

"""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: Dict       ):






         """simple docstring"""


         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(_UpperCAmelCase    ,						_UpperCAmelCase    ,						_UpperCAmelCase       )

         processor.save_pretrained(self.tmpdirname       )

    def 				UpperCamelCase	(     self: List[str]    ,						**UpperCamelCase: Any       ):






         """simple docstring"""


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

    def 				UpperCamelCase	(     self: str    ,						**UpperCamelCase: str       ):






         """simple docstring"""


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

    def 				UpperCamelCase	(     self: int    ,						**UpperCamelCase: List[str]       ):






         """simple docstring"""


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

    def 				UpperCamelCase	(     self: str       ):






         """simple docstring"""


         shutil.rmtree(self.tmpdirname       )

    def 				UpperCamelCase	(     self: int       ):






         """simple docstring"""


         A__										=  [np.random.randint(2_55    ,						size=(3, 30, 4_00)    ,						dtype=np.uinta       )]

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

         return image_inputs

    def 				UpperCamelCase	(     self: Any       ):






         """simple docstring"""


         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=_UpperCAmelCase    ,						padding_value=1.0       )

         A__										=  InstructBlipProcessor.from_pretrained(
             self.tmpdirname    ,						bos_token="""(BOS)"""    ,						eos_token="""(EOS)"""    ,						do_normalize=_UpperCAmelCase    ,						padding_value=1.0       )

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

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

    def 				UpperCamelCase	(     self: Dict       ):






         """simple docstring"""


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

         A__										=  InstructBlipProcessor(
             tokenizer=_UpperCAmelCase    ,						image_processor=_UpperCAmelCase    ,						qformer_tokenizer=_UpperCAmelCase       )

         A__										=  self.prepare_image_inputs()

         A__										=  image_processor(_UpperCAmelCase    ,						return_tensors="""np"""       )
         A__										=  processor(images=_UpperCAmelCase    ,						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: Optional[Any]       ):






         """simple docstring"""


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

         A__										=  InstructBlipProcessor(
             tokenizer=_UpperCAmelCase    ,						image_processor=_UpperCAmelCase    ,						qformer_tokenizer=_UpperCAmelCase       )

         A__										=  '''lower newer'''

         A__										=  processor(text=_UpperCAmelCase       )

         A__										=  tokenizer(_UpperCAmelCase    ,						return_token_type_ids=_UpperCAmelCase       )
         A__										=  qformer_tokenizer(_UpperCAmelCase    ,						return_token_type_ids=_UpperCAmelCase       )

         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: Dict       ):






         """simple docstring"""


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

         A__										=  InstructBlipProcessor(
             tokenizer=_UpperCAmelCase    ,						image_processor=_UpperCAmelCase    ,						qformer_tokenizer=_UpperCAmelCase       )

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

         A__										=  processor(text=_UpperCAmelCase    ,						images=_UpperCAmelCase       )

         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(_UpperCAmelCase       ):
              processor()

    def 				UpperCamelCase	(     self: Any       ):






         """simple docstring"""


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

         A__										=  InstructBlipProcessor(
             tokenizer=_UpperCAmelCase    ,						image_processor=_UpperCAmelCase    ,						qformer_tokenizer=_UpperCAmelCase       )

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

         A__										=  processor.batch_decode(_UpperCAmelCase       )
         A__										=  tokenizer.batch_decode(_UpperCAmelCase       )

         self.assertListEqual(_UpperCAmelCase    ,						_UpperCAmelCase       )





    def 				UpperCamelCase	(     self: Any       ):






         """simple docstring"""


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

         A__										=  InstructBlipProcessor(
             tokenizer=_UpperCAmelCase    ,						image_processor=_UpperCAmelCase    ,						qformer_tokenizer=_UpperCAmelCase       )

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

         A__										=  processor(text=_UpperCAmelCase    ,						images=_UpperCAmelCase       )

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









"""simple docstring"""



from __future__ import annotations



class 					a						:



    """simple docstring"""



    def __init__(     self: Any    ,						UpperCamelCase: str    ,						UpperCamelCase: str       ):






         """simple docstring"""


         A__			,				A__										=  text, pattern
         A__			,				A__										=  len(UpperCamelCase       ), len(UpperCamelCase       )

    def 				UpperCamelCase	(     self: Dict    ,						UpperCamelCase: str       ):






         """simple docstring"""


         for i in range(self.patLen - 1    ,						-1    ,						-1       ):
              if char == self.pattern[i]:
                   return i
         return -1

    def 				UpperCamelCase	(     self: str    ,						UpperCamelCase: int       ):






         """simple docstring"""


         for i in range(self.patLen - 1    ,						-1    ,						-1       ):
              if self.pattern[i] != self.text[current_pos + i]:
                   return current_pos + i
         return -1





    def 				UpperCamelCase	(     self: List[Any]       ):






         """simple docstring"""


         A__										=  []
         for i in range(self.textLen - self.patLen + 1       ):
              A__										=  self.mismatch_in_text(UpperCamelCase       )
              if mismatch_index == -1:
                   positions.append(UpperCamelCase       )
              else:
                   A__										=  self.match_in_pattern(self.text[mismatch_index]       )
                   A__										=  (
                       mismatch_index - match_index
                   )  # shifting index lgtm [py/multiple-definition]
         return positions

SCREAMING_SNAKE_CASE_					:	List[Any]							  =						'ABAABA'
SCREAMING_SNAKE_CASE_					:	List[Any]							  =						'AB'
SCREAMING_SNAKE_CASE_					:	Union[str, Any]							  =						BoyerMooreSearch(text, pattern)
SCREAMING_SNAKE_CASE_					:	int							  =						bms.bad_character_heuristic()

if len(positions) == 0:
 print('No match found')
else:
 print('Pattern found in following positions: ')
 print(positions)






