






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 		lowerCAmelCase     ( unittest.TestCase			):

     '''simple docstring'''

     def       lowerCAmelCase				(  self				:	Dict							)			->  Dict:


            """simple docstring"""

            __lowercase      :							Optional[int]				=     tempfile.mkdtemp()

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

            __lowercase      :							Any				=     InstructBlipProcessor(__a		,     __a		,     __a							)

            processor.save_pretrained(self.tmpdirname							)



     def       lowerCAmelCase				(  self				:	List[str]		,     **__a				:	str							)			->  Dict:


            """simple docstring"""

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



     def       lowerCAmelCase				(  self				:	int		,     **__a				:	Optional[Any]							)			->  Any:


            """simple docstring"""

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



     def       lowerCAmelCase				(  self				:	Any		,     **__a				:	Union[str, Any]							)			->  Any:


            """simple docstring"""

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



     def       lowerCAmelCase				(  self				:	int							)			->  Union[str, Any]:


            """simple docstring"""

            shutil.rmtree(self.tmpdirname							)



     def       lowerCAmelCase				(  self				:	List[Any]							)			->  Tuple:


            """simple docstring"""

            __lowercase      :							List[str]				=     [np.random.randint(255		,     size=(3, 30, 400)		,     dtype=np.uinta							)]

            __lowercase      :							Union[str, Any]				=     [Image.fromarray(np.moveaxis(__a		,     0		,     -1							)							) for x in image_inputs]

            return image_inputs



     def       lowerCAmelCase				(  self				:	List[Any]							)			->  Optional[int]:


            """simple docstring"""

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

            __lowercase      :							Optional[Any]				=     self.get_tokenizer(bos_token="""(BOS)"""		,     eos_token="""(EOS)"""							)
            __lowercase      :							List[str]				=     self.get_image_processor(do_normalize=__a		,     padding_value=1.0							)

            __lowercase      :							str				=     InstructBlipProcessor.from_pretrained(
                self.tmpdirname		,     bos_token="""(BOS)"""		,     eos_token="""(EOS)"""		,     do_normalize=__a		,     padding_value=1.0							)

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

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



     def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  Dict:


            """simple docstring"""

            __lowercase      :							Optional[int]				=     self.get_image_processor()
            __lowercase      :							Tuple				=     self.get_tokenizer()
            __lowercase      :							int				=     self.get_qformer_tokenizer()

            __lowercase      :							Tuple				=     InstructBlipProcessor(
                tokenizer=__a		,     image_processor=__a		,     qformer_tokenizer=__a							)

            __lowercase      :							Any				=     self.prepare_image_inputs()

            __lowercase      :							Any				=     image_processor(__a		,     return_tensors="""np"""							)
            __lowercase      :							Any				=     processor(images=__a		,     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				:	Tuple							)			->  List[str]:


            """simple docstring"""

            __lowercase      :							List[str]				=     self.get_image_processor()
            __lowercase      :							Tuple				=     self.get_tokenizer()
            __lowercase      :							List[str]				=     self.get_qformer_tokenizer()

            __lowercase      :							Tuple				=     InstructBlipProcessor(
                tokenizer=__a		,     image_processor=__a		,     qformer_tokenizer=__a							)

            __lowercase      :							Dict				=     """lower newer"""

            __lowercase      :							Union[str, Any]				=     processor(text=__a							)

            __lowercase      :							str				=     tokenizer(__a		,     return_token_type_ids=__a							)
            __lowercase      :							List[str]				=     qformer_tokenizer(__a		,     return_token_type_ids=__a							)

            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]							)			->  Optional[int]:


            """simple docstring"""

            __lowercase      :							Dict				=     self.get_image_processor()
            __lowercase      :							Dict				=     self.get_tokenizer()
            __lowercase      :							Optional[Any]				=     self.get_qformer_tokenizer()

            __lowercase      :							List[str]				=     InstructBlipProcessor(
                tokenizer=__a		,     image_processor=__a		,     qformer_tokenizer=__a							)

            __lowercase      :							Tuple				=     """lower newer"""
            __lowercase      :							Optional[Any]				=     self.prepare_image_inputs()

            __lowercase      :							List[str]				=     processor(text=__a		,     images=__a							)

            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(__a							):
                   processor()



     def       lowerCAmelCase				(  self				:	Optional[Any]							)			->  List[str]:


            """simple docstring"""

            __lowercase      :							Tuple				=     self.get_image_processor()
            __lowercase      :							Union[str, Any]				=     self.get_tokenizer()
            __lowercase      :							Union[str, Any]				=     self.get_qformer_tokenizer()

            __lowercase      :							List[Any]				=     InstructBlipProcessor(
                tokenizer=__a		,     image_processor=__a		,     qformer_tokenizer=__a							)

            __lowercase      :							Union[str, Any]				=     [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

            __lowercase      :							Optional[int]				=     processor.batch_decode(__a							)
            __lowercase      :							Any				=     tokenizer.batch_decode(__a							)

            self.assertListEqual(__a		,     __a							)



     def       lowerCAmelCase				(  self				:	Tuple							)			->  List[Any]:


            """simple docstring"""

            __lowercase      :							int				=     self.get_image_processor()
            __lowercase      :							Union[str, Any]				=     self.get_tokenizer()
            __lowercase      :							Any				=     self.get_qformer_tokenizer()

            __lowercase      :							int				=     InstructBlipProcessor(
                tokenizer=__a		,     image_processor=__a		,     qformer_tokenizer=__a							)

            __lowercase      :							List[Any]				=     """lower newer"""
            __lowercase      :							Optional[int]				=     self.prepare_image_inputs()

            __lowercase      :							Dict				=     processor(text=__a		,     images=__a							)

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







import fire

from utils import calculate_rouge, save_json
def       snake_case_		(     lowerCAmelCase_       :						Any       ,       lowerCAmelCase_       :						str       ,       lowerCAmelCase_       :						str=None       ,       **lowerCAmelCase_       :						str      ):
							__lowercase      :							Tuple				=     [x.strip() for x in open(lowerCAmelCase_      ).readlines()]
							__lowercase      :							Dict				=     [x.strip() for x in open(lowerCAmelCase_      ).readlines()][: len(lowerCAmelCase_      )]
							__lowercase      :							Tuple				=     calculate_rouge(lowerCAmelCase_       ,       lowerCAmelCase_       ,       **lowerCAmelCase_      )
							if save_path is not None:
														save_json(lowerCAmelCase_       ,       lowerCAmelCase_       ,       indent=lowerCAmelCase_      )
							return metrics  # these print nicely


if __name__ == "__main__":
	fire.Fire(calculate_rouge_path)