self.get_tokenizer()
     UpperCAmelCase_					:					Dict			     =    self.get_qformer_tokenizer()

     UpperCAmelCase_					:					Union[str, Any]			     =    InstructBlipProcessor(
         tokenizer=lowercase_				,   image_processor=lowercase_				,   qformer_tokenizer=lowercase_  )

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

     UpperCAmelCase_					:					List[Any]			     =    processor.batch_decode(lowercase_  )
     UpperCAmelCase_					:					Tuple			     =    tokenizer.batch_decode(lowercase_  )

     self.assertListEqual(lowercase_				,   lowercase_  )







  def        UpperCamelCase__					(		self  ):

     """simple docstring"""
     UpperCAmelCase_					:					List[str]			     =    self.get_image_processor()
     UpperCAmelCase_					:					Optional[Any]			     =    self.get_tokenizer()
     UpperCAmelCase_					:					List[Any]			     =    self.get_qformer_tokenizer()

     UpperCAmelCase_					:					Tuple			     =    InstructBlipProcessor(
         tokenizer=lowercase_				,   image_processor=lowercase_				,   qformer_tokenizer=lowercase_  )

     UpperCAmelCase_					:					Dict			     =    "lower newer"
     UpperCAmelCase_					:					Optional[Any]			     =    self.prepare_image_inputs()

     UpperCAmelCase_					:					Any			     =    processor(text=lowercase_				,   images=lowercase_  )

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




"""simple docstring"""





from diffusers.utils.testing_utils import require_onnxruntime


@require_onnxruntime
class A_	:




  '''simple docstring'''
  pass


