"""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 				snake_case__     (   unittest.TestCase   ):


 def 		a__ (				self		):
        __a     				=  tempfile.mkdtemp()

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

        __a     				=  InstructBlipProcessor(lowerCamelCase  ,						lowerCamelCase  ,						lowerCamelCase		)

        processor.save_pretrained(self.tmpdirname		)


 def 		a__ (				self  ,						**lowerCamelCase		):
        return AutoProcessor.from_pretrained(self.tmpdirname  ,						**lowerCamelCase		).tokenizer


 def 		a__ (				self  ,						**lowerCamelCase		):
        return AutoProcessor.from_pretrained(self.tmpdirname  ,						**lowerCamelCase		).image_processor


 def 		a__ (				self  ,						**lowerCamelCase		):
        return AutoProcessor.from_pretrained(self.tmpdirname  ,						**lowerCamelCase		).qformer_tokenizer


 def 		a__ (				self		):
        shutil.rmtree(self.tmpdirname		)


 def 		a__ (				self		):
        __a     				=  [np.random.randint(255  ,						size=(3, 30, 400)  ,						dtype=np.uinta		)]

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

        return image_inputs


 def 		a__ (				self		):
        __a     				=  InstructBlipProcessor(
            tokenizer=self.get_tokenizer()  ,						image_processor=self.get_image_processor()  ,						qformer_tokenizer=self.get_qformer_tokenizer()  ,						)
        processor.save_pretrained(self.tmpdirname		)

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

        __a     				=  InstructBlipProcessor.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		)
        self.assertIsInstance(processor.qformer_tokenizer  ,						lowerCamelCase		)


 def 		a__ (				self		):
        __a     				=  self.get_image_processor()
        __a     				=  self.get_tokenizer()
        __a     				=  self.get_qformer_tokenizer()

        __a     				=  InstructBlipProcessor(
            tokenizer=lowerCamelCase  ,						image_processor=lowerCamelCase  ,						qformer_tokenizer=lowerCamelCase		)

        __a     				=  self.prepare_image_inputs()

        __a     				=  image_processor(lowerCamelCase  ,						return_tensors="np"		)
        __a     				=  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		):
        __a     				=  self.get_image_processor()
        __a     				=  self.get_tokenizer()
        __a     				=  self.get_qformer_tokenizer()

        __a     				=  InstructBlipProcessor(
            tokenizer=lowerCamelCase  ,						image_processor=lowerCamelCase  ,						qformer_tokenizer=lowerCamelCase		)

        __a     				=  "lower newer"

        __a     				=  processor(text=lowerCamelCase		)

        __a     				=  tokenizer(lowerCamelCase  ,						return_token_type_ids=lowerCamelCase		)
        __a     				=  qformer_tokenizer(lowerCamelCase  ,						return_token_type_ids=lowerCamelCase		)

        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 		a__ (				self		):
        __a     				=  self.get_image_processor()
        __a     				=  self.get_tokenizer()
        __a     				=  self.get_qformer_tokenizer()

        __a     				=  InstructBlipProcessor(
            tokenizer=lowerCamelCase  ,						image_processor=lowerCamelCase  ,						qformer_tokenizer=lowerCamelCase		)

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

        __a     				=  processor(text=lowerCamelCase  ,						images=lowerCamelCase		)

        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(lowerCamelCase		):
               processor()


 def 		a__ (				self		):
        __a     				=  self.get_image_processor()
        __a     				=  self.get_tokenizer()
        __a     				=  self.get_qformer_tokenizer()

        __a     				=  InstructBlipProcessor(
            tokenizer=lowerCamelCase  ,						image_processor=lowerCamelCase  ,						qformer_tokenizer=lowerCamelCase		)

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

        __a     				=  processor.batch_decode(lowerCamelCase		)
        __a     				=  tokenizer.batch_decode(lowerCamelCase		)

        self.assertListEqual(lowerCamelCase  ,						lowerCamelCase		)






 def 		a__ (				self		):
        __a     				=  self.get_image_processor()
        __a     				=  self.get_tokenizer()
        __a     				=  self.get_qformer_tokenizer()

        __a     				=  InstructBlipProcessor(
            tokenizer=lowerCamelCase  ,						image_processor=lowerCamelCase  ,						qformer_tokenizer=lowerCamelCase		)

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

        __a     				=  processor(text=lowerCamelCase  ,						images=lowerCamelCase		)

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

"""simple docstring"""



from ..utils import DummyObject, requires_backends






class 				snake_case__     (   metaclass=snake_case_   ):
 _snake_case   :			Union[str, Any]           =		["""onnx"""]


 def __init__(				self  ,						*lowerCamelCase  ,						**lowerCamelCase		):
        requires_backends(self  ,						["onnx"]		)


 @classmethod
 def 		a__ (				cls  ,						*lowerCamelCase  ,						**lowerCamelCase		):
        requires_backends(cls  ,						["onnx"]		)






 @classmethod
 def 		a__ (				cls  ,						*lowerCamelCase  ,						**lowerCamelCase		):
        requires_backends(cls  ,						["onnx"]		)
